Sensor Energy Optimization Using Fuzzy Logic in Wireless Sensor Networking

Wireless sensor networks is challenging in that it requires an enormous breadth of knowledge from an enormous variety of disciplines. A lot of study has been done to minimize the energy used in routing and number of protocols has been developed. These protocols can be classified as Hierarchical, data centric, location based and Network flow protocols. In this paper, we are particularly focusing on hierarchical protocols. In such types of protocols, the energy efficient clusters are formed with a hierarchy of cluster heads. Each cluster has its representative cluster head which is responsible for collecting and aggregating the data from its respective cluster and then transmitting this data to the Base Station either directly or through the hierarchy of other cluster heads. Fuzzy logic has been successfully applied in various areas including communication and has shown promising results. However, the potentials of fuzzy logic in wireless sensor networks still need to be explored. Optimization of wireless sensor networks involve various tradeoffs, for example, lower transmission power vs. longer transmission duration, multi-hop vs. direct communication, computation vs. communication etc. Fuzzy logic is well suited for application having conflicting requirements. Moreover, in WSN, as the energy metrics vary widely with the type of sensor node implementation platform, using fuzzy logic has the advantage of being easily adaptable to such changes.