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A recent review and a taxonomy for multimedia application in Mobile cloud computing based energy efficient transmission

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Abstract

The mobile devices have entered the race of deploying high tech to the users but inherit a defect of limited battery storage. With the limitationof battery capacity, energy efficiency has been a major concern for Mobile Cloud Computing (MCC). The multimedia application comprises rich media that needs higher processing and computation, and the resource and computation are constrained. Energy-efficient transmission is a big concern because it equips the mobile device with high-end hardware components, but still, are far behind to the battery capacity and computation competence. This paper intends to introduce and investigate the different approaches/algorithms and tools that best fit to save resource utilization and energy consumption rationally. The algorithms like the Genetic Algorithm, Greedy scheduling algorithm, power-aware list-based scheduling, Offloading based task scheduling, media cloud distributed scheduling algorithm, etc. are discussed in this research. The data, Energy-efficient technique, and Cloud server response that defines each of the main components is introduced in this paper that concerns the implementation of the energy-efficient transmission in MCC. We propose these components that illustrate the workflow in the technology. A process when the data is perceived by the technique to adequately deliver a response to the mobile device. An energy-efficient transmission technique for MCC is a development towards the use of mobile cloud computing in this field working to counter the utilization of energy and resources that execute locally. This concept results in reducing the amount of data transmitted with the use of sharing the data externally between the tasks that will save energy. Through this paper, readers will understand the benefit of using the energy-efficient technique in the MCC. Also, the reader will understand the classification groups, validation criteria, future gaps of the 30 literature reviews about the technique, and how they intend to energy optimization in mobile devices.

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Authors and Affiliations

  1. School of Computing and Mathematics, Charles Sturt University, Sydney Campus, Australia

    Nitesh Parajuli, Abeer Alsadoon & P.W.C. Prasad

  2. Department of Computer Techniques Engineering, AL Nisour University College, Baghdad, Iraq

    Rasha S. Ali

  3. Department of Islamic Sciences, Al Iraqia University, Baghdad, Iraq

    Omar Hisham Alsadoon

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  1. Nitesh Parajuli
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  2. Abeer Alsadoon
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  3. P.W.C. Prasad
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  4. Rasha S. Ali
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  5. Omar Hisham Alsadoon
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Correspondence to Abeer Alsadoon.

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HIGHLIGHTS

• The user requested task can be offloaded to the cloud server infrastructure for processing.

• A reviewof different energy-efficient techniques for efficient processing and energy saving.

• Previous publications only discussed on few of the energy-efficient techniques, but our paper discusses on 30 techniques for energy optimization.

• The taxonomy we presented here consists of three system components of data, energy-efficient techniques, and cloud server response, whilst previous solutions only considered the techniques as their system component.

• Proposedthe best solution among the different energy-efficient techniques we discussed in our paper.

• Verification and evaluation have been done by us to access the outcome of the classified techniques and the recommendations have been written by us by recommending the best solutions for energy optimization.

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Parajuli, N., Alsadoon, A., Prasad, P. et al. A recent review and a taxonomy for multimedia application in Mobile cloud computing based energy efficient transmission. Multimed Tools Appl 79, 31567–31594 (2020). https://doi.org/10.1007/s11042-020-09516-y

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