Joint Optimal Software Caching, Computation Offloading and Communications Resource Allocation for Mobile Edge Computing

Wen, Wanli; Cui, Ying; Quek, Tony Q. S.; Zheng, Fu‐Chun; Jin, Shi

doi:10.1109/tvt.2020.2993359

Cited by 67 publications

(30 citation statements)

References 38 publications

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“…In order to improve the makespan and execution cost, M. Yang et al put forward an evolutionary heuristic-based multiobjective task scheduling model for fog environment [32]. Caching is an effective way to reduce the execution delay of tasks in edge computing, and thus some novel caching strategies have been proposed by researchers [33][34][35].…”

Section: Related Workmentioning

confidence: 99%

Blockchain-Enhanced Fair Task Scheduling for Cloud-Fog-Edge Coordination Environments: Model and Algorithm

Cao

et al. 2021

Security and Communication Networks

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The cloud-fog-edge hybrid system is the evolution of the traditional centralized cloud computing model. Through the combination of different levels of resources, it is able to handle service requests from terminal users with a lower latency. However, it is accompanied by greater uncertainty, unreliability, and instability due to the decentralization and regionalization of service processing, as well as the unreasonable and unfairness in resource allocation, task scheduling, and coordination, caused by the autonomy of node distribution. Therefore, this paper introduces blockchain technology to construct a trust-enabled interaction framework in a cloud-fog-edge environment, and through a double-chain structure, it improves the reliability and verifiability of task processing without a big management overhead. Furthermore, in order to fully consider the reasonability and load balance in service coordination and task scheduling, Berger’s model and the conception of service justice are introduced to perform reasonable matching of tasks and resources. We have developed a trust-based cloud-fog-edge service simulation system based on iFogsim, and through a large number of experiments, the performance of the proposed model is verified in terms of makespan, scheduling success rate, latency, and user satisfaction with some classical scheduling models.

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Section: Related Workmentioning

confidence: 99%

Blockchain-Enhanced Fair Task Scheduling for Cloud-Fog-Edge Coordination Environments: Model and Algorithm

Cao

et al. 2021

Security and Communication Networks

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“…The clustering algorithm is a strategy for clustering mobile terminal tasks in the MEC system. For the results obtained after clustering, it is hoped that the maximum distance standard deviation in all clusters is as small as possible [20]. It can not only ensure the quality of service and improve the user experience but also reduce the queuing delay of subsequent tasks, which is conducive to reducing system overhead.…”

Section: Clustering Algorithmmentioning

confidence: 99%

Application of Mobile Edge Computing Technology in Civil Aviation Express Marketing

2021

Wireless Communications and Mobile Computing

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With the popularization of mobile terminals and the rapid development of mobile communication technology, many PC-based services have placed high demands on data processing and storage functions. Cloud laptops that transfer data processing tasks to the cloud cannot meet the needs of users due to low latency and high-quality services. In view of this, some researchers have proposed the concept of mobile edge computing. Mobile edge computing (MEC) is based on the 5G evolution architecture. By deploying multiple service servers on the base station side near the edge of the user’s mobile core network, it provides nearby computing and processing services for user business. This article is aimed at studying the use of caching and MEC processing functions to design an effective caching and distribution mechanism across the network edge and apply it to civil aviation express marketing. This paper proposes to focus on mobile edge computing technology, combining it with data warehouse technology, clustering algorithm, and other methods to build an experimental model of MEC-based caching mechanism applied to civil aviation express marketing. The experimental results in this paper show that when the cache space and the number of service contents are constant, the LECC mechanism among the five cache mechanisms is more effective than LENC, LRU, and RR in cache hit rate, average content transmission delay, and transmission overhead. For example, with the same cache space, ATC under the LECC mechanism is about 4%~9%, 8%~13%, and 18%~22% lower than that of LENC, LRU, and RR, respectively.

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“…They proposed an approximation method with the advantage of low complexity for the solution of it. In [34], Wen et al jointly studied caching, computation offloading and time allocation for minimizing the energy consumption. In [37], Chen et al studied network slicing to support the demand of diverse services of mobile users without investigating computation offloading.…”

Section: Related Workmentioning

confidence: 99%

Optimal Resource Allocation for Multimedia Applications Offloading in Mobile Edge Computing

Chen¹,

Zhao²,

Li³

et al. 2021

IEEE Open J. Comput. Soc.

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Thanks to the development of the technologies in the wireless communications and Internet of Things (IoT), the adoption of mobile devices is growing rapidly. Accordingly, the number of multimedia applications like face recognition and augmented reality generated from various mobile devices is growing at an unprecedented rate. The processing of these multimedia applications needs a lot of computation resources and has to be processed as quickly as possible. However, as these mobile devices have limited computation resources, the undesirable response delay will occur. By offloading the multimedia applications to the edge cloud close to the access point (AP) or the cellular base station (BS), mobile edge computing (MEC) is considered as a prospective approach to improve the quality of service (QoS) and enhance the computing capacity of mobile devices. Multimedia applications offloading in a MEC system are studied in this paper. The objective of the studied problem is to minimize the execution delay of multimedia applications of all mobile devices by allocating both the communication resource and the computing resource in the edge server. An optimization problem is formulated and an efficient multimedia applications offloading scheme is proposed to get the solution. Simulation results are conducted to verify the proposed application offloading method, which show that there is a significant execution delay reduction.

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Joint Optimal Software Caching, Computation Offloading and Communications Resource Allocation for Mobile Edge Computing

Cited by 67 publications

References 38 publications

Blockchain-Enhanced Fair Task Scheduling for Cloud-Fog-Edge Coordination Environments: Model and Algorithm

Blockchain-Enhanced Fair Task Scheduling for Cloud-Fog-Edge Coordination Environments: Model and Algorithm

Application of Mobile Edge Computing Technology in Civil Aviation Express Marketing

Optimal Resource Allocation for Multimedia Applications Offloading in Mobile Edge Computing

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