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Problem statement: Nowadays sensors are very essential for today life to monitor environment where human cannot get involved very often. Wireless Sensor Networks (WSN) are used in many real world applications like environmental monitoring, traffic control, trajectory monitoring. It is more challenging for sensor network to sense and collect a large amount of data which are continuous over time, which in turn need to be forwarded to sink for further decision making process. Clustering of sensory data act as a nucleus job of data mining. A clustering in WSN involves selecting cluster heads and assigning cluster members(sensors) to it for efficient data relay. The contraints in power supply, limited communication, bandwidh, storage resoures are the major challenges in WSN facing today. Conclusion: Proposed study presents K-Means Data Relay (K-MDR) clustering algorithm for grouping sensor nodes there by reducing number of nodes transmitting data to sink node, it reduces the communication overhead and in this manner increase the network performance. Furthermore Conserve and Observe Modes (COM) algorithm reduces the number of nodes within the cluster there by without compromising the coverage face major challenges such as limited communication bandwidth, constraints in power supply and storage resources region of it. The contribution of K-MDR is to reduce power consumption finally the simulation experimental results show that the time efficiency of the algorithm is achieved. |
