Universiti Teknologi Malaysia Institutional Repository

Empirical studies of bio-inspired self-organized secure autonomous routing protocol

Saleem, Kashif and Fisal, Norsheila and Al-Muhtadi, Jalal (2014) Empirical studies of bio-inspired self-organized secure autonomous routing protocol. IEEE Sensors Journal, 14 (7). pp. 2232-2239. ISSN 1530-437X

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Official URL: http://dx.doi.org/10.1109/JSEN.2014.2308725

Abstract

A wireless sensor network (WSN) depends on miniaturized wireless sensor nodes that are deployed to monitor physical phenomena by communicating with each other with limited resources. The major factor to be tackled in the WSN is the network lifetime. A recent WSN routing protocol defined as secure real-time load distribution (SRTLD) uses broadcast packets to perform neighbor discovery and calculation at every hop while transferring data packets. Thus, it has high energy consumption. The proposed novel biological inspired self-organized secure autonomous routing protocol (BIOSARP) enhances SRTLD with an autonomous routing mechanism. In the BIOSARP mechanism, an optimal forwarding decision is obtained using improved ant colony optimization (IACO). In IACO, the pheromone value/probability is computed based on the end-to-end delay, remaining battery power, and link quality metrics. The proposed BIOSARP has been designed to reduce the broadcast and packet overhead in order to minimize the delay, packet loss, and power consumption in the WSN. In this paper, we present the architecture, implementation, and detailed outdoor experimental testbed results of the proposed BIOSARP. These results show that BIOSARP outperforms energy and delay ants algorithm, improved energy-efficient ant-based routing, and SRTLD in simulations and as well as in real testbed experimentation. The empirical study confirmed that BIOSARP offers better performance and can be practically implemented in the WSN applications for structural and environmental monitoring or battlefield surveillance.

Item Type:Article
Uncontrolled Keywords:ant colony optimization, autonomous agents, energy efficiency, evolutionary computation, monitoring, probabilistic logic, routing protocols, wireless sensor networks
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:52665
Deposited By: Siti Nor Hashidah Zakaria
Deposited On:01 Feb 2016 03:53
Last Modified:29 Jun 2018 22:56

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