Abstract
Wireless Sensor Networks (WSN) with a large number of tiny sensor nodes can be used as an effective tool for gathering data in various situations. Hierarchical cluster based routing protocol were proposed for increasing network lifetime in the WSN. Major issues of cluster based routing protocol are power consumption and over heading which reduces the overall lifetime of the sensor network. In this project we propose a new static clustering protocol technique which partitions the network into static clusters with static cluster heads, eliminating the dynamic over heading and reduces the power consumption thereby improving the performance of the network. The performance of the proposed algorithm will be evaluated with the help of network simulation tool.
Highlights
A Wireless Sensor Network is an infrastructure comprised of sensing, computing, and communication elements that gives an administrator the ability to instrument, observe, and react to events and phenomena in a specified environment
Due to advances in wireless communications and electronics over the last few years, the development of networks of low-cost, low-power, multifunctional sensors has received increasing attention. These sensors are small in size and able to sense, process data, and communicate with each other, typically over an RF channel. These are the different issues in wireless sensor networks
In [1] proposes EEPSC (Energy-Efficient Protocol with Static Clustering), a hierarchical static clustering based protocol, which eliminates the overhead of dynamic clustering and engages high power sensor nodes for power consuming tasks and as a result prolongs the network lifetime
Summary
A Wireless Sensor Network is an infrastructure comprised of sensing (measuring), computing, and communication elements that gives an administrator the ability to instrument, observe, and react to events and phenomena in a specified environment. There are four basic components in a sensor network:. Due to advances in wireless communications and electronics over the last few years, the development of networks of low-cost, low-power, multifunctional sensors has received increasing attention. These sensors are small in size and able to sense, process data, and communicate with each other, typically over an RF (radio frequency) channel
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