Robust Energy Scheduling in Vehicle-to-Grid Networks

The uncertainties brought by intermittent renewable generation and uncoordinated charging behaviors of EVs pose great challenges to the reliable operation of power systems, which motivates us to explore the integration of robust optimization with energy scheduling in V2G networks. In this article, we first introduce V2G robust energy scheduling problems and review the stateof- the art contributions from the perspectives of renewable energy integration, ancillary service provision, and proactive demand-side participation in the electricity market. Second, for each category of V2G applications, the corresponding problem formulations, robust solution concepts, and design approaches are describ…

Service-Oriented Wireless Virtualized Networks: An Intelligent Resource Management Approach

Virtual Resource Allocation for Wireless Virtualized Heterogeneous Network with Hybrid Energy Supply

In this work, two novel virtual user association and resource allocation algorithms are introduced for a wireless virtualized heterogeneous network with hybrid energy supply. In the considered system, macro base stations (MBSs) are supplied by the grid power and small base stations (SBSs) have the energy harvesting capability in addition to the grid power supplement. Multiple infrastructure providers (InPs) own the physical resources, i.e., BSs and radio resources. The Mobile Virtual Network Operators (MVNOs) are able to recent these resources from the InPs and operate the virtualized resources for providing services to different users. In particular, aiming to maximize the overall utility …

Energy Efficient Optimization for Computation Offloading in Fog Computing System

In this paper, we investigate the energy efficient computation offloading scheme in a multi-user fog computing system. We consider the users need to make the decision on whether to offload the tasks to the fog node nearby, based on the energy consumption and delay constraint. In particular, we utilize queuing theory to bring a thorough study on the energy consumption and execution delay of the offloading process. Two queuing models are applied respectively to model the execution processes at the mobile device (MD) and fog node. Based on the theoretical analysis, an energy efficient optimization problem is formulated with the objective to minimize the energy consumption subjects to execution…

Energy-Efficient Resource Optimization with Wireless Power Transfer for Secure NOMA Systems

In this paper, we investigate resource allocation algorithm design for secure non-orthogonal multiple access (NOMA) systems empowered by wireless power transfer. With the consideration of an existing eavesdropper, the objective is to obtain secure and energy efficient transmission among multiple users by optimizing time, power and subchannel allocation. Moreover, we also take into consideration for the practical case that the statistics of the channel state information of the eavesdropper is not available. In order to address the optimization problem and its high computational complexity, we propose an iterative algorithm with guaranteed convergence to deliver a suboptimal solution for gene…

Energy Efficient Optimization for Wireless Virtualized Small Cell Networks With Large-Scale Multiple Antenna

Wireless network virtualization is envisioned as a promising framework to provide efficient and customized services for next-generation wireless networks. In wireless virtualized networks (WVNs), limited radio resources are shared among different services providers for providing services to different users with heterogeneous demands. In this paper, we propose a resource allocation scheme for an orthogonal frequency division multiplexing-based WVN, where one small cell base station equipped with a large number of antennas serves the users with different service requirements. In particular, with the objective to obtain the energy efficiency in the uplink, a joint power, subcarrier, and antenn…

Resource Allocation for Edge Computing-Based Blockchain: A Game Theoretic Approach

Blockchain has been progressively applied to various Internet of Things (IoT) platforms. As the efficiency of the blockchain depends on its computing capability, how to make sure the acquisition of the computational resources and participation of the devices would be the driving force. In this work, an edge computing-based blockchain network is considered, where the edge service provider (ESP) offers computational resources for the miners. The focus is to investigate an efficient incentive mechanism for the miners to purchase the computational resources. Accordingly, a two-stage Stackelberg game is formulated between the miners and ESP. By exploring the Stackelberg equilibrium of the optima…

Adaptive Service Offloading for Revenue Maximization in Mobile Edge Computing With Delay-Constraint

Mobile Edge Computing (MEC) is an important and effective platform to offload the computational services of modern mobile applications, and has gained tremendous attention from various research communities. For delay and resource constrained mobile devices, the important issues include: 1) minimization of the service latency; 2) optimal revenue maximization; 3) high quality-of-service (QoS) requirement to offload the computational service offloading. To address the above issues, an adaptive service offloading scheme is designed to provide the maximum revenue and service utilization to MEC. Unlike most of the existing works, we consider both the delay-tolerant and delay-constraint services i…

Energy efficient resource allocation in heterogeneous software defined network: A reverse combinatorial auction approach

In this paper, resource allocation for energy effi- ciency in heterogeneous Software Defined Network (SDN) with multiple network service providers (NSPs) is studied. The considered problem is modeled as a reverse combinatorial auction game, which takes different quality of service (QoS) requirements into account. The heterogeneous network selection associated with power allocation problem is optimized by maximizing the energy efficiency of data transmission. By exploiting the properties of fractional programming, the resulting non-convex Winner Determination Problem (WDP) is transformed into an equivalent subtractive convex optimization problem. The proposed reverse combinatorial auction ga…

Association of Cesarean Delivery With Risk of Neurodevelopmental and Psychiatric Disorders in the Offspring: A Systematic Review and Meta-analysis.

This systematic review and meta-analysis examines the association between birth by cesarean delivery and risk of neurodevelopmental and psychiatric disorders in the offspring compared with birth by vaginal delivery.

Alleviating Class Imbalance Problem in Automatic Sleep Stage Classification

For real-world automatic sleep-stage classification tasks, various existing deep learning-based models are biased toward the majority with a high proportion. Because of the unique sleep structure, most of the current polysomnography (PSG) datasets suffer an inherent class imbalance problem (CIP), in which the number of each sleep stage is severely unequal. In this study, we first define the class imbalance factor (CIF) to describe the level of CIP quantitatively. Afterward, we propose two balancing methods to alleviate this problem from the dataset quantity and the relationship between the class distribution and the applied model, respectively. The first one is to employ the data augmentati…

Energy-Efficient and Secure Resource Allocation for Multiple-Antenna NOMA with Wireless Power Transfer

Non-orthogonal multiple access (NOMA) is considered as one of the promising techniques for providing high data rates in the fifth generation mobile communication. By applying successive interference cancellation schemes and superposition coding at the NOMA receiver, multiple users can be multiplexed on the same subchannel. In this paper, we investigate resource allocation algorithm design for an OFDM-based NOMA system empowered by wireless power transfer. In the considered system, users who need to transmit data can only be powered by the wireless power transfer. With the consideration of an existing eavesdropper, the objective is to obtain secure and energy efficient transmission among mul…

Energy Efficient Resource Allocation for Wireless Power Transfer Enabled Collaborative Mobile Clouds

In order to fully enjoy high rate broadband multimedia services, prolonging the battery lifetime of user equipment is critical for mobile users, especially for smartphone users. In this paper, the problem of distributing cellular data via a wireless power transfer enabled collaborative mobile cloud (WeCMC) in an energy efficient manner is investigated. WeCMC is formed by a group of users who have both functionalities of information decoding and energy harvesting, and are interested for cooperating in downloading content from the operators. Through device-to-device communications, the users inside WeCMC are able to cooperate during the downloading procedure and offload data from the base sta…

Energy Efficiency Optimization for Multi-cell Massive MIMO : Centralized and Distributed Power Allocation Algorithms

This paper investigates the energy efficiency (EE) optimization in downlink multi-cell massive multiple-input multiple-output (MIMO). In our research, the statistical channel state information (CSI) is exploited to reduce the signaling overhead. To maximize the minimum EE among the neighbouring cells, we design the transmit covariance matrices for each base station (BS). Specifically, optimization schemes for this max-min EE problem are developed, in the centralized and distributed ways, respectively. To obtain the transmit covariance matrices, we first find out the closed-form optimal transmit eigenmatrices for the BS in each cell, and convert the original transmit covariance matrices desi…

Collaborative Mobile Clouds: An Energy Efficient Paradigm for Content Sharing

On the way toward enabling efficient content distribution, reducing energy consumption and prolonging battery life of mobile equipment, an emerging paradigm, i.e., mobile cloud, which is based on content distribution, was proposed. As a mobile platform that is oriented toward content distribution, mobile cloud is also foreseen as an energy-efficient solution for future wireless networks. The benefits of using CMC for content distribution or distributed computing from social networking perspectives have been studied earlier. In this article, we first present the concepts of CMC and then discuss the energy-efficiency benefits from the system-level point-of-view as well as open challenges in d…

Distributed Resource Allocation for Energy Efficiency in OFDMA Multicell Networks with Wireless Power Transfer

In this paper, an energy-efficient resource allocation problem is investigated for the wireless power transfer (WPT)-enabled OFDMA multicell networks. In the considered system, multiple base stations (BSs) with a large number of antennas are responsible to provide WPT in the downlink, and the users can recycle and utilize the received energy for uplink data transmission. The role of BS is to execute WPT; thus, there are no data transmissions in the downlink. A time-division protocol is considered to divide the time of downlink WPT and uplink wireless information transfer into separate time slots. With the objective to improve the energy efficiency, we propose the time, subcarrier, and power…

One Dimensional Convolutional Neural Networks for Seizure Onset Detection Using Long-term Scalp and Intracranial EEG

Epileptic seizure detection using scalp electroencephalogram (sEEG) and intracranial electroencephalogram (iEEG) has attracted widespread attention in recent two decades. The accurate and rapid detection of seizures not only reflects the efficiency of the algorithm, but also greatly reduces the burden of manual detection during long-term electroencephalogram (EEG) recording. In this work, a stacked one-dimensional convolutional neural network (1D-CNN) model combined with a random selection and data augmentation (RS-DA) strategy is proposed for seizure onset detection. Firstly, we segmented the long-term EEG signals using 2-sec sliding windows. Then, the 2-sec interictal and ictal segments w…

Energy Efficient Optimization for Solar-Powered UAV Communications System

In this work, we explore the energy efficiency optimization for a solar-powered unmanned aerial vehicle (UAV) communications system. We consider a scenario where a number of ground users (GUs) connect with a solar-powered multi-antenna UAV over a wireless link. First, we are able to derive the relations between the uplink data rate and heading angle of UAV and transmission power of GUs. In addition, the harvested energy from solar light is also affected by UAV’s angle. Accordingly, with the objective to maximize the energy efficiency that is related to uplink data rate and energy consumption, we propose to dynamically adjust the UAV trajectory and gesture, by optimizing its velocity, accele…

Security and Privacy in Wireless IoT

The 13 articles in this special section focus on security and privacy in wireless Internet of Things (IoT). IoT is a paradigm that involves networked physical objects with embedded technologies to collect, communicate, sense, and interact with the external environment through wireless or wired connections. With rapid advancements in IoT technology, the number of IoT devices is expected to surpass 50 billion by 2020, which has also drawn the attention of attackers who seek to exploit the merits of this new technology for their own benefits. There are many potential security and privacy threats to IoT, such as attacks against IoT systems and unauthorized access to private information of end u…

Low Latency Ambient Backscatter Communications with Deep Q-Learning for Beyond 5G Applications

Low latency is a critical requirement of beyond 5G services. Previously, the aspect of latency has been extensively analyzed in conventional and modern wireless networks. With the rapidly growing research interest in wireless-powered ambient backscatter communications, it has become ever more important to meet the delay constraints, while maximizing the achievable data rate. Therefore, to address the issue of latency in backscatter networks, this paper provides a deep Q-learning based framework for delay constrained ambient backscatter networks. To do so, a Q-learning model for ambient backscatter scenario has been developed. In addition, an algorithm has been proposed that employ deep neur…

Incentive Mechanism for Edge-Computing-Based Blockchain

Blockchain has been gradually applied to different Internet of Things (IoT) platforms. As the efficiency of the blockchain mainly depends on the network computing capability, how to make sure the acquisition of the computational resources and participation of the devices would be the driving force. In this work, we focus on investigating incentive mechanism for rational miners to purchase the computational resources. A edge computing-based blockchain network is considered, where the edge service provider (ESP) can provide computational resources for the miners. Accordingly, we formulate a two-stage Stackelberg game between the miners and ESP. The aim is to investigate Stackelberg equilibriu…

Multi-objective optimization for computation offloading in mobile-edge computing

Mobile-edge cloud computing is a new cloud platform to provide pervasive and agile computation augmenting services for mobile devices (MDs) at anytime and anywhere by endowing ubiquitous radio access networks with computing capabilities. Although offloading computations to the cloud can reduce energy consumption at the MDs, it may also incur a larger execution delay. Usually the MDs have to pay cloud resource they used. In this paper, we utilize queuing theory to bring a thorough study on the energy consumption, execution delay and price cost of offloading process in a mobile-edge cloud system. Specifically, both wireless transmission and computing capabilities are explicitly and jointly co…

Transmission Optimization and Resource Allocation for Wireless Powered Dense Vehicle Area Network With Energy Recycling

The wireless-powered communication paradigm brings self-sustainability to the on-vehicle sensors by harvesting the energy from radiated radio frequency (RF) signals. This paper proposes a novel transmission and resource allocation strategy for the scenario where multiple wireless powered vehicle area networks (VAN) co-existed with high density. The considered multi-VAN system consists of a remote master access point (MAP), multiple on-vehicle hybrid access points (HAPs) and sensors. Unlike previous works, we consider that the sensors can recycle the radiated radio frequency energy from all the HAPs when HAPs communicate with MAP, so the dedicated signals for energy harvesting (EH) are unnec…

Parallel and Distributed Resource Allocation With Minimum Traffic Disruption for Network Virtualization

Wireless network virtualization has been advocated as one of the most promising technologies to provide multifarious services and applications for the future Internet by enabling multiple isolated virtual wireless networks to coexist and share the same physical wireless resources. Based on the multiple concurrent virtual wireless networks running on the shared physical substrate, service providers can independently manage and deploy different end-users services. This paper proposes a new formulation for bandwidth allocation and routing problem for multiple virtual wireless networks that operate on top of a single substrate network to minimize the operation cost of the substrate network. We …

UAV-Aided Secure Short-Packet Data Collection and Transmission

Benefiting from the deployment flexibility and the line-of-sight (LoS) channel conditions, unmanned aerial vehicle (UAV) has gained tremendous attention in data collection for wireless sensor networks. However, the high-quality air-ground channels also pose significant threats to the security of UAV aided wireless networks. In this paper, we propose a short-packet secure UAV-aided data collection and transmission scheme to guarantee the freshness and security of the transmission from the sensors to the remote ground base station (BS). First, during the data collection phase, the trajectory, the flight duration, and the user scheduling are jointly optimized with the objective of maximizing t…

Collaborative Content Downloading in VANETs with Fuzzy Comprehensive Evaluation

Vehicle collaborative content downloading has become a hotspot in current vehicular ad-hoc network (VANET) research. However, in reality, the highly dynamic nature of VANET makes users lose resources easily, and the transmission of invalid segment data also wastes valuable bandwidth and storage of the users&rsquo

Channel Increment Strategy-Based 1D Convolutional Neural Networks for Seizure Prediction Using Intracranial EEG

The application of intracranial electroencephalogram (iEEG) to predict seizures remains challenging. Although channel selection has been utilized in seizure prediction and detection studies, most of them focus on the combination with conventional machine learning methods. Thus, channel selection combined with deep learning methods can be further analyzed in the field of seizure prediction. Given this, in this work, a novel iEEG-based deep learning method of One-Dimensional Convolutional Neural Networks (1D-CNN) combined with channel increment strategy was proposed for the effective seizure prediction. First, we used 4-sec sliding windows without overlap to segment iEEG signals. Then, 4-sec …

Propagation Channels for mmWave Vehicular Communications : State-of-the-art and Future Research Directions

Vehicular communications essentially support automotive applications for safety and infotainment. For this reason, industry leaders envision an enhanced role for vehicular communications in the fifth generation of mobile communications technology. Over the years, the number of vehicle- mounted sensors has increased steadily, which potentially leads to more volume of critical data communications in a short time. Also, emerging applications such as remote/autonomous driving and infotainment such as high-definition movie streaming require data-rates on the order of multiple Gb/s. Such high data rates require a large system bandwidth, but very limited bandwidth is available in the sub-6 GHz cel…

LightSleepNet: A Lightweight Deep Model for Rapid Sleep Stage Classification with Spectrograms.

Deep learning has achieved unprecedented success in sleep stage classification tasks, which starts to pave the way for potential real-world applications. However, due to its enormous size, deployment of deep neural networks is hindered by high cost at various aspects, such as computation power, storage, network bandwidth, power consumption, and hardware complexity. For further practical applications (e.g., wearable sleep monitoring devices), there is a need for simple and compact models. In this paper, we propose a lightweight model, namely LightSleepNet, for rapid sleep stage classification based on spectrograms. Our model is assembled by a much fewer number of model parameters compared to…

IEEE Access Special Section Editorial: Exploiting the Benefits of Interference in Wireless Networks: Energy Harvesting and Security

Interference used to be viewed as a harmful factor in wireless networks, which can reduce the quality of information transmission. To combat against interference, many interference management techniques have emerged. Due to the latest research advances, interference (or noise) can also be exploited to offer some benefits to wireless networks. The first aspect is that interference in multi-user networks can be collected as a green power supply for the transceivers, known as wireless energy harvesting. Another application is that one can generate artificial noise to disrupt the adversarial eavesdropping, and guarantee the security of wireless networks. Therefore, conventional interference man…

Internet of Autonomous Vehicles: Architecture, Features, and Socio-Technological Challenges

Mobility is the backbone of urban life and a vital economic factor in the development of the world. Rapid urbanization and the growth of mega-cities is bringing dramatic changes in the capabilities of vehicles. Innovative solutions like autonomy, electrification, and connectivity are on the horizon. How, then, we can provide ubiquitous connectivity to the legacy and autonomous vehicles? This paper seeks to answer this question by combining recent leaps of innovation in network virtualization with remarkable feats of wireless communications. To do so, this paper proposes a novel paradigm called the Internet of autonomous vehicles (IoAV). We begin painting the picture of IoAV by discussing th…

An Efficient and Privacy-Preserving Blockchain-Based Authentication Scheme for Low Earth Orbit Satellite Assisted Internet of Things

Recently, integrating satellite networks (e.g. Low-earth-orbit satellite constellation) into the Internet of Things (IoT) ecosystem has emerged as a potential paradigm to provide more reliable, ubiquitous and seamless network services. The LEO satellite networks serves as a key enabler to transform the connectivity across industries and geographical border. Despite the convenience brought from the LEO satellite networks, it arises security concerns, in which the essential one is to secure the communication between the IoT devices and the LEO satellite network. However, some challenges inheriting from the LEO satellite networks need to be considered : 1) the dynamic topology; 2) the resource…

Average Age of Information in Wireless Powered Mobile Edge Computing System

Mobile edge computing (MEC) has been recognized as a promising technique to provide enhanced computation services for low-power wireless devices at the network edge. How to evaluate the timeliness of the task and data delivery is critical for the development of MEC applications. Considering a wireless powered MEC system, in this letter we study the average age of information (AoI), which is a crucial performance metric to measure the freshness of information. Specifically, in the considered system, a sensor node harvests energy from an energy transmitter and transmits computation tasks to the MEC server. The charging time of the sensor node’s capacitor, the waiting time and service time at …

Context-aware data caching for 5G heterogeneous small cells networks

In this work, we investigate the problem of context-aware data caching in the heterogeneous small cell networks (HSCNs) to provide satisfactory to the end-users in reducing the service latency. In particular, we explore the storage capability of base stations (BSs) in HSCNs and propose a data caching model consists of edge caching elements (CAEs), small cell base stations (SBSs), and macro cell BS (MBS). Then, we concentrate on how to efficiently match the data contents to the different cache entities in order to minimize the overall system service latency. We model it as a distributed college admission (CA) stable matching problem and tackle this issue by utilizing contextual information t…

Service Provisioning and User Association for Heterogeneous Wireless Railway Networks

In addition to comforting passengers' journey, the modern railway system is responsible to support a variety of on-board Internet services to meet the passenger's demands on seamless service provisioning. In order to provide wireless access to the train, one idea attracting increasing attention is to deploy a series of track-side access points (TAPs) with high-speed data rates along the rail lines dedicated to the broadband mobile service provisioning on board. Due to the heavy data traffic flushing into the base stations (BSs) of the cellular networks, TAPs act as a complement to the BSs in data delivery. In this paper, we focus on the TAP association problem for service provisioning in a …

Latency-Oblivious Distributed Task Scheduling for Mobile Edge Computing

Mobile Edge Computing (MEC) is emerging as one of the effective platforms for offloading the resource- and latency-constrained computational services of modern mobile applications. For latency- and resource-constrained mobile devices, the important issues include: 1) minimize end-to-end service latency; 2) minimize service completion time; 3) high quality-of-service (QoS) requirement to offload the complex computational services. To address the above issues, a latencyoblivious distributed task scheduling scheme is designed in this work to maximize the QoS performance and goodput for the MEC services. Unlike most of the existing works, we consider the latency-oblivious property of different …

Dynamic Resource Allocation and Computation Offloading for Edge Computing System

In this work, we propose a dynamic optimization scheme for an edge computing system with multiple users, where the radio and computational resources, and offloading decisions, can be dynamically allocated with the variation of computation demands, radio channels and the computation resources. Specifically, with the objective to minimize the energy consumption of the considered system, we propose a joint computation offloading, radio and computational resource allocation algorithm based on Lyapunov optimization. Through minimizing the derived upper bound of the Lyapunov drift-plus-penalty function, the main problem is divided into several sub-problems at each time slot and are addressed sepa…

Energy Efficient Resource Allocation for OFDMA Two-Way Relay Networks with Channel Estimation Error

In this work, we consider the practical issues of resource allocation problem in OFDMA two-way relay networks: the inaccuracy of channel-state information (CSI) available to the transmitters. Instead, only the estimated channel status is known by the transmitters. In this context, a joint optimization of subcarrier pairing and allocation, relay selection and transmit power allocation is formulated in the OFDMA two-way amplify-and-forward relay networks. Moreover, to ensure the Quality of Service (QoS) requirement, the energy consumption must be minimized without compromising the QoS. Therefore, by applying convex optimization techniques, energy efficient algorithms are developed with the ob…

A Double Auction Mechanism for Virtual Resource Allocation in SDN-based Cellular Network

The explosively growing demands for mobile traffic service bring both challenges and opportunities to wireless net- works, among which, wireless network virtualization is proposed as the main evolution towards 5G. In this paper, we first propose a Software Defined Network (SDN) based wireless virtualization architecture for enabling multi-flow transmission in order to save capital expenses (CapEx) and operation expenses (OpEx) significantly with multiple Infrastructures Providers (InPs) and multiple Mobile Virtual Network Operators (MVNOs). We for- mulate the virtual resource allocation problem with diverse QoS requirements as a social welfare maximization problem with transaction cost. Due…

Recent Advances in Security and Privacy for Future Intelligent Networks

The articles in this special section focus on recent advances in security and privacy for future intelligent networks. Recent booming advancements in networking techniques have led to an evolution toward future intelligent networks (FINs). This trend takes place under a circumstance in which a great number of devices are connected for specific purposes by a variety of novel techniques. In FINs, we envision the benefits of integrating intelligence into networks. Contemporarily, these emerging techniques are still at the exploration stage, leaving many privacy and security challenges unaddressed. Existing researchers have already uncovered a great amount of attacks and threats. The situation …

Energy Harvesting Enabled Energy Efficient Cognitive Machine-to-Machine Communications

Energy harvesting based cognitive machine-to-machine (EH-CM2M) communication has been introduced to overcome the problem of spectrum scarcity and limited battery capacity by enabling M2M transmitters (M2M-TXs) to harvest energy from ambient radio frequency signals, as well as to reuse the resource blocks (RBs) allocated to CUs in an opportunistic manner. However, the complex interference scenarios and the stringent QoS requirements pose new challenges on resource allocation optimization. In this chapter, we consider how to maximize the energy efficiency of M2M-TXs via the joint optimization of channel selection, peer discovery, power control, and time allocation.

Energy efficient resource allocation for secure OFDMA relay systems with eavesdropper

In this paper, we address the energy efficient resource allocation problem for a secure orthogonal frequency division multiple access (OFDMA) relay system. In particular, we consider there is a eavesdropper near the base station (BS) which tries to overtake the information sent by BS. We formulate the joint optimization problem with the objective to optimize the energy efficiency of the considered system by considering subcarrier pairing, secret data rate and power allocation. In addition, the system can assign different priority to different users such that the security of information transmission can be guaranteed. The proposed iterative algorithm not only maximizes the system energy effi…

Collaborative Mobile Clusters

Future wireless communication systems are expected to offer several gigabits data rate. It can be anticipated that the advanced communication techniques can enhance the capability of mobile terminals to support high data traffic. However, aggressive technique induces high energy consumption for the circuits of terminals, which drain the batteries fast and consequently limit user experience in future wireless networks. In order to solve such a problem, a scheme called collaborative mobile cluster is foreseen as one of the potential solutions to reduce energy consumption per node in a network by exploiting collaboration within a cluster of nearby mobile terminals. This chapter provides a deta…

Dynamic Computation Offloading Scheme for Fog Computing System with Energy Harvesting Devices

Fog computing is considered as a promising technology to meet the ever-increasing computation requests from a wide variety of mobile applications. By offloading the computation-intensive requests to the fog node or the central cloud, the performance of the applications, such as energy consumption and delay, are able to be significantly enhanced. Meanwhile, utilizing the recent advances of social network and energy harvesting techniques, the system performance could be further improved. In this paper, we take the social relationships of the energy harvesting MDs into the design of computational offloading scheme in fog computing. With the objective to minimize the social group execution cost…

Energy-efficient resource allocation for OFDMA two-way relay networks with imperfect CSI

Most of the existed works on the radio resource allocation (RRA) problem commonly assume the channel-state information (CSI) can be perfectly obtained by the transmission source. However, such assumption is not practical in the realistic wireless systems. In this work, we consider the practical implementation issues of resource allocation in orthogonal frequency division multiple access (OFDMA) two-way relay networks: the inaccuracy of channel-state information (CSI) available to the source. Instead, only the estimated channel status is known by the source. In this context, a joint optimization of subcarrier pairing and allocation, relay selection, and transmit power allocation is formulate…

IEEE Access Special Section Editorial : Cloud and Big Data-Based Next-Generation Cognitive Radio Networks

In cognitive radio networks (CRN), secondary users (SUs) are required to detect the presence of the licensed users, known as primary users (PUs), and to find spectrum holes for opportunistic spectrum access without causing harmful interference to PUs. However, due to complicated data processing, non-real-time information exchange and limited memory, SUs often suffer from imperfect sensing and unreliable spectrum access. Cloud computing can solve this problem by allowing the data to be stored and processed in a shared environment. Furthermore, the information from a massive number of SUs allows for more comprehensive information exchanges to assist the resource allocation and interference ma…

Individual Independent Component Analysis on EEG: Event-Related Responses Vs. Difference Wave of Deviant and Standard Responses

Independent component analysis (ICA) is often used to spatially filter event-related potentials (ERPs). When an oddball paradigm is applied to elicit ERPs, difference wave (DW, responses of deviant stimuli minus those of standard ones) is often used to remove the common responses between the deviant and the standard. Thus, DW can be produced first, and then ICA is used to decompose the DW. Or, ICA is performed on responses of the deviant and standard stimuli separately, and then DW is applied on the filtered responses. In this study, we compared the two approaches to analyzing mismatch negativity (MMN). We found that DW introduced noise in the time and space domains, resulting in more diffi…

Trajectory Design and Resource Allocation for Multi-UAV Networks : Deep Reinforcement Learning Approaches

The future mobile communication system is expected to provide ubiquitous connectivity and unprecedented services over billions of devices. The unmanned aerial vehicle (UAV), which is prominent in its flexibility and low cost, emerges as a significant network entity to realize such ambitious targets. In this work, novel machine learning-based trajectory design and resource allocation schemes are presented for a multi-UAV communications system. In the considered system, the UAVs act as aerial Base Stations (BSs) and provide ubiquitous coverage. In particular, with the objective to maximize the system utility over all served users, a joint user association, power allocation and trajectory desi…

Resource Allocation for Multi-Access Edge Computing with Fronthaul and Backhaul Constraints

Edge computing is able to provide proximity solutions for the future wireless network to accommodate different types of devices with various computing service demands. Meanwhile, in order to provide ubiquitous connectivities to massive devices over a relatively large area, densely deploying remote radio head (RRH) is considered as a cost-efficient solution. In this work, we consider a vertical and heterogeneous multiaccess edge computing system. In the system, the RRHs are deployed for providing wireless access for the users and the edge node with computing capability can process the computation requests from the users. With the objective to minimize the total energy consumption for process…

3D Matrix-Based Visualization System of Association Rules

With the growing number of mining datasets, it becomes increasingly difficult to explore interesting rules because of the large number of resultant and its nature complexity. Studies on human perception and intuition show that graphical representation could be a better illustration of how to seek information from the data using the capabilities of human visual system. In this work, we present and implement a 3D matrix-based approach visualization system of association rules. The main visual representation applies the extended matrix-based approach with rule-to-items mapping to general transaction data set. A novel method merging rules and assigning weight is proposed in order to reduce the …

Multi-hop D2D Communications with Network Coding : From A Performance Perspective

Multi-hop device-to-device (D2D) communications play an important role in expanding D2D coverage. In this paper, we study a relay-based and network-coding-assisted (in particular, XOR coding) multi-hop D2D communication system. In the system, toward jointly considering the impact of interference and network traffic conditions on the quality of D2D communications, various channel fading models and traffic models are investigated, and the packet loss probability of D2D links is meticulously computed using these models. With the packet loss probability of D2D links, the general closed-form expressions of end-to-end packet loss probability (E2EPLP) of the system with the presence (or absence) o…

Wireless Caching Aided 5G Networks

Energy Efficient Scheduling in Content Distribution Collaborative Mobile Clusters

Most of the existing literatures on green communications aimed to improve the energy efficiency at the base station or data server. However, in order to fully experience high rate broadband multimedia services, prolonging the battery life of user equipment is also critical for the mobile terminals, especially for the smartphone users. In this work, we investigate the problem of designing a content distribution mobile platform named collaborative mobile clusters (CMC) via user cooperation to reduce the energy consumption at the terminal side. Specifically, given numbers of users interested in downloading a common content from the operator, both centralized and distributed user grouping and s…

Adapting to Dynamic LEO-B5G Systems : Meta-Critic Learning Based Efficient Resource Scheduling

Low earth orbit (LEO) satellite-assisted communications have been considered as one of key elements in beyond 5G systems to provide wide coverage and cost-efficient data services. Such dynamic space-terrestrial topologies impose exponential increase in the degrees of freedom in network management. In this paper, we address two practical issues for an over-loaded LEO-terrestrial system. The first challenge is how to efficiently schedule resources to serve the massive number of connected users, such that more data and users can be delivered/served. The second challenge is how to make the algorithmic solution more resilient in adapting to dynamic wireless environments.To address them, we first…

Joint Subcarrier and Phase Shifts Optimization for RIS-aided Localization-Communication System

Joint localization and communication systems have drawn significant attention due to their high resource utilization. In this paper, we consider a reconfigurable intelligent surface (RIS)-aided simultaneously localization and communication system. We first determine the sum squared position error bound (SPEB) as the localization accuracy metric for the presented localization-communication system. Then, a joint RIS discrete phase shifts design and subcarrier assignment problem is formulated to minimize the SPEB while guaranteeing each user’s achievable data rate requirement. For the presented non-convex mixed-integer problem, we propose an iterative algorithm to obtain a suboptimal solution …

Towards Service-oriented 5G: Virtualizing the Networks for Everything-as-a-Service

It is widely acknowledged that the forthcoming 5G architecture will be highly heterogeneous and deployed with a high degree of density. These changes over the current 4G bring many challenges on how to achieve an efficient operation from the network management perspective. In this article, we introduce a revolutionary vision of the future 5G wireless networks, in which the network is no longer limited by hardware or even software. Specifically, by the idea of virtualizing the wireless networks, which has recently gained increasing attention, we introduce the Everything-as-a-Service (XaaS) taxonomy to light the way towards designing the service-oriented wireless networks. The concepts, chall…

Single-trial-based Temporal Principal Component Analysis on Extracting Event-related Potentials of Interest for an Individual Subject

Abstract Temporal principal component analysis (t-PCA) has been widely used to extract event-related potentials (ERPs) at the group level of multiple subjects’ ERP data. The key assumption of group t-PCA analysis is that desired ERPs of all subjects share the same waveforms (i.e., temporal components), whereas waveforms of different subjects’ ERPs can be variant in phases, peak latencies and so on, to some extent. Additionally, several PCA-extracted components coming from the same ERP dataset failed to be statistically analysed simultaneously because their polarities and amplitudes were indeterminate. To fill these gaps, a novel technique was proposed and employed to extract desired ERP fro…

Multi-Resource Management for Multi-Tier Space Information Networks: A Cooperative Game

With the drastic increase of space information network (SIN) traffic and the diversity of network traffic types, the optimal allocation of the scarce network resources is of great significance for optimizing the SIN system capability. In this paper, we propose a multi-resource management method for multi-tier SIN using the cooperative Nash bargaining solution. Since the original problem is a non-convex problem, we firstly make logarithmic transition, and then find a tightest lower bound function to convert the initial problem into a convex one. In order to carry out the optimal bandwidth and power allocation in SIN, we construct a joint bandwidth and power allocation (JBPA) algorithm. Simul…

Multi-Antenna Covert Communication With Jamming in the Presence of a Mobile Warden

Covert communication can hide the information transmission process from the warden to prevent adversarial eavesdropping. However, it becomes challenging when the warden can move. In this paper, we propose a covert communication scheme against a mobile warden, which maximizes the connectivity throughput between a multi-antenna transmitter and a full-duplex jamming receiver with the covert outage probability (COP) limit. First, we analyze the monotonicity of the COP to obtain the optimal location the warden can move. Then, under this worst situation, we optimize the transmission rate, the transmit power and the jamming power of covert communication to maximize the connection throughput. This …

Energy-Efficient Edge Computing Service Provisioning for Vehicular Networks: A Consensus ADMM Approach

In vehicular networks, in-vehicle user equipment (UE) with limited battery capacity can achieve opportunistic energy saving by offloading energy-hungry workloads to vehicular edge computing nodes via vehicle-to-infrastructure links. However, how to determine the optimal portion of workload to be offloaded based on the dynamic states of energy consumption and latency in local computing, data transmission, workload execution and handover, is still an open issue. In this paper, we study the energy-efficient workload offloading problem and propose a low-complexity distributed solution based on consensus alternating direction method of multipliers. By incorporating a set of local variables for e…

Outage Analysis of Relay-Aided Non-Orthogonal Multiple Access with Partial Relay Selection

Non-Orthogonal multiple access (NOMA) holds promise as a spectrally efficient multiple access scheme for 5G communication networks. This work investigates the performance of NOMA in a dual-hop amplify-and-forward (AF) relaying network, which is subject to Nakagami-$m$ fading. Specifically, we obtain a novel closed-form expression of the outage probability for the near and far users when the partial relay selection (PRS) scheme is used for selecting the best among $N$ intermediate relays. The users are considered to employ selection combining technique in order to combine the relayed and the direct transmission signals for an increased reliability of detection. Then, we evaluate the impact o…

Social Network-Based Content Delivery in Device-to-Device Underlay Cellular Networks Using Matching Theory

With the popularity of social network-based services, the unprecedented growth of mobile date traffic has brought a heavy burden on the traditional cellular networks. Device-to-device (D2D) communication, as a promising solution to overcome wireless spectrum crisis, can enable fast content delivery based on user activities in social networks. In this paper, we address the content delivery problem related to optimization of peer discovery and resource allocation by combining both the social and physical layer information in D2D underlay networks. The social relationship, which is modeled as the probability of selecting similar contents and estimated by using the Bayesian nonparametric models…

Data offloading and task allocation for cloudlet-assisted ad hoc mobile clouds

Nowadays, although the data processing capabilities of the modern mobile devices are developed in a fast speed, the resources are still limited in terms of processing capacity and battery lifetime. Some applications, in particular the computationally intensive ones, such as multimedia and gaming, often require more computational resources than a mobile device can afford. One way to address such a problem is that the mobile device can offload those tasks to the centralized cloud with data centers, the nearby cloudlet or ad hoc mobile cloud. In this paper, we propose a data offloading and task allocation scheme for a cloudlet-assisted ad hoc mobile cloud in which the master device (MD) who ha…

Incentive Mechanism for Resource Allocation in Wireless Virtualized Networks with Multiple Infrastructure Providers

To accommodate the explosively growing demands for mobile traffic service, wireless network virtualization is proposed as the main evolution towards 5G. In this work, a novel contract theoretic incentive mechanism is proposed to study how to manage the resources and provide services to the users in the wireless virtualized networks. We consider that the infrastructure providers (InPs) own the physical networks and the mobile virtual network operator (MVNO) has the service information of the users and needs to lease the physical radio resources for providing services. In particular, we utilize the contract theoretic approach to model the resource trading process between the MVNO and multiple…

Operator Revenue Analysis for Device-to-Device Communications Overlaying Cellular Network

Device-to-device (D2D) communications has recently gathered significant research interest due to its efficient utilization of already depleting wireless spectrum. In this article, we considered a scenario where D2D users communicate in the presence of cellular users in an overlay network setup. In order to analyze the revenue of service providers in monetary terms, the paper provides exact expressions of operator profit for both D2D and cellular users. More specifically, we take into account different network parameters including user density, transmit power and channel variations to understand their impact on the total revenue of the operator. Finally, we derive the balancing value of freq…

Spectrum and energy efficient solutions for OFDMA collaborative wireless networks

Sparse nonnegative tensor decomposition using proximal algorithm and inexact block coordinate descent scheme

Nonnegative tensor decomposition is a versatile tool for multiway data analysis, by which the extracted components are nonnegative and usually sparse. Nevertheless, the sparsity is only a side effect and cannot be explicitly controlled without additional regularization. In this paper, we investigated the nonnegative CANDECOMP/PARAFAC (NCP) decomposition with the sparse regularization item using l1-norm (sparse NCP). When high sparsity is imposed, the factor matrices will contain more zero components and will not be of full column rank. Thus, the sparse NCP is prone to rank deficiency, and the algorithms of sparse NCP may not converge. In this paper, we proposed a novel model of sparse NCP w…

Incentive Mechanism for Edge Computing-Based Blockchain: A Sequential Game Approach

The development of the blockchain framework is able to provide feasible solutions for a wide range of Industrial Internet of Things (IIoT) applications. While the IIoT devices are usually resource-limited, how to make sure the acquisition of computational resources and participation of the devices will be the driving force to realize blockchain. In this work, an edge computing-based blockchain framework is considered, where multiple edge service providers (ESPs) can provide computational resources to the IIoT devices. We focus on investigating the trading between the devices and ESPs, where ESPs are the sellers and devices are the buyers. A sequential game is formulated and by exploring the…

Secrecy analysis and learning-based optimization of cooperative NOMA SWIPT systems

Non-orthogonal multiple access (NOMA) is considered to be one of the best candidates for future networks due to its ability to serve multiple users using the same resource block. Although early studies have focused on transmission reliability and energy efficiency, recent works are considering cooperation among the nodes. The cooperative NOMA techniques allow the user with a better channel (near user) to act as a relay between the source and the user experiencing poor channel (far user). This paper considers the link security aspect of energy harvesting cooperative NOMA users. In particular, the near user applies the decode-and-forward (DF) protocol for relaying the message of the source no…

Learn to Cache: Machine Learning for Network Edge Caching in the Big Data Era

The unprecedented growth of wireless data traffic not only challenges the design and evolution of the wireless network architecture, but also brings about profound opportunities to drive and improve future networks. Meanwhile, the evolution of communications and computing technologies can make the network edge, such as BSs or UEs, become intelligent and rich in terms of computing and communications capabilities, which intuitively enables big data analytics at the network edge. In this article, we propose to explore big data analytics to advance edge caching capability, which is considered as a promising approach to improve network efficiency and alleviate the high demand for the radio resou…

Age of Information Based URLLC-enabled UAV Wireless Communications System

This paper considers an unmanned aerial vehicles (UAV) communication network, where UAV operate as an aerial mobile relay between a source and a destination of the network. To capture the “timelines” of the received information at the destination node, a new performance metric named age of information (AoI) is considered. In addition, a short packet communication scheme maintains low latency in the proposed UAV wireless communication system. The finite block-length theory investigates the performances of short packet communications scheme in the UAV-assisted wireless communications system. In this paper, the Average Age of Information (AAoI) is estimated by applying the Stochastic Hybrid Sy…

Single-trial-based temporal principal component analysis on extracting event-related potentials of interest for an individual subject.

Background: Temporal principal component analysis (tPCA) has been widely used to extract event-related potentials (ERPs) at group level of multiple subjects ERP data and it assumes that the underlying factor loading is fixed across participants. However, such assumption may fail to work if latency and phase for one ERP vary considerably across participants. Furthermore, effect of number of trials on tPCA decomposition has not been systematically examined as well, especially for within-subject PCA. New method: We reanalyzed a real ERP data of an emotional experiment using tPCA to extract N2 and P2 from single-trial EEG of an individual. We also explored influence of the number of trials (con…

Reducing Power Consumption of Wireless Networks Through Collaborative DMC Mobile Clusters

Reducing the energy consumption of the wireless network is significantly important to the economic and ecological sustainability of the ICT industry, as high energy consumption may limit the performance of wireless networks and is one of the main network costs. To solve energy consumption problem, especially on the terminal side, a scheme known as distributed mobile cloud (DMC) is considered to be a potential solution. Multiple mobile terminals (MTs) can cooperative to take advantage of good quality links among the MTs to save energy when receiving from the Base Station (BS). In this paper, we aim to find the optimal transmit power to further reduce the energy consumption of DMC. From simul…

Resource Allocation and Computation Offloading for Multi-Access Edge Computing With Fronthaul and Backhaul Constraints

Edge computing is able to provide proximity solutions for the future wireless network to accommodate different types of devices with various computing service demands. Meanwhile, in order to provide ubiquitous connectivities to massive devices over a relatively large area, densely deploying remote radio head (RRH) is considered as a cost-efficient solution. In this work, we consider a vertical and heterogeneous multi-access edge computing system. In the system, the RRHs are deployed for providing wireless access for the users and the edge node with computing capability can process the computation requests from the users. With the objective to minimize the total energy consumption for proces…

Adapting Downlink Power in Fronthaul-Constrained Hierarchical Software-Defined RANs

Abstract The proof-of-concept software-defined radio access network (RAN) is not flexible enough due to the inherent delay and the necessity of high-capacity fronthaul links. We are hence motivated to propose a hierarchical software-defined RAN architecture, over which the base stations (BSs) are abstracted into multiple virtual local controllers while these local controllers are administered by a high-level controller. Under such a hierarchical network architecture, we particularly investigate in this paper how to adapt the BS transmit power over a long term according to the network dynamics under the constraints of mobile user queue stability and limited fronthaul capacity. We first formu…

Optimal Buffer Resource Allocation in Wireless Caching Networks

Wireless caching systems have been exhaustively investigated in recent years. Due to limited buffer capacity, and unbalanced arrival and service rates, the backlogs may exist in the caching node and even cause buffer overflow. In this paper, we first investigate the relationship among backlogs, buffer capacity, data arrival rate and service rate, utilizing the martingale theory which is flexible in handling any arrival and service processes. Then given a target buffer overflow probability, the minimal required buffer portion is determined. If the devoted buffer capacity can fulfill all serving users' minimal buffer requirements, an optimization problem is constructed with the objective to m…

Resource Allocation and Computation Offloading for Wireless Powered Mobile Edge Computing

In this paper, we investigate a resource allocation and computation offloading problem in a heterogeneous mobile edge computing (MEC) system. In the considered system, a wireless power transfer (WPT) base station (BS) with an MEC sever is able to deliver wireless energy to the mobile devices (MDs), and the MDs can utilize the harvested energy for local computing or task offloading to the WPT BS or a Macro BS (MBS) with a stronger computing server. In particular, we consider that the WPT BS can utilize full- or half-duplex wireless energy transmission mode to empower the MDs. The aim of this work focuses on optimizing the offloading decision, full/half-duplex energy harvesting mode and energ…

Energy efficient and distributed resource allocation for wireless powered OFDMA multi-cell networks

In this paper, we investigate the energy efficient resource allocation problem for the wireless powered OFDMA multi-cell networks. In the considered system, the users who have data to transmit in the uplink can only be empowered by the wireless power obtained from multiple base stations (BSs) with a large scale of multiple antennas in the downlink. A time division protocol is considered to divide the time of wireless power transfer (WPT) in the downlink and wireless information transfer (WIT) in the uplink into separate time slot. With the objective to improve the energy efficiency (EE) of the system, we propose the antenna selection, time allocation, subcarrier and power allocation schemes…

Communication-Efficient Federated Learning in Channel Constrained Internet of Things

Federated learning (FL) is able to utilize the computing capability and maintain the privacy of the end devices by collecting and aggregating the locally trained learning model parameters while keeping the local personal data. As the most widely-used FL framework,Jederated averaging (FedAvg) suffers an expensive communication cost especially when there are large amounts of devices involving the FL process. Moreover, when considering asynchronous FL, the slowest device becomes the bottleneck for the cask effect and determines the overall latency. In this work, we propose a communication-efficient federated learning framework with partial model aggregation (CE-FedPA) algorithm to utilize comp…

SingleChannelNet : A model for automatic sleep stage classification with raw single-channel EEG

In diagnosing sleep disorders, sleep stage classification is a very essential yet time-consuming process. Various existing state-of-the-art approaches rely on hand-crafted features and multi-modality polysomnography (PSG) data, where prior knowledge is compulsory and high computation cost can be expected. Besides, it is a big challenge to handle the task with raw single-channel electroencephalogram (EEG). To overcome these shortcomings, this paper proposes an end-to-end framework with a deep neural network, namely SingleChannelNet, for automatic sleep stage classification based on raw single-channel EEG. The proposed model utilizes a 90s epoch as the textual input and employs two multi-conv…

Energy-Efficient M2M Communications in for Industrial Automation

M2M communication with autonomous data acquisition and exchange plays a key role in realizing the “control”-oriented tactile Internet (TI) applications such as industrial automation. In this chapter, we develop a two-stage access control and resource allocation algorithm. In the first stage, we introduce a contract-based incentive mechanism to motivate some delay-tolerant machine-type communication (MTC) devices to postpone their access demands in exchange for higher access opportunities. In the second stage, a long-term cross-layer online resource allocation approach is based on Lyapunov optimization, which jointly optimizes rate control, power allocation, and channel selection without pri…

Service Provisioning with Multiple Service Providers in 5G Ultra-dense Small Cell Networks

In this work, a game theoretical approach for addressing the virtual network service providers (NSPs), small cell provider (SCP) and user interaction in heterogenous small cell networks is presented. In particular, we consider the users can select the services of different NSPs based on their prices. The NSPs have no dedicated hardware and need to rent from the SCP in term of radio resources, e.g., small cell base stations (SBSs) in order to provide satisfied services to the users. Due to the fact that the selfish parties involved aim at maximizing their own profits, a hierarchical dynamic game framework is presented to address interactive decision problem. In the lower-level, a Stackelberg…

Energy efficient optimisation for large‐scale multiple‐antenna system with WPT

In this study, an energy-efficient optimisation scheme for a large-scale multiple-antenna system with wireless power transfer (WPT) is presented. In the considered system, the user is charged by a base station with a large number of antennas via downlink WPT and then utilises the received power to carry out uplink data transmission. Novel antenna selection, time allocation and power allocation schemes are presented to optimise the energy efficiency of the overall system. In addition, the authors also consider channel state information cannot be perfectly obtained when designing the resource allocation schemes. The non-linear fractional programming-based algorithm is utilised to address the …

Energy-Efficient Context-Aware Resource Allocation for Edge-Computing-Empowered Industrial IoT

Edge computing provides a promising paradigm to support the implementation of industrial Internet of Things (IIoT) by offloading computational-intensive tasks from resource-limited machine-type devices (MTDs) to powerful edge servers. However, the performance gain of edge computing may be severely compromised due to limited spectrum resources, capacity-constrained batteries, and context unawareness. In this chapter, we consider the optimization of channel selection which is critical for efficient and reliable task delivery. We aim at maximizing the long-term throughput subject to long-term constraints of energy budget and service reliability. We propose a learning-based channel selection fr…

Energy efficient optimisation for large-scale multiple-antenna system with WPT

In this study, an energy-efficient optimisation scheme for a large-scale multiple-antenna system with wireless power transfer (WPT) is presented. In the considered system, the user is charged by a base station with a large number of antennas via downlink WPT and then utilises the received power to carry out uplink data transmission. Novel antenna selection, time allocation and power allocation schemes are presented to optimise the energy efficiency of the overall system. In addition, the authors also consider channel state information cannot be perfectly obtained when designing the resource allocation schemes. The non-linear fractional programming-based algorithm is utilised to address the …

Socially-aware Dynamic Computation Offloading Scheme for Fog Computing System with Energy Harvesting Devices

Fog computing is considered as a promising technology to meet the ever-increasing computation requests from a wide variety of mobile applications. By offloading the computation-intensive requests to the fog node or the central cloud, the performance of the applications, such as energy consumption and delay, are able to be significantly enhanced. Meanwhile, utilizing the recent advances of social network and energy harvesting (EH) techniques, the system performance could be further improved. In this paper, we take the social relationships of the EH mobile devices (MDs) into the design of computational offloading scheme in fog computing. With the objective to minimize the social group executi…

BEGIN: Big Data Enabled Energy-Efficient Vehicular Edge Computing

Vehicular edge computing is essential to support future emerging multimedia-rich and delay-sensitive applications in vehicular networks. However, the massive deployment of edge computing infrastructures induces new problems including energy consumption and carbon pollution. This motivates us to develop BEGIN (Big data enabled EnerGy-efficient vehIcular edge computiNg), a programmable, scalable, and flexible framework for integrating big data analytics with vehicular edge computing. In this article, we first present a comprehensive literature review. Then the overall design principle of BEGIN is described with an emphasis on computing domain and data domain convergence. In the next section, …

Energy Efficient Resource Allocation for Wireless Powered UAV Wireless Communication System with Short Packet

The unmanned aerial vehicle (UAV), which is prominent in its flexibility and low cost, is considered to be fully utilized in the future wireless communication system to provide flexible services and improve connectivities. In this paper, we investigate the resource allocation problem in a wireless powered UAV communication system. In this considered system, The UAV acts as hybrid access point (HAP), which can first perform wireless power transfer in the downlink and charge the Internet of Thing (IoT) user devices (UDs). The UDs can use the harvested energy to deliver the data to the UAV. In the uplink, we explicitly consider short packet communication (SPC) as the transmission feature, whic…

Software Defined Machine-to-Machine Communication for Smart Energy Management in Power Grids

The successful realization of smart energy management relies on ubiquitous and reliable information exchange among millions of sensors and actuators deployed in the field with little or no human intervention. This motivates us to introduce a unified communication framework for smart energy management by exploring the integration of software-defined networking (SDN) with M2M communication. In this chapter, the overall design of the software-defined M2M (SD-M2M) framework is presented, with an emphasis on its technical contributions to cost reduction, fine granularity resource allocation, and end-to-end QoS guarantee. Then, a case study is conducted for a electric vehicle energy management sy…

Joint Radio and Computational Resource Allocation in IoT Fog Computing

The current cloud-based Internet-of-Things (IoT) model has revealed great potential in offering storage and computing services to the IoT users. Fog computing, as an emerging paradigm to complement the cloud computing platform, has been proposed to extend the IoT role to the edge of the network. With fog computing, service providers can exchange the control signals with the users for specific task requirements, and offload users’ delay-sensitive tasks directly to the widely distributed fog nodes at the network edge, and thus improving user experience. So far, most existing works have focused on either the radio or computational resource allocation in the fog computing. In this work, we inve…

Energy-Efficient Resource Allocationin for D2D Enabled Cellular Networks

Energy-efficiency (EE) is critical for D2D enabled cellular networks due to limited battery capacity and severe co-channel interference. In this chapter, we address the EE optimization problem by adopting a stable matching approach. The NP-hard joint resource allocation problem is formulated as a one-to-one matching problem under two-sided preferences, which vary dynamically with channel states and interference levels. A game-theoretic approach is employed to analyze the interactions and correlations among user equipments (UEs), and an iterative power allocation algorithm is developed to establish mutual preferences based on nonlinear fractional programming. We then employ the Gale–Shapley …

Reputation-Based Blockchain for Spatial Crowdsourcing in Vehicular Networks

The sharing of high-quality traffic information plays a crucial role in enhancing the driving experience and safety performance for vehicular networks, especially in the development of electric vehicles (EVs). The crowdsourcing-based real-time navigation of charging piles is characterized by low delay and high accuracy. However, due to the lack of an effective incentive mechanism and the resource-consuming bottleneck of sharing real-time road conditions, methods to recruit or motivate more EVs to provide high-quality information gathering has attracted considerable interest. In this paper, we first introduce a blockchain platform, where EVs act as the blockchain nodes, and a reputation-base…

Stable-Matching-Based Energy-Efficient Context-Aware Resource Allocation for Ultra-Dense Small Cells

Implementing caching to ultra-densely deployed small cells provides a promising solution for satisfying the stringent quality of service (QoS) requirements of delay-sensitive applications with limited backhaul capacity. With the rapidly increasing energy consumption, in this chapter, the authors investigate the NP-hard energy-efficient context-aware resource allocation problem and formulate it as a one-to-one matching problem. The preference lists in the matching are modeled based on the optimum energy efficiency (EE) under specified matching, which can be obtained by using an iterative power allocation algorithm based on nonlinear fractional programming and Lagrange dual decomposition. Nex…

Energy-Efficient Resource Allocation and User Scheduling for Collaborative Mobile Clouds With Hybrid Receivers

In this paper, we study the resource allocation and user scheduling algorithm for minimizing the energy cost of data transmission in the context of OFDMA collaborative mobile cloud (CMC) with simultaneous wireless information and power transfer (SWIPT) receivers. The CMC, which consists of several collaborating MTs offers one potential solution for downlink con- tent distribution and for the energy consumption reduction at the terminal side. Meanwhile, as RF signal can carry both informa- tion and energy simultaneously, the induced SWIPT has gained much attention for energy efficiency design of mobile nodes. Previous work on the design of CMC system mainly focused on the cloud formulation o…

User-cell association in heterogenous small cell networks: A context-aware approach

Deploying small cells to complement the traditional cellular networks is foreseen as a major feature of the next generation of wireless networks. In this paper, a novel approach for addressing the cell association problem in heterogenous small cell networks is proposed. The presented approach exploits different types of information extracted from the user devices and environment to improve the way in which users are assigned to their serving small cell base stations (SBSs). We formulate the problem within the framework of matching theory, where the players, namely the users and SBSs, have interdependent preferences over the members of the opposite set. We also utilize the fuzzy synthetic ev…

UAV-Aided Multi-Antenna Covert Communication Against Multiple Wardens

In this paper, we propose a UAV-aided covert communication scheme assisted by a multi-antenna jammer to maximize the transmission rate between a ground transmitter and a UAV receiver against several randomly distributed wardens. The transmitter adopts the maximum ratio transmission, while the jammer zero-forces its transmitted signal at the UAV to disturb the monitoring at wardens without interfering the legitimate transmission. First, we analyze the detection performance and derive the optimal threshold for each warden to minimize its detection outage probability (DOP). Then, with the worst situation in which all wardens set their respective optimal thresholds to achieve the minimum global…

Anomaly Detection and Classification of Household Electricity Data : A Time Window and Multilayer Hierarchical Network Approach

With the increasing popularity of the smart grid, huge volumes of data are gathered from numerous sensors. How to classify, store, and analyze massive datasets to facilitate the development of the smart grid has recently attracted much attention. In particular, with the popularity of household smart meters and electricity monitoring sensors, a large amount of data can be obtained to analyze household electricity usage so as to better diagnose the leakage and theft behaviors, identify man-made tampering and data fraud, and detect powerline loss. In this paper, the time window method is first proposed to obtain the features and potential periodicity of household electricity data. Combining th…

Multi-objective Optimization for Computation Offloading in Fog Computing

Fog computing system is an emergent architecture for providing computing, storage, control, and networking capabilities for realizing Internet of Things. In the fog computing system, the mobile devices (MDs) can offload its data or computational expensive tasks to the fog node within its proximity, instead of distant cloud. Although offloading can reduce energy consumption at the MDs, it may also incur a larger execution delay including transmission time between the MDs and the fog/cloud servers, and waiting and execution time at the servers. Therefore, how to balance the energy consumption and delay performance is of research importance. Moreover, based on the energy consumption and delay,…

Energy Efficient Resource Allocation and User Scheduling for Collaborative Mobile Clouds with Hybrid Receivers

In this paper, we study the resource allocation and user scheduling algorithm for minimizing the energy cost of data transmission in the context of OFDMA collaborative mobile cloud (CMC) with simultaneous wireless information and power transfer (SWIPT) receivers. The CMC, which consists of several collaborating MTs offers one potential solution for downlink content distribution and for the energy consumption reduction at the terminal side. Meanwhile, as RF signal can carry both information and energy simultaneously, the induced SWIPT has gained much attention for energy efficiency design of mobile nodes. Previous work on the design of CMC system mainly focused on the cloud formulation or en…

Licensed and Unlicensed Spectrum Management for Energy-Efficient Cognitive M2M

Edge computing has emerged as a promising solution for relieving the tension between resource-limited MTDs and computational-intensive tasks. To realize successful task offloading with limited spectrum, we focus on the cognitive machine-to-machine (CM2M) paradigm which enables a massive number of MTDs to either opportunistically use the licensed spectrum that is temporarily available, or to exploit the under-utilized unlicensed spectrum. We formulate the channel selection problem with both licensed and unlicensed spectrum as an adversarial multi-armed bandit (MAB) problem, and combine the exponential-weight algorithm for exploration and exploitation (EXP3) and Lyapunov optimization to devel…

SAGECELL: Software-Defined Space-Air-Ground Integrated Moving Cells

Ultra-dense networks (UDNs) provide an effective solution to accommodate the explosively growing data traffic of multimedia services and real-time applications. However, the densification of large numbers of static small cells faces many fundamental challenges, including deployment cost, energy consumption and control, and so on. This motivates us to develop software-defined space-air-ground integrated moving cells (SAGECELL), a programmable, scalable, and flexible framework to integrate space, air, and ground resources for matching dynamic traffic demands with network capacity supplies. First, we provide a comprehensive review of state-of-the-art literature. Then the conceptual architectur…