Advertisement

Telecommunication Systems

, Volume 57, Issue 1, pp 51–79 | Cite as

Routing in mobile wireless sensor network: a survey

  • Getsy S SaraEmail author
  • D. Sridharan
Article

Abstract

The Mobile Wireless Sensor Network (MWSN) is an emerging technology with significant applications. The MWSN allows the sensor nodes to move freely and they are able to communicate with each other without the need for a fixed infrastructure. These networks are capable of out-performing static wireless sensor networks as they tend to increase the network lifetime, reduce the power consumption, provide more channel capacity and perform better targeting. Usually routing process in a mobile network is very complex and it becomes even more complicated in MWSN as the sensor nodes are low power, cost effective mobile devices with minimum resources. Recent research works have led to the design of many efficient routing protocols for MWSN but still there are many unresolved problems like retaining the network connectivity, reducing the energy cost, maintaining adequate sensing coverage etc. This paper addresses the various issues in routing and presents the state of the art routing protocols in MWSN. The routing protocols are categorized based on their network structure, state of information, energy efficiency and mobility. The classification presented here summarizes the main features of many published proposals in the literature for efficient routing in MWSN and also gives an insight into the enhancements that can be done to improve the existing routing protocols.

Keywords

Survey Mobile wireless sensor network Routing Mobility and energy efficiency 

Notes

Acknowledgements

This paper is supported by the Junior Research Fellowship for Engineering and Technology under University Grants Commission, India. We would like to thank the anonymous reviewers for their valuable suggestions towards the improvisation of this paper.

References

  1. 1.
    Kansal, A., Rahimi, M., Estrin, D., Kaiser, W. J., Pottie, G. J., & Srivastava, M. B. (2004). Controlled mobility for sustainable wireless sensor networks. In Proceedings of sensor and ad hoc communications and networks (SECON). Google Scholar
  2. 2.
    Munari, A., Schott, W., & Krishnan, S. (2009). Energy efficient routing in mobile wireless sensor networks using mobility prediction. In Proceedings of 34th IEEE conference in local computer networks, Zurich, Switzerland (pp. 514–521). Google Scholar
  3. 3.
    Bari, A., Wazed, S., Jaekel, A., & Bandyopadhyay, S. (2009). A genetic algorithm based approach for energy efficient routing in two-tiered sensor networks. Ad Hoc Networks, 7(4), 665–676. CrossRefGoogle Scholar
  4. 4.
    Yahya, B., & Ben-Othman, J. (2009). An adaptive mobility aware and energy efficient MAC protocol for wireless sensor networks. In Proceedings of 4th IEEE symposium on computers and communications (ISCC 2009), Sousse, Tunisia, July 5–8 (pp. 5–21). Google Scholar
  5. 5.
    Karp, B., & Kung, H. T. (2000). GPSR: greedy perimeter stateless routing for wireless networks. In Proceedings of ACM international conference on mobile computing and networking (MOBICOM) (pp. 243–254). Google Scholar
  6. 6.
    Kusy, B., Lee, H. J., Wicke, M., Milosavljevic, N., & Guibas, L. (2009). Predictive QOS routing to mobile sinks in wireless sensor networks. In Proceedings of ISPN’09, April 13–16, San Francisco, CA, USA. Google Scholar
  7. 7.
    Chen, C., & Ma, J. (2006). MEMOSEN: multi-radio enabled mobile wireless sensor network. In Proc. of AINA’06. Google Scholar
  8. 8.
    Chen, C., Ma, J., & Yu, K. (2006). Designing energy efficient wireless sensor networks with mobile sinks. In Proceedings of WSW’06 at SenSys’06, Colorado, USA, 31 October 2006. Google Scholar
  9. 9.
    Cao, L., Dahlberg, T., & Wang, Y. (2007). Performance evaluation of energy efficient ad hoc routing protocols. In Proceedings of IPCCC. IEEE Press, New York (pp. 306–313). Google Scholar
  10. 10.
    Perkins, C. E. (2008). AdHoc Networking (pp. 225–226). Singapore: Pearson Education South Asia. Google Scholar
  11. 11.
    Perkins, C. E., & Bhagwat, P. (1994). Highly dynamic destination sequenced distance vector routing (DSDV) for mobile computers. In Proceedings of ACM SIGCOMM, August 1994 (pp. 234–244). Google Scholar
  12. 12.
    Chellappan, S., Bai, X., Ma, B., Xuan, D., & Xu, C. (2007). Mobility limited flip-based sensor networks deployment. IEEE Transactions on Parallel and Distributed Systems, 18(2), 199–211. CrossRefGoogle Scholar
  13. 13.
    Camara, D., & Loureiro, A. A. F. (2000). A GPS/ant like routing algorithm for ad hoc networks. In Proceedings of IEEE wireless communication network conference (pp. 1232–1236). Google Scholar
  14. 14.
    Puccinelli, D., Brennan, M., & Haenggi, M. (2007). Reactive sink mobility in wireless sensor networks. In Proceedings of MobiOpp’07, San Juan, Puerto Rico, USA, June 11. Google Scholar
  15. 15.
    Dantu, K., Rahimi, M. H., Shah, H., Babel, S., Dhariwal, A., & Sukhatme, G. S. (2005). Robomote: enabling mobility in sensor networks. In Proceedings of IPSN 2005 (pp. 404–409). Google Scholar
  16. 16.
    Demirbas, M., Soysal, O., & Tosun, A. S. (2007). DATA SALMON: a greedy mobile basestation protocol for efficient data collection in wireless sensor networks. In Proceedings of IEEE int. conf. on dist. comp. in sensor systems. Google Scholar
  17. 17.
    Diggavi, S., Grossglauser, M., & Dnc, T. S. E. (2002). Even one-dimensional mobility increases ad hoc wireless capacity. In Proceedings of IEEE int’l. symp. information theory (ISIT), Lausanne, Switzerland, June ‘02. Google Scholar
  18. 18.
    Dubois-Ferriere, H., Grossglauser, M., & Vetterli, M. (2003). Age matters: efficient route discovery in mobile ad hoc networks using encounter ages. In ACM Mobihoc, June ‘03. Google Scholar
  19. 19.
    Natalizio, E., & Loscrí, V. (2011). Controlled mobility in mobile sensor networks: advantages, issues and challenges. Telecommunication Systems, doi: 10.1007/s11235-011-9561-x.
  20. 20.
    Ye, F., Luo, H., Cheng, J., Lu, S. W., & Zhang, L. (2002). A two tier data dissemination model for large scale wireless sensor networks. In Proceedings of ACM international conference on mobile computing and networking (MOBICOM). Google Scholar
  21. 21.
    Zhao, F., & Guibas, L. (2004). Wireless sensor networks—an information processing approach. Amsterdam: Elsevier. Google Scholar
  22. 22.
    Ganeriwal, S., Kansal, A., & Srivastava, M. B. (2004). Self-aware actuation for fault repair in sensor networks. In IEEE int’l conf. on robotics and automation (ICRA), April ‘04. Google Scholar
  23. 23.
    Srivastava, G., Boustead, P., & Chicharo, J. F. (2003). Comparison of topology control algorithms for ad hoc networks. In Proceedings of Australian telecommunications networks and applications conference (ATNAC’03), Melbourne. Google Scholar
  24. 24.
    Gavidia, D., & Van Steen, M. (2008). A probabilistic replication and storage scheme for large wireless networks of small devices. In Proceedings of 5th IEEE int’l conf. mobile and ad hoc sensor systems (MASS). New York: IEEE Press. Google Scholar
  25. 25.
    Getsy, S. S., Neelavathi, P. S., & Sridharan, D. (2009). Energy efficient ad hoc on demand multipath distance vector routing protocol. The International Journal of Recent Trends in Engineering, 2(3), 10–12. Google Scholar
  26. 26.
    Getsy, S. S., Neelavathi, P. S., & Sridharan, D. (2010). Evaluation and comparison of emerging energy efficient routing protocols in MANET. Journal of the National Institute of Information and Communications Technology, 1, 37–46. Google Scholar
  27. 27.
    Getsy, S. S., Kalaiarasi, S. R., Neelavathi, P., & Sridharan, D. (2010). Energy efficient mobile wireless sensor network routing protocol. In Lecture notes of computer science (pp. 642–650). Berlin: Springer. Google Scholar
  28. 28.
    Anastasi, G., Conti, M., Di Francesco, M., & Passarella, A. (2009). Energy conservation in wireless sensor networks: a survey. Ad Hoc Networks, 7, 537–568. CrossRefGoogle Scholar
  29. 29.
    Gomez, C., Salvatella, P., Alonso, O., & Paradells, J. (2006). Tiny AODV: adapting AODV for IEEE 802.15.4 mesh sensor networks: theoretical discussion and performance evaluation in a real environment. In Proceedings of the international conference WoWMoM. Google Scholar
  30. 30.
    Grossglauser, M., & Dnc, T. S. E. (2002). Mobility increases the capacity of ad hoc wireless networks. IEEE/ACM Transactions on Networking, 10(4), 477–486. CrossRefGoogle Scholar
  31. 31.
    Huo, G., & Wang, X. (2008). An opportunistic routing for mobile wireless sensor networks based on RSSI. In Proceedings of 4th international conference on wireless communications, networking and mobile computing (WiCOM’08), Dalian (pp. 1–4). Google Scholar
  32. 32.
    Liang, G., & Vaidya, N. (2009). Cooperation helps power saving. In Proceedings of 6th international conference on mobile adhoc and sensor systems (MASS’09), 12–15 October (pp. 439–447). CrossRefGoogle Scholar
  33. 33.
    Wang, G., Cao, G., La Porta, T., & Zhang, W. (2005). Sensor relocation in mobile sensor networks. In Proceedings of IEEE conference on computer and communications (INFOCOM) (pp. 2302–2312). Google Scholar
  34. 34.
    Cao, G., & Singhal, M. (2001). A delay-optimal quorum-based mutual exclusion algorithm for distributed systems. IEEE Transactions on Parallel and Distributed Systems, 12(12), 1256–1268. CrossRefGoogle Scholar
  35. 35.
    Heinzelman, W., & Balakrishnan, H. (1999). Adaptive protocols for information dissemination in wireless sensor networks. In Proceedings of 5th ACM/IEEE MOBICOM, Seatle, WA, August 1999 (pp. 304–309). Google Scholar
  36. 36.
    Heinzelman, W., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd international conference on system science (HICSS’00), Hawaii, USA, January 2000. Google Scholar
  37. 37.
    Hatime, H., Namuduri, K., & Watkins, J. M. (2011). OCTOPUS: an on-demand communication topology updating strategy for mobile sensor networks. IEEE Sensors Journal, 11(4), 1004–1012. CrossRefGoogle Scholar
  38. 38.
    Hartenstein, H., Kasemann, M., & Vollmer, D. (2002). Location based routing for vehicular ad-hoc networks. In Proceedings of MOBICOM’02, Atlanta, Georgia, USA, September 2002 (pp. 23–28). Google Scholar
  39. 39.
    Hwang, K., In, J., & Eom, D. (2006). Distributed dynamic shared tree for minimum energy data aggregation of multiple mobile sinks in wireless sensor networks. In Proceedings of EWSN. Google Scholar
  40. 40.
    IEEE LAN MAN Standards, Part 11 (1999). Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications High Speed Physical l Year in 5 GHz Band. In ANSI/IEEE Std., September (1999). Google Scholar
  41. 41.
    Demirkol, I., Ersoy, C., & Algoz, F. (2006). MAC protocols for Wireless Sensor Networks: A Survey. IEEE Communications Magazine, 4(4), 115–121. CrossRefGoogle Scholar
  42. 42.
    Intanagonwiwat, C., Govindhan, R., & Estrin, D. (2000). Directed diffusion: a scalable and robust communication paradigm for sensor networks. In Proceedings of ACM MOBICOM 2000, Boston, MA (pp. 56–67). Google Scholar
  43. 43.
    Chatzigiannakis, I., Kinalis, A., & Nikoletseas, S. (2006). Sink mobility protocols for data collection in wireless sensor networks. In Proceedings of MobiWac’06, 2 October ’06, Torremolinos, Malaga, Spain (p. 52). Google Scholar
  44. 44.
    Iwata, A., Chiang, C. C., Pei, G., Gerla, M., & Chen, T. W. (1999). Scalable routing strategies for ad hoc wireless networks. IEEE Journal on Selected Areas in Communications, 17(8), 1369–1379. CrossRefGoogle Scholar
  45. 45.
    Iyengar, S. S., Wu, H.-C., Balakrishnan, N., & Chang, S. Y. (2007). Biologically inspired cooperative routing for wireless mobile sensor networks. IEEE Systems Journal, 1(1), 29–37. CrossRefGoogle Scholar
  46. 46.
    Choi, J.-M., Cho, Y.-B., Choi, S.-S., & Lee, S.-H. (2009). A cluster header-based energy–efficient mobile sink supporting routing protocol in wireless sensor networks. In Proceedings of the 6th international conference ECTI-CON2009, 6–9 May (pp. 648–651). Google Scholar
  47. 47.
    Jain, S., Shah, R. C., Brunette, W., Borriello, G., & Roy, S. (2006). Exploiting mobility for energy efficient data collection in wireless sensor networks. Mobile Networks and Applications, 11(3), 327–339. CrossRefGoogle Scholar
  48. 48.
    Al-Karaki, J. N., & Kamal, A. E. (2004). Routing techniques in wireless sensor networks: a survey. In IEEE Wirel. Commun., December 2004 (pp. 6–28). Google Scholar
  49. 49.
    Al-Karaki, J. N., & Al-Malkawi, I. T. (2008). On energy efficient routing for wireless sensor networks. In Proceedings of international conference on innovations in information technology, December 2008. Google Scholar
  50. 50.
    Jea, D., Somasundra, A., & Srivastava, M. (2005). Multiple controlled mobile elements (data mules) for data collection in sensor networks. In Proceedings of IEEE int. conf. on dist. comp. in sensor systems. Google Scholar
  51. 51.
    Haerri, J., & Bonnet, C. (2004). On the classification of routing protocols in mobile ad hoc networks. In EURECOM, research report RR-04-115, August 2004. France: Institute EURECOM, Department of Mobile Communication. Google Scholar
  52. 52.
    Ji, W.-W., & Liu, Z. (2008). Locating ineffective sensor nodes in wireless sensor networks. IET Communications, 2(3), 432–439. CrossRefGoogle Scholar
  53. 53.
    Kim, J. M., & Cho, T. H. (2007). Genetic algorithm based routing method for efficient data transmission in sensor networks. In Lecture notes in computer science (Vol. 4681, pp. 273–282). Google Scholar
  54. 54.
    Ng, J.-M., & Lu, I.-T. (1999). A peer-to-peer zone-based two level link state routing for mobile ad hoc networks. IEEE Journal on Selected Areas in Communications, 17(8), 1415–1425. CrossRefGoogle Scholar
  55. 55.
    Juang, P., Oki, H., Wang, Y., Martonosi, M., Peh, L. S., & Rubenstein, D. (2002). Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with zebranet. In ACM ASPLOS (pp. 96–107). Google Scholar
  56. 56.
    Luo, J., & Hubaux, J.-P. (2005). Joint mobility and routing for lifetime elongation in wireless sensor networks. In Proceedings of the 24th annual conference of the IEEE communications societies (INFOCOM’05), FL, USA. Google Scholar
  57. 57.
    Sharif, K., Dahlberg, T. A., & Cao, L. (2010). Anycast based lightweight routing protocol for mobile sink discovery in sensor networks. In Proceedings of IEEE consumer communications and networking conference (CCNC’2010), Las Vegas, Nevada, USA, 9–12 January. Google Scholar
  58. 58.
    Akkaya, K., & Younis, M. (2005). A survey on routing protocols for wireless sensor networks. Ad Hoc Networks, 3, 325–349. CrossRefGoogle Scholar
  59. 59.
    Kim, K., Yun, J., Yun, J., Lee, B., & Han, K. (2009). A location based routing protocol in mobile sensor networks. In Proceedings of the international conference of advanced communication technology (ICACT’2009), Feb. 15–18, 2009 (pp. 1342–1345). Google Scholar
  60. 60.
    Kweon, K., Ghim, H., Hong, J., & Yoon, H. (2009). Grid- based energy efficient routing from multiple sources to multiple mobile sinks in wireless sensor networks. In Proceedings of 4th international conference on wireless pervasive computing, Melbourne, Australia (pp. 185–189). Google Scholar
  61. 61.
    Chen, K.-H., Huang, J.-M., & Hsiao, C.-C. (2009). CHIRON: an energy efficient chain based hierarchical routing protocol in wireless sensor networks. In Proceedings of wireless telecommunications symposium (WTS’09) (pp. 1–5). CrossRefGoogle Scholar
  62. 62.
    Almazaydeh, L., Abdelfattah, E., Al-Bzoor, M., & Al-Rahayfeh, A. (2010). Performance evaluation of routing protocols in wireless sensor networks. International Journal of Computer Science and Information Technology, 2(2), 64–73. CrossRefGoogle Scholar
  63. 63.
    Nguyen, L. T., Defago, X., Beuran, R., & Shinoda, Y. (2008). Energy efficient routing scheme for mobile wireless sensor networks. In Proceedings of IEEE international symposium on wireless communication systems 2008 (ISWCS ’08) (pp. 568–572). CrossRefGoogle Scholar
  64. 64.
    Zou, L., Lu, M., & Xiong, Z. (2004). PAGER-m: a novel location based routing protocol for mobile sensor networks. In Proceedings of first international workshop on broadband wireless services and applications (BroadWISE). Google Scholar
  65. 65.
    Lee, U., Magistretti, E. O., Zhou, B. O., Gerla, M., Bellavista, P., & Corradi, A. (2006). Efficient data harvesting in mobile sensor platforms. In Proceedings of PerCom workshops (pp. 352–356). Google Scholar
  66. 66.
    Ben Saad, L, & Toarancheau, B. (2011). Sinks mobility strategy in IPv6 based WSNs for network lifetime improvement. In Proceedings of 4th IFIP international conference on new technologies, mobility and security (NTMS), Paris, France (pp. 7–10). Google Scholar
  67. 67.
    Li, J., & Mohapatra, P. (2007). Analytical modeling and mitigation techniques for the energy hole problem in sensor networks. Pervasive and Mobile Computing, 3(3), 233–254. CrossRefGoogle Scholar
  68. 68.
    Li, L., Sun, L., Ma, J., & Chen, C. (2008). A receiver-based opportunistic forwarding protocol for mobile sensor networks. In Proceedings of the the 28th international conference on distributed computing systems workshops (ICDCSW) (pp. 198–203). Google Scholar
  69. 69.
    Qabajeh, L. K., Kiah, L. M., & Qabajeh, M. M. (2009). A qualitative comparison of position based routing protocols for ad-hoc networks. International Journal of Computer Science and Network Security, 9(2), 131–140. Google Scholar
  70. 70.
    Qin, L., & Kunz, T. (2004). Survey on mobile ad hoc network routing protocols and cross-layer design. Technical report SCE-04-14, Systems and Computer Engineering, Carleton University, August 2004. Google Scholar
  71. 71.
    Arboleda, L. M. C., & Nasser, N. (2006). Cluster based routing protocol for mobile sensor networks. In Third international conference on quality of service in heterogeneous wired/wireless networks, August 7–9, 2006, Waterloo, Canada. Google Scholar
  72. 72.
    Lin, H., Lu, M., Milosavljevic, N., Gao, J., & Guibas, L. J. (2008). Composable information gradients in wireless sensor networks. In Proceedings of IPSN’08, April 2008 (pp. 121–132). Google Scholar
  73. 73.
    Liu, B., Brass, P., Dousse, O., Nain, P., & Towsley, D. (2005). Mobility improve coverage of sensor networks. In Proceedings of ACM MobiHoc. Google Scholar
  74. 74.
    Borsani, L., Gugliemi, S., Redondi, A., & Cesana, M. (2011). Tree based routing protocol for mobile wireless sensor networks. In Proceedings of 2011 eighth international conference on wireless on-demand network systems and services (pp. 164–170). CrossRefGoogle Scholar
  75. 75.
    Choi, L., Jung, J. K., Cho, B.-H., & Choi, H. (2008). M-Geocast: robust and energy efficient geometric routing for mobile sensor networks. In LNCS: Vol. 5287. Proceedings of IFIP international federation for information processing (SEUS’2008) (pp. 304–316). Google Scholar
  76. 76.
    Mahesh, K. M., & Samir, D. A. S. (2001). On-demand multipath distance vector routing in ad hoc networks. In Proceedings of international conference for network protocols. Google Scholar
  77. 77.
    Khan, M. I., Gangsterer, W. N., & Haring, G. (2007). Congestion avoidance and energy efficient routing protocol for wireless sensor networks with mobile sink. Journal of Networks, 2(6), 42–49. CrossRefGoogle Scholar
  78. 78.
    Nabi, M., Blagojevic, M., Geilen, M., Basten, T., & Hendriks, T. (2010). MCMAC: an optimized medium access control protocol for mobile clusters in wireless sensor networks. In Proceedings of Secon’2010 (pp. 28–36). Google Scholar
  79. 79.
    Weiser, M. (1991). In The computer for the twenty-first century. Scie. Am., September 1991. Google Scholar
  80. 80.
    Marta, M., & Cardei, M. (2009). Improved sensor network lifetime with multiple mobile sinks. Pervasive and Mobile Computing, 5(5), 542–555. CrossRefGoogle Scholar
  81. 81.
    Mauve, M., Widmer, J., & Hartenstein, H. (2001). A survey on position-based routing in mobile ad hoc networks. Journal of IEEE Network, 01, 30–39. CrossRefGoogle Scholar
  82. 82.
    Roth, M., & Wicker, S. (2003). Termite: ad-hoc networking with stigmergy. In Proceedings of GLOBECOM’2003 (pp. 2937–2941). Google Scholar
  83. 83.
    McDonald, A. B., & Znati, T. F. (1999). A mobility-based framework for adaptive clustering in wireless ad hoc networks. IEEE Journal on Selected Areas in Communications, 17(8), 1466–1487. CrossRefGoogle Scholar
  84. 84.
    Gunes, M., Sorges, U., & Bouazizi, I. (2002). ARA—the ant colony based routing algorithm for MANETs. In Proceedings of international workshop on ad hoc networking (IWAHN’2002), Vancouver, British Columbia, Canada, 18–21 August (Vol. 02, pp. 1–7). Google Scholar
  85. 85.
    Yu, M., Malvankar, A., Su, W., & Foo, S. Y. (2007). A link availability-based QOS aware routing protocol for mobile adhoc sensor networks. Journal of computer Communications, 30, 3823–3831. CrossRefGoogle Scholar
  86. 86.
    Rahimi, M., Shah, H., Sukhatme, G. S., Heideman, J., & Estrin, D. (2003). Studying the feasibility of energy harvesting in a mobile sensor network. In Proc. of the 2003 IEEE international conference on robotics and automation, Taipei, Taiwan. Google Scholar
  87. 87.
    Tarique, M., Tepe, K. E., & Naserian, M. (2005). Energy saving dynamic source routing for ad hoc wireless networks. In Proceedings of modeling and optimization in mobile, ad hoc, and wireless networks, April 2005 (pp. 305–310). Google Scholar
  88. 88.
    Soyturk, M., & Altilar, T. (2006). A novel stateless energy efficient routing algorithm for large scale wireless sensor networks with multiple sinks. In Proceedings of IEEE annual, wireless and microwave technology conference (pp. 1–5). Google Scholar
  89. 89.
    Ababneh, N., & Selvadurai, S. (2006). Topology control algorithms for wireless sensor networks: an overview. International Journal on Wireless & Optical Communications, 3(1), 49–68. CrossRefGoogle Scholar
  90. 90.
    Beijar, N. (2004). Zone Routing Protocol (ZRP). Networking Laboratory, Helsinki University of Technology, Finland, Nicklas.Beijar@hut.fi. Google Scholar
  91. 91.
    Black, N., & Moore, S. (1994). Guass seidal iterative method. http://mathworld.wolfram.com/Gauss-SeidelMethod.html.
  92. 92.
    Olariu, S., & Stojmenovic, I. (2006). Design guidelines for maximizing lifetime and avoiding energy holes in sensor networks with uniform distribution and uniform reporting. In Proceedings of IEEE INFOCOM. Google Scholar
  93. 93.
    Perkins, C. E., & Royer, E. M. (1999). Adhoc on demand distance vector routing. In Mobile computing systems and applications. proceedings of WMCSA’99, February 1999 (pp. 90–100). Google Scholar
  94. 94.
    Kuosmanen, P. (2003). Classification of ad hoc routing protocols. http://eia.udg.es/~lilianac/docs/classification-of-ad-hoc.pdf, Naval Academy, Finland.
  95. 95.
    Jiang, Q., & Manivannan, D. (2004). Routing protocols for sensor networks. In Proceedings of the IEEE consumer communications and networking conference (CCNC’2004), 5–8 January 2004, Las Vegas, Nevada, USA. Google Scholar
  96. 96.
    Rahimi, M., Shah, H., Sukhatme, G. S., Heidemann, J., & Estrin, D. (2003). Studying the feasibility of energy harvesting in a mobile sensor network. In Proceedings of IEEE int’l conf. on robotics and automation. Google Scholar
  97. 97.
    Ramanathan, R., & Rosales-Hain, R. (2000). Topology control of multihop wireless networks using transmit power adjustment. In Proceedings of nineteenth annual joint conference of the IEEE computer and communications societies (INFOCOM) (pp. 404–413). Google Scholar
  98. 98.
    Subrata, R., & Zomaya, A. Y. (2003). Evolving cellular automata for location management in mobile computing networks. IEEE Transactions on Parallel and Distributed Systems, 14(1), 13–26. CrossRefGoogle Scholar
  99. 99.
    Floyd, R. W. (1962). Algorithm 97—shortest path. Communications of the ACM, 5(6), 345. CrossRefGoogle Scholar
  100. 100.
    Kuntz, R., Montavont, J., & Noël, T. (2011). Improving the medium access in highly mobile wireless sensor networks. Telecommunication Systems. doi: 10.1007/s11235-011-9565-6.
  101. 101.
    Munir, S. A., Biaoren, W. J., Wang, B., Xie, D., & Ma, J. (2007). Mobile wireless sensor network: architecture and enabling technologies for ubiquitous computing. In Proceedings of the 21st international conference on advanced information networking and applications workshop (AINAW‘07). Google Scholar
  102. 102.
    Choi, S.-Y., Kim, J.-S., Lee, J.-H., & Rim, K.-W. (2010). REDM: robust and energy efficient dynamic routing for a mobile sink in a multi hop sensor network. In Second international conference on communication software and networks (pp. 178–182). Google Scholar
  103. 103.
    Shah, R. C., Roy, S., Jain, S., & Brunette, W. (2003). Data MULEs: modeling and analysis of a three-tier architecture for sparse sensor networks. In Ad hoc networks journal, September 2003 (Vol. 1, pp. 215–233). Amsterdam: Elsevier. Google Scholar
  104. 104.
    Shah, R. C., Roy, S., Jain, S., & Brunette, W. (2003). DATAMULES: modelling a three tiered architecture for sparse sensor networks. In Proceedings of first IEEE int’l workshop on sensor network protocols and applications. Google Scholar
  105. 105.
    Sivagami, A., Pavai, K., Sridharan, D., & Satya, M. S. A. V. (2008). Design issues on tree based aggregation algorithms in wireless sensor networks. International Journal of IT and Knowledge Management, 1(2), 449–462. Google Scholar
  106. 106.
    Son, D., & Helmy, A. (2004). The effect of mobility-induced location errors on geographic routing in mobile ad hoc and sensor networks: analysis and improvement using mobility prediction. IEEE Transactions on Mobile Computing, 3(3), 233–245. CrossRefGoogle Scholar
  107. 107.
    Basagni, S., Carosi, A., Melachrinoudis, E., Petrioli, C., & Wang, Z. M. (2008). Controlled sink mobility for prolonging wireless sensor networks lifetime. Journal of Wireless Networks, 831–858. Google Scholar
  108. 108.
    Lindsey, S., & Raghavendra, C. S. P. (2002). Power efficient gathering in sensor information systems. In Proceedings of IEEE aerospace conference (Vol. 3, pp. 1125–1130). Google Scholar
  109. 109.
    Stojmenovic, I., & Lin, X. (2001). Loop free hybrid single path/flooding routing algorithms with guaranteed delivery for wireless networks. IEEE Transactions on Parallel and Distributed Systems, 12(10), 1023–1032. CrossRefGoogle Scholar
  110. 110.
    Chang, T.-J., Wang, K., & Hsieh, Y.-L. (2008). A color theory based energy efficient routing algorithm for mobile wireless sensor networks. International Journal of Computer Networks and Communications, 52, 531–541. CrossRefGoogle Scholar
  111. 111.
    Venkitasubramaniam, P., Adireddy, S., & Tong, L. (2004). Sensor networks with mobile access: optimal random access and coding. IEEE Journal on Selected Areas in Communications, 22(6), 1058–1068. CrossRefGoogle Scholar
  112. 112.
    Wang, W., Srinivasan, V., & Chua, K. (2005). Using mobile relays to prolong the lifetime of wireless sensor networks. In Proceedings of MobiCom. Google Scholar
  113. 113.
    Wang, W. D., & Zhu, Q. X. (2008). RSS-Based Monte-Carlo localization for mobile sensor networks. IET Communications, 2(5), 673–681. CrossRefGoogle Scholar
  114. 114.
    Wang, W., Srinivasan, V., & Chua, K.-C. (2005). Using mobile relays to prolong the lifetime of wireless sensor networks. In Proceeding of MobiCom’05. Google Scholar
  115. 115.
    Huang, W.-W., Eng, Y.-L., Wen, J., & Yu, M. (2009). Energy efficient multihop hierarchical routing protocol for wireless sensor networks. In Proceedings of international conference on networks security, wireless communications and trusted computing (pp. 469–472). Google Scholar
  116. 116.
    Heinzelman, W. R., Kulik, J., & Balakrishnan, H. (1999). Adaptive protocols for information dissemination in wireless sensor networks. In Proceedings of Mobicom’99, Seattle Washington, USA (pp. 174–185). Google Scholar
  117. 117.
    Huang, X., Zhai, H., & Fang, Y. (2008). Robust cooperative routing protocol in mobile wireless sensor networks. IEEE Transactions on Wireless Communications, 7(12), 5278–5285. CrossRefGoogle Scholar
  118. 118.
    Guan, X., Guan, L., Wang, X. G., & Ohtsuki, T. (2010). A new load balancing and data collection algorithm for energy saving in wireless sensor networks. Telecommunications Systems, 45, 313–322. doi: 10.1007/s11235-009-9269-3. CrossRefGoogle Scholar
  119. 119.
    Liu, X., Wang, Q., & Jin, X. (2008). An energy efficient routing protocol for wireless sensor networks. In Proceeding of the 7th world congress on intelligent control and automation, 25–27 June 25–27 2008, Chongqing, China (pp. 1728–1733). Google Scholar
  120. 120.
    Zou, X., Ramamurthy, B., & Maglivera, S. (2002). Routing techniques in wireless ad hoc networks—classification and comparison. In Proceedings of the sixth world multiconference on systemics, cybernetics, and informatics (SCI 2002). Google Scholar
  121. 121.
    Luo, Y., Xu, Y., Huang, L., & Xu, H. (2008). A tracking range based ant colony routing protocol for mobile wireless sensor network. In Proceedings of the 4th international conference on mobile ad-hoc and sensor networks (pp. 116–121). Google Scholar
  122. 122.
    Yarvis, M., Kushalnagar, N., Singh, H., Rangarajan, A., Liu, Y., & Singh, S. (2005). Exploiting heterogeneity in sensor networks. In Proceedings of IEEE INFOCOM’2005, Miami, FL. Google Scholar
  123. 123.
    Yang, Y., Fonoage, M. I., & Cardei, M. (2009). Improving network lifetime with mobile wireless sensor networks. Computer Communications. doi: 10.1016/j.comcom.2009.11.010. Google Scholar
  124. 124.
    Yu, F., Park, S., Lee, E., & Kim, S.-H. (2010). Elastic routing: a novel geographic routing for mobile sinks in wireless sensor networks. IET Communications, 4(6), 716–727. CrossRefGoogle Scholar
  125. 125.
    Yu, K., & Guo, Y. J. (2009). Anchor-free localization algorithm and performance analysis in wireless sensor networks. IET Communications, 3(4), 549–560. CrossRefGoogle Scholar
  126. 126.
    Yuen, K., Liang, B., & Li, B. (2006). A distributed framework for correlated data gathering in sensor network. In Proceedings of IFIP 2006. Google Scholar
  127. 127.
    Zaidi, Z. R., & Mark, B. L. (2004). Mobility estimation for wireless networks based on an autoregressive model. In Proceeding of the IEEE GLOBECOM’2004, Dallas, Texas, 4 December. Google Scholar
  128. 128.
    Hameed Mir, Z., & Ko, Y.-B. (2007). A quadtree-based hierarchical data dissemination for mobile sensor networks. Telecommunications Systems, 36, 117–128. doi: 10.1007/s11235-007-9062-0. CrossRefGoogle Scholar
  129. 129.
    (SAM) Ma, Z., & Krings, A. W. (2008). Insect population inspired wireless sensor networks: a unified architecture with survival analysis, evolutionary game theory and hybrid fault models. In Proceedings of IEEE international conference on biomedical engineering and informatics (BMEI’2008) (pp. 636–643). Google Scholar
  130. 130.
    Duan, Z.-F., Guo, F., Deng, M.-X., & Yu, M. (2009). Shortest path routing protocol for multi-layer mobile wireless sensor networks. In International conference on network security, wireless communication and trusted computing (pp. 106–110). Google Scholar
  131. 131.
    Zhong, Z., & Nelakuditi, S. (2007). On the efficacy of opportunistic routing. In Proceedings of Secom’2007 (pp. 441–450). Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of Electronics & Communication Engineering, College of EngineeringAnna UniversityGuindy ChennaiIndia
  2. 2.ChennaiIndia

Personalised recommendations