Energy-Efficient Scheduling for Mobile Sensors Using Connection Graphs in a Hybrid Wireless Sensor Network with Obstacles

This paper considers the scheduling problem of mobile sensors in a hybrid wireless sensor network (WSN) with obstacles. In a WSN, static sensors monitor the environment and report where events appear in the sensing field. Then, mobile sensors are dispatched to these event locations to perform in-depth analysis. The sensing field may contain obstacles of any shape and size. A big challenge is how to efficiently dispatch the mobile sensor to find an obstacle-avoiding shortest path. To remedy this issue, we propose an efficient scheduling mechanism based on connection graphs in this paper. Specifically, the region of network is divided into grid cells with the same size. Consequently, the search space of the shortest path is restricted to the connection graphs composed of some grid cells. Through simulation, we verify the effectiveness of our method. The paper contributes to developing an energy-efficient dispatch solution in the presence of obstacles.

[1]  Yen-Wen Chen,et al.  Energy consumption bounds analysis and its applications for grid based wireless sensor networks , 2013, J. Netw. Comput. Appl..

[2]  S. Sitharama Iyengar,et al.  Finding obstacle-avoiding shortest paths using implicit connection graphs , 1996, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[3]  Ivan Stojmenovic,et al.  TOPICS IN AD HOC AND SENSOR NETWORKS , 2022 .

[4]  I. Stojmenovic,et al.  Task assignment in wireless sensor and robot networks , 2012, 2012 20th Telecommunications Forum (TELFOR).

[5]  Mark Zwolinski,et al.  Lee router modified for global routing , 1990, Comput. Aided Des..

[6]  You-Chiun Wang Efficient Dispatch of Multi-Capability Mobile Sensors in Hybrid Wireless Sensor Networks , 2012 .

[7]  Guang-Ming Dai,et al.  Planning of moving path based on simplified terrain , 2003, Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).

[8]  Hung-Min Sun,et al.  CDAMA: Concealed Data Aggregation Scheme for Multiple Applications in Wireless Sensor Networks , 2013, IEEE Transactions on Knowledge and Data Engineering.

[9]  Juan C. Cuevas-Martínez,et al.  Knowledge-based duty cycle estimation in wireless sensor networks: Application for sound pressure monitoring , 2013, Appl. Soft Comput..

[10]  Lionel M. Ni,et al.  Energy consumption monitoring for sensor nodes in SNAP , 2013, Int. J. Sens. Networks.

[11]  Chih-Min Chao,et al.  Design of Structure-Free and Energy-Balanced Data Aggregation in Wireless Sensor Networks , 2009, HPCC.

[12]  Ying Zhang,et al.  Rigidity guided localisation for mobile robotic sensor networks , 2010, Int. J. Ad Hoc Ubiquitous Comput..

[13]  Shalini Kumari,et al.  Dispatch of mobile sensors in the presence of Obstacles Using Modified Dijkstra Algorithm , 2012 .

[14]  Shuo Yang,et al.  Wireless Sensor Network Platform for Intrinsic Optical Fiber pH Sensors , 2014, IEEE Sensors Journal.

[15]  Yu-Chee Tseng,et al.  Energy-Balanced Dispatch of Mobile Sensors in a Hybrid Wireless Sensor Network , 2010, IEEE Transactions on Parallel and Distributed Systems.

[16]  Phone Lin,et al.  APS: Distributed air pollution sensing system on Wireless Sensor and Robot Networks , 2012, Comput. Commun..

[17]  Yunhui Liu,et al.  Finding the shortest path of a disc among polygonal obstacles using a radius-independent graph , 1995, IEEE Trans. Robotics Autom..

[18]  Sherali Zeadally,et al.  Energy-aware sensor node relocation in mobile sensor networks , 2014, Ad Hoc Networks.

[19]  G K Shwetha,et al.  Energy-Balanced Dispatch of Mobile Sensors in Hybrid Wireless Sensor Network with Obstacles , 2012 .

[20]  Tai-Lin Chin,et al.  Load balance for mobile sensor patrolling in surveillance sensor networks , 2012, 2012 IEEE Wireless Communications and Networking Conference (WCNC).

[21]  Minzan Li,et al.  Temporal and spatial variability of soil moisture based on WSN , 2013, Math. Comput. Model..

[22]  Cem Ersoy,et al.  Wireless sensor networks for healthcare: A survey , 2010, Comput. Networks.

[23]  Yu Gu,et al.  ESWC: Efficient Scheduling for the Mobile Sink in Wireless Sensor Networks with Delay Constraint , 2013, IEEE Transactions on Parallel and Distributed Systems.

[24]  M. H. Supriya,et al.  Localisation of underwater targets using sensor networks , 2013, Int. J. Sens. Networks.

[25]  You-Chiun Wang,et al.  A Two-Phase Dispatch Heuristic to Schedule the Movement of Multi-Attribute Mobile Sensors in a Hybrid Wireless Sensor Network , 2014, IEEE Transactions on Mobile Computing.

[26]  Hossam S. Hassanein,et al.  On the robustness of grid-based deployment in wireless sensor networks , 2006, IWCMC '06.

[27]  Yingshu Li,et al.  Processing Area Queries in Wireless Sensor Networks , 2009, 2009 Fifth International Conference on Mobile Ad-hoc and Sensor Networks.

[28]  Yu-Chee Tseng,et al.  Mobility management algorithms and applications for mobile sensor networks , 2012, Wirel. Commun. Mob. Comput..

[29]  Jun Luo,et al.  Joint Sink Mobility and Routing to Maximize the Lifetime of Wireless Sensor Networks: The Case of Constrained Mobility , 2010, IEEE/ACM Transactions on Networking.

[30]  Jine Tang,et al.  EGF-tree: an energy-efficient index tree for facilitating multi-region query aggregation in the internet of things , 2013, 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing.

[31]  Weihua Sheng,et al.  Distributed Multi-Actuator Control for Workload Balancing in Wireless Sensor and Actuator Networks , 2011, IEEE Transactions on Automatic Control.