Energy-efficient routing algorithms based on swarm intelligence for wireless sensor networks

Adamu, Murtala Zungeru (2013) Energy-efficient routing algorithms based on swarm intelligence for wireless sensor networks. PhD thesis, University of Nottingham.

[img] PDF (Thesis - as examined) - Repository staff only - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (18MB)


High efficient routing is an important factor to be considered in the design of limited energy resource Wireless Sensor Networks (WSNs). WSN environment has limited resources in terms of on-board energy, transmission power, processing, and storage, and this prompt for careful resource management and new routing protocol so as to counteract the challenges. This work first introduces the concept of wireless sensor networks, routing in WSNs, and its design factors as they affect routing protocols. Next, a comprehensive review of the most prominent routing protocols in WSN, from the classical routing protocols to swarm intelligence based protocols is presented. From the literature study, it was found that comparing routing protocols in WSNs is currently a very challenging task for protocol designers. Often, much time is required to re-create and re-simulate algorithms from descriptions in published papers to perform the comparison. Compounding the difficulty is that some simulation parameters and performance metrics may not be mentioned. We then see a need in the research community to have standard simulation and performance metrics for comparing different protocols. To this end, we re-simulate different protocols using a Matlab based simulator; Routing Modeling Application Simulation Environment (RMASE), and gives simulation results for standard simulation and performance metrics which we hope will serve as a benchmark for future comparisons for the research community.

Also, from the literature study, Energy Efficient Ant-Based Routing (EEABR) protocol was found to be the most efficient protocol due to its low energy consumption and low memory usage in WSNs nodes. Following this efficient protocol, an Improved Energy Efficient Ant-Based Routing (IEEABR) Protocol was proposed. Simulation were performed using Network Simulator-2 (NS-2), and from the results, our proposed algorithm performs better in terms of energy utilization efficiency, average energy of network nodes, and minimum energy of nodes. We further improved on the proposed protocol and simulation performed in another well-known WSNs MATLAB-based simulator; Routing Modeling Application Simulation Environment (RMASE), using static, mobile and dynamic scenario. Simulation results show that the proposed algorithm increases energy efficiency by up to 9% and 64% in converge-cast and target-tracking scenarios, respectively, over the original EEABR and also found to out-perform other four Ant-based routing protocols. We further show how this algorithm could be used for energy management in sensor network in the presence of energy harvesters.

However, high number of control packets is generated by the IEEABR due to the proactive nature of its path establishment. As such, a new routing protocol for WSNs that has less control packets due to its on-demand (reactive) nature is proposed. This new routing protocol termed Termite-hill is borrowed from the principles behind the termite’s mode of communication. We first study the foraging principles of a termite colony and utilize the inspirational concepts to develop a distributed, simple and energy-efficient routing protocol for WSNs. We perform simulation studies to compare the behavior and performance of the Termite-hill design with an existing classical and on-demand protocol (AODV) and other Swarm Intelligence (SI) based WSN protocols in both static, dynamic and mobility scenarios of WSN. The simulation results demonstrate that Termite-hill outperforms its competitors in most of the assumed scenarios and metrics with less latency.

Further studies show that the current practice in modeling and simulation of wireless sensor network (WSN) environments has been towards the development of functional WSN systems for event gathering, and optimization of the necessary performance metrics using heuristics and intuition. The evaluation and validation are mostly done using simulation approaches and practical implementations. Simulation studies, despite their wide use and merits of network systems and algorithm validation, have some drawbacks like long simulation times, and practical implementation might be cost ineffective if the system is not properly studied before the design. We therefore argue that simulation based validation and practical implementation of WSN systems and environments should be further strengthened through mathematical analysis. To conclude this work and to gain more insight on the behavior of the termite-hill routing algorithm, we developed our modeling framework for WSN topology and information extraction in a grid based and line based randomly distributed sensor network. We strengthen the work with a model of the effect of node mobility on energy consumption of Termite-hill routing algorithm as a function of event success rate and occasional change in topology. The results of our mathematical analysis were also compared with the simulation results.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Ang, Kenneth Li-Minn
Prabaharan, Savari R. S.
Keywords: swarm intelligence
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculties/Schools: University of Nottingham, Malaysia > Faculty of Science and Engineering — Engineering > Department of Electrical and Electronic Engineering
Item ID: 13127
Depositing User: EP, Services
Date Deposited: 08 Dec 2017 04:19
Last Modified: 07 May 2020 14:16

Actions (Archive Staff Only)

Edit View Edit View