Abstract
Mobile cloud computing (MCC) is a methodology, which is developed due to the inability of mobile devices to process large of amount of data and utilize less amount of energy as such the computers that can process the large amount data as compared to mobile devices. So in order overcome this problem, MCC came into existence which is used to increase the computation power and utilize energy of mobile devices that is required to process large data; to overcome this issue, there are several techniques that we discuss in this paper and their proposed solution to enhance the computation ability of mobile devices by using less energy. Techniques involve in taking off the data from mobile devices to the cloud server and perform the computation in cloud server, and when the computation of data is completed, then send back that particular data to the mobile devices. Thus, this paper studies about how to reduce the energy consumption of mobile devices by using certain parameters such as bandwidth and execution time.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Itani W, Kayssi A, Chehab A (2010) Energy-efficient incremental integrity for securing storage in mobile cloud computing. IEEE
Niu C, Yang S, Wang F (2015) A unified energy efficiency and spectral efficiency tradeoff for mobile cloud computing in OFDM-based networks. IEEE, pp 306–311
Guo S, Liu J, Yang Y, Xiao B, Li Z (2018) Energy-efficient dynamic computation offloading and cooperative task scheduling in mobile cloud computing. IEEE
Satyanarayanan M, Bahl P, Caceres R, Davies N (2009) The case for VM based cloudlets in mobile computing. IEEE Pervasive Comput 8(4):14–23
Yang L, Cao J, Cheng H, Ji Y (2015) Multi-user computation partitioning for latency sensitive mobile cloud applications. IEEE Trans Comput 64(8):2253–2266
Yang L, Cao J, Tang S, Li T, Chan ATS (2013) A framework for partitioning and execution of data stream applications in mobile cloud computing. ACM SIGMETRICS Perform Eval Rev 40(4):23–32
Huang D, Wang P, Niyato D (2012) A dynamic offloading algorithm for mobile computing. IEEE Trans Wireless Commun 11(6):1991–1995
Arroba P, Moya JM, Ayala JL, Buyya R (2015) DVFS-aware consolidation for energy-efficient clouds. IEEE, pp 494–495
Boukerche A, Guan S, De Grande RE (2018) A task-centric mobile cloud-based system to enable energy-aware efficient offloading. IEEE
Zhang W, Wen Y (2015) Energy-efficient task execution for application as a general topology in mobile cloud computing. IEEE
Saab SA, Chehab A, Kayssi A (2013) Energy efficiency in mobile cloud computing total offloading selectively works. Does selective offloading totally work? IEEE, pp 164–168
Vinh TL, Pallavali R, Houacine F, Bouzefrane S (2016) Energy efficiency in mobile cloud computing architectures. IEEE, pp 327–331
Liu F, Shu P, Lui JCS (2015)“AppATP: an energy conserving adaptive mobile-cloud transmission protocol. IEEE
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Pal, S., Dumka, A. (2021). Classification of Energy Efficiency in Mobile Cloud Computing. In: Goar, V., Kuri, M., Kumar, R., Senjyu, T. (eds) Advances in Information Communication Technology and Computing. Lecture Notes in Networks and Systems, vol 135. Springer, Singapore. https://doi.org/10.1007/978-981-15-5421-6_41
Download citation
DOI: https://doi.org/10.1007/978-981-15-5421-6_41
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-5420-9
Online ISBN: 978-981-15-5421-6
eBook Packages: EngineeringEngineering (R0)