Guide to Thesis and what this mean for Master’s Student in Information and Communication Technologies (ICT) including Telecommunications (TC) and Computer Science (CS). You can find a brief guidance on how to write thesis on our guidance page.
This page is dedicated to my master’s thesis entitled “Intelligent Multilevel Clustering in Heterogeneous Wireless Sensor Networks” and the special study as a prerequisite of the thesis named “Energy Efficient Sensor Networks“.
[box title=”Abstract of my Thesis” color=”#333333″]
Latest innovations in Wireless Sensor Networks (WSNs) have brought many possibilities for generating intelligence into the system specifically designed for custom needs. The most suitable network architecture for WSN is still an open issue, because architecture requirements vary according to need. The possibilities with heterogeneous networks and associated nodes within it can be deployed in eeffective hierarchy that multiple events can be handled appropriately besides improvement in the network life time. On this proposed work for Heterogeneous Wireless Sensor Networks (HWSN), the objective is to create intelligence among multiple events and process accordingly, while still preserving and giving more lifespan to the network.
In this architecture, event and energy, heterogeneity is considered to be prevalent in a large WSN wherein multilevel clusters are formed optimally. Lite nodes of each sensor type route directly to the temporary cluster heads. Then, the transmission of information takes places to immobile or micro mobile cluster head which before transmitting data to the fixed base station process for significance of an event intelligibly. Furthermore, since a large number of nodes are deployed uniformly, the uniform information collection is possible. The network longevity as compared with LEACH is also still higher in spite of heterogeneous network.
Keywords of the thesis: Biased Energy Network, Protocol Architecture, Event-sensing, Heterogeneous Network, Multi-level Clustering, Intelligent Network