Date of Award

5-1-2013

Degree Name

Master of Science

Department

Computer Science

First Advisor

Akkaya, Kemal

Abstract

Wireless sensor networks (WSNs) have been used in many applications by deploying tiny and stationary sensors. In recent years, a lot of studies proposed to introduce mobility capability to sensor nodes in order to exploit the advantages of mobility, particularly to restore connectivity in disjoint WSNs. While the studies demonstrated various capabilities of the proposed connectivity algorithms via simulation, real node and testbed implementations were mostly lacking due to unavailability of proper mobile nodes. Since this may hinder the direct applicability of the algorithms in realistic settings, testbeds which can be constructed with low-cost and commercial-off-the-shelf (COTS) hardware are required for realistic evaluations of the connectivity restoration algorithms. In this thesis, we design a low-cost mobile sensor node called iRobotSense, by integrating iRobot Create platform with IRIS sensor. Then, a mobile sensor network (MSN) testbed of iRobotSense nodes is used to implement and evaluate a widely used connectivity restoration algorithms, namely PADRA. Furthermore, all of the previous works exploiting mobility of the nodes to achieve recovery in a partitioned network have assumed reachability of the nodes to the selected destinations via a direct path movement. However, in real-world applications, such assumption makes the schemes impractical in case of encountering obstacles or intolerable terrains. Besides, even if direct path movement is successful, optimal energy efficiency cannot be attained by neglecting the elevation or friction of the terrain. Thus, in the recovery efforts, terrain type, elevation as well as the obstacles should be taken into account. In this thesis, we re-design an existing connectivity restoration approach in disjoint MSNs to fit these requirements and evaluate the performance issues when realistic terrains are assumed. Rather than following a direct path, movement trajectory is determined based on a path planning algorithm which considers the risk and elevation of terrain sections to be visited while avoiding obstacles and highly elevated terrain sections.

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