Advertisement

Wireless Personal Communications

, Volume 97, Issue 3, pp 3355–3425 | Cite as

Data Aggregation in Wireless Sensor Networks: Previous Research, Current Status and Future Directions

  • Sukhchandan RandhawaEmail author
  • Sushma Jain
Article

Abstract

Wireless sensor networks (WSNs) consist of large number of small sized sensor nodes, whose main task is to sense the desired phenomena in a particular region of interest. These networks have large number of applications such as habitat monitoring, disaster management, security and military etc. Sensor nodes are very small in size and have limited processing capability as these nodes have very low battery power. WSNs are also prone to failure, due to low battery power constraint. Data aggregation is an energy efficient technique in WSNs. Due to high node density in sensor networks same data is sensed by many nodes, which results in redundancy. This redundancy can be eliminated by using data aggregation approach while routing packets from source nodes to base station. Researchers still face trouble to select an efficient and appropriate data aggregation technique from the existing literature of WSNs. This research work depicts a broad methodical literature analysis of data aggregation in the area of WSNs in specific. In this survey, standard methodical literature analysis technique is used based on a complete collection of 123 research papers out of large collection of 932 research papers published in 20 foremost workshops, symposiums, conferences and 17 prominent journals. The current status of data aggregation in WSNs is distributed into various categories. Methodical analysis of data aggregation in WSNs is presented which includes techniques, tools, methodology and challenges in data aggregation. The literature covered fifteen types of data aggregation techniques in WSNs. Detailed analysis of this research work will help researchers to find the important characteristics of data aggregation techniques and will also help to select the most suitable technique for data aggregation. Research issues and future research directions have also been suggested in this research literature.

Keywords

Data aggregation Wireless sensor networks Energy efficiency Quality of service 

References

  1. 1.
    Tan, H. Ö., & Korpeoglu, I. (2003). Power efficient data gathering and aggregation in wireless sensor networks. ACM SIGMOD Record, 32(4), 66–71.Google Scholar
  2. 2.
    Pourpeighambar, S. B., Aminian, M., & Sabaei, M. (2011). Energy efficient data aggregation of moving object in wireless sensor networks. In Australasian telecommunication networks and applications conference (pp. 1–8).Google Scholar
  3. 3.
    Krishnamachari, L., Estrin, D., & Wicker, S. (2002). The impact of data aggregation in wireless sensor networks. In Proceedings of 22nd international conference of distributed computing system work (pp. 575–578).Google Scholar
  4. 4.
    Qayyum, B., Saeed, M., & Roberts, J. A. (2015). Data aggregation in wireless sensor networks with minimum delay and minimum use of energy: A comparative study. In Accepted for publication in Electronic Workshops in Computing (eWiC). British Computer Society.Google Scholar
  5. 5.
    Cayirci, E. (2003). Data aggregation and dilution by modulus addressing in wireless sensor networks. IEEE Communication Letters, 7(8), 355–357.Google Scholar
  6. 6.
    Dagar, M., & Mahajan, S. (2013). Data aggregation in wireless sensor network: A survey. International Journal of Information and Computation Technology, 3(3), 167–174.Google Scholar
  7. 7.
    Tan, H. Ö., & Körpeoǧlu, I. (2003). Power efficient data gathering and aggregation in wireless sensor networks. ACM SIGMOD Record, 32(4), 66–71.Google Scholar
  8. 8.
    Madden, S., Franklin, M. J. Hellerstein, J. M., & Hong, W. (2002). TAG: A tiny aggregation service for ad hoc sensor networks. In Proceedings of 5th symposium operating systems design implementation (Vol. 36, no. SI, pp. 131–146).Google Scholar
  9. 9.
    Al-Karaki, I. N., UI-Mustafa, R., & Kamal, A. E. (2004). Data aggregation in wireless sensor networks—Exact and approximate algorithms. In Work. High performance switching and routing, 2004. HPSR (pp. 241–245).Google Scholar
  10. 10.
    Massad, Y. E., Goyeneche, M., Astrain, J. J. & Villadangos, J. (2008). Data aggregation in wireless sensor networks. In 3rd international conference information communication technologies from theory to applications (Vol. 2, pp. 1040–1052).Google Scholar
  11. 11.
    Rajagopalan, R., & Varshney, P. K. (2006). Data-aggregation techniques in sensor networks: A survey. IEEE Communications Surveys and Tutorials, 8(4), 48–63.Google Scholar
  12. 12.
    Jesus, P., Baquero, C., & Almeida, P. S. (2015). A survey of distributed data aggregation algorithms. IEEE Communications Surveys & Tutorials, 17(1), 381–404.Google Scholar
  13. 13.
    Kalpakis, K., Dasgupta, K., & Namjoshi, P. (2003). Efficient algorithms for maximum lifetime data gathering and aggregation in wireless sensor networks. Computer Networks, 42(6), 697–716.zbMATHGoogle Scholar
  14. 14.
    Lu, G., Krishnamachari, B., & Raghavendra, C. S. (2004). An adaptive energy-efficient and low-latency MAC for data gathering in wireless sensor networks. In 18th international parallel distributed processing symposium 2004 proceedings, 2004.Google Scholar
  15. 15.
    Li, W., Bandai, M., & Watanabe, T. (2010). Tradeoffs among delay, energy and accuracy of partial data aggregation in wireless sensor networks. In Proceedings of IEEE international conference advanced information networking and applications AINA (pp. 917–924).Google Scholar
  16. 16.
    Li, H., Lin, K., & Li, K. (2011). Energy-efficient and high-accuracy secure data aggregation in wireless sensor networks. Computer Communications, 34(4), 591–597.MathSciNetGoogle Scholar
  17. 17.
    Liu, C. X., Liu, Y., Zhang, Z. J., & Cheng, Z. Y. (2013). High energy-efficient and privacy-preserving secure data aggregation for wireless sensor networks. International Journal of Communication Systems, 26(3), 380–394.Google Scholar
  18. 18.
    Li, H., Wu, C., Hua, Q. S., & Lau, F. C. M. (2011). Latency-minimizing data aggregation in wireless sensor networks under physical interference model. Ad Hoc Networks, 12, 52–68.Google Scholar
  19. 19.
    Shan, M., Chen, G., Luo, D., Zhu, X., & Wu, X. (2014). Building maximum lifetime shortest path data aggregation trees in wireless sensor networks. ACM Transactions on Sensor Networks, 11(1), 11–18.Google Scholar
  20. 20.
    Tsai, S. Y., Sou, S. I., & Tsai, M. H. (2014). Reducing energy consumption by data aggregation in M2M networks. Wireless Personal Communications, 74(4), 1231–1244.Google Scholar
  21. 21.
    Randhawa, S., & Jain, S. (2017). An intelligent PSO-based energy efficient load balancing multipath technique in wireless sensor networks. Turkish Journal of Electrical Engineering & Computer Sciences, 25(4), 3113–3131.Google Scholar
  22. 22.
    Randhawa, S., & Jain, S. (2015). A systematic review on energy aware QoS routing in wireless sensor networks. International Journal of Energy, Information and Communications, 6(5), 1–14.Google Scholar
  23. 23.
    Al-Karaki, J. N., Ul-Mustafa, R., & Kamal, A. E. (2009). Data aggregation and routing in wireless sensor networks: Optimal and heuristic algorithms. Computer Networks, 53(7), 945–960.zbMATHGoogle Scholar
  24. 24.
    Li, M., Xu,, Wang, S., & Tang, S. (2009). Efficient data aggregation in multi-hop wireless sensor networks under physical interference model. In IEEE 6th international conference on mobile adhoc and sensor systems (pp. 353–362).Google Scholar
  25. 25.
    Rout, R. R., & Ghosh, S. K. (2014). Adaptive data aggregation and energy efficiency using network coding in a clustered wireless sensor network: An analytical approach. Computer Communications, 40, 65–75.Google Scholar
  26. 26.
    Mantri, D., Prasad, N. R., & Prasad, R. (2013). MHBCDA: Mobility and heterogeneity aware bandwidth efficient cluster based data aggregation for wireless sensor network. In 3rd International conference on wireless communications, vehicular technology, information theory and aerospace & electronics systems (VITAE) (pp. 24–27).Google Scholar
  27. 27.
    Banerjee, R. (2014). Cluster based routing algorithm with evenly load distribution for large scale networks. In 2014 International conference on computer communication and informatics (ICCCI) (no. I, pp. 1–6).Google Scholar
  28. 28.
    Intanagonwiwat, C., Estrin, D., Govindan, R., & Heidemann, J. (2002). Impact of network density on data aggregation in wireless sensor networks. In Proceedings of 22nd international conference of distributed computing system (pp. 17–18).Google Scholar
  29. 29.
    Chatterjea, S. (2003). A dynamic data aggregation scheme for wireless sensor networks. In Proceedings of the 14th ProRISC workshop on circuits, systems and signal processing (pp. 1–7). Japan: Kokurakita.Google Scholar
  30. 30.
    He, T., Blum, B. M., Stankovic, J. A., & Abdelzaher, T. (2004). AIDA: Adaptive application-independent data aggregation in wireless sensor networks. ACM Transactions on Embedded Computing Systems (TECS), 3(2), 426–457.Google Scholar
  31. 31.
    Hu, F., Cao, X., & May, C. (2005). Optimized scheduling for data aggregation in wireless sensor networks. In International conference on information technology: Coding and computing, 2005. ITCC 2005 (pp. 557–561).Google Scholar
  32. 32.
    Çam, H., Özdemir, S., Nair, P., Muthuavinashiappan, D., & Sanli, H. O. (2006). Energy-efficient secure pattern based data aggregation for wireless sensor networks. Computer Communications, 29(4), 446–455.Google Scholar
  33. 33.
    Gao, J., Guibas, L., Milosavljevic, N., & Hershberger, J. (2007). Sparse data aggregation in sensor networks. In 6th International conference on information processing in sensor networks, ACM Proceeding (pp. 430–439).Google Scholar
  34. 34.
    Yu, B., Li, J., & Li, Y. (2009). Distributed data aggregation scheduling in wireless sensor network. In IEEE INFOCOM 200928th conference of computation communication (pp. 2159–2167).Google Scholar
  35. 35.
    Jiang, H., Jin, S., Wang, C., & Member, S. (2010). Parameter-based data aggregation for statistical information extraction in wireless sensor networks. IEEE Transactions Vehicular Technology, 59(8), 3992–4001.Google Scholar
  36. 36.
    Li, Y., Guo, L., & Prasad, S. K. (2010). An energy-efficient distributed algorithm for minimum-latency aggregation scheduling in wireless sensor networks. In Proceeding of IEEE international conference distributed computing systems (pp. 827–836).Google Scholar
  37. 37.
    Villas, L. A., Guidoni, D. L., Araujo, R. B., Boukerche, A., & Loureiro, A. F. (2010). A scalable and dynamic data aggregation aware routing protocol for wireless sensor networks. In Proceedings of the 13th ACM international conference on modeling, analysis, and simulation of wireless and mobile systems (pp. 110–117).Google Scholar
  38. 38.
    Wei, G., Ling, Y., Guo, B., Xiao, B., & Vasilakos, A. V. (2011). Prediction-based data aggregation in wireless sensor networks: Combining grey model and Kalman Filter. Computer Communications, 34(6), 793–802.Google Scholar
  39. 39.
    Jung, W. S., Lim, K. W., Ko, Y. B., & Park, S. J. (2011). Efficient clustering-based data aggregation techniques for wireless sensor networks. Wireless Networks, 17(5), 1387–1400.Google Scholar
  40. 40.
    Guo, W., Xiong, N., Vasilakos, A. V., Chen, G., & Cheng, H. (2011). Multi-source temporal data aggregation in wireless sensor networks. Wireless Personal Communications, 56(3), 359–370.Google Scholar
  41. 41.
    Chen, C. M., Lin, Y. H., Lin, Y. C., & Sun, H. M. (2012). RCDA: Recoverable concealed data aggregation for data integrity in wireless sensor networks. IEEE Transactions Parallel and Distributed Systems, 23(4), 727–734.Google Scholar
  42. 42.
    Mantri, D., Prasad, N. R., Prasad, R., & Ohmori, S. (2012). Two tier cluster based data aggregation (TTCDA) in wireless sensor network. IEEE International Conference Advanced Networks Telecommunciations Systems, 2012, 117–122.Google Scholar
  43. 43.
    Kuo,T. W., & Tsai, M. J. (2012). On the construction of data aggregation tree with minimum energy cost in wireless sensor networks: NP-completeness and approximation algorithms. In Proceedings of IEEE INFOCOM (pp. 2591–2595).Google Scholar
  44. 44.
    Virmani, D., Sharma, T., & Sharma, R. (2013). Adaptive energy aware data aggregation tree for wireless sensor networks. International Journal of Hybrid Information Technology, 6, 26–36.Google Scholar
  45. 45.
    Ren, F., Zhang, J., Wu, Y., He, T., & Chen, C. (2013). Attribute-aware data aggregation using potential-based dynamic routing in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 24, 881–892.Google Scholar
  46. 46.
    Mantri, D., Prasad, N. R., & Prasad, R. (2013). Grouping of clusters for efficient data aggregation (GCEDA) in wireless sensor network. In 3rd IEEE International advance computing conference IACC 2013 (pp. 132–137).Google Scholar
  47. 47.
    Kumar, M., & Rajkumar, N. (2013). SCT based adaptive data aggregation for wireless sensor networks. Wireless Personal Communications, 75(4), 2121–2133.Google Scholar
  48. 48.
    Li, D., Zhu, Q., Du, H., & Li, J. (2012). An improved distributed data aggregation scheduling in wireless sensor networks. Journal of Combinatorial Optimization, 27(2), 221–240.MathSciNetzbMATHGoogle Scholar
  49. 49.
    Mantri, D. S., Prasad, N. R., & Prasad, R. (2015). Bandwidth efficient cluster-based data aggregation for wireless sensor network. Computers & Electrical Engineering, 41, 256–264.Google Scholar
  50. 50.
    Lee, H., Hwang, H., Duc, T. L., Shon, M. H., Choo, H., & Kim, D. S. (2015). Restructuring binomial trees for delay-aware and energy-efficient data aggregation in wireless sensor networks. In Proceedings of the 9th international conference on ubiquitous information management and communication (pp. 13–20).Google Scholar
  51. 51.
    Liu, Y., Liu, C. X., & Zeng, Q. (2015). Improved trust management based on the strength of ties for secure data aggregation in wireless sensor networks. Telecommunication Systems, 62(2), 319–325.Google Scholar
  52. 52.
    Azad, P., & Sharma, V. (2015). Pareto-optimal clustering scheme using data aggregation for wireless sensor networks. International Journal of Electronics, 102(7), 1165–1176.Google Scholar
  53. 53.
    Asemani, M., & Esnaashari, M. (2015). Learning automata based energy efficient data aggregation in wireless sensor networks. Wireless Networks, 21(6), 2035–2053.Google Scholar
  54. 54.
    Kitchenham, B. A., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. Technical Report EBSE-2007-01, School of Computer Science and Mathematics, Keele University, Keele and Department of Computer Science, University of Durham, Durham, UK (p. 65).Google Scholar
  55. 55.
    Chen, H., Mineno, H., & Mizuno, T. (2008). Adaptive data aggregation scheme in clustered wireless sensor networks. Computer Communications, 31(15), 3579–3585.Google Scholar
  56. 56.
    Wu, W., Cao, J., Wu, H., & Li, J. (2012). Robust and dynamic data aggregation in wireless sensor networks: A cross-layer approach. In 2012 9th International conference on ubiquitous intelligent computing (Vol. 57, pp. 306–313).Google Scholar
  57. 57.
    Zheng, J., Member, S., Wang, P., & Li, C. (2010). Distributed data aggregation using Slepian–Wolf coding in cluster-based wireless sensor networks. IEEE Transactions on Vehicular Technology, 59(5), 2564–2574.Google Scholar
  58. 58.
    Maraiya, K., Kant, K., & Gupta, N. (2011). Efficient cluster head selection scheme for data aggregation in wireless sensor network. International Journal Computer Applications, 23(9), 10–18.Google Scholar
  59. 59.
    Yuea, J., Zhang, W., Xiao, W., Tang, D., & Tang, J. (2012). Energy efficient and balanced cluster-based data aggregation algorithm for wireless sensor networks. Procedia Engineering, 29, 2009–2015.Google Scholar
  60. 60.
    Sinha, A., & Lobiyal, D. K. (2013). Performance evaluation of data aggregation for cluster-based wireless sensor network. Human-Centric Computing and Information Sciences, 3(1), 1–13.Google Scholar
  61. 61.
    Xu, X., Ansari, R., Khokhar, A., & Vasilakos, A. V. (2015). Hierarchical data aggregation using compressive sensing (HDACS) in WSNs. ACM Transactions on Sensor Networks (TOSN), 11(3), 1–25.Google Scholar
  62. 62.
    Ozdemir, S., & Xiao, Y. (2011). Integrity protecting hierarchical concealed data aggregation for wireless sensor networks. Computer Networks, 55(8), 1735–1746.Google Scholar
  63. 63.
    Lin, Y. H., Chang, S. Y., & Sun, H. M. (2013). CDAMA: Concealed data aggregation scheme for multiple applications in wireless sensor networks. IEEE Transactions on Knowledge and Data Engineering, 25(7), 1471–1483.Google Scholar
  64. 64.
    Zhang, C., Li, C., & Zhao, Y. (2015). A balance privacy-preserving data aggregation model in wireless sensor networks. International Journal of Distributed Sensor Networks, 2015, 1–10.Google Scholar
  65. 65.
    Sicari, S., Grieco, L. A., Boggia, G., & Porisini, A. C. (2012). DyDAP: A dynamic data aggregation scheme for privacy aware wireless sensor networks. Journal of Systems and Software, 85(1), 152–166.Google Scholar
  66. 66.
    Chen, Y. P., Liestman, A. L., & Liu, J. (2006). A hierarchical energy-efficient framework for data aggregation in wireless sensor networks. IEEE Transactions Vehicular Technology, 55(3), 789–796.Google Scholar
  67. 67.
    Xu, H., Huang, L., Zhang, Y., Huang, H., Jiang, S., & Liu, G. (2010). Energy-efficient cooperative data aggregation for wireless sensor networks. Journal of Parallel and Distributed Computing, 70(9), 953–961.zbMATHGoogle Scholar
  68. 68.
    Xiang, L., Luo, J., & Vasilakos, A. (2011). Compressed data aggregation for energy efficient wireless sensor networks. In 8th Annual IEEE communications society conference sensor, mesh ad hoc communications networks (pp. 46–54).Google Scholar
  69. 69.
    Chao, C. M., & Hsiao, T. Y. (2014). Design of structure-free and energy-balanced data aggregation in wireless sensor networks. Journal of Network and Computer Applications, 37, 229–239.Google Scholar
  70. 70.
    Engouang, T. D., Liu, Y., & Zhang, Z. (2014). GABs: A game-based secure and energy efficient data aggregation for wireless sensor networks. International Journal of Distributed Sensor Networks, 501, 1–31.Google Scholar
  71. 71.
    Liu, C., Liu, Y., & Zhang, Z. (2013). Improved reliable trust-based and energy-efficient data aggregation for wireless sensor networks. International Journal of Distributed Sensor Networks, 2013, 1–13.Google Scholar
  72. 72.
    Krishna, M. B., & Doja, M. N. (2015). Multi-objective meta-heuristic approach for energy-efficient secure data aggregation in wireless sensor networks. Wireless Personal Communications, 81(1), 1–16.Google Scholar
  73. 73.
    Ramachandran, G. S., Daniels, W., Proença, J., Michiels, S., Joosen, W., Hughes, D., & Porter, B. (2015). Hitch Hiker: A remote binding model with priority based data aggregation for wireless sensor networks. In Proceedings of the 18th international ACM SIGSOFT symposium on component-based software engineering (pp. 43–48).Google Scholar
  74. 74.
    Xiao, S., Li, B., & Yuan, X. (2015). Maximizing precision for energy-efficient data aggregation in wireless sensor networks with lossy links. Ad Hoc Networks, 26, 103–113.Google Scholar
  75. 75.
    Zhang, J., Wu, Q., Ren, F., He, T., & Lin, C. (2010). Effective data aggregation supported by dynamic routing in wireless sensor networks. IEEE International Conference Communications, 2010, 1–6.Google Scholar
  76. 76.
    Liu, H., Liu, Z., Li, D., Lu, X., & Du, H. (2013). Approximation algorithms for minimum latency data aggregation in wireless sensor networks with directional antenna. Theoretical Computer Science, 497, 139–153.MathSciNetzbMATHGoogle Scholar
  77. 77.
    Xue, Y., Cui, Y., & Nahrstedt, K. (2005). Maximizing lifetime for data aggregation in wireless sensor networks. Mobile Networks and Applications, 10(6 SPEC. ISS), 853–864.Google Scholar
  78. 78.
    Tang, X., & Xu, J. (2006). Extending network lifetime for precision-constrained data aggregation in wireless sensor networks. In Proceedings IEEE INFOCOM. Google Scholar
  79. 79.
    Yum, S. P. (2008). Optimal routing and data aggregation for maximizing lifetime of wireless sensor networks. IEEE/ACM Transactions on Networking, 16(4), 892–903.Google Scholar
  80. 80.
    Awang, A., & Agarwal, S. (2015). Data aggregation using dynamic selection of aggregation points based on RSSI for wireless sensor networks. Wireless Personal Communications, 80(2), 611–633.Google Scholar
  81. 81.
    Misra, R., & Mandal, C. (2006). Ant-aggregation: Ant colony algorithm for optimal data aggregation in wireless sensor networks. In IFIP international conference on wireless and optical communications networks (pp. 1–5). Bangalore.Google Scholar
  82. 82.
    Yucheng, W. L., & Fan, K. C. (2007). An ant colony algorithm for data aggregation in wireless sensor networks. In SensorComm international conference on sensor technologies and applications (pp. 101–106).Google Scholar
  83. 83.
    Lin, C., Wu, G., Xia, F., Li, M., Yao, L., & Pei, Z. (2012). Energy efficient ant colony algorithms for data aggregation in wireless sensor networks. Journal of Computer and System Sciences, 78(6), 1686–1702.MathSciNetzbMATHGoogle Scholar
  84. 84.
    Ho, J. H., Shih, H. C., Liao, B. Y., & Chu, S. C. (2012). A ladder diffusion algorithm using ant colony optimization for wireless sensor networks. Information Sciences (NY), 192, 204–212.Google Scholar
  85. 85.
    Lu, Y., Comsa, I. S., Kuonen, P., & Hirsbrunner, B. (2015). Dynamic data aggregation protocol based on multiple objective tree in wireless sensor networks. In 2015 IEEE tenth international conference on intelligent sensors, sensor networks and information processing (ISSNIP) (pp. 1–7).Google Scholar
  86. 86.
    Paul, B., & Gopinathan, E. (2014). Hybrid data aggregation technique in wireless sensor network through classification of fruitful messages. In Fourth international conference advances computing and communications (pp. 157–175).Google Scholar
  87. 87.
    Pham, T., Kim, E. J., & Moh, M. (2004). On data aggregation quality and energy efficiency of wireless sensor network protocols—extended summary. In Proceedings of first international conference broadband networks (pp. 3–5).Google Scholar
  88. 88.
    Chen, I. R., Speer, A. P., & Eltoweissy, M. (2011). Adaptive fault-tolerant QoS control algorithms for maximizing system lifetime of query-based wireless sensor networks. IEEE Transactions on Dependable and Secure Computing, 8(2), 161–176.Google Scholar
  89. 89.
    Misra, S., & Thomasinous, P. D. (2010). A simple, least-time, and energy-efficient routing protocol with one-level data aggregation for wireless sensor networks. Journal of Systems and Software, 83(5), 852–860.Google Scholar
  90. 90.
    Chen, C., Lee, K., Park, J., & Baek, S. J. (2015). Minimum cost data aggregation for wireless sensor networks computing functions of sensed data. Journal of Sensors, 1–15.Google Scholar
  91. 91.
    Bagaa, M., Derhab, A., Lasla, N., Ouadjaout, A., & Badache, N. (2012). Semi-structured and unstructured data aggregation scheduling in wireless sensor networks. In Proceedings of IEEE INFOCOM (pp. 2671–2675).Google Scholar
  92. 92.
    Jhumka, A., Bradbury, M., & Saginbekov, S. (2014). Efficient fault-tolerant collision-free data aggregation scheduling for wireless sensor networks. Journal of Parallel and Distributed Computing, 74(1), 1789–1801.zbMATHGoogle Scholar
  93. 93.
    Joo, C., Choi, J. G., & Shroff, N. B. (2010). Delay performance of scheduling with data aggregation in wireless sensor networks. In IEEE proceedings INFOCOM.Google Scholar
  94. 94.
    Bagaa, M., Younis, M., Djenouri, D., Derhab, A., & Badache, N. (2015). Distributed low-latency data aggregation scheduling in wireless sensor networks. ACM Transactions on Sensor Networks (TOSN), 11(3), 1–36.Google Scholar
  95. 95.
    Kwon, S., Ko, J. H., Kim, J., & Kim, C. (2011). Dynamic timeout for data aggregation in wireless sensor networks. Computer Networks, 55(3), 650–664.zbMATHGoogle Scholar
  96. 96.
    Tan, H. O., Korpeoglu, I., & Stojmenovi, I. (2011). Computing localized power-efficient data aggregation trees for sensor networks. IEEE Transactions on Parallel Distributed Systems, 22(3), 489–500.Google Scholar
  97. 97.
    Hakoura, B., & Rabbat, M. G. (2012). Data aggregation in wireless sensor networks: A comparison of collection tree protocols and gossip algorithms. In 25th IEEE Canadian conference on electrical and computer engineering (CCECE) (pp. 1–4).Google Scholar
  98. 98.
    Yousefi, H., Yeganeh, M. H., Alinaghipour, N., & Movaghar, A. (2012). Structure-free real-time data aggregation in wireless sensor networks. Computer Communications, 35(9), 1132–1140.Google Scholar
  99. 99.
    Lin, J., Xiong, N., Vasilakos, A. V., Chen, G., & Guo, W. (2011). Evolutionary game-based data aggregation model for wireless sensor networks. IET Communications, 5(12), 1691.MathSciNetGoogle Scholar
  100. 100.
    Wang, W., Srinivasan, V., & Chua, K. (2008). Extending the lifetime of wireless sensor networks through mobile relays. IEEE/ACM Transaction Networking, 16(5), 1108–1120.Google Scholar
  101. 101.
    Jiang, H., Jin, S., & Wang, C. (2011). Prediction or not? An energy-efficient framework for clustering-based data collection in wireless sensor networks. IEEE Transactions Parallel and Distributed Systems, 22(6), 1064–1071.Google Scholar
  102. 102.
    Meng, L., Zhang, H., & Zou, Y. (2011). A data aggregation transfer protocol based on clustering and data prediction in wireless sensor networks. In 7th International conference wireless communications networking and mobile computing (pp. 1–5).Google Scholar
  103. 103.
    Dietzel, S., Bako, B., Schoch, E., & Kargl, F. (2009). A fuzzy logic based approach for structure-free aggregation in vehicular ad-hoc networks. In Proceedings of the sixth ACM international workshop on VehiculAr InterNETworking VANET 09 (p. 79).Google Scholar
  104. 104.
    Haghighi, M. S., Xiang, Y., Varadharajan, V., & Quinn, B. (2015). A stochastic time-domain model for burst data aggregation in IEEE 802.15.4 wireless sensor networks. IEEE Transactions on Computers, 64(3), 627–639.MathSciNetzbMATHGoogle Scholar
  105. 105.
    Jung, W. S., Lim, K. W., Ko, Y. B., & Park, S. J. (2009). A hybrid approach for clustering-based data aggregation in wireless sensor networks. In 2009 Third international conference on digital society (pp. 112–117).Google Scholar
  106. 106.
    Kim, M. G., Han, Y. T., & Park, H. S. (2011). Energy-aware hybrid data aggregation mechanism considering the energy hole problem in asynchronous MAC-based WSNs. IEEE Communications Letters, 15(11), 1169–1171.Google Scholar
  107. 107.
    Chaudhury, B. P., & Nayak, A. K. (2015). Energy saving performance analysis of hierarchical data aggregation protocols used in wireless sensor network. In Advances in intelligent systems and computing (Vol. 309, pp. 79–89). Springer.Google Scholar
  108. 108.
    Saini, K.,  Kumar, P., & Sharma, J. (2013). A survey on data aggregation techniques for wireless sensor networks. International Journal of Advanced Research in Computer Engineering & Technology, 3(7), 901–903.Google Scholar
  109. 109.
    Xu, X., Li, X. Y., Mao, X., Tang, S., & Wang, S. (2011). A delay-efficient algorithm for data aggregation in multihop wireless sensor networks. IEEE Transactions Parallel and Distributed Systems, 23(1), 163–175.Google Scholar
  110. 110.
    Groat, M. M., Hey, W., & Forrest, S. (2011). KIPDA: k-indistinguishable privacy-preserving data aggregation in wireless sensor networks. In Proceedings IEEE INFOCOM (pp. 2024–2032).Google Scholar
  111. 111.
    Su, L., Gao, Y., Yang, Y., & Cao, G. (2011). Towards optimal rate allocation for data aggregation in wireless sensor networks. In Proceedings of Twelfth ACM international symposium mobile ad hoc networking and computingMobiHoc.Google Scholar
  112. 112.
    Enachescu, M., Goel, A., Govindan, R., & Motwani, R. (2005). Scale-free aggregation in sensor networks. Theoretical Computer Science, 344(1), 15–29.MathSciNetzbMATHGoogle Scholar
  113. 113.
    He, W., Nguyen, H., Liuy, X., Nahrstedt, K., & Abdelzaher, T. (2008). iPDA: An integrity-protecting private data aggregation scheme for wireless sensor networks. In MILCOM 2008 IEEE military communications conference (pp. 1–7).Google Scholar
  114. 114.
    Esnaashari, M., & Meybodi, M. R. (2010). Data aggregation in sensor networks using learning automata. Wireless Networks, 16(3), 687–699.zbMATHGoogle Scholar
  115. 115.
    Huang, S. I., Shieh, S., & Tygar, J. D. (2010). Secure encrypted-data aggregation for wireless sensor networks. Wireless Networks, 16(4), 915–927.Google Scholar
  116. 116.
    Ozdemir, S., & Çam, H. (2010). Integration of false data detection with data aggregation and confidential transmission in wireless sensor networks. IEEE/ACM Transactions on Networking, 18(3), 736–749.Google Scholar
  117. 117.
    He, W., Liu, X., Nguyen, H., Nahrstedt, K., & Abdelzaher, T. (2007). PDA: Privacy-preserving data aggregation in wireless sensor networks. In IEEE INFOCOM 200726th IEEE international conference on computer communications (pp. 2045–2053).Google Scholar
  118. 118.
    Patil, N. S., & Patil, P. R. (2010). Data aggregation in wireless sensor network. In Proceedings of IEEE international conference computational intelligence and computing research (pp. 28–29).Google Scholar
  119. 119.
    Tsitsipis, D., Dima, S. M., Kritikakou, A., Panagiotou, C., & Koubias, S. (2011). Data merge: A data aggregation technique for wireless sensor networks. In IEEE 16th conference on emerging technologies & factory automation (pp. 1–4).Google Scholar
  120. 120.
    Hamid, A., Ehsan, S., & Hamdaoui, B. (2014). Rate-constrained data aggregation in power-limited multi-sink wireless sensor networks. In International wireless communications and mobile computing conference (IWCMC) (pp. 500–504).Google Scholar
  121. 121.
    Lou, E., Hill, D. L., & Raso, J. V. (2010). HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. Medical Biological and Engineering Computing, 48(3), 235–243.Google Scholar
  122. 122.
    Lindsey, S., Raghavendra, C., & Sivalingam, K. M. (2002). Data gathering algorithms in sensor networks using energy metrics. IEEE Transaction on Parallel and Distributed Systems, 13(9), 924–935.Google Scholar
  123. 123.
    Ding, M., Cheng, X., & Xue, G. (2003). Aggregation tree construction in sensor networks. In 2003 IEEE 58th vehicular technology conference VTC 2003-Fall (IEEE Cat. No.03CH37484) (Vol. 4, pp. 2168–2172).Google Scholar
  124. 124.
    Xue, Y., Cui, Y., & Nahrstedt, K. (2005). Maximizing lifetime for data aggregation in wireless sensor networks. Mobile Networks and Applications, Special Issue on Energy Constraints and Lifetime Performance in Wireless Sensor Networks, 10(6), 853–864.Google Scholar
  125. 125.
    Hong, B., & Prasanna, V. K. (2004). Optimizing system life time for data gathering in network sensor systems. In Proceeding of algorithms wireless and ad-hoc networks. Google Scholar
  126. 126.
    Cristescu, R., Beferull-Lozano, B., & Vetterli, M. (2004). On network correlated data gathering. IEEE INFOCOM, 4(4), 2571–2582.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Computer Science and Engineering DepartmentThapar UniversityPatialaIndia

Personalised recommendations