Peer-to-Peer Enhanced Task Scheduling for D2D Enabled MEC Network

Xie, Zhigang; Song, Xin; Xu, Siyang

doi:10.1109/access.2020.3013025

Cited by 17 publications

(5 citation statements)

References 31 publications

(40 reference statements)

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“…In Chen, Zhang, and Yuan (2020), authors focused on jointly optimizing the decisions to maximize the utility of the MEC system which accounted for both the computation throughput and the fairness among different cells, by formulating a stochastic optimization problem subject to the constraints of queue stability and energy budget. In Xie et al (2020), authors proposed a peer-to-peer enhanced task scheduling framework to minimize the average task duration in device-to-device enabled MEC network by jointly optimizing the task scheduling decision and the computational resource allocation. In Jiang et al (2020), authors proposed a hybrid deep learning based online offloading framework where a large-scale path-loss fuzzy c-means algorithm was first proposed and used to predict the optimal positions of ground vehicles and unmanned aerial vehicles.…”

Section: Related Workmentioning

confidence: 99%

Preschool education optimization based on mobile edge computing under COVID‐19

2022

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The COVID-19 pandemic has brought profound changes in people's live and work. It has also accelerated the development of education from traditional model to online model, which is particularly important in preschool education. Preschoolers communicate with teachers through online video, so how to provide high quality and low latency online teaching has become a new challenge. In cloud computing, users offload computing tasks to the cloud to meet the high computing demands of their devices, but cloud-based solutions have led to huge bandwidth usage and unpredictable latency. In order to solve this problem, mobile edge computing (MEC) deploys the server at the edge of the network to provide the service with close range and low latency. In task scheduling, edge computing (EC) devices have rational thinking, and they are unwilling to collaborate with MEC server to perform tasks due to their selfishness. Therefore, it is necessary to design an effective incentive mechanism to encourage the collaboration of EC devices. Through analysis of MEC server and EC devices, we propose a distributed task scheduling algorithm-Stackelberg game approach based on alternating direction method of multipliers, which selects the appropriate incentive mechanism to encourage the collaboration of EC devices.The experimental results demonstrate that the proposed approach can rapidly converge to a certain accuracy within 40 iterations, and in incentive mechanism comparison and quality of experience, the proposed approach also has a good performance in anti-jitter and low latency.

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Section: Related Workmentioning

confidence: 99%

Preschool education optimization based on mobile edge computing under COVID‐19

2022

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“…In [34], the authors creatively proposed a deep learning architecture based on tightly connected network and proposed a corresponding multitask parallel scheduling algorithm. In [35], a peer-to-peer (P2P) enhanced task scheduling framework to minimize the average task duration in device-to-device (D2D) network was proposed. In the framework, an iterative algorithm based on alternating optimization and sorting technology was used to solve the approximate optimal scheduling solution.…”

Section: Related Workmentioning

confidence: 99%

“…Obviously, these factors also have a great impact on the efficiency of subsequent task scheduling. Although papers [31][32][33][34][35] focus on these two factors to optimize the task offloading process, they are not considered as a whole. However, task slicing is closely related to its offloading sequence, and different slicing schemes should correspond to different offloading sequence to optimize the execution delay of the task to the maximum extent.…”

Section: Related Workmentioning

confidence: 99%

An Effective Task Offloading Method for Separable Complex Mobile Terminal Tasks

Liu

Zhou

Wang

et al. 2022

Wireless Communications and Mobile Computing

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Due to limited energy and computing power of IoT devices, they cannot handle complex tasks. Edge computing technology effectively solves the requirements of computing power and response delay for complex tasks in devices by migrating computing power to the vicinity of IoT devices. For a separable complex task on IoT terminal, we focus on the effects of data distribution, dependencies, and offloading sequence of subtasks on its total delay when it is offloaded to edge servers. Through comprehensively considering these factors, we study the slicing and choreographing method during the offloading process of a complex task. Firstly, a task slicing method based on hierarchical clustering is presented and an improved hierarchical clustering algorithm is used to obtain the optimal solution of task partitioning. Secondly, a task choreographing method based on overlapping the longest path is presented. Finally, through the simulation experiments of complex tasks with different structures and loads, the effectiveness of our method is verified.

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“…In order to support wireless networks and improve their Quality of Service (QoS), UAVs may be deployed rapidly and effectively due to their flexibility and mobility [41]. In the latter, MEC allows users to offload computational tasks to the edge server [42], which may reduce device costs and improve QoS [43]. However, the presence of D2D technology in the B5G network plays a vital role in assisting MEC and UAVs to enable communications when conventional terrestrial networks are damaged or infeasible [44].…”

Section: Introductionmentioning

confidence: 99%

A Survey of Resource Management in D2D Communication for B5G Networks

et al. 2023

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Due to the vast rise of users, the variety of application requirements, and the enormous necessity for ubiquitous connectivity anytime and anywhere, integration of new technologies and ideas are required. Therefore, Device to Device (D2D) communication technology has been regarded as a critical concern for Beyond Fifth Generation (B5G) networks. In the D2D technology, devices in close proximity may connect without using a Base Station (BS). Consequently, improving the capacity and performance of traditional networks. The major objectives are to accomplish a high geared data rate, increase the network coverage with low latency, and improve Energy Efficiency (EE) and Spectrum Efficiency (SE). However, the coexistence of D2D technology in the traditional network can pose many issues and challenges, such as power control, interference, spectrum access, security, and mode selection. Consequently, a comprehensive survey that includes an investigation of the current issues in D2D technology is required. In this survey, we present a new categorization of the most important aspects of resource management in B5G D2D communication, such as power allocation, spectrum allocation, interference management, and mode selection. Furthermore, we discuss the limitations and open issues of the current techniques and propose a model approach and future directions for D2D communication in B5G wireless networks. Our survey aims to assist researchers in exploring and improving D2D communication within the framework of forthcoming wireless networks.

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Peer-to-Peer Enhanced Task Scheduling for D2D Enabled MEC Network

Cited by 17 publications

References 31 publications

Preschool education optimization based on mobile edge computing under COVID‐19

Preschool education optimization based on mobile edge computing under COVID‐19

An Effective Task Offloading Method for Separable Complex Mobile Terminal Tasks

A Survey of Resource Management in D2D Communication for B5G Networks

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