Abstract
Many applications in wireless sensor networks (WSNs) benefit significantly from organizing nodes into groups, called clusters, because data aggregation and data filtering applied in each cluster can greatly help to reduce traffic. The size of a cluster is measured by the hop distance from the farthest node to the cluster head. Rather than 1-hop clustering, K-hop clustering is preferred by many energy-constrained applications. However, existing solutions fail to distribute clusters evenly across the sensing field, which may lead to unbalanced energy consumption and network inefficiency. Moreover, they incur high communication overhead. We propose an Evenly Distributed Clustering (EDC) algorithm. Constrained by the maximum cluster size K, EDC distributes clusters uniformly, and minimizes the number of clusters. By introducing a relative synchronization technique, EDC converges fast with low communication overhead. It also helps to improve the successful transmission rate from nodes to their cluster heads. The simulation results indicate that EDC outperforms other existing algorithms.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Mainwaring, A., Polastre, J., Szewczyk, R., Culler, D.: Wireless Sensor Networks for Habitat Monitoring. In: ACM International Workshop on Wireless Sensor Networks and Applications (WSNA), ACM Press, New York (2002)
Woo, A., Tong, T., Culler, D.: Taming the Underlying Challenges of Reliable Multihop Routing in Sensor Networks. SenSys (2003)
Amis, A.D., Prakash, R., Vuong, T.H., Huynh, D.T.: Max-Min D-Cluster Formation in Wireless Ad Hoc Networks. INFOCOM (2000)
Park, V.D., Corson, M.S., Highly, A.: Adaptive Distributed Routing Algorithm for Mobile Wireless Networks. INFOCOM (1997)
Perkins, C.E., Bhagwat, P.: Highly Dynamic Destination-Sequenced Distance-Vector Routing (DSDV) for Mobile Computers. SIGCOMM (1994)
Bandyopadhyay, S., Coyle, E.J.: An Energy Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks. INFOCOM (2003)
Chatterjee, M., Das, S., Turgut, D.: WCA: A Weighted Clustering Algorithm for Mobile Ad hoc Networks. Journal of Cluster Computing, Special issue on Mobile Ad hoc Networking 5, 193–204 (2002)
Baker, D., Ephremides, A.: The Architectural Organization of a Mobile Radio Network via a Distributed Algorithm. IEEE Transactions on Communications 29, 1694–1701 (1981)
Ephremides, A., Wieselthier, J.E., Baker, D.: A Design Concept for Reliable Mobile Radio Networks with Frequency Hopping Signaling. Proceeding of IEEE 75(1), 56–73 (1987)
Heinzelman, W., Chandrakasan, A., Balakrishnan, H.: An Application-Specific Protocol Architecture for Wireless Microsensor Networks. IEEE Transactions on Wireless Communications 1(4), 660–669 (2002)
Parekh, A.: Selecting Routers in Ad-hoc Wireless Networks. SBT/IEEE International Telecommunications Symposium (1994)
Cerpa, A., Estrin, D.: ASCENT: Addaptive Self-Configuring sEnsor Networks Topologies. INFOCOM (2002)
Chen, B., Jamieson, K., Balakrishnan, H., Morris, R.: Span: An Energy-Efficient Coordination Algorithm for Topology Maintenance in Ad Hoc Wireless Networks. MobiCom (2000)
Xu, Y., Heidemann, J., Estrin, D.: Geography-informed Energy Conservation for Ad Hoc Routing. MobiCom (2001)
Wu, J., Dai, F., Distributed, A.: Formation of a Virtual Backbone in Ad Hoc Networks using Adjustable Transmission Ranges. ICDCS (2004)
Dai, F., Wu, J.: On Constructing k-Connected k-Dominating Set in Wireless Networks. IPDPS (2005)
Ma, J., Gao, M., Zhang, Q., Ni, L.M., Zhu, W.: Localized Low-Power Topology Control Algorithms in IEEE 802.15.4-based Sensor Networks. ICDCS (2005)
Levis, P., Madden, S., Gay, D., Polastre, J., Szewczyk, R., Woo, A., Brewer, E., Culler, D.: The Emergence of Networking Abstractions and Techniques in TinyOS. NSDI (2004)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Chen, Q., Ma, J., Zhu, Y., Zhang, D., Ni, L.M. (2007). An Energy-Efficient K-Hop Clustering Framework for Wireless Sensor Networks. In: Langendoen, K., Voigt, T. (eds) Wireless Sensor Networks. EWSN 2007. Lecture Notes in Computer Science, vol 4373. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69830-2_2
Download citation
DOI: https://doi.org/10.1007/978-3-540-69830-2_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69829-6
Online ISBN: 978-3-540-69830-2
eBook Packages: Computer ScienceComputer Science (R0)