Share / Export Citation / Email / Print / Text size:

International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic


eISSN: 1178-5608



VOLUME 9 , ISSUE 3 (September 2016) > List of articles


Chengwei Hu *

Keywords : Mobile cloud computing, Wireless Sensor Networks (WSN), Cloud Architectures, Secure Data Storage, framework, integration

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 9, Issue 3, Pages 1,563-1,591, DOI:

License : (CC BY-NC-ND 4.0)

Received Date : 23-March-2016 / Accepted: 21-July-2016 / Published Online: 01-September-2016



Together with an explosive growth of the mobile applications and emerging of cloud computing concept, mobile cloud computing (MCC) has been introduced to be a potential technology for mobile services. Wireless Sensor Networks (WSN) is the technology that connects the virtual world and the physical world where nodes can autonomously communicate among each other and with intelligent systems. This paper describes the concept of wireless sensor networks and mobile cloud computing. Recently, much research has proposed to integrate wireless sensor networks (WSNs) with mobile cloud computing, so that powerful cloud computing can be exploited to process the sensory data accumulated by WSNs and provide these date to the mobile users on demand. The current WSN-MCC integration schemes have several drawbacks. This paper proposes a data processing framework, which aims at transmitting desired data to the mobile users in a rapid, reliable and even more secure manner. The proposed framework decreases the storage requirements for sensor nodes and networks gateway. And it minimizes the traffic overhead and bandwidth requirement for sensor networks. Additionally, the framework can predict the future trend of sensory data and provide security for this sensory data. This framework ensures the mobile users obtain their desired data faster.

Content not available PDF Share



[1] D.-Y. Chen and J.-T. Tsai, “Resource-limited intelligent photo management on mobile platforms,” in Machine Learning and Cybernetics (ICMLC), 2011 International Conference on, Jul 2011, pp. 627–630.
[2] P. Angin, B. Bhargava, and S. Helal, “A mobile-cloud collaborative traffic lights detector for blind navigation,” in Proceedings of the 2010 Eleventh International Conference on Mobile Data Management, ser.MDM ’10. Washington, DC, USA: IEEE Computer Society, 2010, pp. 396–401.
[3] G. Yu, H. Song, and J. Gao, "Unmanned Nmanned Aerial Vehicle Path Planning Based On Tlbo Algorithm," International Journal on Smart Sensing & Intelligent Systems, Vol. 7, pp. 1310-1325, 2014.
[4] ZH. Yu, L. Feng, H. Jie, “Amn-Pso Method For Jamming Unmanned Aerial Vehicle Network”, International Journal on Smart Sensing & Intelligent Systems, Vol. 8, No. 4, pp. 2042-2064, 2015.
[5] M. Goharimanesh, A. Akbari, “Optimum parameters of nonlinear integrator using design of experiments based on Taguchi method”, Journal of Computational Applied Mechanics, Vol. 46, No. 2, pp.233-241, 2015.
[6] M. Alvarado, F. Gonzalez, A. Fletcher, and A. Doshi, "Towards The Development Of A Low Cost Airborne Sensing System To Monitor Dust Particles After Blasting At OpenPit Mine Sites," in IEEE Sensors, Vol. 15, pp. 19667-19687, Busan, South Korea, Nov. 01-04, 2015.
[7] Y. Peng, W. Guo, M. Liu, and S. Xie, "Active Modeling Based Yaw Control of Unmanned Rotorcraft," International Journal on Smart Sensing & Intelligent Systems, Vol. 7, pp. 380-399, 2014.
[8] Y. LI, C. Chen, and W. Chen, "Research On Longitudinal Control Algorithm For Flying Wing UAV Based On LQR Technology," International Journal on Smart Sensing and Intelligent Systems, Vol. 6, pp. 2155-2181, 2013
[9] Y. Takabe, K. Matsumoto, M. Yamagiwa, and M. Uehara, “Proposed sensor network for living environments using cloud computing,” inProc. 15th Int. Conf. Netw.-Based Inf. Syst., 2012, pp. 838–843.
[10] G. Fortino, M. Pathan, and G. D. Fatta, “Bodycloud: Integration of cloud computing and body sensor networks,” in Proc. IEEE 4th Int. Conf. Cloud Comput. Technol. Sci., 2012, pp. 851–856.
[11] B.-G. Chun, S. Ihm, P. Maniatis, M. Naik, and A. Patti, “Clonecloud: elastic execution between mobile device and cloud,” in Proceedings of the sixth conference on Computer systems, ser. EuroSys ’11. New York, NY, USA: ACM, 2011, pp. 301–314.
[12] B.-G. Chun and P. Maniatis, “Augmented smartphone applications through clone cloud execution,” in Proceedings of the 12th conference on Hot topics in operating systems, ser. HotOS’09. Berkeley, CA, USA: USENIX Association, 2009, pp. 8–8.
[13] X. H. Li, H. Zhang, and Y. F. Zhang, “Deploying Mobile Computation in Cloud Service,” in Proceedings of the First International Conference for Cloud Computing (CloudCom), 2009, p. 301.
[15] Q. Wang, C. Wang, J. Li, K. Ren, and W. Lou, “Enabling public verifiability and data dynamics for storage security in cloud computing,”in European Symposium on Research in Computer Security (ESORICS) 2009, Saint Malo, France, Sep 2009.
[16] S. Zhu, S. Setia, and S. Jajodia., LEAP: Efficient Security Mechanisms for Large-Scale Distributed Sensor Networks., CCS'03, October 2010
[17] Y. Zou and K. Chakrabarty, Sensor deployment and target localization in distributed sensor net-works, ACM Transactions on Embedded Computing Systems, 3, 1, 2004, 61-91.
[18] S. Poduri and G. Sukhatme, Constrained coverage for mobile sensor networks, IEEE Intl. Conf. on Robotics and Automation (ICRA’04), 2004, 165-171.
[19] R. Kannan, S.Sarangi, S.S. Iyengar and L. Ray, Sensor-centric quality of routing in sensor networks,INFOCOM, 2003.
[20] R. Kannan, S. Sarangi, S. Ray and S. Iyengar, Minimal sensor integrity: Computing the vulnerability of sensor grids, Info. Proc. Letters, 86, 1, 2003, 49-55.
[21] R. Kannan and S. S. Iyengar, Game-theoretic models for reliable, path-length and energy-constrained routing in wireless sensor networks, IEEE Journal on Selected Areas in Communications, 2004
[22] M. Yuriyama and T. Kushida, “Sensor-cloud infrastructure—Physical sensor management with virtualized sensors on cloud computing,” in Proc. 13th Int. Conf. Netw. Based Inf. Syst., 2010, pp. 1–8.
[23] S. Slijepcevic and M. Potkonjak, Power efficient optimization of wireless sensor networks, IEEE Intl. Conf. on Communications, 2011.
[24] A. Spyropoulos and C. Raghavendra, Energy efficient communications in ad hoc networks using directional antenna, IEEE INFOCOM, 2012.
[25] I. Stojmenovic, and Xu Lin, Power-aware localized routing in wireless networks, IEEE Transactions on Parallel and Distributed Systems, 2010.
[26] R. Szewczyk, E. Osterweil, J. Polastre, M. Hamilton, A. Mainwaring and D. Estrin, Habitat moni-toring with sensor networks, CACM, 47, 6, 2014, 34-40.
[27] Q. Zhang, L. Cheng, and R. Boutaba, “Cloud computing: State-of-theart and research challenges,” J. Ineternet Serv. Appl., vol. 1, no. 1, pp. 7–18, May 2010.
[28] H. T. Dinh, C. Lee, D. Niyato, and P. Wang, “A survey of mobile cloud computing: Architecture, applications, and approaches,” Wireless Commun. Mobile Comput., vol. 13, no. 18, pp. 1587–1611, Dec. 2013.
[29] C. Zhu, V. C. M. Leung, X. Hu, L. Shu, and L. T. Yang, “A review of key issues that concern the feasibility of mobile cloud computing,” in Proc. IEEE Int. Conf. Cyber, Phys. Soc. Comput., 2013, pp. 769– 776.
[30] S. Wang and S. Dey, “Adaptive mobile cloud computing to enable rich mobile multimedia applications,” IEEE Trans. Multimedia, vol. 15, no. 4, pp. 870–883, Jun. 2013.