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

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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.

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References

  1. Tan, H. Ö., & Korpeoglu, I. (2003). Power efficient data gathering and aggregation in wireless sensor networks. ACM SIGMOD Record, 32(4), 66–71.

    Article  Google Scholar 

  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).

  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).

  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.

  5. Cayirci, E. (2003). Data aggregation and dilution by modulus addressing in wireless sensor networks. IEEE Communication Letters, 7(8), 355–357.

    Article  Google Scholar 

  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. Tan, H. Ö., & Körpeoǧlu, I. (2003). Power efficient data gathering and aggregation in wireless sensor networks. ACM SIGMOD Record, 32(4), 66–71.

    Article  Google Scholar 

  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).

  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).

  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).

  11. Rajagopalan, R., & Varshney, P. K. (2006). Data-aggregation techniques in sensor networks: A survey. IEEE Communications Surveys and Tutorials, 8(4), 48–63.

    Article  Google Scholar 

  12. Jesus, P., Baquero, C., & Almeida, P. S. (2015). A survey of distributed data aggregation algorithms. IEEE Communications Surveys & Tutorials, 17(1), 381–404.

    Article  Google Scholar 

  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.

    Article  MATH  Google Scholar 

  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.

  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).

  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.

    Article  MathSciNet  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

  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.

    Article  Google Scholar 

  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.

    Article  MATH  Google Scholar 

  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).

  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.

    Article  Google Scholar 

  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).

  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).

  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).

  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.

  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.

    Article  Google Scholar 

  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).

  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.

    Article  Google Scholar 

  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).

  34. Yu, B., Li, J., & Li, Y. (2009). Distributed data aggregation scheduling in wireless sensor network. In IEEE INFOCOM 2009—28th conference of computation communication (pp. 2159–2167).

  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.

    Article  Google Scholar 

  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).

  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).

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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. 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).

  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.

  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.

    Article  Google Scholar 

  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).

  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. 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.

    Article  MathSciNet  MATH  Google Scholar 

  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.

    Article  Google Scholar 

  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).

  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.

  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.

    Article  Google Scholar 

  53. Asemani, M., & Esnaashari, M. (2015). Learning automata based energy efficient data aggregation in wireless sensor networks. Wireless Networks, 21(6), 2035–2053.

  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).

  55. Chen, H., Mineno, H., & Mizuno, T. (2008). Adaptive data aggregation scheme in clustered wireless sensor networks. Computer Communications, 31(15), 3579–3585.

    Article  Google Scholar 

  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).

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

  62. Ozdemir, S., & Xiao, Y. (2011). Integrity protecting hierarchical concealed data aggregation for wireless sensor networks. Computer Networks, 55(8), 1735–1746.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  MATH  Google Scholar 

  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).

  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.

    Article  Google Scholar 

  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. 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.

  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.

    Article  Google Scholar 

  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).

  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.

    Article  Google Scholar 

  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. 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.

    Article  MathSciNet  MATH  Google Scholar 

  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.

    Article  Google Scholar 

  78. Tang, X., & Xu, J. (2006). Extending network lifetime for precision-constrained data aggregation in wireless sensor networks. In Proceedings IEEE INFOCOM.

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

  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).

  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.

    Article  MathSciNet  MATH  Google Scholar 

  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.

    Article  Google Scholar 

  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).

  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).

  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).

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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.

  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).

  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.

    Article  MATH  Google Scholar 

  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.

  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.

  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.

    Article  MATH  Google Scholar 

  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.

    Article  Google Scholar 

  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).

  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.

    Article  Google Scholar 

  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.

    Article  MathSciNet  Google Scholar 

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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).

  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).

  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.

    Article  MathSciNet  MATH  Google Scholar 

  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).

  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.

    Article  Google Scholar 

  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.

  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.

  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. 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).

  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 computing—MobiHoc.

  112. Enachescu, M., Goel, A., Govindan, R., & Motwani, R. (2005). Scale-free aggregation in sensor networks. Theoretical Computer Science, 344(1), 15–29.

    Article  MathSciNet  MATH  Google Scholar 

  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).

  114. Esnaashari, M., & Meybodi, M. R. (2010). Data aggregation in sensor networks using learning automata. Wireless Networks, 16(3), 687–699.

    Article  MATH  Google Scholar 

  115. Huang, S. I., Shieh, S., & Tygar, J. D. (2010). Secure encrypted-data aggregation for wireless sensor networks. Wireless Networks, 16(4), 915–927.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  117. He, W., Liu, X., Nguyen, H., Nahrstedt, K., & Abdelzaher, T. (2007). PDA: Privacy-preserving data aggregation in wireless sensor networks. In IEEE INFOCOM 2007—26th IEEE international conference on computer communications (pp. 2045–2053).

  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).

  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).

  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).

  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.

    Article  Google Scholar 

  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.

    Article  Google Scholar 

  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).

  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. 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.

  126. Cristescu, R., Beferull-Lozano, B., & Vetterli, M. (2004). On network correlated data gathering. IEEE INFOCOM, 4(4), 2571–2582.

    Google Scholar 

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Authors and Affiliations

  1. Computer Science and Engineering Department, Thapar University, Patiala, Punjab, 147004, India

    Sukhchandan Randhawa & Sushma Jain

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  1. Sukhchandan Randhawa
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  2. Sushma Jain
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Correspondence to Sukhchandan Randhawa.

Appendix 1: Acronyms

Appendix 1: Acronyms

WSN

Wireless Sensor Network

TAG

Tiny AGgregation

CH

Cluster Head

DAT

Data Aggregation Technique

FoS

Focus of Study

SCT

Semantic Correlation Tree

QoS

Quality of Service

LEACH

Low Energy Adaptive Clustering Hierarchy

PEGASIS

Power Efficient data GAthering protocol for Sensor Information Systems

EADAT

Energy Aware Distributed heuristic Aggregation Transmission

PEDAP-PA

Power Efficient Data gathering and Aggregation Protocol Power Aware

RFEC

Restricted Flow problem with Edge Capacities

DMAC

Delay aware Medium Access Control

HEED

Hybrid Energy Efficient Distributed Clustering Approach

AIDA

Application Independent Data Aggregation

CMLDA

Clustered Maximum Lifetime Data gathering with Aggregation

TDMA

Time Division Multiple Access

AEDT

Adaptive Energy aware Data aggregation Tree

TTCDA

Two Tier Cluster based Data Aggregation

GCEDA

Grouping nodes and Clusters for Efficient Data Aggregation

DASDR

Data Aggregation Supported by Dynamic Routing

DST

Dynamic and Scalable Tree

ESPDA

Energy efficient Secure Pattern based Data Aggregation

LMST

Local Minimum Spanning Tree

CTP

Collective Tree Protocol

KFDA

Kalman-Filter based Data Aggregation

GMDA

Grey-Model-based Data Aggregation

AEDT

Adaptive Energy aware Data aggregation Tree

DAACA

Data Aggregation Ant Colony Algorithms

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Randhawa, S., Jain, S. Data Aggregation in Wireless Sensor Networks: Previous Research, Current Status and Future Directions. Wireless Pers Commun 97, 3355–3425 (2017). https://doi.org/10.1007/s11277-017-4674-5

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