Improving the reliability of optimised link state routing in a smart grid neighbour area network based wireless mesh network using multiple metrics

Tsado, Y., Gamage, K. A.A. , Adebisi, B., Lund, D., Rabie, K. and Ikpehai, A. (2017) Improving the reliability of optimised link state routing in a smart grid neighbour area network based wireless mesh network using multiple metrics. Energies, 10(3), 287. (doi: 10.3390/en10030287)

Abstract

Reliable communication is the backbone of advanced metering infrastructure (AMI). Within the AMI, the neighbourhood area network (NAN) transports a multitude of traffic, each with unique requirements. In order to deliver an acceptable level of reliability and latency, the underlying network, such as the wireless mesh network(WMN), must provide or guarantee the quality-of-service (QoS) level required by the respective application traffic. Existing WMN routing protocols, such as optimised link state routing (OLSR), typically utilise a single metric and do not consider the requirements of individual traffic; hence, packets are delivered on a best-effort basis. This paper presents a QoS-aware WMN routing technique that employs multiple metrics in OLSR optimal path selection for AMI applications. The problems arising from this approach are non deterministic polynomial time (NP)-complete in nature, which were solved through the combined use of the analytical hierarchy process (AHP) algorithm and pruning techniques. For smart meters transmitting Internet Protocol (IP) packets of varying sizes at different intervals, the proposed technique considers the constraints of NAN and the applications’ traffic characteristics. The technique was developed by combining multiple OLSR path selection metrics with the AHP algorithminns-2. Compared with the conventional link metric in OLSR, the results show improvements of about 23% and 45% in latency and Packet Delivery Ratio (PDR), respectively, in a 25-node grid NAN.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Gamage, Professor Kelum
• Authors: Tsado, Y., Gamage, K. A.A., Adebisi, B., Lund, D., Rabie, K., and Ikpehai, A.
• College/School: College of Science and Engineering > School of Engineering
• Journal Name: Energies
• Publisher: MDPI
• ISSN: 1996-1073
• ISSN (Online): 1996-1073
• Published Online: 28 February 2017
• Copyright Holders: Copyright © 2017 The Authors
• First Published: First published in Energies 10(3):287
• Publisher Policy: Reproduced under a Creative Commons License