Abstract
Offloading in cloud computing is a way to execute big files in short times due to the available processing resources on core computers. However in some cases it is vital to execute the file locally on the node if the file size is less than a threshold size. There is a trade off in this issue due to the limited power of the node, therefore, in this paper a novel algorithm is proposed where the file size in each case is measured and then a decision is taken to either execute the file on the node or to send the file to be processed in the core cloud. The main reason is to save time of the execution of the file. However, the second and important reason, is to save the limited node energy in some large file, where the power consumption of the node will be very high. The measurement of the file size and the execution time and the power consumption for the local node and the core cloud is measured to represent an input to the execution decision.
Similar content being viewed by others
References
Altamimi M, Naik K (2014) A practical task offloading decision engine for mobile devices to use energy-as-a-service (EaaS). In: 2014 IEEE World Congress on services (SERVICES). IEEE, pp 452–453
Altamimi M, Palit R, Naik K, Nayak A (2012) Energy-as-a-service (EaaS): on the efficacy of multimedia cloud computing to save smartphone energy. In: 2012 IEEE 5th international conference on cloud computing (CLOUD). IEEE, pp 764–771
Altamimi M, Abdrabou A, Naik K, Nayak A (2015) Energy cost models of smartphones for task offloading to the cloud. IEEE Trans Emerg Top Comput 3(3):384–398
Gao B, He L, Liu L, Li K, Jarvis SA (2012) From mobiles to clouds: developing energy-aware offloading strategies for workflows. In: Proceedings of the 2012 ACM/IEEE 13th international conference on grid computing. IEEE Computer Society, pp 139–146
Jararweh Y, Ababneh F, Khreishah A, Dosari F (2014) Scalable cloudlet-based mobile computing model. Proc Comput Sci 34:434–441
Justino T, Buyya R (2014) Outsourcing resource-intensive tasks from mobile apps to clouds: android and aneka integration. In: 2014 IEEE international conference on cloud computing in emerging markets (CCEM). IEEE, pp 1–8
Kemp R, Palmer N, Kielmann T, Bal H (2012) Cuckoo: a computation offloading framework for smartphones. In: Gris M, Yang G (eds) Mobile computing, applications, and services. Springer, Berlin, Heidelberg, pp 59–79
Kumar K, Lu YH (2010) Cloud computing for mobile users: Can offloading computation save energy? Computer 4:51–56
Kumar K, Liu J, Lu Y-H, Bhargava B (2013) A survey of computation offloading for mobile systems. In: Mobile Networks and Applications. Springer, US, pp 129–140
Magurawalage CMS, Yang K, Hu L, Zhang J (2014) Energy-efficient and network-aware offloading algorithm for mobile cloud computing. Comput Netw 74:22–33
Qian H, Andresen D (2015) Reducing mobile device energy consumption with computation offloading. In: 2015 16th IEEE/ACIS international conference on software engineering, artificial intelligence, networking and parallel/distributed computing (SNPD). IEEE, pp 1–8
Shiraz M, Sookhak M, Gani A, Shah SAA (2015) A study on the critical analysis of computational offloading frameworks for mobile cloud computing. J Netw Comput Appl 47:47–60
Wolski R, Gurun S, Krintz C, Nurmi D (2008) Using bandwidth data to make computation offloading decisions. In: IEEE international symposium on parallel and distributed processing, 2008. IPDPS 2008. IEEE, pp 1–8
Zhou B, Dastjerdi AV, Calheiros RN, Srirama SN, Buyya R (2015) A context sensitive offloading scheme for mobile cloud computing service. In: 2015 IEEE 8th international conference on cloud computing (CLOUD). IEEE, pp 869–876
Acknowledgments
The authors of this work than the UK–India Educational and Research Partnership for sponsoring this research under the collaboration UKIERI Project between Anglia Ruskin University in the UK and The ABV-Indian Institute of Information Technology and Management in Gwalior, India.
Author information
Authors and Affiliations
Corresponding authors
Rights and permissions
About this article
Cite this article
Aldmour, R., Yousef, S., Yaghi, M. et al. New cloud offloading algorithm for better energy consumption and process time. Int J Syst Assur Eng Manag 8 (Suppl 2), 730–733 (2017). https://doi.org/10.1007/s13198-016-0515-2
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13198-016-0515-2