Enhancing Mobile Efficiency: A Cloud-Powered Paradigm for Extended Battery Life and Enhanced Processing Capabilities

Dua Agha; Veena Kumari; Areej Fatemah Meghji

Authors

Dua Agha Department of Software Engineering, Mehran University of Engineering and Technology Jamshoro, Pakistan
Veena Kumari Department of Software Engineering, Mehran University of Engineering and Technology Jamshoro, Pakistan
Areej Fatemah Meghji Department of Software Engineering. Mehran University of Engineering and Technology

Keywords:

Cloud Computing, Mobile Cloud Computing, Battery Optimization, Offloading, Firebase

Abstract

In an interconnected world where mobile phones are essential to everyday operations, the constraints of these devices in terms of processing power, memory, storage, and energy efficiency are becoming increasingly apparent. This research introduces an innovative solution by integrating Mobile Cloud Computing (MCC) to address these challenges. The research focuses on the creation of an Android application called "ServiVerse" that efficiently drains the phone's battery to imitate real-world conditions. The software is accompanied by a Firebase-connected battery optimizer, which provides users with complete insights into battery state, cleaning history, and graphical representations of performance. The system's distinguishing feature is outsourcing power-intensive operations to a cloud server, resulting in increased energy efficiency and battery life. The study demonstrated successful battery optimization tactics adapted to individual users, such as the amount of cache and RAM deleted and storage space freed up on the mobile devices. This strategy has proven to be vital in addressing a key concern about background processing and the loss of power generation on mobiles, which is providing users with more efficient and longer-lasting battery life.

Author Biography

Areej Fatemah Meghji, Department of Software Engineering. Mehran University of Engineering and Technology

The Demo of this Application is available at https://youtu.be/m-a27PN1-M4

References

H. K. Shaikha and A. B. Sallow, “Mobile Cloud Computing: A Review,” Acad. J. Nawroz Univ., vol. 6, no. 3, pp. 129–134, Aug. 2017, doi: 10.25007/AJNU.V6N3A96.

S. C. Toader, R. I. Ciobanu, and C. Dobre, “Smart Computation Offloading for Mobile Clouds,” 2023 IEEE Int. Conf. Pervasive Comput. Commun. Work. other Affil. Events, PerCom Work. 2023, pp. 62–67, 2023, doi: 10.1109/PERCOMWORKSHOPS56833.2023.10150282.

C. Nigam, G. Sharma, and E. Menghani, “Comprehensive Review and Analysis on Mobile Cloud Computing and Users Offloading using Improved Optimization Approach for Edge Computing,” Int. J. Intell. Syst. Appl. Eng., vol. 10, no. 1s, pp. 234–242, Oct. 2022, Accessed: Feb. 06, 2024. [Online]. Available: https://ijisae.org/index.php/IJISAE/article/view/2286

P. Eastham, A. Sharma, U. Syed, S. Vassilvitskii, and F. Yu, “Learning Battery Consumption of Mobile Devices,” 2016.

M. Ali, J. M. Zain, M. F. Zolkipli, and G. Badshah, “Mobile cloud computing & mobile battery augmentation techniques: A survey,” 2014 IEEE Student Conf. Res. Dev. SCOReD 2014, Mar. 2014, doi: 10.1109/SCORED.2014.7072944.

M. R. Nakhkash, T. N. Gia, I. Azimi, A. Anzanpour, A. M. Rahmani, and P. Liljeberg, “Analysis of performance and energy consumption of wearable devices and mobile gateways in IoT applications,” ACM Int. Conf. Proceeding Ser., vol. Part F148162, pp. 68–73, 2019, doi: 10.1145/3312614.3312632.

“View of A Systematic Survey of Simulation Tools for Cloud and Mobile Cloud Computing Paradigm.” Accessed: Feb. 06, 2024. [Online]. Available: https://jisrc.szabist.edu.pk/ojs/index.php/jisrc/article/view/40/30

V. P. Estamsetty, “Cloud Computing , Mobile Cloud Computing and its Comparative Study,” no. January, 2021, doi: 10.13140/RG.2.2.30812.41601.

B. G. Chun, S. Ihm, P. Maniatis, M. Naik, and A. Patti, “CloneCloud: Elastic execution between mobile device and cloud,” EuroSys’11 - Proc. EuroSys 2011 Conf., pp. 301–314, 2011, doi: 10.1145/1966445.1966473.

Y. Hmimz, M. El Ghmary, T. Chanyour, and M. O. Cherkaoui Malki, “Computation offloading to a mobile edge computing server with delay and energy constraints,” 2019 Int. Conf. Wirel. Technol. Embed. Intell. Syst. WITS 2019, Apr. 2019, doi: 10.1109/WITS.2019.8723733.

S. Cao, X. Tao, Y. Hou, and Q. Cui, “An energy-optimal offloading algorithm of mobile computing based on HetNets,” 2015 Int. Conf. Connect. Veh. Expo, ICCVE 2015 - Proc., pp. 254–258, Apr. 2016, doi: 10.1109/ICCVE.2015.68.

D. J. S. Raj, “Improved Response Time and Energy Management for Mobile Cloud Computing Using Computational Offloading,” J. ISMAC, vol. 2, no. 1, pp. 38–49, Mar. 2020, doi: 10.36548/JISMAC.2020.1.004.

M. A. Elgendy, A. Shawish, and M. I. Moussa, “MCACC: New approach for augmenting the computing capabilities of mobile devices with Cloud Computing,” Proc. 2014 Sci. Inf. Conf. SAI 2014, pp. 79–86, Oct. 2014, doi: 10.1109/SAI.2014.6918175.

Y. Sun, J. Wu, L. Chen, T. Liu, M. Yao, and W. Sun, “Latency optimization for mobile edge computing with dynamic energy harvesting,” Proc. - 2019 IEEE Intl Conf Parallel Distrib. Process. with Appl. Big Data Cloud Comput. Sustain. Comput. Commun. Soc. Comput. Networking, ISPA/BDCloud/SustainCom/SocialCom 2019, pp. 79–83, Dec. 2019, doi: 10.1109/ISPA-BDCLOUD-SUSTAINCOM-SOCIALCOM48970.2019.00022.

Y. Miao, G. Wu, M. Li, A. Ghoneim, M. Al-Rakhami, and M. S. Hossain, “Intelligent task prediction and computation offloading based on mobile-edge cloud computing,” Futur. Gener. Comput. Syst., vol. 102, pp. 925–931, Jan. 2020, doi: 10.1016/J.FUTURE.2019.09.035.

A. Ali et al., “An Efficient Dynamic-Decision Based Task Scheduler for Task Offloading Optimization and Energy Management in Mobile Cloud Computing,” Sensors 2021, Vol. 21, Page 4527, vol. 21, no. 13, p. 4527, Jul. 2021, doi: 10.3390/S21134527.

A. Akbar and P. R. Lewis, “Towards the optimization of power and bandwidth consumption in mobile-cloud hybrid applications,” 2017 2nd Int. Conf. Fog Mob. Edge Comput. FMEC 2017, pp. 213–218, Jun. 2017, doi: 10.1109/FMEC.2017.7946433.

N. Dange, K. Devadkar, and D. Kalbande, “Scheduling of task in collaborative environment using mobile cloud,” Proc. - Int. Conf. Glob. Trends Signal Process. Inf. Comput. Commun. ICGTSPICC 2016, pp. 579–583, Jun. 2017, doi: 10.1109/ICGTSPICC.2016.7955367.

I. Kaur, S. Sharma, and M. Arora, “Research Paper on Enhanced Battery for Android Phones using the Power of Cloud through Data Synchronization,” 2014.

A. Wajid, N. Nigar, S. Islam, and M. K. Shahzad, “A SURVEY ON MOBILE CLOUD COMPUTING PROBLEMS AND SOLUTIONS,” Pak. J. Sci., vol. 75, no. 1, pp. 71–77, Mar. 2023, doi: 10.57041/PJS.V75I1.824.

B. Assistant Professor, “Mobile Cloud Computing: Implementation using Android and Firebase API,” Int. J. Creat. Res. Thoughts, vol. 6, no. 2, pp. 2320–2882, 2018, Accessed: Feb. 06, 2024. [Online]. Available: www.ijcrt.orgwww.ijcrt.org

A. B. Semma, M. Ali, M. Saerozi, Mansur, and Kusrini, “Cloud computing: google firebase firestore optimization analysis,” Indones. J. Electr. Eng. Comput. Sci., vol. 29, no. 3, pp. 1719–1728, Mar. 2023, doi: 10.11591/IJEECS.V29.I3.PP1719-1728.