EECCP: an energy-efficient coverage- and connectivity preserving algorithm under border effects in wireless sensor networks

Wireless sensor networks (WSNs) can be used to monitor the interested region using multi-hop communication. Coverage is a primary metric to evaluate the capacity of monitoring. Connectivity also needs to be guaranteed so that the sink node can receive all sensed data from the region for future processing. In this paper, a connected full/partial coverage problem under border effects is studied. We consider the scenario where the sensor nodes are distributed in a circle-shaped region randomly. First, the network coverage provided by N nodes is derived by the mathematical expression exactly. Then the lower bound of the network connectivity probability is also derived. Since nodes are equipped with energy-limited batteries, energy conservation in such networks is of paramount importance to prolong the network lifetime. Accordingly, we propose a location-independent, energy-efficient data routing algorithm EECCP which considers the network coverage and sensor connectivity simultaneously. Compared with other related algorithms, the extensive simulation results demonstrate that our algorithm can achieve the connected, full/partial coverage requirement.

[1]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[2]  Deborah Estrin,et al.  ASCENT : Adaptive Self-Configuring sEnsor Networks Topologies . , 2002 .

[3]  Edward J. Coyle,et al.  Minimizing communication costs in hierarchically-clustered networks of wireless sensors , 2004, Comput. Networks.

[4]  Wang,et al.  Analysis of coverage problem under border effects in wireless sensor networks , 2008 .

[5]  Robert Tappan Morris,et al.  Span: An Energy-Efficient Coordination Algorithm for Topology Maintenance in Ad Hoc Wireless Networks , 2001, MobiCom '01.

[6]  Miodrag Potkonjak,et al.  Power efficient organization of wireless sensor networks , 2001, ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240).

[7]  Jennifer C. Hou,et al.  Maintaining Sensing Coverage and Connectivity in Large Sensor Networks , 2005, Ad Hoc Sens. Wirel. Networks.

[8]  Jie Wu,et al.  Energy-efficient coverage problems in wireless ad-hoc sensor networks , 2006, Comput. Commun..

[9]  Guoliang Xing,et al.  Integrated coverage and connectivity configuration in wireless sensor networks , 2003, SenSys '03.

[10]  Mathew D. Penrose,et al.  On k-connectivity for a geometric random graph , 1999, Random Struct. Algorithms.

[11]  Songwu Lu,et al.  PEAS: a robust energy conserving protocol for long-lived sensor networks , 2003, 23rd International Conference on Distributed Computing Systems, 2003. Proceedings..

[12]  Yan Jin,et al.  EEMC: An Energy-Efficient Multi-Tier Clustering Algorithm for Large-Scale Wireless Sensor Networks , 2006, 2006 International Conference on Wireless Communications, Networking and Mobile Computing.

[13]  Samir R. Das,et al.  Connected sensor cover: self-organization of sensor networks for efficient query execution , 2006, TNET.

[14]  Di Tian,et al.  A coverage-preserving node scheduling scheme for large wireless sensor networks , 2002, WSNA '02.

[15]  Yang Xiao,et al.  IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, PAPER ID: TPDS-0307-0605.R1 1 Random Coverage with Guaranteed Connectivity: Joint Scheduling for Wireless Sensor Networks , 2022 .

[16]  Deborah Estrin,et al.  An energy-efficient MAC protocol for wireless sensor networks , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

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