HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks
IEEE Transactions on Mobile Computing
An efficient clustering scheme for large and dense mobile ad hoc networks (MANETs)
Computer Communications
Performance analysis of MANET clustering algorithm in group mobility model
ICCOMP'07 Proceedings of the 11th WSEAS International Conference on Computers
An energy-aware and intelligent cluster-based event detection scheme in wireless sensor networks
International Journal of Sensor Networks
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
Mobility identification and clustering in sparse mobile networks
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
An energy efficient clustering protocol for routing in Wireless Sensor Network
International Journal of Ad Hoc and Ubiquitous Computing
Efficient multilevel clustering for large-scale heterogeneous wireless sensor networks
Proceedings of the 2011 International Conference on Communication, Computing & Security
Stable and energy efficient clustering of wireless ad-hoc networks with LIDAR algorithm
PWC'06 Proceedings of the 11th IFIP TC6 international conference on Personal Wireless Communications
Detecting communities in sparse MANETs
IEEE/ACM Transactions on Networking (TON)
A distributed backbone formation algorithm for mobile ad hoc networks
ISPA'06 Proceedings of the 4th international conference on Parallel and Distributed Processing and Applications
An Energy-Efficient Multilevel Clustering Algorithm for Heterogeneous Wireless Sensor Networks
International Journal of Mobile Computing and Multimedia Communications
Hi-index | 0.00 |
Abstract: Routing in ad-hoc net works is a difficult challenge that involves a tradeoff between efficiency and responsiveness. An ad-hoc network routing algorithm must adapt rapidly enough to topology changes to meet the performance demands of users, without over-utilizing network resources. This paper presents the (a, t)-Cluster-frame work which utilizes a distributed dynamic clustering strategy to organize nodes into clusters in which the probability of path failure due to node movement can be bounded over time. The objective of the clustering strategy is to achieve scalability and support robust, efficient routing subject to a wide range of mobility rates. Based on the (a, t)-Cluster scheme, routes within clusters are maintained on a proactive basis; whereas, hierarchical routing between clusters is managed on a demand-basis. Simulation results show that the cluster organization can be effectively adapted to node mobility and that routing is both more robust and efficient than routing in fully proactive, reactive or fixed-hybrid schemes.