Clustered wireless sensor networks

The study of topology in randomly deployed wireless sensor networks (WSNs) is important in addressing the fundamental issue of stochastic coverage resulting from randomness in the deployment procedure and power management algorithms. This dissertation defines and studies clustered WSNs, WSNs whose topology due to the deployment procedure and the application requirements results in the phenomenon of clustering or clumping of nodes. The first part of this dissertation analyzes a range of topologies of clustered WSNs and their impact on the primary sensing objectives of coverage and connectivity. By exploiting the inherent advantages of clustered topologies of nodes, this dissertation presents techniques for optimizing the primary performance metrics of power consumption and network capacity. It analyzes clustering in the presence of obstacles, and studies varying levels of redundancy to determine the probability of coverage in the network. The proposed models for clustered WSNs embrace the domain of a wide range of topologies that are prevalent in actual real-world deployment scenarios, and call for clustering-specific protocols to enhance network performance. It has been shown that power management algorithms tailored to various clustering scenarios optimize the level of active coverage and maximize the network lifetime. The second part of this dissertation addresses the problem of edge effects and heavy traffic on queuing in clustered WSNs. In particular, an admission control model called directed ignoring model has been developed that aims to minimize the impact of edge effects in queuing by improving queuing metrics such as packet loss and wait time.

Name thesis:degree_name

Doctor of Philosophy in Electrical Engineering - (Ph.D.)

Discipline thesis:degree_discipline

Electrical and Computer Engineering

Year

2009

Author dc:creator

• Machado, Renita Margaret

Contributors dc:contributor

• Sirin Tekinay
• Guiling Wang
• Nirwan Ansari

• Wireless sensor networks
• Clustered topologies
• Cognitive networks
• Electrical and Electronics

Repository record dc:identifier

https://digitalcommons.njit.edu/dissertations/913

OAI identifier oai:identifier

oai:digitalcommons.njit.edu:dissertations-1968