SelectCast: Scalable Data Aggregation Scheme in Wireless Sensor Networks

In this work, for a wireless sensor network (WSN) of n randomly placed sensors with node density \lambda \in [1,n], we study the tradeoffs between the aggregation throughput and gathering efficiency. The gathering efficiency refers to the ratio of the number of the sensors whose data have been gathered to the total number of sensors. Specifically, we design two efficient aggregation schemes, called single-hop-length (SHL) scheme and multiple-hop-length (MHL) scheme. By novelly integrating these two schemes, we theoretically prove that our protocol achieves the optimal tradeoffs, and derive the optimal aggregation throughput depending on a given threshold value (lower bound) on gathering efficiency. Particularly, we show that under the MHL scheme, for a practically important set of symmetric functions called divisible perfectly compressible (DPC) functions, including the mean, max, and various kinds of indicator functions, etc., the data from \Theta (n) sensors can be aggregated to the sink at the throughput of a constant order \Theta (1), implying that, our MHL scheme is indeed scalable.

[1]  Panganamala Ramana Kumar,et al.  Toward a theory of in-network computation in wireless sensor networks , 2006, IEEE Communications Magazine.

[2]  Yunhao Liu,et al.  Capacity of large scale wireless networks under Gaussian channel model , 2008, MobiCom '08.

[3]  Makhlouf Aliouat,et al.  Data Aggregation Security Challenge in Wireless Sensor Networks , 2011, Ad Hoc Sens. Wirel. Networks.

[4]  Jean-Claude Bermond,et al.  Optimal Gathering Algorithms in Multi-Hop Radio Tree-Networks with Interferences , 2010, Ad Hoc Sens. Wirel. Networks.

[5]  Richard J. Barton,et al.  Toward Optimal Data Aggregation in Random Wireless Sensor Networks , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[6]  Shaojie Tang,et al.  Energy-efficient Lossy Data Aggregation in Wireless Sensor Networks? , 2011, Ad Hoc Sens. Wirel. Networks.

[7]  József Balogh,et al.  On k−coverage in a mostly sleeping sensor network , 2008, Wirel. Networks.

[8]  Shaojie Tang,et al.  Scaling laws on multicast capacity of large scale wireless networks , 2009, IEEE INFOCOM 2009.

[9]  Xiang-Yang Li,et al.  Complexity of Data Collection, Aggregation, and Selection for Wireless Sensor Networks , 2011, IEEE Transactions on Computers.

[10]  Selim G. Akl,et al.  A local algorithm to compute multiple connected dominating sets in wireless sensor networks , 2011, Int. J. Parallel Emergent Distributed Syst..

[11]  Saurabh Ganeriwal,et al.  Aggregation in sensor networks: an energy-accuracy trade-off , 2003, Ad Hoc Networks.

[12]  Panganamala Ramana Kumar,et al.  Capacity bounds for ad hoc and hybrid wireless networks , 2004, CCRV.

[13]  Yi Qin,et al.  Throughput and Delay Analysis for Convergecast with MIMO in Wireless Networks , 2012, IEEE Transactions on Parallel and Distributed Systems.

[14]  R. Srikant,et al.  Distributed Symmetric Function Computation in Noisy Wireless Sensor Networks , 2007, IEEE Transactions on Information Theory.

[15]  Qilian Liang,et al.  A Model-Based Approach for Outlier Detection in Sensor Networks , 2011, Ad Hoc Sens. Wirel. Networks.

[16]  Mingyan Liu,et al.  On the Many-to-One Transport Capacity of a Dense Wireless Sensor Network and the Compressibility of Its Data , 2003, IPSN.

[17]  Xiaohua Jia,et al.  Minimum-latency aggregation scheduling in multihop wireless networks , 2009, MobiHoc '09.

[18]  Sencun Zhu,et al.  SDAP: A Secure Hop-by-Hop Data Aggregation Protocol for Sensor Networks , 2008 .

[19]  Ivan Stojmenovic,et al.  Sensor Placement in Sensor and Actuator Networks , 2010 .

[20]  Wei Wang,et al.  Trade-offs between mobility and density for coverage in wireless sensor networks , 2007, MobiCom '07.

[21]  Ayfer Özgür,et al.  Hierarchical Cooperation Achieves Optimal Capacity Scaling in Ad Hoc Networks , 2006, IEEE Transactions on Information Theory.

[22]  Guohong Cao,et al.  Minimizing the Cost of Mine Selection Via Sensor Networks , 2009, IEEE INFOCOM 2009.

[23]  Jie Gao,et al.  Sparse Data Aggregation in Sensor Networks , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

[24]  Prasun Sinha,et al.  Scalable data aggregation for dynamic events in sensor networks , 2006, SenSys '06.

[25]  Yi Qin,et al.  Converge-cast with MIMO , 2011, 2011 Proceedings IEEE INFOCOM.

[26]  Jianping Pan,et al.  Please Scroll down for Article International Journal of Parallel, Emergent and Distributed Systems Energy-optimal Grid-based Clustering in Wireless Microsensor Networks with Data Aggregation Energy-optimal Grid-based Clustering in Wireless Microsensor Networks with Data Aggregation , 2022 .

[27]  Shaojie Tang,et al.  Canopy closure estimates with GreenOrbs: sustainable sensing in the forest , 2009, SenSys '09.

[28]  Panganamala Ramana Kumar,et al.  Computing and communicating functions over sensor networks , 2005, IEEE Journal on Selected Areas in Communications.

[29]  Cheng Wang,et al.  Multicast Throughput for Hybrid Wireless Networks under Gaussian Channel Model , 2011, IEEE Trans. Mob. Comput..

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

[31]  Peng-Jun Wan,et al.  Coverage by randomly deployed wireless sensor networks , 2005, IEEE Transactions on Information Theory.

[32]  M. Penrose.  The longest edge of the random minimal spanning tree , 1997 .

[33]  T. Moscibroda,et al.  The Worst-Case Capacity of Wireless Sensor Networks , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

[34]  Xiaoying Gan,et al.  Converge Cast: On the Capacity and Delay Tradeoffs , 2012, IEEE Transactions on Mobile Computing.

[35]  Massimo Franceschetti,et al.  Closing the Gap in the Capacity of Wireless Networks Via Percolation Theory , 2007, IEEE Transactions on Information Theory.

[36]  Minghua Chen,et al.  Capacity of Large-Scale CSMA Wireless Networks , 2009, IEEE/ACM Transactions on Networking.

[37]  Guohong Cao,et al.  Optimizing tree reconfiguration for mobile target tracking in sensor networks , 2004, IEEE INFOCOM 2004.

[38]  Indranil Gupta,et al.  Performance Tradeoffs Among Percolation-Based Broadcast Protocols in Wireless Sensor Networks , 2009, 2009 29th IEEE International Conference on Distributed Computing Systems Workshops.

[39]  Shaojie Tang,et al.  Aggregation Capacity of Wireless Sensor Networks: Extended Network Case , 2011, IEEE Transactions on Computers.

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

[41]  Jennifer C. Hou,et al.  On the upper bound of α-lifetime for large sensor networks , 2005, TOSN.

[42]  Dong Xuan,et al.  Directed coverage in wireless sensor networks: Concept and quality , 2009, 2009 IEEE 6th International Conference on Mobile Adhoc and Sensor Systems.

[43]  Rencheng Jin,et al.  Energy-Efficient Hierarchical Routing for Wireless Sensor Networks , 2011, Ad Hoc Sens. Wirel. Networks.

[44]  Panganamala Ramana Kumar,et al.  RHEINISCH-WESTFÄLISCHE TECHNISCHE HOCHSCHULE AACHEN , 2001 .

[45]  Siyuan Chen,et al.  Capacity of data collection in randomly-deployed wireless sensor networks , 2011, Wirel. Networks.

[46]  Guohong Cao,et al.  DCTC: dynamic convoy tree-based collaboration for target tracking in sensor networks , 2004, IEEE Transactions on Wireless Communications.