Call for Paper - November 2019 Edition
IJCA solicits original research papers for the November 2019 Edition. Last date of manuscript submission is October 21, 2019. Read More

Mobile Agent Initiated Energy Efficient Data Aggregation in WSNs: MAEDA

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Shivangi Katiyar, Devendra Prasad
10.5120/ijca2016909170

Shivangi Katiyar and Devendra Prasad. Article: Mobile Agent Initiated Energy Efficient Data Aggregation in WSNs: MAEDA. International Journal of Computer Applications 140(1):10-15, April 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Shivangi Katiyar and Devendra Prasad},
	title = {Article: Mobile Agent Initiated Energy Efficient Data Aggregation in WSNs: MAEDA},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {140},
	number = {1},
	pages = {10-15},
	month = {April},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

A sensor node in WSNs has limited resources (e.g., memory capacity, battery power etc.) and among all, energy is the most crucial factor because refilling or recharging of power is not possible here. There are many possible ways to conserve energy in WSNs; data aggregation is one of them. Applications of WSNs cross a broad scale including environment monitoring, Habitat monitoring, monitoring Water and Air quality, Gas emission, etc. The above mentioned applications and many other needs Data Aggregation because here sensors frequently reports sensed values to the Processing Elements without removing redundant and disused entries. This paper proposes Mobile Agent initiated Energy efficient Data Aggregation (MAEDA) approach to prolong network lifetime. This method skillfully integrates Mobile Agent (MA) with wireless sensor networks. The proposed method is emulated by MATLAB platform; our simulation results are very impressive and prove that MAEDA is able to save more energy in data aggregation as well as prolonged network lifetime than other existing one.

References

  1. Min Yoon, Yong-Ki Kim and Jae-Woo Chang, “A New Data Aggregation Scheme to Support Energy Efficiency and Privacy Preservation for Wireless Sensor Networks”, International Journal of Security and Its Applications, Vol. 7, pp. 129-142, January 2013.
  2. Abdul Waheed Khan, Abdul Hanan Abdullah , Mohammad Hossein Anisi and Javed Iqbal Bangash, “A Comprehensive Study of Data Collection Schemes Using Mobile Sinks in Wireless Sensor Networks”, Academic journal –Sensors, vol. 14, issue 2, pp. 2510-2548, February 2014.
  3. Md. Sajidul Islam, Imtiaz Bin Rahim and Mosarrat Jahan, “An Energy-Efficient Data Aggregation Tree Construction Algorithm for Wireless Sensor Networks”, International Journal of Computer Networks and Wireless Communications (IJCNWC), Vol.4, No.5, pp.264-269,October 2014.
  4. Priya Kasirajan, “Data aggregation in wireless sensor networks”, masters theses, Spring, 2010.
  5. Alan Mainwaring, Joseph Polastre, Robert Szewczyk, David Culler and John Anderson, “Wireless Sensor Networks for Habitat Monitoring”, Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications, WSNA '02, pp. 88-97, 2002.
  6. J. Valverde, V. Rosello, G. Mujica, J. Portilla, A. Uriarte, and T. Riesgo, “Wireless Sensor Network for Environmental Monitoring: Application in a Coffee Factory”, International Journal of Distributed Sensor Networks, vol. 2012, 2012.
  7. Govind P. Gupta, Manoj Misra, and Kumkum Garg, “An Energy Efficient Distributed Approach-Based Agent Migration Scheme for Data Aggregation in Wireless Sensor Networks”, Journal of Information Processing System, pp. 1-17, August 2013.
  8. Mobile agents: A new software paradigm for distributed application development, CIS-white paper.
  9. Yashpal Singh, Kamal Deep and S Niranjan, “Multiple Criteria Clustering of Mobile Agents in WSN”, International Journal of Wireless & Mobile Networks (IJWMN) Vol. 4, pp.183-193, June 2012.
  10. Ankit jagga, Kuldeep and Vijay rana, “A Hybrid Approach for Deploying Mobile Agents in Wireless Sensor Network”, in proceedings of International Conference on Recent Advances and Future Trends in Information Technology (iRAFIT2012), pp.1-4, 2012.
  11. Y.-C. Tseng, S.-P. Kuo, H.-W. Lee, and C.-F. Huang, “Location tracking in a wireless sensor network by mobile agents and its data fusion strategies,” Computer Journal, vol. 47, pp. 448–460, 2004.
  12. H. Qi, Y. Xu, and X. Wang, “Mobile-agent-based collaborative signal and information processing in sensor networks,” Proceedings of the IEEE, vol. 91, pp. 1172–1183, 2003.
  13. M. Rubinstein, “Scalability of mobile agents based on a network management application,” Journal of communications and networks, Vol. 5, pp. 240-248, September 2003.
  14. A. Fuggetta, G. P. Picco, and G. Vigna, “Understanding code mobility,” IEEE Transactions on Software Engineering, vol. 24, pp. 342–361, 1998.
  15. Shivangi Katiyar and Devendra Prasad, “A Comprehensive Survey of Data Processing Approaches” International Journal of Computer Applications (IJCA), Volume 126, pp.38-45, September 2015.
  16. Juby K Baby and P K Poonguzhali, “Energy Balanced Routing Method for In-Network Data Aggregation in Wireless Sensor Networks”, IOSR Journal of Electronics and Communication Engineering (IOSR-JECE), Vol.9, Issue.3, pp. 5-14, June 2014.
  17. Mohammad Hossein Anisi, Abdul Hanan Abdullah and Shukor Abd Razak, “Energy-Efficient Data Collection in Wireless Sensor Networks”, Science research journal, Vol.3, pp. 329-333, October 2011.
  18. Ali Norouzi, Faezeh Sadat Babamir and Zeynep Orman, “A Tree Based Data Aggregation Scheme for Wireless Sensor Networks Using GA”, Scientific research journal, Vol. 4, pp. 191-196, August 2012.
  19. M. Francesco, D. Das, S.K. A and G. Anastasi, “Data Collection inWireless Sensor Networks with Mobile Elements: A Survey”, 2011.
  20. Van Le, D. Oh, H.Yoon and S. HiCoDG, “A Hierarchical Data-Gathering Scheme Using Cooperative Multiple Mobile Elements”, Sensors, pp. 24278–24304, 2014.
  21. Tuhin Paul and Kevin Gordon Stanley, “Data Collection from Wireless Sensor Networks Using a Hybrid Mobile Agent-based Approach”, In proceeding of the 39th annual IEEE conference on Local Computer Networks, pp. 288-295, 2014.
  22. Zheng Gengsheng and Hu Zhengbing, “Chain Routing based on Coordinates-oriented clustering strategy in WSNs”, In Proceeding of the IEEE conference on Computer Network and Multimedia Technology, pp. 1-4, January 2009.
  23. Onur Soysal and Murat Demirbas, “Data Spider: A Resilient Mobile Basestation Protocol for Efficient Data Collection in Wireless Sensor Networks”, DCOSS, pp.393-408, 2010.
  24. Mohsin Raza Jafri, Nadeem Javaid, Akmal Javaid and Zahoor Ali Khan, “Maximizing the Lifetime of Multi-Chain PEGASIS Using Sink Mobility”, World Applied Sciences Journal, pp. 1283-1289, 2013.
  25. Bartolom´e Rubio, Manuel D´ıaz and Jos´e M. Troya, “Programming Approaches and Challenges for Wireless Sensor Networks” second IEEE international conference on systems and networks communications ICSNC, August 2007.
  26. Ozlem Durmaz Incel, Amitabha Ghosh, Bhaskar Krishnamachari, and Krishnakant Chintalapudi, “Fast Data Collection in Tree based Wireless Sensor Networks”, IEEE Transactions on Mobile Computing, Vol. 11, No. 1, January 2012.
  27. Nakayama, H., Z. Fadlullah, N. Ansari and N. Kato, 2011. “A novel scheme for wsan sink mobility based on clustering and set packing techniques”, IEEE Transactions on Automatic Control, Vol.56, No.20, pp. 2381-2389, October 2011.

Keywords

Sink, Mobile Agent, Data aggregation.