A comparative analysis of energy conservation approaches in hybrid wireless sensor networks data collection protocols

Telecommunication Systems

Volumn 61, Issue 1, 2016, Pages 159-179

  Abdul Salaam, Gaddafi ^a,d   Abdullah, Abdul Hanan ^a   Anisi, Mohammad Hossein ^b   Gani, Abdullah ^b   Alelaiwi, Abdulhameed ^c  

^a UNIVERSITI TEKNOLOGI MALAYSIA   (Malaysia)

^b UNIVERSITY OF MALAYA   (Malaysia)

^c KING SAUD UNIVERSITY   (Saudi Arabia)

^d KWAME NKRUMAH UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Ghana)

Author keywords

Data collection; Energy; Hybrid wireless sensor network; Latency; Lifetime; Mobile sink

Indexed keywords

ACCIDENT PREVENTION; DATA ACQUISITION; ENERGY CONSERVATION; ENERGY EFFICIENCY; ENERGY UTILIZATION; HYBRID SENSORS; MILITARY APPLICATIONS; SENSOR NODES; TAXONOMIES;

DATA COLLECTION; ENERGY; HYBRID WIRELESS SENSOR NETWORKS; LATENCY; LIFETIME; MOBILE SINKS;

WIRELESS SENSOR NETWORKS;

EID: 84953369707     PISSN: 10184864     EISSN: 15729451     Source Type: Journal    
DOI: 10.1007/s11235-015-0092-8     Document Type: Article

References (103)

1. Akhtar, F., & Rehmani, M. H. (2015). Energy replenishment using renewable and traditional energy resources for sustainable wireless sensor networks: A review. Renewable & Sustainable Energy Reviews, 45, 769–784.
2. Akkaya, K., & Younis, M. (2005). A survey on routing protocols for wireless sensor networks. Ad Hoc Networks, 3(3), 325–349.
3. Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38(4), 393–422.
4. Ammari, H. M. (2012). On the problem of K-coverage in mission-oriented mobile wireless sensor networks. Computer Networks, 56(7), 1935–1950.
5. Ammari, H. M. (2013). Joint K-coverage and data gathering in sparsely deployed sensor networks: Impact of purposeful mobility and heterogeneity. ACM Transactions on Sensor Networks, 10(1), 8.
6. Anastasi, G., Borgia, E., Conti, M., & Di Francesco, M. (2011). Reliable data delivery in sparse wsns with multiple mobile sinks: An experimental analysis. In 2011 IEEE Symposium on Computers and Communications (ISCC) (pp. 698–705).
7. Anastasi, G., Conti, M., Di Francesco, M., & Passarella, A. (2009). Energy conservation in wireless sensor networks: A survey. Ad Hoc Networks, 7(3), 537–568.
8. Anisi, M. H., Abdul-Salaam, G., & Abdullah, A. H. (2015). A survey of wireless sensor network approaches and their energy consumption for monitoring farm fields in precision agriculture. Precision Agriculture, 16(2), 216–238.
9. Anisi, M. H., Abdullah, A. H., Coulibaly, Y., & Razak, S. A. (2013). Edr: Efficient data routing in wireless sensor networks. International Journal of Ad Hoc and Ubiquitous Computing, 12(1), 46–55.
10. Anisi, M. H., Abdullah, A. H., Razak, S. A., & Ngadi, M. A. (2012). An overview of data routing approaches for wireless sensor networks. Sensors, 12(4), 3964–3996.
11. Benharref, A., & Serhani, M. A. (2014). Novel cloud and SOA-based framework for E-health monitoring using wireless biosensors. IEEE Journal of Biomedical and Health Informatics, 18(1), 46–55.
12. Chen, L., Wang, J., Peng, X., & Kui, X. (2015). An energy-efficient and relay hop bounded mobile data gathering algorithm in wireless sensor networks. International Journal of Distributed Sensor Networks.
13. Chen, S., Coolbeth, M., Dinh, H., Kim, Y.-A., & Wang, B. (2009). Data collection with multiple sinks in wireless sensor networks. In B. Liu, A. Bestavros, D.-Z. Du, & J. Wang (Eds.), Wireless algorithms, systems, and applications (pp. 284–294). Berlin/Heidelberg: Springer.
14. Chen, Y.-L., Wang, N.-C., Shih, Y.-N., & Lin, J.-S. (2013). Improving low-energy adaptive clustering hierarchy architectures with sleep mode for wireless sensor networks. Wireless Personal Communications, 75, 1–20.
15. Chen, Y., Tang, Y., Xu, G., Qian, H., & Xu, Y. (2011). A data gathering algorithm based on swarm intelligence and load balancing strategy for mobile sink. In 2011 9th World Congress on Intelligent Control and Automation (WCICA) (pp. 1002–1007).
16. Chen, Y. P., Liestman, A. L., & Liu, J. (2006). A hierarchical energy-efficient framework for data aggregation in wireless sensor networks. IEEE Transactions on Vehicular Technology, 55(3), 789–796.
17. Cheng, C.-T., & Tse, C. K. (2013). A delay-aware network structure for wireless sensor networks with consecutive data collection processes. IEEE Sensors Journal, 13(6), 2413–2422.
18. Costa, D. G., & Guedes, L. A. (2010). The coverage problem in video-based wireless sensor networks: A survey. Sensors, 10(9), 8215–8247.
19. Danpu, L., Kailin, Z., & Jie, D. (2013). Energy-efficient transmission scheme for mobile data gathering in wireless sensor networks. Communications, China, 10(3), 114–123.
20. Di Francesco, M., Das, S. K., & Anastasi, G. (2011). Data collection in wireless sensor networks with mobile elements: A survey. ACM Transactions on Sensor Networks, 8(1), 7.
21. Ebrahimi, D., & Assi, C. (2014). Compressive data gathering using random projection for energy efficient wireless sensor networks. Ad Hoc Networks, 16, 105–119.
22. Eu, Z. A., Tan, H.-P., & Seah, W. K. (2010). Opportunistic routing in wireless sensor networks powered by ambient energy harvesting. Computer Networks, 54(17), 2943–2966.
23. Faheem, Y., Boudjit, S., & Chen, K. (2011). Dynamic sink location update scope control mechanism for mobile sink wireless sensor networks. In 2011 8th International Conference on Wireless On-Demand Network Systems and Services (WONS) (pp. 171–178).
24. Fan, K.-W., Zheng, Z., & Sinha, P. (2008). Steady and fair rate allocation for rechargeable sensors in perpetual sensor networks. In Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems (pp. 239–252).
25. Farris, I., Militano, L., Iera, A., Molinaro, A., & Spinella, S. C. (2015). Tag-based cooperative data gathering and energy recharging in wide area rfid sensor networks. Ad Hoc Networks.
26. Fernandes, M. A., Matos, S. G., Peres, E., Cunha, C. R., Lopez, J. A., Ferreira, P. J. S. G., et al. (2013). A framework for wireless sensor networks management for precision viticulture and agriculture based on IEEE 1451 standard. Computers and Electronics in Agriculture, 95, 19–30.
27. Ganeriwal, S., Kansal, A., & Srivastava, M. B. (2004). Self aware actuation for fault repair in sensor networks. robotics and automation, 2004. In IEEE International Conference on Proceedings ICRA’04. 2004 (pp. 5244–5249).
28. Garcia, M., Sendra, S., Lloret, J., & Canovas, A. (2013). Saving energy and improving communications using cooperative group-based wireless sensor networks. Telecommunication Systems, 52(4), 2489–2502.
29. Gomaa, R., Adly, I., Sharshar, K., Safwat, A., & Ragai, H. (2013). Zigbee wireless sensor network for radiation monitoring at nuclear facilities. In 2013 6th Joint IFIP Wireless and Mobile Networking Conference (WMNC) (pp. 1–4).
30. Gu, Y., Bozdag, D., Ekici, E., Özgüner, F., & Lee, C.-G. (2005). Partitioning based mobile element scheduling in wireless sensor networks. In SECON (pp. 386–395).
31. Guo, S., Wang, C., & Yang, Y. (2014). Joint mobile data gathering and energy provisioning in wireless rechargeable sensor networks. IEEE Transactions on Mobile Computing, 13(12), 2836–2852.
32. Ha, I., Djuraev, M., & Ahn, B. (2014). An energy-efficient data collection method for wireless multimedia sensor networks. International Journal of Distributed Sensor Networks.
33. Halder, S., & Das, B. S. (2014). Enhancement of wireless sensor network lifetime by deploying heterogeneous nodes. Journal of Network and Computer Applications, 38, 106–124.
34. Han, G., Guo, H., Zhang, C., & Shu, L. (2014). Parameter optimisation in duty-cycled wireless sensor networks under expected network lifetime. International Journal of Ad Hoc and Ubiquitous Computing, 15(1), 57–67.
35. He, L., Fu, L., Zheng, L., Gu, Y., Cheng, P., Chen, J., & Pan, J. (2014). Esync: An energy synchronized charging protocol for rechargeable wireless sensor networks. In Proceedings of the 15th ACM International Symposium on Mobile Ad Hoc Networking and Computing (pp. 247–256).
36. Hu, Y., Ding, Y., Hao, K., Ren, L., & Han, H. (2014). An immune orthogonal learning particle swarm optimisation algorithm for routing recovery of wireless sensor networks with mobile sink. International Journal of Systems Science, 45(3), 337–350.
37. Incel, O. D., Ghosh, A., Krishnamachari, B., & Chintalapudi, K. (2012). Fast data collection in tree-based wireless sensor networks. IEEE Transactions on Mobile Computing, 11(1), 86–99.
38. Iwanicki, K., & Van Steen, M. (2009). Multi-hop cluster hierarchy maintenance in wireless sensor networks: A case for Gossip-rased protocols. In U. Roedig & C. J. Sreenan (Eds.), Wireless sensor networks, proceedings (pp. 102–117).
39. Jawhar, I., Mohamed, N., Al-Jaroodi, J., & Zhang, S. (2014). A framework for using unmanned aerial vehicles for data collection in linear wireless sensor networks. Journal of Intelligent and Robotic Systems: Theory and Applications, 74(1–2), 437–453.
40. Jia, L., Rajaraman, R., & Scheideler, C. (2003). On local algorithms for topology control and routing in ad hoc networks. In Proceedings of the 15th Annual ACM Symposium on Parallel Algorithms and Architectures (pp. 220–229).
41. Jin, W., Yue, Y., Jianwei, Z., Sungyoung, L., & Sherratt, R. S. (2013). Mobility based energy efficient and multi-sink algorithms for consumer home networks. IEEE Transactions on Consumer Electronics, 59(1), 77–84.
42. Khan, A. W., Abdullah, A. H., Anisi, M. H., & Bangash, J. I. (2014). A comprehensive study of data collection schemes using mobile sinks in wireless sensor networks. Sensors, 14(2), 2510–2548.
43. Khan, A. W., Abdullah, A. H., Razzaque, M. A., & Bangash, J. I. (2015a). Vgdra: A virtual grid-based dynamic routes adjustment scheme for mobile sink-based wireless sensor networks. IEEE Sensors Journal, 15(1), 526–534.
44. Khan, A. W., Abdullah, A. H., Razzaque, M. A., Bangash, J. I., & Altameem, A. (2015b). Vgdd: A virtual grid based data dissemination scheme for wireless sensor networks with mobile sink. International Journal of Distributed Sensor Networks.
45. Khan, J. A., Qureshi, H. K., & Iqbal, A. (2015c). Energy management in wireless sensor networks: A survey. Computers & Electrical Engineering, 41, 159–176.
46. Konstantopoulos, C., Pantziou, G., Gavalas, D., Mpitziopoulos, A., & Mamalis, B. (2012). A Rendezvous-based approach enabling energy-efficient sensory data collection with mobile sinks. IEEE Transactions on Parallel and Distributed Systems, 23(5), 809–817.
47. Kumar, D., & Patel, R. (2011). Multi-hop data communication algorithm for clustered wireless sensor networks. International Journal of Distributed Sensor Networks.
48. Lambrou, T. P., & Panayiotou, C. G. (2013). Collaborative path planning for event search and exploration in mixed sensor networks. The International Journal of Robotics Research, 32(12), 1424–1437.
49. Larios, D. F., Barbancho, J., Sevillano, J. L., Rodriguez, G., Molina, F. J., Gasull, V. G., et al. (2013). Five years of designing wireless sensor networks in the Donana biological reserve (Spain): An applications approach. Sensors, 13(9), 12044–12069.
50. Levin, L., Efrat, A., & Segal, M. (2014). Collecting data in ad-hoc networks with reduced uncertainty. Ad Hoc Networks, 17, 71–81.
51. 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.
52. Li, Z., Wang, N., Franzen, A., Taher, P., Godsey, C., Zhang, H., et al. (2014). Practical deployment of an in-field soil property wireless sensor network. Computer Standards & Interfaces, 36(2), 278–287.
53. Liang, W., Luo, J., & Xu, X. (2013). Network lifetime maximization for time-sensitive data gathering in wireless sensor networks with a mobile sink. Wireless Communications & Mobile Computing, 13(14), 1263–1280.
54. Lin, C.-J., Chou, P.-L., & Chou, C.-F. (2006). Hcdd: Hierarchical cluster-based data dissemination in wireless sensor networks with mobile sink. In Proceedings of the 2006 International Conference on Wireless Communications and Mobile Computing (pp. 1189–1194).
55. Liu, R.-S., Fan, K.-W., Zheng, Z., & Sinha, P. (2011). Perpetual and fair data collection for environmental energy harvesting sensor networks. IEEE/ACM Transactions on Networking, 19(4), 947–960.
56. Liu, W., Lu, K., Wang, J., Huang, L., & Wu, D. O. (2012). On the throughput capacity of wireless sensor networks with mobile relays. IEEE Transactions on Vehicular Technology, 61(4), 1801–1809.
57. Lu, K.-H., Hwang, S.-F., Su, Y.-Y., Chang, H.-N., & Dow, C.-R. (2012). Hierarchical ring-based data gathering for dense wireless sensor networks. Wireless Personal Communications, 64(2), 347–367.
58. Luo, H., Ye, F., Cheng, J., Lu, S., & Zhang, L. (2005). Ttdd: Two-tier data dissemination in large-scale wireless sensor networks. Wireless Networks, 11(1–2), 161–175.
59. Ma, M., Yang, Y., & Zhao, M. (2013). Tour planning for mobile data-gathering mechanisms in wireless sensor networks. IEEE Transactions on Vehicular Technology, 62(4), 1472–1483.
60. Madani, S. A., Hayat, K., & Khan, S. U. (2012). Clustering-based power-controlled routing for mobile wireless sensor networks. International Journal of Communication Systems, 25(4), 529–542.
61. Mamalis, B., Gavalas, D., Konstantopoulos, C., & Pantziou, G. (2009). Clustering in wireless sensor networks. In Y. Zhang, L. T. Yang, & J. Chen (Eds.), RFID and sensor networks: architectures, protocols, security and integrations (pp. 324–353).
62. Medhi, N., & Sarma, N. (2012). Mobility aided cooperative mimo transmission in wireless sensor networks. In S. K. Jena & B. Majhi (Eds.), 2nd International Conference on Communication, Computing & Security (ICCCS-2012) (pp. 362–370).
63. Moon, J., & Leeb, S. B. (2015). Analysis model for magnetic energy harvesters. IEEE Transactions on Power Electronics, 30(8), 4302–4311.
64. Munir, S. A., Ren, B., Jiao, W., Wang, B., Xie, D. and Ma, J. (2007). Mobile wireless sensor network: architecture and enabling technologies for ubiquitous computing. In 21st International Conference on Advanced Information Networking and Applications Workshops, 2007, AINAW’07 (pp. 113–120).
65. Narendra, K., & Varun, V. (2014). A comparative analysis of energy-efficient routing protocols in wireless sensor networks. In Emerging Research in Electronics, Computer Science and Technology (pp. 399–405). Springer.
66. Nazir, B., & Hasbullah, H. (2013). Energy efficient and Qos aware routing protocol for clustered wireless sensor network. Computers & Electrical Engineering, 39(8), 2425–2441.
67. Ngai, E.-H., Zhou, Y., Lyu, M. R., & Liu, J. (2006). Reliable reporting of delay-sensitive events in wireless sensor-actuator networks. In 2006 IEEE International Conference on Mobile Adhoc and Sensor Systems (MASS) (pp. 101–108).
68. Ortiz, A. M., Royo, F., Olivares, T., Castillo, J. C., Orozco-Barbosa, L., & Marron, P. J. (2013). Fuzzy-logic based routing for dense wireless sensor networks. Telecommunication Systems, 52(4), 2687–2697.
69. Pottie, G. J., & Kaiser, W. J. (2000). Wireless integrated network sensors. Communications of the ACM, 43(5), 51–58.
70. Qiuling, T., Changyin, S., Huan, W., & Ye, L. (2010). Cross-layer energy efficiency analysis and optimization in WSN. In 2010 International Conference on Networking, Sensing and Control (ICNSC) (pp. 138–142). Accessed 10–12 Apr 2010.
71. Rahimi, M., Shah, H., Sukhatme, G., Heideman, J., & Estrin, D. (2003). Studying the feasibility of energy harvesting in a mobile sensor network. In Proceedings of ICRA ’03. IEEE International Conference on Robotics and Automation, 2003 (vol. 11, pp. 19–24). Accessed 14–19 Sept 2003.
72. Ranjani, S. S., Krishnan, S. R., Thangaraj, C., & Devi, K. V. (2013). Achieving energy conservation by cluster based data aggregation in wireless sensor networks. Wireless Personal Communications, 73(3), 731–751.
73. Rault, T., Bouabdallah, A., & Challal, Y. (2014). Energy efficiency in wireless sensor networks: A top-down survey. Computer Networks, 67, 104–122.
74. Sara, G. S., & Sridharan, D. (2014). Routing in mobile wireless sensor network: A survey. Telecommunication Systems, 57(1), 51–79.
75. Shah, R. C., Roy, S., Jain, S., & Brunette, W. (2003). Data Mules: Modeling and analysis of a three-tier architecture for sparse sensor networks. Ad Hoc Networks, 1(2–3), 215–233.
76. Shankar, T., & Shanmugavel, S. (2014). Energy optimization in cluster based wireless sensor networks. Journal of Engineering Science and Technology, 9(2), 246–260.
77. Shi, L., Zhang, B., Huang, K., & Ma, J. (2011). An efficient data-driven routing protocol for wireless sensor networks with mobile sinks. In 2011 IEEE International Conference on Communications (ICC) (pp. 1–5).
78. Shin, I., Kim, M., Mutka, M. W., Choo, H., & Lee, T.-J. (2009). Mcbt: Multi-hop cluster based stable backbone trees for data collection and dissemination in WSNs. Sensors, 9(8), 6028–6045.
79. Shrivastava, P., & Pokle, S. B. (2014). Energy efficient scheduling strategy for data collection in wireless sensor networks, pp. 170–173.
80. Swami, A., Zhao, Q., Hong, Y.-W., & Tong, L. (2007). Wireless sensor networks: Signal processing and communications. New York: Wiley.
81. Tseng, Y.-C., Wu, F.-J., & Lai, W.-T. (2013). Opportunistic data collection for disconnected wireless sensor networks by mobile Mules. Ad Hoc Networks, 11(3), 1150–1164.
82. Tyagi, S., & Kumar, N. (2013). A systematic review on clustering and routing techniques based upon leach protocol for wireless sensor networks. Journal of Network and Computer Applications, 36(2), 623–645.
83. Tzung-Cheng, C., Tzung-Shi, C., & Ping-Wen, W. (2011). On data collection using mobile robot in wireless sensor networks. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 41(6), 1213–1224.
84. Van Le, D., Oh, H., & Yoon, S. (2014). Hicodg: A hierarchical data-gathering scheme using cooperative multiple mobile elements. Sensors, 14(12), 24278–24304.
85. Verma, A., Sawant, H., & Tan, J. (2006). Selection and navigation of mobile sensor nodes using a sensor network. Pervasive and Mobile Computing, 2(1), 65–84.
86. Wang, C., Li, J., Ye, F. and Yang, Y. (2013a). Multi-vehicle coordination for wireless energy replenishment in sensor networks. In 2013 IEEE 27th International Symposium on Parallel & Distributed Processing (IPDPS) (pp. 1101–1111).
87. Wang, G., Wang, T., Jia, W., Guo, M., & Li, J. (2009). Adaptive location updates for mobile sinks in wireless sensor networks. The Journal of Supercomputing, 47(2), 127–145.
88. Wang, J., Li, B., Xia, F., Kim, C.-S., & Kim, J.-U. (2014a). An energy efficient distance-aware routing algorithm with multiple mobile sinks for wireless sensor networks. Sensors, 14(8), 15163–15181.
89. Wang, J., Yang, X., Li, B., Lee, S., & Jeon, S. (2013b). A mobile sink based uneven clustering algorithm for wireless sensor networks. Journal of Internet Technology, 14(6), 895–902.
90. Wang, J., Zuo, L., Shen, J., Li, B., & Lee, S. (2014b). Multiple mobile sink-based routing algorithm for data dissemination in wireless sensor networks. Concurrency and Computation: Practice and Experience.
91. Wang, S., Vasilakos, A., Jiang, H., Ma, X., Liu, W., Peng, K., Liu, B., & Dong, Y. (2011). Energy efficient broadcasting using network coding aware protocol in wireless ad hoc network. In 2011 IEEE International Conference on Communications (ICC) (pp. 1–5).
92. Wang, Y.-C. (2014). Mobile sensor networks: System hardware and dispatch software. ACM Computing Surveys, 47(1), 12.
93. Wen, Y. F., Anderson, T. A., & Powers, D. M. (2014). On energy-efficient aggregation routing and scheduling in IEEE 802.15. 4-based wireless sensor networks. Wireless Communications and Mobile Computing, 14(2), 232–253.
94. Wichmann, A., Chester, J., & Korkmaz, T. (2012). Smooth path construction for data mule tours in wireless sensor networks. In 2012 IEEE Global Communications Conference (GLOBECOM) (pp. 86–92).
95. Wimalajeewa, T., & Jayaweera, S. K. (2010). Impact of mobile node density on detection performance measures in a hybrid sensor network. IEEE Transactions on Wireless Communications, 9(5), 1760–1769.
96. Xu, L., Delaney, D. T., O’hare, G. M., & Collier, R. (2013). The impact of transmission power control in wireless sensor networks. In 2013 12th IEEE International Symposium on Network Computing and Applications (NCA) (pp. 255–258).
97. Yin, F., Li, Z., & Wang, H. (2013). Energy-efficient data collection in multiple mobile gateways WSN-MCN convergence system. pp. 271–276.
98. You-Chiun, W., Wen-Chih, P., & Yu-Chee, T. (2010). Energy-balanced dispatch of mobile sensors in a hybrid wireless sensor network. IEEE Transactions on Parallel and Distributed Systems, 21(12), 1836–1850.
99. Yuan, F., Zhan, Y., & Wang, Y. (2014). Data density correlation degree clustering method for data aggregation in WSN. IEEE Sensors Journal, 14(4), 1089–1098.
100. Zhang, J., & Varadharajan, V. (2010). Wireless sensor network key management survey and taxonomy. Journal of Network and Computer Applications, 33(2), 63–75.
101. Zhao, M., Li, J., & Yang, Y. (2014). A framework of joint mobile energy replenishment and data gathering in wireless rechargeable sensor networks. IEEE Transactions on Mobile Computing, 13(12), 2689–2705.
102. Zhao, M., Ma, M., & Yang, Y. (2011). Efficient data gathering with mobile collectors and space-division multiple access technique in wireless sensor networks. IEEE Transactions on Computers, 60(3), 400–417.
103. Zhong, M., & Cassandras, C. G. (2011). Distributed coverage control and data collection with mobile sensor networks. IEEE Transactions on Automatic Control, 56(10), 2445–2455.