Power-aware routing in mobile ad hoc networks
MobiCom '98 Proceedings of the 4th annual ACM/IEEE international conference on Mobile computing and networking
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Application-specific protocol architectures for wireless networks
Application-specific protocol architectures for wireless networks
Lightweight time synchronization for sensor networks
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks
IEEE Transactions on Mobile Computing
Cluster-Head Election Using Fuzzy Logic for Wireless Sensor Networks
CNSR '05 Proceedings of the 3rd Annual Communication Networks and Services Research Conference
An Energy Efficient Cluster-Head Selection for Wireless Sensor Networks
ISMS '10 Proceedings of the 2010 International Conference on Intelligent Systems, Modelling and Simulation
An application-specific protocol architecture for wireless microsensor networks
IEEE Transactions on Wireless Communications
A strategic deployment and cluster-header selection for wireless sensor networks
IEEE Transactions on Consumer Electronics
IEEE Communications Magazine
Node clustering in wireless sensor networks: recent developments and deployment challenges
IEEE Network: The Magazine of Global Internetworking
Nested clusters with intercluster routing
The Journal of Supercomputing
An efficient compressive data gathering routing scheme for large-scale wireless sensor networks
Computers and Electrical Engineering
Efficient event prewarning for sensor networks with multi microenvironments
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
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Clustering is an effective approach for organizing a network into a connected hierarchy, load balancing, and prolonging the network lifetime. On the other hand, fuzzy logic is capable of wisely blending different parameters. This paper proposes an energy-aware distributed dynamic clustering protocol (ECPF) which applies three techniques: (1) non-probabilistic cluster head (CH) elections, (2) fuzzy logic, and (3) on demand clustering. The remaining energy of the nodes is the primary parameter for electing tentative CHs via a non-probabilistic fashion. A non-probabilistic CH election is implemented by introducing a delay inversely proportional to the residual energy of each node. Therefore, tentative CHs are selected based on their remaining energy. In addition, fuzzy logic is employed to evaluate the fitness (cost) of a node in order to choose a final CH from the set of neighboring tentative CHs. On the other hand, every regular (non CH) node elects to connect to the CH with the least fuzzy cost in its neighborhood. Besides, in ECPF, CH elections are performed sporadically (in contrast to performing it every round). Simulation results demonstrate that our approach performs better than well known protocols (LEACH, HEED, and CHEF) in terms of extending network lifetime and saving energy.