Search results for "Edge Computing"
showing 10 items of 42 documents
Edge-Based Missing Data Imputation in Large-Scale Environments
2021
Smart cities leverage large amounts of data acquired in the urban environment in the context of decision support tools. These tools enable monitoring the environment to improve the quality of services offered to citizens. The increasing diffusion of personal Internet of things devices capable of sensing the physical environment allows for low-cost solutions to acquire a large amount of information within the urban environment. On the one hand, the use of mobile and intermittent sensors implies new scenarios of large-scale data analysis
Energy Efficient Optimization for Computation Offloading in Fog Computing System
2017
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…
An introduction to knowledge computing
2014
This paper deals with the challenges related to self-management and evolution of massive knowledge collections. We can assume that a self-managed knowledge graph needs a kind of a hybrid of: an explicit declarative self-knowledge (as knowledge about own properties and capabilities) and an explicit procedural self-knowledge (as knowledge on how to utilize own properties and the capabilities for the self-management).We offer an extension to a traditional RDF model of describing knowledge graphs according to the Semantic Web standards so that it will also allow to a knowledge entity to autonomously perform or query from remote services different computational executions needed. We also introdu…
Resource Allocation for Edge Computing-Based Blockchain: A Game Theoretic Approach
2020
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
2019
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…
Requirements for Energy Efficient Edge Computing: A Survey
2018
Internet of Things is evolving heavily in these times. One of the major obstacle is energy consumption in the IoT devices (sensor nodes and wireless gateways). The IoT devices are often battery powered wireless devices and thus reducing the energy consumption in these devices is essential to lengthen the lifetime of the device without battery change. It is possible to lengthen battery lifetime by efficient but lightweight sensor data analysis in close proximity of the sensor. Performing part of the sensor data analysis in the end device can reduce the amount of data needed to transmit wirelessly. Transmitting data wirelessly is very energy consuming task. At the same time, the privacy and s…
A Task Execution Scheme for Dew Computing with State-of-the-Art Smartphones
2021
The computing resources of today’s smartphones are underutilized most of the time. Using these resources could be highly beneficial in edge computing and fog computing contexts, for example, to support urban services for citizens. However, new challenges, especially regarding job scheduling, arise. Smartphones may form ad hoc networks, but individual devices highly differ in computational capabilities and (tolerable) energy usage. We take into account these particularities to validate a task execution scheme that relies on the computing power that clusters of mobile devices could provide. In this paper, we expand the study of several practical heuristics for job scheduling including executi…
Edge Computing-enabled Intrusion Detection for C-V2X Networks using Federated Learning
2022
Intrusion detection systems (IDS) have already demonstrated their effectiveness in detecting various attacks in cellular vehicle-to-everything (C-V2X) networks, especially when using machine learning (ML) techniques. However, it has been shown that generating ML-based models in a centralized way consumes a massive quantity of network resources, such as CPU/memory and bandwidth, which may represent a critical issue in such networks. To avoid this problem, the new concept of Federated Learning (FL) emerged to build ML-based models in a distributed and collaborative way. In such an approach, the set of nodes, e.g., vehicles or gNodeB, collaborate to create a global ML model trained across thes…
Efficiency of temporal sensor data compression methods to reduce LoRa-based sensor node energy consumption
2022
Purpose Minimizing the energy consumption in a wireless sensor node is important for lengthening the lifetime of a battery. Radio transmission is the most energy-consuming task in a wireless sensor node, and by compressing the sensor data in the online mode, it is possible to reduce the number of transmission periods. This study aims to demonstrate that temporal compression methods present an effective method for lengthening the lifetime of a battery-powered wireless sensor node. Design/methodology/approach In this study, the energy consumption of LoRa-based sensor node was evaluated and measured. The experiments were conducted with different LoRaWAN data rate parameters, with and without …
Co-simulated Digital Twin on the Network Edge: the case of platooning
2022
This paper presents an approach to create high fidelity Digital-Twin models for distributed multi-agent cyber-physical systems based on the combination of simulating components, generated from different modeling languages, each tailored for the specific domain of the subsystem. The approach specifically addresses the wireless communication domain, exploiting a Python module as a simulating component to evaluate the impact of network delay among the distributed elements of the system under analysis. A case study with a platoon of four vehicles following a leading car, all modeled in Simulink, is used to show the applicability of the approach, allowing the comparison between a Vehicle-to-Vehi…