An Adequate Computation Offloading in Mobile Cloud Computing

Authors

  • CH. Ellaji  Department of Computer Science and Engineerin, SoET, SPMVV, Tirupathi, Andhra Pradesh, India
  • C. Pradeepthi  Department of Computer Science and Engineerin, SoET, SPMVV, Tirupathi, Andhra Pradesh, India
  • P. JayaSri  Department of Computer Science and Engineerin, SoET, SPMVV, Tirupathi, Andhra Pradesh, India

DOI:

https://doi.org//10.32628/CSEIT195635

Keywords:

Mobile Cloud Computing(MCC), Cloud Computing(CC), Offloading Computation, partitioning algorithm

Abstract

The development and upgrades that mobile gadgets have encountered, they are as yet considered as restricted registering gadgets. Presently, clients become the more requesting and hope to execute computational serious applications on their mobile gadgets. Accordingly, Mobile Cloud Computing (MCC) coordinates versatile figuring and Cloud Computing (CC) so as to broaden capacities of mobile devices utilizing of?oading procedures. Computational of?oading handles restrictions of Smart Mobile Devices (SMDs, for example, constrained battery lifetime, constrained preparing capabilities, and constrained Storage capacity by of?oading the execution and outstanding burden to other rich frameworks with better execution and assets. Here, the current of?oading systems, Compuatational of?oading strategies, and evaluate them alongside their principle basic issues. In addition, it investigates distinctive significant parameters dependent on which the systems are actualized, for example, of?oading technique and level of dividing. At last, it condenses the issues in of?oading systems in the MCC space that requires further research.

References

  1. M. Armbrust, A. Fox, R. Griffith, A.D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, et al, A view of cloud computing, Commun. ACM 53 (4) (2010) 50–58.
  2. R. Barga, D. Gannon, D. Reed, The client and the cloud: democratizing research computing, IEEE Internet Comput. 15 (1) (2011) 72.
  3. B. Butler, Gartner: Cloud Putting Crimp in Traditional Software, Hardware Sales, Networkworld, 2012.
  4. R. Buyya, C.S. Yeo, S. Venugopal, J. Broberg, I. Brandic, Cloud computing and emerging it platforms: Vision, hype, and reality for delivering computing as the 5th utility, Future Generat. Comput. Syst. 25 (6) (2009) 599–616.
  5. W.-C. Chuang, B. Sang, S. Yoo, R. Gu, M. Kulkarni, C. Killian, Eventwave: programming model and runtime support for tightly-coupled elastic cloud applications, in: Proceedings of the 4th annual Symposium on Cloud Computing, ACM, 2013, p. 21.
  6. B.-G. Chun, S. Ihm, P. Maniatis, M. Naik, A. Patti, CloneCloud: elastic execution between mobile device and cloud, in: Proceedings of the Sixth Conference on Computer Systems, ACM, 2011, pp. 301–314.
  7. B.-G. Chun, P. Maniatis, Augmented smartphone applications through clone cloud execution, HotOS 9 (2009) 8–11.
  8. E. Cuervo, A. Balasubramanian, D.-K. Cho, A. Wolman, S. Saroiu, R. Chandra, P. Bahl, Maui: making smartphones last longer with code offload, in: Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services, ACM, 2010, pp. 49–62.
  9. Y. Cui, X. Ma, H. Wang, I. Stojmenovic, J. Liu, A survey of energy efficient wireless transmission and modeling in mobile cloud computing, Mobile Networks and Applications 18 (1) (2013) 148–155.
  10. J. Dean, S. Ghemawat, Mapreduce: simplified data processing on large clusters, Commun. ACM 51 (1) (2008) 107–113.
  11. H.T. Dinh, C. Lee, D. Niyato, P. Wang, A survey of mobile cloud computing: architecture, applications, and approaches, Wireless Commun. Mobile Comput. 13 (18) (2013) 1587–1611.
  12. A. Dou, V. Kalogeraki, D. Gunopulos, T. Mielikainen, V.H. Tuulos, Misco: a mapreduce framework for mobile systems, in: Proceedings of the 3rd International Conference on Pervasive Technologies Related to Assistive Environments, ACM, 2010, p. 32.
  13. I. Giurgiu, O. Riva, G. Alonso, Dynamic software deployment from clouds to mobile devices, in: Middleware 2012, ACM, 2012, pp. 394–414.
  14. M.S. Gordon, D.A. Jamshidi, S. Mahlke, Z.M. Mao, X. Chen, Comet: Code offload by migrating execution transparently, in: Presented as part of the 10th USENIX Symposium on Operating Systems Design and Implementation (OSDI 12), 2012, pp. 93–106.
  15. K. Ha, G. Lewis, S. Simanta, M. Satyanarayanan, Cloud Offload in Hostile Environments, Technical Report, DTIC Document, 2011.
  16. S. Hakak, S.A. Latif, G. Amin, A review on mobile cloud computing and issues in it, Int. J. Comput. Appl. 75 (11) (2013).
  17. J. Hauswald, T. Manville, Q. Zheng, R. Dreslinski, C. Chakrabarti, T. Mudge, A hybrid approach to offloading mobile image classification, in: International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE, IEEE, 2014, pp. 8375–8379.
  18. A. Huth, J. Cebula, The Basics of Cloud Computing, United States Computer, 2011.
  19. R. Kemp, N. Palmer, T. Kielmann, H. Bal, Cuckoo: a computation offloading framework for smartphones, in: Mobile Computing, Applications, and Services, Springer, 2010, pp. 59–79.
  20. K. Kumar, Y.-H. Lu, Cloud computing for mobile users: can offloading computation save energy?, Computer 43 (4) (2010) 51–56
  21. S. Kundu, J. Mukherjee, A.K. Majumdar, B. Majumdar, S.S. Ray, Algorithms and heuristics for efficient medical information display in PDA, Comput. Biol. Med. 37 (9) (2007) 1272–1282.
  22. G.A. Lewis, S. Echeverr’ıa, S. Simanta, B. Bradshaw, J. Root, Cloudlet-based cyber-foraging for mobile systems in resource constrained edge environments, in: Companion Proceedings of the 36th International Conference on Software Engineering, ACM, 2014, pp. 412–415.
  23. S. Mathew, Overview of Amazon Web Services, Amazon Whitepapers, 2014.
  24. J. Matthews, M. Chang, Z. Feng, R. Srinivas, M. Gerla, Powersense: power aware dengue diagnosis on mobile phones, in: Proceedings of the First ACM Workshop on Mobile Systems, Applications, and Services for Healthcare, ACM, 2011, p. 6.
  25. P. Mell, T. Grance, The Nist Definition of Cloud Computing, 2011.
  26. A. Mtibaa, A. Fahim, K.A. Harras, M.H. Ammar, Towards resource sharing in mobile device clouds: power balancing across mobile devices, ACM SIGCOMM Comput. Commun. Rev. 43 (4) (2013) 51–56.
  27. Y. Nimmagadda, K. Kumar, Y.-H. Lu, C.G. Lee, Real-time moving object recognition and tracking using computation offloading, in: International Conference on Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ, IEEE, 2010, pp. 2449– 2455.
  28. H. Qian, D. Andresen, Jade: reducing energy consumption of android app, Int. J. Network. Distrib. Comput (IJNDC) 3 (3) (2015) 150–158 (Atlantis Press).
  29. M. Satyanarayanan, P. Bahl, R. Caceres, N. Davies, The case for vm-based cloudlets in mobile computing, IEEE Pervasive Comput. 8 (4) (2009) 14–23.
  30. M. Shiraz, E. Ahmed, A. Gani, Q. Han, Investigation on runtime partitioning of elastic mobile applications for mobile cloud computing, J. Supercomput. 67 (1) (2014) 84–103.
  31. M. Shiraz, A. Gani, R.H. Khokhar, R. Buyya, A review on distributed application processing frameworks in smart mobile devices for mobile cloud computing, IEEE Commun. Surv. Tutorials 15 (3) (2013) 1294–1313.
  32. M. Smit, M. Shtern, B. Simmons, M. Litoiu, Partitioning applications for hybrid and federated clouds, in: Proceedings of the 2012 Conference of the Center for Advanced Studies on Collaborative Research, IBM Corp., 2012, pp. 27–41.
  33. M. Tulloch, Introducing Windows Azure for IT Professionals, Microsoft Press, 2013.
  34. C. Wang, Z. Li, Parametric analysis for adaptive computation offloading, ACM SIGPLAN Notices, vol. 39, ACM, 2004, pp. 119–130.
  35. S. Wang, S. Dey, Rendering adaptation to address communication and computation constraints in cloud mobile gaming, in: Global Telecommunications Conference (GLOBECOM2010), 2010 IEEE, IEEE, 2010, pp. 1–6.
  36. F. Xia, F. Ding, J. Li, X. Kong, L.T. Yang, J. Ma, Phone2cloud: exploiting computation offloading for energy saving on smartphones in mobile cloud computing, Inform. Syst. Front. 16 (1) (2014) 95–111.
  37. K. Yang, S. Ou, H.-H. Chen, On effective offloading services for resource-constrained mobile devices running heavier mobile internet applications, Commun. Mag. IEEE 46 (1) (2008) 56–63.
  38. B. Zhao, Z. Xu, C. Chi, S. Zhu, G. Cao, Mirroring smartphones for good: a feasibility study, in: Mobile and Ubiquitous Systems: Computing, Networking, and Services, Springer, 2010, pp. 26– 38.
  39. C. Wang, K. Ren, J. Wang, Secure and practical outsourcing of linear programming in cloud computing, in: INFOCOM, 2011 Proceedings IEEE, IEEE, 2011, pp. 820–828.
  40. https://www.marketsandmarkets.com/Market-Reports /mobile- applications-228.html
  41. https://www.businesswire.com/news/home/20110609005403/en/ Worldwide-Smartphone-Market-Expected-Grow-55-2011.
  42. Conti M, Chong S, Fdida S, Jia W, Karl H, et al. (2011) Research challenges towards the Future Internet. Comput commun 34: 2115-2134.
  43. Gavalas D, Economou D (2010) Development platforms for mobile applications: status and trends. IEEE Software 28: 77-86.

Downloads

Published

2019-12-30

Issue

Section

Research Articles

How to Cite

[1]
CH. Ellaji, C. Pradeepthi, P. JayaSri, " An Adequate Computation Offloading in Mobile Cloud Computing , IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 6, pp.208-216, November-December-2019. Available at doi : https://doi.org/10.32628/CSEIT195635