A QoS-Aware Data Aggregation Strategy for Resource Constrained IoT-Enabled AMI Network in Smart Grid

Asfandyar Khan; Syed Hamad Shirazi; Muhammad Adeel; Muhammad Assam; Yazeed Yasin Ghadi; Heba G. Mohamed; Yong Xie

doi:10.1109/ACCESS.2023.3312552

IEEE Access (Jan 2023)

A QoS-Aware Data Aggregation Strategy for Resource Constrained IoT-Enabled AMI Network in Smart Grid

Asfandyar Khan,
Syed Hamad Shirazi,
Muhammad Adeel,
Muhammad Assam,
Yazeed Yasin Ghadi,
Heba G. Mohamed,
Yong Xie

Affiliations

Asfandyar Khan: ORCiD; Department of Computer Science and Information Technology, Hazara University Mansehra, Mansehra, Pakistan
Syed Hamad Shirazi: ORCiD; Department of Computer Science and Information Technology, Hazara University Mansehra, Mansehra, Pakistan
Muhammad Adeel: ORCiD; The Hong Kong Polytechnic University, Hung Hom, Hong Kong
Muhammad Assam: Department of Software Engineering, University of Science and Technology at Bannu, Bannu, Khyber Pakhtunkhwa, Pakistan
Yazeed Yasin Ghadi: ORCiD; Department of Computer Science, Al Ain University, Al Ain, United Arab Emirates
Heba G. Mohamed: Department of Electrical Engineering, College of Engineering, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
Yong Xie: Department of Computer Technology and Applications, Qinghai University, Xining, China

DOI: https://doi.org/10.1109/ACCESS.2023.3312552
Journal volume & issue: Vol. 11
pp. 98988 – 99004

Abstract

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Emerging Internet of Things (IoT) technologies and applications have enabled the Smart Grid Utility control center to connect, monitor, control, and exchange data between the smart appliances, smart meters (SMs), data concentrators (DCs) and control center server (CCS) over the Internet. In particular, DC receives different Advanced Metering Infrastructure (AMI) applications data from multiple SMs for processing, queuing, aggregation, and forwarding onward towards the CCS over the things networking. However, DCs are expensive component of the AMI network. Recently, SMs are used as relay-devices to accomplish a cost-effective AMI network infrastructure to avoid the DC placement and bottleneck problem. However, SMs are recourse constrained (limited CPU, RAM, storage, and network capacity) intelligent devices which faces numerous communication challenges during outage conditions and summer peak hours where bulk amount of data with different traffic rates and latency are exchanged with the Utility control center. Therefore, an efficient data aggregation is required at relay-devices to deal with high volume of data exchange rates in order to optimize the constrained-resources of the AMI network. In this article, we propose a hybrid data aggregation strategy implemented on an aggregator-head (AH) in the clustering topology which performs data aggregation on the Interval Meter Reading (IMR) application data. AH induction greatly reduces the workload of the cluster-heads (CHs), and efficiently utilizes the constrained-resource of AMI devices in a cost effective-manner. The proposed strategy is evaluated for different existing approaches using the CloudSim simulation tool. Experimental and simulation results are obtained and compared which show the effectiveness of the proposed strategy such that limited resources are optimized, CH workload is minimized, and QoS of AMI applications are maintained.

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

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