A Mobile Cloud Computing Framework for Execution of Data as a Service using Cloudlet


  • Santosh Kumar Yadav PhD Scholar NITTTR Chandigarh
  • Rakesh Kumar Associate Professor and Head, Department of Computer Science and Engineering, School of Engineering & Technology,Central University of Mahendergarh, India




As mobile devices are becoming more powerful in computation, storage and power which makes it suitable for MCC (mobile cloud computing). Besides getting used in MCC, mobile devices also have roles in various emerging technologies like, ubiquitous computing, pervasive computing, context aware based computing, big data analysis, utility computing, fog computing and 5G based technologies. In mobile cloud computing, cloudlet is used as an intermediate between cloud and mobile devices. These cloudlets are resource rich mobile devices. This paper focus on mobile cloud computing enabled cloudlet-based computation. Cloudlet based computation has intercloudlet communication framework which is improved further to FMCC (Framework of mobile cloudlet centre) based computing environment. This framework later improved to SKYR (Scalable Key-parameter Yield of Resources) framework. SKYR framework worked on four major problems of FMCC framework. In this paper we have further improved the performance analysis expression and algorithm for SKYR framework. This improved algorithm and expression will help in efficient analysis of cloud-cloudlet based computation system’s performance.


Huerta-Canepa, G., & Lee, D. (2010). A virtual cloud computing provider for mobile devices. In Proceedings of 1st ACM workshop on mobile cloud computing & services: Social networks and beyond (MCS’10).

Satyanarayanan, M., Bahl, P., Caceres, R., & Davies, N. (2009). The case for VM-based cloudlets in mobile computing. IEEE Pervasive Computing, 8(4), 14–23.

Satyanarayanan, M. (2010). Mobile computing: The next decade. In Proceedings of 1st ACM workshop on mobile cloud computing & services: Social networks and beyond (MCS’10), pp. 2–10.

Chun, B., Ihm, S., Maniatis, P., Naik, M., & Patti, A. (2011). CloneCloud: Elastic execution between mobile device and cloud. In Proceedings of 6th conference on computer systems (EuroSys), pp. 301–314.

Satyanarayanan, M., Lewis, G., Morris, E., Simanta, S., Boleng J., & Ha, K. (2013). The role of cloudlet in hostile environments. In Proceedings of IEEE conference on pervasive computing, pp. 40–49.

Lewis, G., Echeverria, S., Simanta, S., Bradshaw, B., & Root, J. (2014). Tactical cloudlets: Moving cloud computing to the edge. In Proceedings of IEEE military communications conference, pp. 1440–1446.

Tawalbeh, L., Jararweh, Y., Ababneh, F., & Dosari, F. (2015). Large scale cloudlets deployment for efficient mobile cloud computing. Journal of Networks, 10(1), 70–76.

Xiao, Y., Simoens, P., Pillai, P., Ha, K., & Satyanarayanan, M. (2013). Lowering the barriers to largescale mobile crowd sensing. In Proceedings of ACM conference.

Satyanarayanan, M., Chen, Z., Ha, K., Hu, W., Richer W., & Pillai, P. (2014). Cloudlet: At the leading edge of mobile-cloud convergence. In Proceedings of 6th international conference on mobile computing, application and services (MobiCASE), pp. 1–9.

Rawadi, J. M., Artail, H., & Safa, H. (2014). Providing local cloud service to mobile devices with intercloudlet communication. In Proceedings of 17th IEEE mediterranean electrotechnical conference, Beirut, Lebanon, pp. 134–138.

Artail, A., Frenn, K., Artail H., & Safa, H. (2015). A framework of mobile cloudlet center based on the use of mobile devices as cloudlets. In Proceedings of 29th IEEE international conference on advanced information networking and applications, pp. 777–784.

Khan, A., Othman, M., Xia, F., Khan, A.N. (2015). Context -aware mobile cloud computing and its challenges. IEEE Cloud Computing, 2(3), 42-49.

Satyanarayanan, M. (2017). The emergence of edge computing. IEEE Computer, 50(1), 30-39.

Zhang, Y., Guo, K., Ren, J., Zhou, Y., Wang, J., Chen, J. (2017). Transparent computing: A promising network computing paradigm. IEEE Computing in Science & Engineering, 19(1), 7-20.

Kumar, R., Yadav, S.K. (2017). Scalable Key Parameter Yield of Resources Model for Performance Enhancement in Mobile Cloud Computing. Springer’s Wireless Personal Communications 95 (4), 3969-4000.

Singh, S.P., Nayyar, A., Kumar, R., & Sharma, A. (2019). Fog computing: from architecture to edge computing and big data processing. The Journal of Supercomputing, 75(4), 2070-2105.

Singh, P., Gupta, P., Jyoti, K., & Nayyar, A. (2019). Research on auto- scaling of web application in cloud: Survey, trends and future directions. Scaling Computing: Practice and Experience, 20 (2), 399-432.

Kaur, A., Gupta, P., Singh, M., & Nayyar, A. (2019). Data placement in era of cloud computing: a survey, taxonomy and open research issues. Scalable Computing: Practices and Experience, 20(2), 377-398.

Nayyar, A., (2011). Private virtual infrastructure (PVI) model for cloud computing. International Journal of Software Engineering Research and Practices, 1(1), 10-14.

Luong, N.C., Wang, P., Niyato, D., Yonggang, W., Han, Z. (2016). Resource Management in Cloud Networking Using Economic Analysis and Pricing Models: A Survey. IEEE Communications Surveys & Tutorials, 19(2), 954-1001.