Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Data Gathering Algorithms in Sensor Networks Using Energy Metrics
IEEE Transactions on Parallel and Distributed Systems
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
A framework for spatio-temporal query processing over wireless sensor networks
DMSN '04 Proceeedings of the 1st international workshop on Data management for sensor networks: in conjunction with VLDB 2004
Cluster-Head Election Using Fuzzy Logic for Wireless Sensor Networks
CNSR '05 Proceedings of the 3rd Annual Communication Networks and Services Research Conference
Adaptive clustering in wireless sensor networks by mining sensor energy data
Computer Communications
Optimal Distributed Detection in Clustered Wireless Sensor Networks
IEEE Transactions on Signal Processing - Part II
An application-specific protocol architecture for wireless microsensor networks
IEEE Transactions on Wireless Communications
A centralized energy-efficient routing protocol for wireless sensor networks
IEEE Communications Magazine
Hi-index | 0.00 |
A wireless sensor network consists of some sensor nodes that can be effective tool gathering data in various environments. Clustering is one of the methods used to gather information in which sensor nodes are clustered into groups and in each group all sensors communicate only with cluster heads (CHs). CHs send the collected information to a Base Station. Since the energy of the sensors is limited and sending information in each time reduces the nodes' energy, optimal selecting a CH will be notably effective in decreasing energy consumption of the nodes and therefore increases the network life time. In this paper we present a clustering method to choose the CH in an optimal way without need for information of nodes' location, based on two parameters of the energy and number of neighbors, considering the mobility of the nodes. The considerable point in the results is that the performance of our algorithm is uniformly in the three cases.