JOURNAL ARTICLE

Market-Based Resource Allocation of Distributed Cloud Computing Services: Virtual Energy Storage Systems

Yuechuan TaoJing QiuShuying LaiXianzhuo SunJunhua Zhao

Year: 2022 Journal:   IEEE Internet of Things Journal Vol: 9 (22)Pages: 22811-22821   Publisher: Institute of Electrical and Electronics Engineers

Abstract

The cloud-based application is a major developing feature of smart grids. Apart from centralized Internet data centers (IDCs), distributed cloud resources (CRs) can also provide cloud computing services with low latency and high reliability. For the distributed cloud computing, CRs aggregators (CRAs) will integrate the distributed idle computing resources, which are dispersed energy consumers in the system, to form virtual IDCs. This article presents a market-based computing resource allocation method for distributed cloud computing services. The computing resource allocation refers to the approach to allocating the computing workloads to different CRs. First, the batch workload scheduling (BWS)-based virtual energy storage system (VESS) model and thermal inertia (TI)-based VESS model are proposed to help CRAs better aggregate the distributed CRs and characterize the energy consumption flexibility of the virtual IDCs. Then, the energy trading behavior of the CRAs in the transactive energy market is modeled in the resource allocation process. Case studies are conducted on a 55-bus electricity system. It can be found that energy consumption costs can be reduced by applying the proposed methodology, and revenues from providing cloud computing services can be increased.

Keywords:
Cloud computing Computer science Distributed computing Energy consumption Utility computing Virtual machine Resource allocation Scheduling (production processes) Computer network Cloud computing security Operating system Engineering

Metrics

14
Cited By
5.32
FWCI (Field Weighted Citation Impact)
32
Refs
0.95
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cloud Computing and Resource Management
Physical Sciences →  Computer Science →  Information Systems
Smart Grid Energy Management
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Distributed and Parallel Computing Systems
Physical Sciences →  Computer Science →  Computer Networks and Communications

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