Cluster-based energy-efficient MAC protocol for wireless sensor networks
MetadataShow full item record
TheWireless Sensor Networks (WSNs) employs thousands of small sensors that communicate between themselves in a distributed manner using Medium Access Control (MAC) protocols. The energy required for wireless sensors is obtained from non-rechargeable energy sources. Due to their small size, wireless sensors are highly constrained in terms of battery energy. Hence, energy efficiency is considered a key factor in the design of a WSN. MAC protocols play an important role in the successful operation of WSNs. Energy efficiency can be achieved by introducing some significant changes that effect the energy consumption at the MAC layer. Existing protocols achieve energy savings, trading off either latency or throughput. The Sensor Medium Access Control (SMAC) is one such protocol that identifies a few sources of energy wastage and proposes an adaptive sleep-and-listen scheme to minimize energy wastage. This thesis studies the S-MAC protocol and proposes a new one Cluster-Based Energy-Efficient Medium Access Control (CBMAC), which attempts to increase energy savings by introducing changes to the existing S-MAC protocol. CBMAC introduces a clustering mechanism, in which the nodes form clusters and elect a cluster head. The cluster head takes care of data transfer and synchronization issues, while the cluster nodes are allowed to spend maximum time in the sleep state. The role of the cluster head is shared among several nodes over time in order to achieve uniform energy utilization in the network. The energy savings achieved with the CBMAC protocol are primarily due to the increased sleep-time fraction for cluster nodes. The clustering mechanism also reduces control overhead, which is prevalent in the S-MAC protocol due to the periodic control packet exchanges. CBMAC was studied under various topologies, and the results show significant energy savings over the S-MAC protocol, particularly in low-data-traffic scenarios.
Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science.