Optimal Number of Clusters in Dense Wireless Sensor Networks: A Cross-Layer Approach

Cluster-based sensor networks have the advantages of reducing energy consumption and link-maintenance cost. One fundamental issue in cluster-based sensor networks is determining the optimal number of clusters. In this paper, we suggest a physical (PHY)/medium access control (MAC)/network (NET) cross-layer analytical approach for determining the optimal number of clusters, with the objective of minimizing energy consumption in a high-density sensor network. Our cross-layer design can incorporate many effects, including lognormal shadowing and a two-slope path loss model in the PHY layer, various MAC scheduling, and multihop routing schemes. Compared with the base-line case with one cluster per observation area (OA), a sensor network with the proposed optimal number of clusters can reduce the energy consumption by more than 80% in some cases. We also verify by simulations that the analytical optimal cluster number can still effectively function, regardless of the different densities of sensors in various OAs.

[1]  Vishnu Navda,et al.  Efficient gathering of correlated data in sensor networks , 2008, TOSN.

[2]  Anna Scaglione,et al.  On the Interdependence of Routing and Data Compression in Multi-Hop Sensor Networks , 2002, MobiCom '02.

[3]  Catherine Rosenberg,et al.  Design guidelines for wireless sensor networks: communication, clustering and aggregation , 2004, Ad Hoc Networks.

[4]  Ramesh Govindan,et al.  The impact of spatial correlation on routing with compression in wireless sensor networks , 2008, TOSN.

[5]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[6]  Deborah Estrin,et al.  Geography-informed energy conservation for Ad Hoc routing , 2001, MobiCom '01.

[7]  Deborah Estrin,et al.  Statistical model of lossy links in wireless sensor networks , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[8]  Deborah Estrin,et al.  Topology Control Protocols to Conserve Energy in Wireless Ad Hoc Networks , 2003 .

[9]  David Malone,et al.  Modeling the 802.11 distributed coordination function in non-saturated conditions , 2005, IEEE Communications Letters.

[10]  A.E. Kamal,et al.  On the optimal clustering in mobile ad hoc networks , 2004, First IEEE Consumer Communications and Networking Conference, 2004. CCNC 2004..

[11]  Deborah Estrin,et al.  Dimensions: why do we need a new data handling architecture for sensor networks? , 2003, CCRV.

[12]  Julio Solano-González,et al.  Connectivity Based k-Hop Clustering in Wireless Networks , 2003, Telecommun. Syst..

[13]  R. Verdone,et al.  Simulation of an energy efficient carrier sensing multiple access protocol for clustered wireless sensor networks , 2004, International Workshop on Wireless Ad-Hoc Networks, 2004..

[14]  Alhussein A. Abouzeid,et al.  Information-Theoretic Bounds for Mobile Ad-hoc Networks Routing Protocols , 2003, ICOIN.

[15]  Alessandro Panconesi,et al.  Localized protocols for ad hoc clustering and backbone formation: a performance comparison , 2006, IEEE Transactions on Parallel and Distributed Systems.

[16]  Edward J. Coyle,et al.  Minimizing communication costs in hierarchically clustered networks of wireless sensors , 2003, 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003..

[17]  A.H. Tewfik,et al.  Performance analysis of multi-rate 802.11 WLANs under finite load and saturation conditions , 2005, VTC-2005-Fall. 2005 IEEE 62nd Vehicular Technology Conference, 2005..

[18]  Marco Zuniga,et al.  Analyzing the transitional region in low power wireless links , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..

[19]  Pravin Varaiya,et al.  Throughput analysis of an extended service set in IEEE 802.11 , 2004, IEEE Global Telecommunications Conference, 2004. GLOBECOM '04..

[20]  Yu Liu,et al.  A Game Theoretic Approach to Efficient Mixed Strategies for Intrusion Detection , 2006, 2006 IEEE International Conference on Communications.

[21]  Cauligi S. Raghavendra,et al.  PEGASIS: Power-efficient gathering in sensor information systems , 2002, Proceedings, IEEE Aerospace Conference.

[22]  Mani B. Srivastava,et al.  On modeling networks of wireless microsensors , 2001, SIGMETRICS '01.

[23]  E.J. Duarte-Melo,et al.  Energy efficiency of many-to-one communications in wireless networks , 2002, The 2002 45th Midwest Symposium on Circuits and Systems, 2002. MWSCAS-2002..

[24]  A. Girotra,et al.  Performance Analysis of the IEEE 802 . 11 Distributed Coordination Function , 2005 .

[25]  E. Stein,et al.  Real Analysis: Measure Theory, Integration, and Hilbert Spaces , 2005 .

[26]  Lui Sha,et al.  Dynamic clustering for acoustic target tracking in wireless sensor networks , 2003, IEEE Transactions on Mobile Computing.

[27]  Soung Chang Liew,et al.  Offered load control in IEEE 802.11 multi-hop ad-hoc networks , 2004, 2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE Cat. No.04EX975).

[28]  Kaveh Pahlavan,et al.  Principles of Wireless Networks: A Unified Approach , 2011 .

[29]  Olav N. Østerbø,et al.  Non-saturation and saturation analysis of IEEE 802.11e EDCA with starvation prediction , 2005, MSWiM '05.

[30]  Mingyan Liu,et al.  Analysis of energy consumption and lifetime of heterogeneous wireless sensor networks , 2002, Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE.

[31]  Li-Chun Wang,et al.  Adaptive contention window-based cluster head election mechanisms for wireless sensor networks , 2005, VTC-2005-Fall. 2005 IEEE 62nd Vehicular Technology Conference, 2005..

[32]  Gerhard Maierbacher,et al.  Source-Optimized Clustering for Distributed Source Coding , 2006 .

[33]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[34]  Deborah Estrin,et al.  ASCENT: adaptive self-configuring sensor networks topologies , 2004, IEEE Transactions on Mobile Computing.

[35]  Kee Chaing Chua,et al.  A Capacity Analysis for the IEEE 802.11 MAC Protocol , 2001, Wirel. Networks.

[36]  Anantha Chandrakasan,et al.  Design Considerations for Energy-Efficient Radios in Wireless Microsensor Networks , 2004, J. VLSI Signal Process..

[37]  Cyrus Shahabi,et al.  The Clustered AGgregation (CAG) technique leveraging spatial and temporal correlations in wireless sensor networks , 2007, TOSN.

[38]  V. Ramachandran,et al.  Distributed classification of Gaussian space-time sources in wireless sensor networks , 2004, IEEE Journal on Selected Areas in Communications.

[39]  Li-Chun Wang,et al.  A cross-layer design of clustering architecture for wireless sensor networks , 2004, IEEE International Conference on Networking, Sensing and Control, 2004.

[40]  Ramesh Govindan,et al.  Scale Free Aggregation in Sensor Networks , 2004, ALGOSENSORS.

[41]  Gang Zhou,et al.  Impact of radio irregularity on wireless sensor networks , 2004, MobiSys '04.

[42]  Ramesh Govindan,et al.  Understanding packet delivery performance in dense wireless sensor networks , 2003, SenSys '03.

[43]  C.J. Kikkert,et al.  Radio propagation model for long-range ad hoc wireless sensor network , 2005, 2005 International Conference on Wireless Networks, Communications and Mobile Computing.

[44]  Robert A. Scholtz,et al.  Performance Analysis of , 1998 .

[45]  Konstantinos Kalpakis,et al.  An efficient clustering-based heuristic for data gathering and aggregation in sensor networks , 2003, 2003 IEEE Wireless Communications and Networking, 2003. WCNC 2003..

[46]  Leonidas J. Guibas,et al.  Collaborative signal and information processing: an information-directed approach , 2003 .

[47]  Ian F. Akyildiz,et al.  Spatial correlation-based collaborative medium access control in wireless sensor networks , 2006, IEEE/ACM Transactions on Networking.

[48]  Konstantinos Psounis,et al.  A clustering method that uses lossy aggregation of data , 2004, SenSys '04.

[49]  Joan García-Haro,et al.  An accurate radio channel model for wireless sensor networks simulation , 2005, Journal of Communications and Networks.

[50]  Fikret Sivrikaya,et al.  Time synchronization in sensor networks: a survey , 2004, IEEE Network.

[51]  Bruno Sinopoli,et al.  Distributed control applications within sensor networks , 2003, Proc. IEEE.

[52]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[53]  Gerhard Maierbacher,et al.  CTH04-3: Source-Optimized Clustering for Distributed Source Coding , 2006, IEEE Globecom 2006.