Skip to main content

Advertisement

SpringerLink
Log in

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

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2:
Fig. 3
Fig. 4
Fig. 5
Fig 6

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Ahmad H, Saxena N, Roy A, De P (2018) Battery-aware rate adaptation for extending video streaming playback time. Multimed Tools Appl 77(18):23877–23908

    Google Scholar 

  2. Ahmed E, Gani A, Khan MK, Buyya R, Khan SU (2015) Seamless application execution in mobile cloud computing: motivation, taxonomy, and open challenges. J Netw Comput Appl 52:154–172

    Google Scholar 

  3. S Ahn, J Lee, S Park, SHS Newaz, and JK Choi (2018), “Competitive partial computation offloading for maximizing energy efficiency in Mobile cloud computing,” Access, IEEE, vol. 6, pp. 899–912

  4. A Alasaad, K Shafiee, H Behairy, and V Leung (2015). “Innovative schemes for resource allocation in the cloud for media streaming applications,” IEEE Transactions on Parallel Distributed Systems, no. 1, pp. 1–1

  5. W Alsalih, S Akl, and H Hassancin (2005). “Energy-aware task scheduling: towards enabling mobile computing over MANETs,” in Parallel and Distributed Processing Symposium, 2005. Proceedings. 19th IEEE International, p. 8 pp.: IEEE

  6. Badidi E, Atif Y, Sheng MZ, Maheswaran M (2018) On personalized cloud service provisioning for Mobile users using adaptive and context-aware service composition. Computing

  7. Bani Hani Q, Dichter J (2017) Energy-efficient service-oriented architecture for mobile cloud handover. Journal of Cloud Computing 6(1):1–13

    Google Scholar 

  8. C Bartolini, D El Kateb, Y Le Traon, and D Hagen (2015), “Cloud providers viability: how to address it from an IT and legal perspective?,” in International Conference on Grid Economics and Business Models, pp. 281–295: Springer

  9. Cao Y, Song F, Liu Q, Huang M, Wang H, You I (2017) A LDDoS-aware energy-efficient Multipathing scheme for Mobile cloud computing systems. IEEE Access 5:21862–21872

    Google Scholar 

  10. V. Cardellini et al. 2016, “A game-theoretic approach to computation offloading in mobile cloud computing.(Report),” vol. 157, no. 2, p. 421

  11. Chalack VA, Razavi S, Gudakahriz S (2017) Resource allocation in cloud environment using approaches based particle swarm optimization. Int J Comput Appl Technol Res 6(2):87–90

    Google Scholar 

  12. Chang Z, Gong J, Ristaniemi T, Niu Z (2016) Energy-efficient resource allocation and user scheduling for collaborative Mobile clouds with hybrid receivers. IEEE Trans Veh Technol 65(12):9834–9846

    Google Scholar 

  13. Chang Z, Zhou S, Ristaniemi T, Niu Z (2018) Collaborative Mobile clouds: an energy efficient paradigm for content sharing. IEEE Wirel Commun 25(2):186–192

    Google Scholar 

  14. Chen X (2015) Decentralized computation offloading game for mobile cloud computing. IEEE Transactions on Parallel and Distributed Systems 26(4):974–983

    Google Scholar 

  15. Chen M, Hao Y, Li Y, Lai C-F, Wu D (2015) On the computation offloading at ad hoc cloudlet: architecture and service modes. IEEE Commun Mag 53(6):18–24

    Google Scholar 

  16. Chen K, Shen H (2015) Maximizing P2P file access availability in mobile ad hoc networks though replication for efficient file sharing. IEEE Trans Comput 64(4):1029–1042

    MathSciNet  MATH  Google Scholar 

  17. Chen K, Shen H, Zhang H (2014) Leveraging social networks for P2P content-based file sharing in disconnected MANETs. IEEE Trans Mob Comput 13(2):235–249

    Google Scholar 

  18. CA Chen, M Won, R Stoleru, and G Xie (2015). Energy-efficient fault-tolerant data storage and processing in mobile cloud., pp. 28–41

  19. Chen X, Wu J, Cai Y, Zhang H, Chen T (2015) Energy-efficiency oriented traffic offloading in wireless networks: a brief survey and a learning approach for heterogeneous cellular networks. IEEE Journal on Selected Areas in Communications 33(4):627–640

    Google Scholar 

  20. Chen H, Zhu X, Guo H, Zhu J, Qin X, Wu J (2015) Towards energy-efficient scheduling for real-time tasks under uncertain cloud computing environment. The Journal of Systems & Software 99(C):20–35

    Google Scholar 

  21. G Chunhui, Z Zhan, X Xin, and Y Zhengyu (2018). “Bolt detection signal analysis method based on ICEEMD,” Shock and Vibration, vol 2018

  22. Chunlin L, Chuanli M, Yi C, Youlong L (2018) Optimal media service selection scheme for mobile users in mobile cloud. Wirel Netw:1–14

  23. E Cuervo et al. (2010). “MAUI: making smartphones last longer with code offload,” in Proceedings of the 8th international conference on Mobile systems, applications, and services, pp. 49–62: ACM

  24. E Cuervo et al. (2010). MAUI: Making smartphones last longer with code offload., pp. 49–62

  25. Dong Huang D, Ping Wang D, Niyato D (2012) A dynamic offloading algorithm for Mobile computing. Wireless Communications, IEEE Transactions on 11(6):1991–1995

    Google Scholar 

  26. Dong P, Wang J, Huang J, Wang H, Min G (2016) Performance enhancement of multipath TCP for wireless communications with multiple radio interfaces. IEEE Trans Commun 64(8):3456–3466

    Google Scholar 

  27. S Durga and S Mohan (2013). “Mobile cloud media computing applications: A survey,” in Proceedings of the Fourth International Conference on Signal and Image Processing 2012 (ICSIP 2012), pp. 619–628: Springer

  28. Durga S, Mohan S, Peter JD, Surya S (2018) Context-aware adaptive resource provisioning for mobile clients in intra-cloud environment. Clust Comput

  29. L Ferdouse, M Li, L Guan, and A Anpalagan (2016). “Bayesian workload scheduling in multimedia cloud networks,” in Computer Aided Modelling and Design of Communication Links and Networks (CAMAD), 2016 IEEE 21st International Workshop on, pp. 83–88: IEEE

  30. M Gamba, A Gonella, and CE Palazzi (2015). “Design issues and solutions in a modern home automation system,” in Computing, Networking and Communications (ICNC), 2015 International Conference on, pp. 1111–1115: IEEE

  31. X Gong, W Liu, J Zhang, H Xu, W Zhao, and C Liu (2016), WWOF: An Energy Efficient Offloading Framework for Mobile Webpage., pp. 160–169

  32. L Gu, D Zeng, A Barnawi, S Guo, and I Stojmenovic (2015). “Optimal task placement with QoS constraints in geo-distributed data centers using DVFS,” IEEE Transactions on Computers, no. 1, pp. 1–1

  33. Guo X, Liu L, Chang Z, Ristaniemi T (2018) Data offloading and task allocation for cloudlet-assisted ad hoc mobile clouds. Wirel Netw 24(1):79–88

    Google Scholar 

  34. S Guo, J Liu, Y Yang, B Xiao, and Z Li (2018). Energy-efficient dynamic computation offloading and cooperative task scheduling in mobile cloud computing., pp. 1–1

  35. He J, Xue Z, Wu D, Wu DO, Wen Y (2014) CBM: online strategies on cost-aware buffer Management for Mobile Video Streaming. IEEE Transactions on Multimedia 16(1):242–252

    Google Scholar 

  36. Hu CC, Lai CF, Hou JG, Huang YM (2017) Timely scheduling algorithm for P2P streaming over MANETs. Comput Netw 127:56–67

    Google Scholar 

  37. Jacobsson A, Boldt M, Carlsson B (2016) A risk analysis of a smart home automation system. Futur Gener Comput Syst 56:719–733

    Google Scholar 

  38. Jo S, Yoo W, Chung J (2018) Video quality adaptation for extended playback time on Mobile devices with limited energy. IEEE Commun Lett 22(6):1260–1263

    Google Scholar 

  39. Kaewpuang R, Niyato D, Wang P, Hossain E (2013) A framework for cooperative resource management in mobile cloud computing. IEEE Journal on Selected Areas in Communications 31(12):2685–2700

    Google Scholar 

  40. Kaur T, Chana I (2016) Energy aware scheduling of deadline-constrained tasks in cloud computing. Clust Comput 19(2):679–698

    Google Scholar 

  41. Khorramnejad K, Ferdouse L, Guan L, Anpalagan A Performance of integrated workload scheduling and pre-fetching in multimedia mobile cloud computing. Journal of Cloud Computing 7(1):13

  42. S Kosta, A Aucinas, P Hui, R Mortier, and X Zhang (2012). “Thinkair: Dynamic resource allocation and parallel execution in the cloud for mobile code offloading,” in Infocom, 2012 Proceedings IEEE, pp. 945–953: IEEE

  43. AS Kumar and M Venkatesan (2018). “Task scheduling in a cloud computing environment using HGPSO algorithm,” Clust Comput, pp. 1–7

  44. Kumari R, Kaushal S, Chilamkurti N (2018) Energy conscious multi-site computation offloading for mobile cloud computing. Soft Comput 22(20):6751–6764

    Google Scholar 

  45. Kwak J, Kim Y, Lee J, Chong S (2015) DREAM: dynamic resource and task allocation for energy minimization in Mobile cloud systems. Selected Areas in Communications, IEEE Journal on 33(12):2510–2523

    Google Scholar 

  46. L Lan, Z Xiaoyong, L Kaiyang, J Fu, and P Jun (2018). “An energy-aware task offloading mechanism in multiuser Mobile-edge cloud computing,” Mobile Information Systems, vol, 2018

  47. Li Y, Chen M, Dai W, Qiu M (2017) Energy optimization with dynamic task scheduling Mobile cloud computing. IEEE Syst J 11(1):96–105

    Google Scholar 

  48. Li Z, Zhu X, Gahm J, Pan R, Hu H, Begen AC, Oran D (2014) Probe and adapt: rate adaptation for HTTP video streaming at scale. IEEE Journal on Selected Areas in Communications 32(4):719–733

    Google Scholar 

  49. Lin C-C, Syu YC, Chang CJ, Wu JJ, Liu P, Cheng PW, Hsu WT (2015) Energy-efficient task scheduling for multi-core platforms with per-core DVFS. Journal of Parallel and Distributed Computing 86(C):71–81

    Google Scholar 

  50. Lin Xiang FY, Xiaohu Ge F, Cheng-Xiang Wang F, Li F, Reichert F (2013) Energy efficiency evaluation of cellular networks based on spatial distributions of traffic load and power consumption. IEEE Trans Wirel Commun 12(3):961–973

    Google Scholar 

  51. Liu T, Chen F, Ma Y, Xie Y (2016) An energy-efficient task scheduling for mobile devices based on cloud assistant. Futur Gener Comput Syst 61(C):1–12

    Google Scholar 

  52. J Liu and J Guo (2015). Energy efficient scheduling of real-time tasks on multi-core processors with voltage islands

  53. L Liu, X Guo, Z Chang, and T Ristaniemi (2018). “Joint optimization of energy and delay for computation offloading in cloudlet-assisted mobile cloud computing,” Wirel Netw, pp. 1–14

  54. Liu Y, Lee MJ, Zheng Y (2016) Adaptive multi-resource allocation for cloudlet-based Mobile cloud computing system. IEEE Trans Mob Comput 15(10):2398–2410

    Google Scholar 

  55. Ma X, Zhao Y, Zhang L, Wang H, Peng L (2013) When mobile terminals meet the cloud: computation offloading as the bridge. IEEE Netw 27(5):28–33

    Google Scholar 

  56. AM Manasrah and H Ba Ali (2018). “Workflow scheduling using hybrid GA-PSO algorithm in cloud computing,” Wireless Communications Mobile Computing, vol, 2018

  57. Meng X, Wang Y, Gong Y (2015) Perspective of space and time based replica population organizing strategy in unstructured peer-to-peer networks. J Netw Comput Appl 49:1–14

    Google Scholar 

  58. MB Mollah, M Azad and A Vasilakos (2017). Security and privacy challenges in mobile cloud computing: survey and way ahead., pp. 34–54

  59. Neto JLD, Yu S-y, Macedo DF, Nogueira JMS, Langar R, Secci S (2018) ULOOF: a user level online offloading framework for Mobile edge computing. IEEE Trans Mob Comput 17:2660–2674

    Google Scholar 

  60. Ou S, Yang K, Zhang J (2007) An effective offloading middleware for pervasive services on mobile devices. Pervasive and Mobile Computing 3(4):362–385

    Google Scholar 

  61. Pan S, Chen Y (2018) A bandwidth allocation and energy-optimal transmission rate scheduling scheme in multi-services wireless networks. AEUE - International Journal of Electronics and Communications 95:97–106

    Google Scholar 

  62. Paris S, Martignon F, Filippini I, Lin Chen I (2015) An efficient auction-based mechanism for Mobile data offloading. Mobile Computing, IEEE Transactions on 14(8):1573–1586

    Google Scholar 

  63. Qiu M, Ming Z, Li J, Gai K, Zong Z (2015) Phase-change memory optimization for green cloud with genetic algorithm. IEEE Trans Comput 64(12):3528–3540

    MathSciNet  MATH  Google Scholar 

  64. AM Senthil Kumar and M Venkatesan (2018). “Task scheduling in a cloud computing environment using HGPSO algorithm,” Clust Comput, pp. 1–7

  65. Shi T, Yang M, Li X, Lei Q, Jiang Y (2016) An energy-efficient scheduling scheme for time-constrained tasks in local mobile clouds. Pervasive Mobile Computing 27:90–105

    Google Scholar 

  66. Su P, Shengping W, Weiwei Z, Shengmei L (2016) Optimization of energy consumption in the Mobile Cloud systems.(Report). KSII Transactions on Internet and Information Systems 10(9):4044

    Google Scholar 

  67. V Sundararaj (2017). Optimized denoising scheme via opposition based Self-adaptive learning PSO algorithm for Wavelet Based ECG Signal Noise Reduction., p. 1

  68. V. Sundararaj (2018). “Optimal task assignment in mobile cloud computing by queue based ant-bee algorithm,” Wirel Pers Commun, pp. 1–25

  69. Sundararaj V, Muthukumar S, Kumar R (2018) An optimal cluster formation based energy efficient dynamic scheduling hybrid MAC protocol for heavy traffic load in wireless sensor networks. Computers and Security 77:277–288

    Google Scholar 

  70. Tang C, Hao M, Wei X, Chen W (2018) Energy-aware task scheduling in mobile cloud computing. Distributed and Parallel Databases 36(3):529–553

    Google Scholar 

  71. C Tang et al. (2018), A Mobile cloud based scheduling strategy for industrial internet of things., pp. 1–1

  72. Wang Z, Gu Z, Yao M, Shao Z (2015) Endurance-aware allocation of data variables on NVM-based scratchpad memory in real-time embedded systems. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 34(10):1600–1612

    Google Scholar 

  73. F Wang, J Liu, and M Chen (2012). “CALMS: Cloud-assisted live media streaming for globalized demands with time/region diversities,” in INFOCOM, 2012 Proceedings IEEE, pp. 199–207: IEEE

  74. Q Wang, T Morgan Steinman, and W Wang (2017). Quality driven modulation rate optimization for energy efficient wireless video relays

  75. Wang J, Tang J, Xue G, Yang D (2017) Towards energy-efficient task scheduling on smartphones in mobile crowd sensing systems. Comput Netw 115:100–109

    Google Scholar 

  76. Wang X, Wang J, Wang X, Chen X (2017) Energy and delay tradeoff for application offloading in Mobile cloud computing. Systems Journal, IEEE 11(2):858–867

    Google Scholar 

  77. F Xia, X Zhao, J Zhang, J Ma, and X Kong (2014), BeeCup: A bio-inspired energy-efficient clustering protocol for mobile learning., pp. 449–460.

  78. Xue S, Zhang Y, Xu X, Xing G, Xiang H, Ji S (2017) Q E T : a QoS-based energy-aware task scheduling method in cloud environment. Clust Comput 20(4):3199–3212

    Google Scholar 

  79. S Yang, D Kwon, H Yi, Y Cho, Y Kwon, and Y Paek (2014). “Techniques to minimize state transfer costs for dynamic execution offloading in mobile cloud computing,” IEEE Transactions on Mobile Computing, no. 11, pp. 2648–2660

  80. Yang C, Li L, You S, Yan B, Du X (2017) Cloud computing-based energy optimization control framework for plug-in hybrid electric bus. Energy 125:11–26

    Google Scholar 

  81. Zeng Z, Truong-Huu T, Veeravalli B, Tham C-K (2016) Operational cost-aware resource provisioning for continuous write applications in cloud-of-clouds. Clust Comput 19(2):601–614

    Google Scholar 

  82. Zhang L, Fu D, Liu J, Ngai EC-H, Zhu W (2017) On energy-efficient offloading in Mobile cloud for real-time video applications. IEEE Transactions on Circuits and Systems for Video Technology 27(1):170–181

    Google Scholar 

  83. Zhang J, Liu W, Zhao W, Ma X, Xu H, Gong X, Liu C, Yu H (2018) A webpage offloading framework for smart devices. Mobile Networks and Applications 23(5):1350–1363

    Google Scholar 

  84. Zhang J, Wang ZJ, Guo S, Yang D, Fang G, Peng C, Guo M (2018) Power consumption analysis of video streaming in 4G LTE networks. Wirel Netw 24(8):3083–3098

    Google Scholar 

  85. Zhang W, Wen Y, Guan K, Kilper D, Luo H, Wu DO (2013) Energy-optimal mobile cloud computing under stochastic wireless channel. IEEE Trans Wirel Commun 12(9):4569–4581

    Google Scholar 

  86. Zhang J, Zhou Z, Li S, Gan L, Zhang X, Qi L, Xu X, Dou W (2018) Hybrid computation offloading for smart home automation in mobile cloud computing. Pers Ubiquit Comput 22(1):121–134

    Google Scholar 

  87. Zhong J, Su J (2010) A real-time moving object tracking system based on visual prediction. Jiqiren 32(4):516–521

    Google Scholar 

  88. Zhou B, Dastjerdi AV, Calheiros RN, Buyya R (2018) An Online Algorithm for Task Offloading in Heterogeneous Mobile Clouds. ACM Transactions on Internet Technology 18(2):23

    Google Scholar 

  89. Zhou B, Dastjerdi A, Calheiros R, Buyya R (2018) An online algorithm for task offloading in heterogeneous Mobile clouds. ACM Transactions on Internet Technology (TOIT) 18(2):1–25

    Google Scholar 

  90. Zhou B, Dastjerdi AV, Calheiros RN, Srirama SN, Buyya R (2017) mCloud: a context-aware offloading framework for heterogeneous mobile cloud. IEEE Trans Serv Comput 10(5):797–810

    Google Scholar 

  91. Zhu W, Zhuang Y, Zhang L (2017) A three-dimensional virtual resource scheduling method for energy saving in cloud computing. Futur Gener Comput Syst 69:66–74

    Google Scholar 

Download references

Author information

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

Authors
  1. Nitesh Parajuli
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Abeer Alsadoon
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. P.W.C. Prasad
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rasha S. Ali
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Omar Hisham Alsadoon
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Abeer Alsadoon.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-020-09516-y

Keywords

Search

Navigation