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Erschienen in: Wireless Personal Communications 3/2017

28.07.2017

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

verfasst von: Sukhchandan Randhawa, Sushma Jain

Erschienen in: Wireless Personal Communications | Ausgabe 3/2017

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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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Literatur
1.
Zurück zum Zitat Tan, H. Ö., & Korpeoglu, I. (2003). Power efficient data gathering and aggregation in wireless sensor networks. ACM SIGMOD Record, 32(4), 66–71.CrossRef Tan, H. Ö., & Korpeoglu, I. (2003). Power efficient data gathering and aggregation in wireless sensor networks. ACM SIGMOD Record, 32(4), 66–71.CrossRef
2.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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. 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.
Zurück zum Zitat Cayirci, E. (2003). Data aggregation and dilution by modulus addressing in wireless sensor networks. IEEE Communication Letters, 7(8), 355–357.CrossRef Cayirci, E. (2003). Data aggregation and dilution by modulus addressing in wireless sensor networks. IEEE Communication Letters, 7(8), 355–357.CrossRef
6.
Zurück zum Zitat Dagar, M., & Mahajan, S. (2013). Data aggregation in wireless sensor network: A survey. International Journal of Information and Computation Technology, 3(3), 167–174. Dagar, M., & Mahajan, S. (2013). Data aggregation in wireless sensor network: A survey. International Journal of Information and Computation Technology, 3(3), 167–174.
7.
Zurück zum Zitat Tan, H. Ö., & Körpeoǧlu, I. (2003). Power efficient data gathering and aggregation in wireless sensor networks. ACM SIGMOD Record, 32(4), 66–71.CrossRef Tan, H. Ö., & Körpeoǧlu, I. (2003). Power efficient data gathering and aggregation in wireless sensor networks. ACM SIGMOD Record, 32(4), 66–71.CrossRef
8.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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). 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.
Zurück zum Zitat Rajagopalan, R., & Varshney, P. K. (2006). Data-aggregation techniques in sensor networks: A survey. IEEE Communications Surveys and Tutorials, 8(4), 48–63.CrossRef Rajagopalan, R., & Varshney, P. K. (2006). Data-aggregation techniques in sensor networks: A survey. IEEE Communications Surveys and Tutorials, 8(4), 48–63.CrossRef
12.
Zurück zum Zitat Jesus, P., Baquero, C., & Almeida, P. S. (2015). A survey of distributed data aggregation algorithms. IEEE Communications Surveys & Tutorials, 17(1), 381–404.CrossRef Jesus, P., Baquero, C., & Almeida, P. S. (2015). A survey of distributed data aggregation algorithms. IEEE Communications Surveys & Tutorials, 17(1), 381–404.CrossRef
13.
Zurück zum Zitat 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.MATHCrossRef 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.MATHCrossRef
14.
Zurück zum Zitat 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. 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.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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.MathSciNetCrossRef 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.MathSciNetCrossRef
17.
Zurück zum Zitat 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.CrossRef 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.CrossRef
18.
Zurück zum Zitat 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.CrossRef 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.CrossRef
19.
Zurück zum Zitat 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.CrossRef 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.CrossRef
20.
Zurück zum Zitat 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.CrossRef 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.CrossRef
21.
Zurück zum Zitat 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. 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.
Zurück zum Zitat 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.CrossRef 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.CrossRef
23.
Zurück zum Zitat 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.MATHCrossRef 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.MATHCrossRef
24.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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.CrossRef 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.CrossRef
26.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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. 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.
Zurück zum Zitat 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.CrossRef 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.CrossRef
31.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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.CrossRef 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.CrossRef
33.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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). 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).
35.
Zurück zum Zitat 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.CrossRef 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.CrossRef
36.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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.CrossRef 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.CrossRef
39.
Zurück zum Zitat 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.CrossRef 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.CrossRef
40.
Zurück zum Zitat 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.CrossRef 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.CrossRef
41.
Zurück zum Zitat 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.CrossRef 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.CrossRef
42.
Zurück zum Zitat 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. 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.
43.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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. 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.
Zurück zum Zitat 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.CrossRef 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.CrossRef
46.
Zurück zum Zitat 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). 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.
Zurück zum Zitat Kumar, M., & Rajkumar, N. (2013). SCT based adaptive data aggregation for wireless sensor networks. Wireless Personal Communications, 75(4), 2121–2133. Kumar, M., & Rajkumar, N. (2013). SCT based adaptive data aggregation for wireless sensor networks. Wireless Personal Communications, 75(4), 2121–2133.
48.
Zurück zum Zitat 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.MathSciNetMATHCrossRef 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.MathSciNetMATHCrossRef
49.
Zurück zum Zitat 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.CrossRef 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.CrossRef
50.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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. 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.
Zurück zum Zitat Azad, P., & Sharma, V. (2015). Pareto-optimal clustering scheme using data aggregation for wireless sensor networks. International Journal of Electronics, 102(7), 1165–1176.CrossRef Azad, P., & Sharma, V. (2015). Pareto-optimal clustering scheme using data aggregation for wireless sensor networks. International Journal of Electronics, 102(7), 1165–1176.CrossRef
53.
Zurück zum Zitat Asemani, M., & Esnaashari, M. (2015). Learning automata based energy efficient data aggregation in wireless sensor networks. Wireless Networks, 21(6), 2035–2053. Asemani, M., & Esnaashari, M. (2015). Learning automata based energy efficient data aggregation in wireless sensor networks. Wireless Networks, 21(6), 2035–2053.
54.
Zurück zum Zitat 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). 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.
Zurück zum Zitat Chen, H., Mineno, H., & Mizuno, T. (2008). Adaptive data aggregation scheme in clustered wireless sensor networks. Computer Communications, 31(15), 3579–3585.CrossRef Chen, H., Mineno, H., & Mizuno, T. (2008). Adaptive data aggregation scheme in clustered wireless sensor networks. Computer Communications, 31(15), 3579–3585.CrossRef
56.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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.CrossRef 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.CrossRef
58.
Zurück zum Zitat 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.CrossRef 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.CrossRef
59.
Zurück zum Zitat 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.CrossRef 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.CrossRef
60.
Zurück zum Zitat 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.CrossRef 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.CrossRef
61.
Zurück zum Zitat 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. 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.
Zurück zum Zitat Ozdemir, S., & Xiao, Y. (2011). Integrity protecting hierarchical concealed data aggregation for wireless sensor networks. Computer Networks, 55(8), 1735–1746.CrossRef Ozdemir, S., & Xiao, Y. (2011). Integrity protecting hierarchical concealed data aggregation for wireless sensor networks. Computer Networks, 55(8), 1735–1746.CrossRef
63.
Zurück zum Zitat 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.CrossRef 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.CrossRef
64.
Zurück zum Zitat 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. 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.
Zurück zum Zitat 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.CrossRef 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.CrossRef
66.
Zurück zum Zitat 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.CrossRef 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.CrossRef
67.
Zurück zum Zitat 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.MATHCrossRef 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.MATHCrossRef
68.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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.CrossRef 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.CrossRef
70.
Zurück zum Zitat 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. 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.
71.
Zurück zum Zitat 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. 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.
Zurück zum Zitat 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.CrossRef 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.CrossRef
73.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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.CrossRef 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.CrossRef
75.
Zurück zum Zitat 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. 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.
76.
Zurück zum Zitat 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.MathSciNetMATHCrossRef 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.MathSciNetMATHCrossRef
77.
Zurück zum Zitat 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.CrossRef 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.CrossRef
78.
Zurück zum Zitat Tang, X., & Xu, J. (2006). Extending network lifetime for precision-constrained data aggregation in wireless sensor networks. In Proceedings IEEE INFOCOM. Tang, X., & Xu, J. (2006). Extending network lifetime for precision-constrained data aggregation in wireless sensor networks. In Proceedings IEEE INFOCOM.
79.
Zurück zum Zitat 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.CrossRef 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.CrossRef
80.
Zurück zum Zitat 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.CrossRef 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.CrossRef
81.
Zurück zum Zitat 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. 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.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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.MathSciNetMATHCrossRef 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.MathSciNetMATHCrossRef
84.
Zurück zum Zitat 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.CrossRef 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.CrossRef
85.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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.CrossRef 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.CrossRef
89.
Zurück zum Zitat 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.CrossRef 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.CrossRef
90.
Zurück zum Zitat 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. 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.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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.MATHCrossRef 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.MATHCrossRef
93.
Zurück zum Zitat Joo, C., Choi, J. G., & Shroff, N. B. (2010). Delay performance of scheduling with data aggregation in wireless sensor networks. In IEEE proceedings INFOCOM. 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.
Zurück zum Zitat 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. 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.
Zurück zum Zitat 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.MATHCrossRef 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.MATHCrossRef
96.
Zurück zum Zitat 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.CrossRef 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.CrossRef
97.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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.CrossRef 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.CrossRef
99.
Zurück zum Zitat 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.MathSciNetCrossRef 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.MathSciNetCrossRef
100.
Zurück zum Zitat 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.CrossRef 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.CrossRef
101.
Zurück zum Zitat 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.CrossRef 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.CrossRef
102.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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.MathSciNetMATHCrossRef 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.MathSciNetMATHCrossRef
105.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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.CrossRef 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.CrossRef
107.
Zurück zum Zitat 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. 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.
Zurück zum Zitat 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. 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.
Zurück zum Zitat 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. 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.
110.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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. 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.
112.
Zurück zum Zitat Enachescu, M., Goel, A., Govindan, R., & Motwani, R. (2005). Scale-free aggregation in sensor networks. Theoretical Computer Science, 344(1), 15–29.MathSciNetMATHCrossRef Enachescu, M., Goel, A., Govindan, R., & Motwani, R. (2005). Scale-free aggregation in sensor networks. Theoretical Computer Science, 344(1), 15–29.MathSciNetMATHCrossRef
113.
Zurück zum Zitat 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). 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.
Zurück zum Zitat Esnaashari, M., & Meybodi, M. R. (2010). Data aggregation in sensor networks using learning automata. Wireless Networks, 16(3), 687–699.MATHCrossRef Esnaashari, M., & Meybodi, M. R. (2010). Data aggregation in sensor networks using learning automata. Wireless Networks, 16(3), 687–699.MATHCrossRef
115.
Zurück zum Zitat Huang, S. I., Shieh, S., & Tygar, J. D. (2010). Secure encrypted-data aggregation for wireless sensor networks. Wireless Networks, 16(4), 915–927.CrossRef Huang, S. I., Shieh, S., & Tygar, J. D. (2010). Secure encrypted-data aggregation for wireless sensor networks. Wireless Networks, 16(4), 915–927.CrossRef
116.
Zurück zum Zitat 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.CrossRef 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.CrossRef
117.
Zurück zum Zitat 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). 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).
118.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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.CrossRef 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.CrossRef
122.
Zurück zum Zitat 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.CrossRef 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.CrossRef
123.
Zurück zum Zitat 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). 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.
Zurück zum Zitat 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. 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.
125.
Zurück zum Zitat 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. 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.
Zurück zum Zitat Cristescu, R., Beferull-Lozano, B., & Vetterli, M. (2004). On network correlated data gathering. IEEE INFOCOM, 4(4), 2571–2582. Cristescu, R., Beferull-Lozano, B., & Vetterli, M. (2004). On network correlated data gathering. IEEE INFOCOM, 4(4), 2571–2582.
Metadaten
Titel
Data Aggregation in Wireless Sensor Networks: Previous Research, Current Status and Future Directions
verfasst von
Sukhchandan Randhawa
Sushma Jain
Publikationsdatum
28.07.2017
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 3/2017
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-017-4674-5

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