Recent research has indicated that using the mobility of the actuator in wireless sensor and actuator networks (WSANs) to achieve mobile data collection can greatly increase the sensor network lifetime. However, mobile data collection may result in unacceptable collection delays in the network if the path of the actuator is too long. Because real-time network applications require meeting data collection delay constraints, planning the path of the actuator is a very important issue to balance the prolongation of the network lifetime and the reduction of the data collection delay. In this paper, a multi-hop routing mobile data collection algorithm is proposed based on dynamic polling point selection with delay constraints to address this issue. The algorithm can actively update the selection of the actuator’s polling points according to the sensor nodes’ residual energies and their locations while also considering the collection delay constraint. It also dynamically constructs the multi-hop routing trees rooted by these polling points to balance the sensor node energy consumption and the extension of the network lifetime. The effectiveness of the algorithm is validated by simulation.
References
[1]
Zeng, Y.; Sreenan, C.; Sitanayah, L.; Xiong, N.; Park, J.H.; Zheng, G. An emergency-adaptive routing scheme for wireless sensor networks for building fire hazard monitoring. Sensors 2011, 11, 2899–2919.
[2]
Shin, I.; Kim, M.; Mutka, M.; Choo, H.; Lee, T.J. MCBT: Multi-hop cluster based stable backbone trees for data collection and dissemination in WSNs. Sensors 2009, 9, 6028–6045.
[3]
Shah, R.C.; Roy, S.; Jain, S.; Brunette, W. Data MULEs: Modeling and analysis of a three-tier architecture for sparse sensor networks. Ad Hoc Netw. 2003, 1, 215–233.
[4]
Gu, Y.; Bozdag, D.; Ekici, E. Mobile Element Based Differentiated Message Delivery in Wireless Sensor Networks. Proceedings of the International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM 2006), Buffalo, New York, USA, 26–29 June 2006; pp. 83–92.
[5]
Zhao, M.; Yang, Y. A Framework for Mobile Data Gathering with Load Balanced Clustering and MIMO Uploading. Proceedings of the 2011 IEEE INFOCOM, Shanghai, China, 10–15 April 2011; pp. 2759–2767.
[6]
Zhao, M.; Ma, M.; Yang, Y. Efficient data gathering with mobile collectors and space-division multiple access technique in wireless sensor networks. IEEE Trans. Comp. 2011, 60, 400–417.
[7]
Gao, S.; Zhang, H.; Das, S. Efficient data collection in wireless sensor networks with path-constrained mobile sinks. IEEE Trans. Mobile Comput. 2011, 10, 592–608.
[8]
Konstantopoulos, C.; Pantziou, G.; Gavalas, D.; Mpitziopoulos, A.; Mamalis, B. A rendezvous-based approach enabling energy-efficient sensory data collection with mobile sinks. IEEE Trans. Parallel Distrib. Syst. 2012, 23, 809–817.
[9]
Oliveira, H.; Barreto, R.; Fontao, A.; Loureiro, A.A.F.; Nakamura, E. A Novel Greedy Forward Algorithm for Routing Data toward a High Speed Sink in Wireless Sensor Networks. Proceedings of the 19th International Conference on Computer Communications and Networks (ICCCN), Zurich, Switzerland, 2–5 August 2010; pp. 1–7.
[10]
Luo, J.; Hubaux, J.P. Joint Mobility and Routing for Lifetime Elongation in Wireless Sensor Networks. Proceedings of the IEEE INFOCOM 24th Annual Joint Conference of the IEEE Computer and Communications Societies, Miami, FL, USA, 13–17 March 2005; Volume 3, pp. 1735–1746.
[11]
Luo, J.; Hubaux, J.P. Joint sink mobility and routing to maximize the lifetime of wireless sensor networks: The case of constrained mobility. IEEE ACM Trans. Netw. 2010, 18, 871–884.
[12]
Gatzianas, M.; Georgiadis, L. A distributed algorithm for maximum lifetime routing in sensor networks with mobile sink. IEEE Trans. Wirel. Commun. 2008, 7, 984–994.
[13]
Basagni, S.; Carosi, A.; Petrioli, C.; Phillips, C. Coordinated and controlled mobility of multiple sinks for maximizing the lifetime of wireless sensor networks. Wirel. Netw. 2011, 17, 759–778.
[14]
Erman, A.T.; Havinga, P. Data Dissemination of Emergency Messages in Mobile Multi-Sink Wireless Sensor Networks. Proceedings of the 9th IFIP Annual Mediterranean on Ad Hoc Networking Workshop (Med-Hoc-Net), Juan Les Pins, France, 23–25 June 2010; pp. 1–8.
[15]
Freitas, E.P.; Heimfarth, T.; Vinel, A.; Wagner, F.; Pereira, C.; Larsson, T. Cooperation among wirelessly connected static and mobile sensor nodes for surveillance applications. Sensors 2013, 13, 12903–12928.
[16]
Keung, G.; Li, B.; Zhang, Q. Message delivery capacity in delay-constrained mobile sensor networks: Bounds and realization. IEEE Trans. Wirel. Commun. 2011, 10, 1552–1559.
[17]
Xing, G.; Li, M.; Wang, T.; Jia, W.; Huang, J. Efficient rendezvous algorithms for mobility-enabled wireless sensor networks. IEEE Trans. Mob. Comput. 2012, 11, 47–60.
[18]
Zhao, M.; Yang, Y. Bounded relay hop mobile data gathering in wireless sensor networks. IEEE Trans. Comput. 2012, 61, 265–277.
[19]
Lai, S.; Ravindran, B. Achieving max-min lifetime and fairness with rate allocation for data aggregation in sensor networks. Ad Hoc Netw. 2011, 9, 821–834.
[20]
Cheng, Z.; Heinzelman, W.B. Discovering long lifetime routes in mobile ad hoc networks. Ad Hoc Netw. 2008, 6, 661–674.
[21]
Terrasson, G.; Briand, R.; Basrour, S.; Dupe, V.; Arrijuria, O. Energy Model for the Design of Ultra-Low Power Nodes for Wireless Sensor Networks. Proceedings of the Eurosensors XXIII Conference, Lausanne, Switzerland, 6–9 September 2009; pp. 1195–1198.
[22]
AbdelSalam, H.S.; Olariu, S. Toward adaptive sleep schedules for balancing energy consumption in wireless sensor networks. IEEE Trans. Comput. 2012, 61, 1443–1458.
[23]
Nesamony, S.; Vairamuthu, M.; Orlowska, M. On Optimal Route of a Calibrating Mobile Sink in a Wireless Sensor Network. Proceedings of the Fourth International Conference on Networked Sensing Systems (INSS '07), Braunschweig, Germany, 6–8 June 2007; pp. 61–64.
[24]
Keller, J.; Gray, M.; Givens, J. A fuzzy K-nearest neighbor algorithm. IEEE Trans. Syst. Man Cybernet. 1985, SMC-15, 580–585.
[25]
Yuan, Y.; Peng, Y.; Li, S.; Tang, W. Efficient heuristic algorithm for the mobile sink routing problem. J. Comlnun. 2011, 32, 107–117.
[26]
Xing, G.; Wang, T.; Jia, W.; Li, M. Rendezvous Design Algorithms for Wireless Sensor Networks With a Mobile Base Station. Proceedings of the 9th ACM International Symposium on Mobile Ad Hoc Networking and Computing, Hong Kong, China; 2008; pp. 489–500.
