IEEE Transactions on Network Science and Engineering · 2020 · 34 citations · 38 references
ComputingComputer ScienceComputer SystemsEdge ComputingMobile ComputingVirtualizationCompute Resource ManagementEdge Computing InfrastructureEdge Resource ManagementEnergy-efficient Mobile ComputingMobile Edge ComputingTask OffloadingCoordinationEdge Computing OffloadingEdge Task OffloadingEnergy-aware Task OffloadingMobile Edge Computing ArchitectureMobile Edge OffloadingService OffloadingVirtual Machines
The popularity of mobile devices has driven the occurrence of ultra-dense wireless networks (UDNs) to accommodate high volumes of data therein generated by mobile users (MUs) running various mobile applications, such as virtual reality/augmented reality (VR/AR) and online gaming. Since many such mobile applications are computation-intensive, mobile edge computing (MEC), a promising computing paradigm that can provide on-demand computation resources (i.e., virtual machines (VMs)), is considered to adopt for allowing MUs to offload their computation tasks to EgSvrs in the proximity. Previous works have developed many schemes to schedule computation tasks to be offloaded to edge servers (EgSvrs). However, these developed schemes are centralized, which are vulnerable to congested coordination operations, and have no trustworthiness guarantee as well. In this paper, we propose to design a decentralized coordination scheme to orchestrate MUs and EgSvrs for scheduling computation tasks to their right VMs by taking advantage of blockchain technology. Specifically, we develop an efficient task-VM matching algorithm that jointly considers task execution time and energy consumption. Particularly, we prove the stability of the task-VM matching achieved by the developed matching algorithm. Besides, we further implement the developed task-VM matching algorithm on the blockchain by developing a smart matching contract to perform task-VM matching on the blockchain without trusted third parties. Extensive simulation results demonstrate that our decentralized coordination scheme can improve the performance significantly and converge to a stable state very quickly.
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