CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

A Context Aware Mechanism for Mobile Devices to Efficiently Acquire Resources Remotely

by Kashif Tasneem, Ayesha Siddiqui, Anum Liaquat
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 41
Year of Publication: 2019
Authors: Kashif Tasneem, Ayesha Siddiqui, Anum Liaquat
10.5120/ijca2019918489

Kashif Tasneem, Ayesha Siddiqui, Anum Liaquat . A Context Aware Mechanism for Mobile Devices to Efficiently Acquire Resources Remotely. International Journal of Computer Applications. 182, 41 ( Feb 2019), 12-17. DOI=10.5120/ijca2019918489

@article{ 10.5120/ijca2019918489,
author = { Kashif Tasneem, Ayesha Siddiqui, Anum Liaquat },
title = { A Context Aware Mechanism for Mobile Devices to Efficiently Acquire Resources Remotely },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2019 },
volume = { 182 },
number = { 41 },
month = { Feb },
year = { 2019 },
issn = { 0975-8887 },
pages = { 12-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number41/30365-2019918489/ },
doi = { 10.5120/ijca2019918489 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:13:57.961400+05:30
%A Kashif Tasneem
%A Ayesha Siddiqui
%A Anum Liaquat
%T A Context Aware Mechanism for Mobile Devices to Efficiently Acquire Resources Remotely
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 41
%P 12-17
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Mobile devices are becoming very popular due to their portability and small size, but they are still not comparable to that of PC. Computational and network intensive applications cannot run efficiently on mobile devices due to their limited batteries and energy deficient systems. Recent works to improve mobile device efficiency include mobile cloud computing, mobile edge computing, and device to device communication. Shifting the computations on the cloud will reduce the burden of mobile device but at the same time, this implementation presents many challenges. In this paper, an algorithm is proposed which can deal with the resource acquisition from different sources by using a context aware system. Implementation of that algorithm is left for future work.

References
  1. Zhou, Bowen, and Rajkumar Buyya. "Augmentation Techniques for Mobile Cloud Computing: A Taxonomy, Survey, and Future Directions." ACM Computing Surveys (CSUR) 51.1 (2018): 13.
  2. Erol-Kantarci, M., & Sukhmani, S. (2018). Caching and Computing at the Edge for Mobile Augmented Reality and Virtual Reality (AR/VR) in 5G. In Ad Hoc Networks (pp. 169-177). Springer, Cham.
  3. Guerrero-Contreras, G., Garrido, J. L., Balderas-Diaz, S., & Rodríguez-Domínguez, C. (2017). A context-aware architecture supporting service availability in mobile cloud computing. IEEE Transactions on Services Computing, 10(6), 956-968.
  4. Bahmani, K., Argyriou, A., Erol-Kantarci, M.: Backhaul relaxation through caching. In: Imran, M., Raza, S.A., Shakir, M.Z. (eds.) Access, Fronthaul and Backhaul for 5G Wireless Networks. IET (2017)
  5. Tang, L., He, S., & Li, Q. (2017). Double-sided bidding mechanism for resource sharing in mobile cloud. IEEE Transactions on Vehicular Technology, 66(2), 1798-1809.
  6. Chen, X., Jiao, L., Li, W., & Fu, X. (2016). Efficient multi-user computation offloading for mobile-edge cloud computing. IEEE/ACM Transactions on Networking, 24(5), 2795-2808.
  7. Ali, F. A., Simoens, P., Verbelen, T., Demeester, P., & Dhoedt, B. (2016). Mobile device power models for energy efficient dynamic offloading at runtime. Journal of Systems and Software, 113, 173-187.
  8. Mao, Y., Zhang, J., & Letaief, K. B. (2016). Dynamic computation offloading for mobile-edge computing with energy harvesting devices. IEEE Journal on Selected Areas in Communications, 34(12), 3590-3605.
  9. Yang, L., Cao, J., Liang, G., & Han, X. (2016). Cost aware service placement and load dispatching in mobile cloud systems. IEEE Transactions on Computers, 65(5), 1440-1452.
  10. C. Shi, K. Habak, P. Pandurangan, M. Ammar, M. Naik, E. Zegura, Cosmos: Computation offloading as a service for mobile devices, in: Proceedings of the 15th ACM International Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc '14, ACM, New York, NY, USA, 2014, pp. 287-296.
  11. European Telecommunications Standards Institute (ETSI), “Mobile-edge computing-Introductory technical white paper,” Sep. 2014.
  12. S. Al Noor, R. Hasan, and M.M. Haque. Cellcloud: a novel cost-effective formation of mobile cloud based on bidding incentives. In IEEE International Conference on Cloud Computing, pages 200–207, 2014.
  13. N. Fernando, S. Loke, W. Rahayu, Honeybee: A programming framework for mobile crowd computing, in: K. Zheng, M. Li, H. Jiang (Eds.), Mobile and Ubiquitous Systems: Computing, Networking, and Services, Vol. 120 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Springer Berlin Heidelberg, 2013, pp. 224-236.
  14. N. Fernando, S. Loke, and W. Rahayu, “Mobile cloud computing: A survey,” Future Gener. Comput. Syst., vol. 29, no. 1, pp. 84–106, 2013.
  15. A. Grazioli, M. Picone, F. Zanichelli, and M. Amoretti, “Code migration in mobile clouds with the NAM4J middleware,” in Proc. IEEE 14th Int. Conf. Mobile Data Manage., Jun. 2013, vol. 2, pp. 194–199.
  16. M. Kjrgaard, H. Blunck, Unsupervised power profiling for mobile devices, in: A. Puiatti, T. Gu (Eds.), Mobile and Ubiquitous Systems: Computing, Networking, and Services, Vol. 104 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Springer Berlin Heidelberg, 2012, pp. 138-149.
  17. C. Yoon, D. Kim, W. Jung, C. Kang, H. Cha, Appscope: Application energy metering framework for android smartphones using kernel activity monitoring, in: Proceedings of the 2012 USENIX Conference on Annual Technical Conference, USENIX ATC'12, USENIX Association, Berkeley, CA, USA, 2012, pp. 36-36.
  18. M. Kim, J. Kong, S. W. Chung, Enhancing online power estimation accuracy for smartphones, Consumer Electronics, IEEE Transactions on 58 (2) (2012) 333-339.
  19. S. Kosta, A. Aucinas, P. Hui, R. Mortier, X. Zhang, Thinkair: Dynamic resource allocation and parallel execution in the cloud for mobile code offloading, in: in INFOCOM, 2012 Proceedings IEEE. IEEE, 2012, pp. 945-953.
  20. C. Shi, V. Lakafosis, M. H. Ammar, E. W. Zegura, Serendipity: Enabling remote computing among intermittently connected mobile devices, in: Proceedings of the Thirteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc '12, ACM, New York, NY, USA, 2012, pp. 145-154.
  21. T. Verbelen, P. Simoens, F. D. Turck, B. Dhoedt, Aiolos: Middleware for improving mobile application performance through cyber foraging, Journal of Systems and Software 85 (11) (2012) 2629-2639.
  22. E. Miluzzo, R. Caceres, and Y. Chen. Vision: mclouds-computing on clouds of mobile devices. In Proceedings of ACM Workshop on Mobile Cloud Computing and Services, 2012.
  23. F. Bonomi, R. Milito, J. Zhu, S. Addepalli. Fog computing and its role in the Internet of Things. In Proc. ACM MCC, pp.13-16, August 2012, Helsinki, Finland.
  24. 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, EuroSys '11, ACM, New York, NY, USA, 2011, pp. 301-314.
  25. S. Sudevalayam and P. Kulkarni, “Energy harvesting sensor nodes: Survey and implications,” IEEE Commun. Surveys Tuts., vol. 13, no. 3, pp. 443-461, Jul. 2011.
  26. L. Zhang, B. Tiwana, R. Dick, Z. Qian, Z. Mao, Z. Wang, L. Yang, Accurate online power estimation and automatic battery behavior-based power model generation for smartphones, in: Hardware/Software Codesign and System Synthesis (CODES+ISSS), 2010 IEEE/ACM/IFIP International Conference on, 2010, pp. 105-114.
  27. 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, MobiSys '10, ACM, New York, NY, USA, 2010, pp. 49-62.
  28. 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, PETRA '10, ACM, New York, NY, USA, 2010, pp. 32:1-32:8.
  29. A. Shye, B. Scholbrock, G. Memik, Into the wild: studying real user activity patterns to guide power optimizations for mobile architectures, in: Proceedings of the 42nd Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 42, ACM, New York, NY, USA, 2009, pp. 168-178.
  30. M. Satyanarayanan, P. Bahl, R. Caceres, and N. Davies. The case for VM-based cloudlets in mobile computing. In IEEE Pervasive Computing, vol.8, no.4, pp.14-23, October 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Cloud Computing Cache Computing Fog Computing Mobile Edge Offloading

Powered by PhDFocusTM