0000000000262013
AUTHOR
Di Zhang
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…
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…
On Assessing Vulnerabilities of the 5G Networks to Adversarial Examples
The use of artificial intelligence and machine learning is recognized as the key enabler for 5G mobile networks which would allow service providers to tackle the network complexity and ensure security, reliability and allocation of the necessary resources to their customers in a dynamic, robust and trustworthy way. Dependability of the future generation networks on accurate and timely performance of its artificial intelligence components means that disturbance in the functionality of these components may have negative impact on the entire network. As a result, there is an increasing concern about the vulnerability of intelligent machine learning driven frameworks to adversarial effects. In …
Joint User Association and Dynamic Beam Operation for High Latitude Muti-beam LEO Satellites
In Low Earth Orbit (LEO) satellites, which run in polar orbit, the area of overlap among beams becomes wider as the latitude of satellites increases, which leads to intolerable interference and extra energy consumption. To minimize the onboard power with QoS requirements, we propose an energy optimization model with considering power allocation, user association and dynamic beam ON/OFF operation jointly. Moreover, the frequent beam ON/OFF operations lead to the large number of user handovers, so handover cost is also considered in the model. The original problem is decomposed into two levels due to the high coupling of variables and the successive convex approximation is employed. A low com…
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…
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…
Pathways towards a sustainable future envisioned by early-career conservation researchers
Scientists have warned decision-makers about the severe consequences of the global environmental crisis since the 1970s. Yet ecological degradation continues and little has been done to address climate change. We investigated early-career conservation researchers' (ECR) perspectives on, and prioritization of, actions furthering sustainability. We conducted a survey (n = 67) and an interactive workshop (n = 35) for ECR attendees of the 5th European Congress of Conservation Biology (2018). Building on these data and discussions, we identified ongoing and forthcoming advances in conservation science. These include increased transdisciplinarity, science communication, advocacy in conservati…
On Attacking Future 5G Networks with Adversarial Examples : Survey
The introduction of 5G technology along with the exponential growth in connected devices is expected to cause a challenge for the efficient and reliable network resource allocation. Network providers are now required to dynamically create and deploy multiple services which function under various requirements in different vertical sectors while operating on top of the same physical infrastructure. The recent progress in artificial intelligence and machine learning is theorized to be a potential answer to the arising resource allocation challenges. It is therefore expected that future generation mobile networks will heavily depend on its artificial intelligence components which may result in …