Improved Energy-Efficient Ant-Based Routing Algorithm in Wireless Sensor Networks

1 Introduction

The advancement in technology has produced the availability of small and low cost sensor nodes with capability of sensing types of physical, environmental conditions, data processing, and wireless communication (Akyildiz et al., 2002; Katz et al., 1999; Min et al., 2001; Rabaey et al., 2000; Sohrabi et al., 2000). The sensing circuitry measures ambient conditions related to the environment surrounding the sensor, which transforms them into an electric signal. Processing such a signal, reveals some properties about objects located and/or events happening in the vicinity of the sensor. The sensor sends such collected data, usually via radio transmitter, to a command center (sink) either directly or through a data concentration center (a gateway). The decrease in the size and cost of sensors, resulting from such technological advances, has fueled interest in the possible use of large set of disposable unattended sensors. Such interest has motivated intensive research in the past few years addressing the potential of collaboration among sensors in data gathering and processing and the coordination and management of the sensing activity and data flow to the sink. A natural architecture for such collaborative distributed sensors is a network with wireless links that can be formed among the sensors in an ad hoc manner.

The main goal of our study is to maintain network lifetime at a maximum, while reducing Energy usage by the nodes and discover the shortest paths from the source nodes to the base node (sink) using a Improved Energy-Efficient Ant-Based Routing Algorithm (IEEABR).

The chapter is organized in the following format: The introductory part of the chapter provided in section 1, covers a general perspective and the objective of the chapter. Section 2 the WSNs and previous work on routing, deals with wireless sensor networks while looking at its applications and routing algorithms, different methods of routing using the popular ACO and generally comparing the different methods of routing. Section 3 gives detailed explanation of our proposed algorithm, the IEEABR. Section 4 looks in to analyze simulation results while also looking at the simulation environment and the trace files. Finally, section 5 concludes the chapter with an open research problems and future work to be done, and a comparative summary of our results with the IABR and EEABR. At the end of the section were provision for References and Additional readings for detail of some routing Algorithms.