WSN Using Collective Scheme of Energy Efficient Grouping and Evidence Retrieval
Abstract
The two-layer network structure has been widely adopted in wireless sensor networks (WSNs) for managing sensor nodes. In such a structure, the low layer nodes communicate with their cluster head, followed by the cluster-head nodes communicating with the base station operating in either a one hop or a multi-hop manner. The main focus of node-clustering algorithms is minimizing energy consumption due to strictly limited resources in WSNs. Also, WSNs are data intensive networks with the capability of providing users with accurate data. Unfortunately, data missing is common in WSNs. In this paper, we propose a novel joint design of sensor nodes clustering and data recovery, where the WSNs is organized in a two-layer manner with our developed clustering algorithm, and then the missing data is recovered based on this two-layer structure. Furthermore, in the proposed clustering algorithm, we take both the energy-efficiency and data forecasting accuracy into consideration and investigate the tradeoff between them. This is based on the key observation that the high energy-efficiency of the network can be achieved by reducing the distances among the nodes in a cluster, while the accuracy of the forecasting results can be improved by increasing the correlation of the data stream among the nodes in a cluster. Simulation results demonstrate that our joint design outperforms the existing algorithms in terms of energy consumption and forecasting accuracy.
Keywords
References
- [1] M. R. Palattella, M. Dohler, A. Grieco, G. Rizzo, J. Torsner, T. Engel, and L. Ladid, “Internet of things in the 5G era: Enablers, architecture, and business models,” IEEE Journal on Selected Areas in Communications, vol. 34, pp. 510–527, Mar. 2016. [Google Scholar]
- [2] A. Zanella, N. Bui, A. Castellani, and L. Vangelista, “Internet of things for smart cities,” Internet of Things Journal IEEE, vol. 1, pp. 22–32, Feb. 2014. [Google Scholar]
- [3] S.CiraniandM.Picone,“Wearablecomputingfortheinternetofthings,” It Professional, vol. 17, pp. 35–41, Sep. 2015. [4] M. Simsek, A. Aijaz, M. Dohler, and J. Sachs, “5G-enabled tactile internet,” IEEE Journal on Selected Areas in Communications, vol. 34, pp. 460–473, Mar. 2016. [Google Scholar]
- [5] J. Fan, F. Han, and H. Liu, “Challenges of big data analysis,” National Science Review, vol. 1, no. 2, pp. 293–314, 2014. [Google Scholar]
- [6] Y. Shi, J. Zhang, and K. B. Letaief, “Group sparse beamforming for green Cloud-RAN,” IEEE Transactions on Wireless Communications, vol. 13, pp. 2809–2823, May 2014. [Google Scholar]
- [7] M. Peng, S. Yan, K. Zhang, and C. Wang, “Fog-computing-based radio access networks: issues and challenges,” IEEE Network, vol. 30, pp. 46– 53, Jul. 2016. [Google Scholar]
- [8] Y. Shi, J. Zhang, K. B. Letaief, and B. Bai, “Large-scale convex optimization for ultra-dense Cloud-RAN,” IEEE Wireless Communications, vol. 22, pp. 84–91, Jun. 2015. [Google Scholar]
- [9] M. Chiang and T. Zhang, “Fog and IoT: An overview of research opportunities,” IEEE Internet of Things Journal, vol. PP, no. 99, pp. 1–1, 2016. [Google Scholar]
Details
Primary Language
English
Subjects
-
Journal Section
Research Article
Publication Date
March 14, 2017
Submission Date
February 26, 2016
Acceptance Date
December 2, 2016
Published in Issue
Year 2017 Volume: 8 Number: 1
APA
Kumar, S. P. S., & Chandramohan, S. (2017). WSN Using Collective Scheme of Energy Efficient Grouping and Evidence Retrieval. International Journal of Educational Researchers, 8(1), 19-24. https://izlik.org/JA22MB23FD
AMA
1.Kumar SPS, Chandramohan S. WSN Using Collective Scheme of Energy Efficient Grouping and Evidence Retrieval. IJERs. 2017;8(1):19-24. https://izlik.org/JA22MB23FD
Chicago
Kumar, S. P. Santhosh, and S Chandramohan. 2017. “WSN Using Collective Scheme of Energy Efficient Grouping and Evidence Retrieval”. International Journal of Educational Researchers 8 (1): 19-24. https://izlik.org/JA22MB23FD.
EndNote
Kumar SPS, Chandramohan S (March 1, 2017) WSN Using Collective Scheme of Energy Efficient Grouping and Evidence Retrieval. International Journal of Educational Researchers 8 1 19–24.
IEEE
[1]S. P. S. Kumar and S. Chandramohan, “WSN Using Collective Scheme of Energy Efficient Grouping and Evidence Retrieval”, IJERs, vol. 8, no. 1, pp. 19–24, Mar. 2017, [Online]. Available: https://izlik.org/JA22MB23FD
ISNAD
Kumar, S. P. Santhosh - Chandramohan, S. “WSN Using Collective Scheme of Energy Efficient Grouping and Evidence Retrieval”. International Journal of Educational Researchers 8/1 (March 1, 2017): 19-24. https://izlik.org/JA22MB23FD.
JAMA
1.Kumar SPS, Chandramohan S. WSN Using Collective Scheme of Energy Efficient Grouping and Evidence Retrieval. IJERs. 2017;8:19–24.
MLA
Kumar, S. P. Santhosh, and S Chandramohan. “WSN Using Collective Scheme of Energy Efficient Grouping and Evidence Retrieval”. International Journal of Educational Researchers, vol. 8, no. 1, Mar. 2017, pp. 19-24, https://izlik.org/JA22MB23FD.
Vancouver
1.S. P. Santhosh Kumar, S Chandramohan. WSN Using Collective Scheme of Energy Efficient Grouping and Evidence Retrieval. IJERs [Internet]. 2017 Mar. 1;8(1):19-24. Available from: https://izlik.org/JA22MB23FD