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Towards Data and Computation Offloading in Mobile Cloud Computing: Taxonomy, Overview, and Future Directions

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Abstract

The rapid developments in the mobile application context illuminate the demand for more resources and processing power at Smart Mobile Devices (SMDs). Mobile Cloud Computing (MCC) enables the SMDs to offload their workloads on the remote cloud servers and benefit from the MCC’s extensive resources to deal with this issue. To this end, numerous offloading schemes are provided in the literature to enhance the SMD's efficiency by offloading their workloads on the nearby cloudlets or remote cloud computing resources. This article puts forward a comprehensive survey and taxonomy of the offloading approaches designed and proposed for MCCs. It first classifies them based on the algorithms which have been used for making the offloading decisions. Then, in each category, it illuminates how the offloading decisions are made to improve application performance and mobile devices' energy efficiency, regarding offloading factors such as deadlines, costs, etc. The evaluation metrics, simulator, offloading type, and architecture of the studied schemes are compared and illuminated in each category. Furthermore, regarding the various properties of the studied offloading methods, the offloading domain's leading issues and challenges are discussed. Lastly, the concluding points are provided, and directions for the subsequent studies in the offloading context are specified.

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References

  1. Debnath, H., Gezzi, G., Corradi,A., Gehani N., Ding, X., Curtmola, R. et al. (2018). Collaborative offloading for distributed mobile-cloud apps," in 2018 6th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud), 2018, pp. 87–94.

  2. Masdari, M., & Jalali, M. (2016). A survey and taxonomy of DoS attacks in cloud computing. Security and Communication Networks, 9, 3724–3751.

    Article  Google Scholar 

  3. Masdari, M., Nabavi, S. S., & Ahmadi, V. (2016). An overview of virtual machine placement schemes in cloud computing. Journal of Network and Computer Applications, 66, 106–127.

    Article  Google Scholar 

  4. Masdari, M., ValiKardan, S., Shahi, Z., & Azar, S. I. (2016). Towards workflow scheduling in cloud computing: a comprehensive analysis. Journal of Network and Computer Applications, 66, 64–82.

    Article  Google Scholar 

  5. Masdari, M., Salehi, F., Jalali, M., & Bidaki, M. (2017). A survey of PSO-based scheduling algorithms in cloud computing. Journal of Network and Systems Management, 25, 122–158.

    Article  Google Scholar 

  6. Junior, W., Oliveira, E., Santos, A., & Dias, K. (2019). A context-sensitive offloading system using machine-learning classification algorithms for mobile cloud environment. Future Generation Computer Systems, 90, 503–520.

    Article  Google Scholar 

  7. Elgendy, I., Zhang, W., Liu, C., & Hsu, C.-H. (2018). An efficient and secured framework for mobile cloud computing. IEEE Transactions on Cloud Computing.

  8. Liu, L., Guo, X., Chang, Z., & Ristaniemi, T. (2018). Joint optimization of energy and delay for computation offloading in cloudlet-assisted mobile cloud computing. Wireless Networks, pp. 1–14.

  9. Beraldi, R., Massri, K., Abderrahmen, M., & Alnuweiri, H. (2013). Towards automating mobile cloud computing offloading decisions: An experimental approach. in ICSNC 2013: The Eighth International Conference on Systems and Networks Communications.

  10. Luzuriaga, J., Cano, J. C., Calafate, C., & Manzoni, P. (2013). Evaluating computation offloading trade-offs in mobile cloud computing: A sample application. In CLOUD COMPUTING 2013, The Fourth International Conference on Cloud Computing, GRIDs, and Virtualization, 2013, pp. 138–143.

  11. Byun, H., Park,B.-K.., & Jeong, Y.-S.(2016). Mobile Agent Oriented Service for Offloading on Mobile Cloud Computing. In Advances in Computer Science and Ubiquitous Computing. Heidelberg, Springer, pp. 920–925.

  12. Yang, S., Kwon, Y., Cho, Y., Yi, H., Kwon, D., Youn, J., et al. (2013). Fast dynamic execution offloading for efficient mobile cloud computing. In Pervasive Computing and Communications (PerCom). IEEE International Conference on, pp 20–28.

  13. Shiraz, M., & Gani, A. (2014). A lightweight active service migration framework for computational offloading in mobile cloud computing. The Journal of Supercomputing, 68, 978–995.

    Article  Google Scholar 

  14. Wu, H. (2018). Multi-objective decision-making for mobile cloud offloading: A survey. IEEE Access, 6, 3962–3976.

    Article  Google Scholar 

  15. Noor, T. H., Zeadally, S., Alfazi, A., & Sheng, Q. Z. (2018). Mobile cloud computing: Challenges and future research directions. Journal of Network and Computer Applications, 115, 70–85.

    Article  Google Scholar 

  16. Jiang, Y., He, J., Li, Q., & Xiao, X. (2014). A dynamic execution offloading model for efficient mobile cloud computing. In Global Communications Conference (GLOBECOM). IEEE, pp 2302–2307.

  17. Zhou, B., Dastjerdi, A. V., Calheiros, R. N., & Buyya, R. (2018). An online algorithm for task offloading in heterogeneous mobile clouds. In ACM Transactions on Internet Technology (TOIT), vol. 18, p. 23, 2018.

  18. Gu, F., Niu, J., Qi, Z., & Atiquzzaman, M. (2018). Partitioning and offloading in smart mobile devices for mobile cloud computing: State of the art and future directions. Journal of Network and Computer Applications.

  19. Enzai, M., Idawati, N., & Tang, M. (2016). A heuristic algorithm for multi-site computation offloading in mobile cloud computing. Procedia Computer Science, 80, 1232–1241.

    Article  Google Scholar 

  20. Rodriguez, C. P., & Souza, G. (2011). Decision-Making Model for Offshore Offloading Operations Based on Probabilistic Risk Assessment. In Vulnerability, Uncertainty, and Risk: Analysis, Modeling, and Management, pp. 385–393.

  21. Fiandrino, C., Kliazovich, D., Bouvry, P., & Zomaya, A. Y. (2015). “Network-assisted offloading for mobile cloud applications,” in Communications (ICC). IEEE International Conference on, 2015, 5833–5838.

  22. Shuja J., Gani, A., Naveed, A., Ahmed, E., & Hsu, C.-H. (2017). Case of ARM emulation optimization for offloading mechanisms in Mobile Cloud Computing.** Future Generation Computer Systems, vol. 76, pp. 407–417

  23. Jia, M., Cao, J., & Yang, L. (2014). “Heuristic offloading of concurrent tasks for computation-intensive applications in mobile cloud computing,” in Computer Communications Workshops (INFOCOM WKSHPS). IEEE Conference on, 2014, 352–357.

  24. Kumar, K., & Lu, Y.-H. (2010). Cloud computing for mobile users: Can offloading computation save energy? Computer, 43, 51–56.

    Article  Google Scholar 

  25. Shiraz, M., Sookhak, M., Gani, A., & Shah, S. A. A. (2015). A study on the critical analysis of computational offloading frameworks for mobile cloud computing. Journal of Network and Computer Applications, 47, 47–60.

    Article  Google Scholar 

  26. Chen, M.-H., Dong, M., & Liang, B. (2016). “Joint offloading decision and resource allocation for mobile cloud with computing access point,” in Acoustics, Speech and Signal Processing (ICASSP). IEEE International Conference on, 2016, 3516–3520.

  27. Wang, X., Wang, J., Wang, X., & Chen, X. (2017). Energy and delay tradeoff for application offloading in mobile cloud computing. IEEE Systems Journal, 11, 858–867.

    Article  Google Scholar 

  28. Chen, M.-H., Liang, B., & Dong, M. (2018). Multi-user multi-task offloading and resource allocation in mobile cloud systems. IEEE Transactions on Wireless Communications, 17, 6790–6805.

    Article  Google Scholar 

  29. Goudarzi, M., Zamani, M., & Toroghi Haghighat, A. (2017). A genetic‐based decision algorithm for multisite computation offloading in mobile cloud computing. International Journal of Communication Systems, 30,, e3241.

  30. Mahmoodi, S. E.., Subbalakshmi, K., & Uma, R. (2019). Classification of Mobile Cloud Offloading. In Spectrum-Aware Mobile Computing. Heidelberg: Springer, 2019, pp. 7–11.

  31. Boukerche, A.., Guan, S., & Grande, R. E. D. (2019). Sustainable Offloading in Mobile Cloud Computing: Algorithmic Design and Implementation. ACM Computing Surveys (CSUR), vol. 52, p. 11, 2019.

  32. La, H. J., & Kim, S. D. (2014).A taxonomy of offloading in mobile cloud computing. In Service-Oriented Computing and Applications (SOCA), 2014 IEEE 7th International Conference on, 2014, pp. 147–153.

  33. Lee, H.-S., & Lee, J.-W. (2018). Task offloading in heterogeneous mobile cloud computing: Modeling, analysis, and cloudlet deployment. IEEE Access, 6, 14908–14925.

    Article  Google Scholar 

  34. Kumar, D., & Sharma, R. (2017). Data synchronization and offloading techniques for energy optimization in mobile cloud computing. In Infocom Technologies and Unmanned Systems (Trends and Future Directions)(ICTUS). International Conference on, 2017, pp 633–638.

  35. Mahmoodi, S. E., Subbalakshmi, K., & Uma, R. (2019). Cognitive Cloud Offloading Using Multiple Radios. In Spectrum-Aware Mobile Computing. Heiddelberg: Springer, 2019, pp. 23–33.

  36. Akherfi, K., Gerndt, M., & Harroud, H. (2018). Mobile cloud computing for computation offloading: Issues and challenges. Applied computing and informatics, 14, 1–16.

    Article  Google Scholar 

  37. Kumari, R., & Kaushal, S. (2017). Application Offloading Using Data Aggregation in Mobile Cloud Computing Environment. In Leadership, Innovation and Entrepreneurship as Driving Forces of the Global Economy. Heidelberg: Springer, 2017, pp. 17–29.

  38. Su, W.-T., & Ng, K. S. (2013). Mobile cloud with smart offloading system. In Communications in China (ICCC). IEEE/CIC International Conference on, 2013, pp 680–685.

  39. Flores, H., & Srirama, S. N. Adaptive code offloading and resource-intensive task delegation for mobile cloud applications. In Proceeding 4th ACM workshop on Mobile Cloud Computing and services (MCS ‘13), pp. 9–16.

  40. Huang, T., Chen, Y., Xue, Ji, H., Xue, Y., Qi, L., et al. (2018). Energy-Efficient Computation Offloading for Multimedia Workflows in Mobile Cloud Computing. In International Conference on Testbeds and Research Infrastructures, 2018, pp. 113–123.

  41. Liwang, M., Wang, J., Gao, Z., Du, X., & Guizani, M. (2019). Game theory based opportunistic computation offloading in cloud-enabled IoV. IEEE Access, 7, 32551–32561.

    Article  Google Scholar 

  42. Magurawalage, C. M. S., Yang, K., Hu, L., & Zhang, J. (2014). Energy-efficient and network-aware offloading algorithm for mobile cloud computing. Computer Networks, 74, 22–33.

    Article  Google Scholar 

  43. Lin, T.-Y., Lin, T.-A., Hsu, C.-H., & King, C.-T. (2013). Context-aware decision engine for mobile cloud offloading. In Wireless Communications and Networking Conference Workshops (WCNCW). IEEE, 2013, pp 111–116.

  44. Shiraz, M., Gani, A., Shamim, A., Khan, S., & Ahmad, R. W. (2015). Energy efficient computational offloading framework for mobile cloud computing. Journal of Grid Computing, 13, 1–18.

    Article  Google Scholar 

  45. Choi, K., Lee, J., Kim, Y., Kang, S., & Han, H. (2015). Feasibility of the computation task offloading to GPGPU-enabled devices in mobile cloud. In Cloud and Autonomic Computing (ICCAC). International Conference on, 2015, pp 244–251.

  46. Tseng, F.-H., Cho, H.-H., Chang, K.-D., Li, J.-C., & Shih, T. K. (2018). Application-oriented offloading in heterogeneous networks for mobile cloud computing. Enterprise Information Systems, 12, 398–413.

    Article  Google Scholar 

  47. Lee, K., & Shin, I. (2015). User mobility model based computation offloading decision for mobile cloud. Journal of Computing Science and Engineering, 9, 155–162.

    Article  Google Scholar 

  48. Kwon, Y., Yi, H., Kwon, D., Yang, S., Cho, Y., & Paek, Y. (2016). Precise execution offloading for applications with dynamic behavior in mobile cloud computing. Pervasive and Mobile Computing, vol. 27, pp. 58–74, 2016/04/01/ 2016.

  49. Junior, W., França, A., Dias, K., & de Souza, J. N. (2017). Supporting mobility-aware computational offloading in mobile cloud environment. Journal of Network and Computer Applications, 94, 93–108.

    Article  Google Scholar 

  50. Khanna, A., Kero, A., & Kumar, D. (2016). Mobile cloud computing architecture for computation offloading. In Next Generation Computing Technologies (NGCT), 2016 2nd International Conference on, 2016, pp. 639–643.

  51. Tao, Y. Zhang, Y., & Ji, Y. (2015). Efficient Computation Offloading Strategies for Mobile Cloud Computing. In Advanced Information Networking and Applications (AINA), 2015 IEEE 29th International Conference on, 2015, pp. 626–633.

  52. Pu, L., Xu, J., Jin, X., & Zhang, J. (2013). “SmartVirtCloud: virtual cloud assisted application offloading execution at mobile devices’’ discretion," in Wireless Communications and Networking Conference (WCNC).” IEEE, 2013, 4398–4403.

  53. Barbera, M. V., Kosta, S., Mei, A., Perta, V. C., & Stefa, J. (2014). “Mobile offloading in the wild: Findings and lessons learned through a real-life experiment with a new cloud-aware system,” in INFOCOM. Proceedings IEEE, 2014, pp 2355–2363.

  54. Goyal, M., & Saini, P. (2016). “A fault-tolerant energy-efficient computational offloading approach with minimal energy and response time in mobile cloud computing,” in Parallel, Distributed and Grid Computing (PDGC). Fourth International Conference on, 2016, pp 44–49.

  55. Chen, S., Wang, Y., & Pedram, M. (2013) A semi-Markovian decision process based control method for offloading tasks from mobile devices to the cloud. In GLOBECOM, 2013, pp. 2885–2890.

  56. Xia, F., Ding, F., Li, J., Kong, X., Yang, L. T., & Ma, J. (2014). Phone2Cloud: Exploiting computation offloading for energy saving on smartphones in mobile cloud computing. Information Systems Frontiers, 16, 95–111.

    Article  Google Scholar 

  57. Mahmoodi, S. E., Uma, R., & Subbalakshmi, K. (2016). Optimal joint scheduling and cloud offloading for mobile applications. IEEE Transactions on Cloud Computing, 2016.

  58. Shi, Y., Chen, S., & Xu, X. (2018). MAGA: a mobility-aware computation offloading decision for distributed mobile cloud computing. IEEE Internet of Things Journal, 5, 164–174.

    Article  Google Scholar 

  59. Meng, T., Wolter, K., Wu, H., & Wang, Q. (2018). A secure and cost-efficient offloading policy for Mobile Cloud Computing against timing attacks. Pervasive and Mobile Computing, vol. 45, pp. 4–18, 2018/04/01/ 2018.

  60. Zhang, W., & Wen, Y. (2018). Energy-efficient task execution for application as a general topology in mobile cloud computing. IEEE Transactions on cloud Computing, 6, 708–719.

    Article  Google Scholar 

  61. Sundararaj, V. (2019). Optimal task assignment in mobile cloud computing by queue based Ant-Bee algorithm. Wireless Personal Communications, 104, 173–197.

    Article  Google Scholar 

  62. Liu, D., Khoukhi, L., & Hafid, A. (2017). “Decentralized data offloading for mobile cloud computing based on game theory,” in. Second International Conference on Fog and Mobile Edge Computing (FMEC), 2017, 20–24.

  63. Chen, M.-H., Liang, B., & Dong, M. (2017). Joint offloading and resource allocation for computation and communication in mobile cloud with computing access point. In INFOCOM 2017-IEEE Conference on Computer Communications, IEEE, 2017, pp. 1–9.

  64. Ma, X., Lin, C., Xiang, X., & Chen, V. (2015). Game-theoretic analysis of computation offloading for cloudlet-based mobile cloud computing. In Proceedings of the 18th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, 2015, pp. 271–278.

  65. Wang, T., Wei, X., Tang, C., & Fan, J. (2018). Efficient multi-tasks scheduling algorithm in mobile cloud computing with time constraints. Peer-to-Peer Networking and Applications, 11, 793–807.

    Article  Google Scholar 

  66. Chen, M.-H., Dong, M., & Liang, B. (2018). Resource Sharing of a Computing Access Point for Multi-user Mobile Cloud Offloading with Delay Constraints. IEEE Transactions on Mobile Computing, 2018.

  67. Cheng, J., Shi, Y., Bai, B., & Chen, W. (2016). Computation offloading in cloud-RAN based mobile cloud computing system. In Communications (ICC). IEEE International Conference on, 2016, pp 1–6.

  68. Ellouze, A., Gagnaire, M., & Haddad, A.(2015). A mobile application offloading algorithm for mobile cloud computing. In Mobile Cloud Computing, Services, and Engineering (MobileCloud), 2015 3rd IEEE International Conference on, 2015, pp. 34–40.

  69. Li, J., Bu, K, Liu, X., & Xiao, B. (2013) Enda: Embracing network inconsistency for dynamic application offloading in mobile cloud computing. In Proceedings of the second ACM SIGCOMM workshop on Mobile cloud computing, 2013, pp. 39–44.

  70. Wu, H., Wang, Q., & Wolter, K. (2013). Tradeoff between performance improvement and energy saving in mobile cloud offloading systems. In Communications Workshops (ICC). IEEE International Conference on, 2013, pp 728–732.

  71. Song, J., Cui, Y., Li, M., Qiu, J., & Buyya, R. (2014). Energy-traffic tradeoff cooperative offloading for mobile cloud computing. In Quality of Service (IWQoS), 2014 IEEE 22nd International Symposium of, 2014, pp. 284–289.

  72. Zhou, Z., Zhang, H., Ye, L., & Du, X. (2016). Cuckoo: flexible compute-intensive task offloading in mobile cloud computing. Wireless Communications and Mobile Computing, 16, 3256–3268.

    Article  Google Scholar 

  73. Deng, S., Huang, L., Taheri, J., & Zomaya, A. Y. (2015). Computation offloading for service workflow in mobile cloud computing. IEEE Transactions on Parallel and Distributed Systems, 26, 3317–3329.

    Article  Google Scholar 

  74. Dhanya, N., & Kousalya, G. (2015).Adaptive and Secure Application Partitioning for Offloading in Mobile Cloud Computing. In International Symposium on Security in Computing and Communication, 2015, pp. 45–53.

  75. Goudarzi, M., Movahedi, Z., & Nazari, M. (2016). Efficient multisite computation offloading for mobile cloud computing. In Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld). Intl IEEE Conferences, 2016, pp 1131–1138.

  76. Chen, X., Jiao, L., Li, W., & Fu, X. (2016). Efficient multi-user computation offloading for mobile-edge cloud computing. IEEE/ACM Transactions on Networking, pp. 2795–2808.

  77. Tianze, L., Muqing, W., & Min, Z. (2016). A stackelberg game based task offloading mechanism for ad-hoc based mobile cloud computing. In Wireless Communication Systems (ISWCS), 2016 International Symposium on, 2016, pp. 618–622.

  78. Kchaou, H., Kechaou, Z., & Alimi, A. M. (2015). Towards an offloading framework based on Big Data analytics in Mobile Cloud Computing Environments. Procedia Computer Science, 53, 292–297.

    Article  Google Scholar 

  79. Haghighi, V., & Moayedian, N. S. (2018). An offloading strategy in mobile cloud computing considering energy and delay constraints. IEEE Access, 6, 11849–11861.

    Article  Google Scholar 

  80. Kuang, Z., Guo, S., Liu, J., & Yang, Y. (2018). A quick-response framework for multi-user computation offloading in mobile cloud computing. Future Generation Computer Systems, 81, 166–176.

    Article  Google Scholar 

  81. Pan, S., Liu, C., Zeng, D., Yao, H., & Qian, Z. (2018). “Fine-Grained Task-Dependency Offloading in Mobile Cloud Computing. In 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications (pp. 977–982). Cloud & Big Data Computing: Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI).

  82. Chen, M.-H., Dong, M., & Liang, B. (2018). Resource sharing of a computing access point for multi-user mobile cloud offloading with delay constraints. IEEE Transactions on Mobile Computing, 17, 2868–2881.

    Article  Google Scholar 

  83. Guo, S., Liu, J., Yang, Y., Xiao, B., & Li, Z. (2019). Energy-efficient dynamic computation offloading and cooperative task scheduling in mobile cloud computing. IEEE Transactions on Mobile Computing, 18, 319–333.

    Article  Google Scholar 

  84. Zhang, Y., He, J., & Guo, S. (2018). Energy-Efficient Dynamic Task Offloading for Energy Harvesting Mobile Cloud Computing. In 2018 IEEE International Conference on Networking, Architecture and Storage (NAS), 2018, pp. 1–4.

  85. Hasan, R., Hossain, M., & Khan, R. (2018). Aura: An incentive-driven ad-hoc IoT cloud framework for proximal mobile computation offloading. Future Generation Computer Systems, 86, 821–835.

    Article  Google Scholar 

  86. Flores, H., Hui, P., Nurmi, P., Lagerspetz, E., Tarkoma, S., Manner, J., et al. (2018). Evidence-aware mobile computational offloading. IEEE Transactions on Mobile Computing, 17, 1834–1850.

    Article  Google Scholar 

  87. Wang, K., Yang, K., & Magurawalage, C. S. (2018). Joint energy minimization and resource allocation in C-RAN with mobile cloud. IEEE Transactions on Cloud Computing, 6, 760–770.

    Article  Google Scholar 

  88. Somula, R., Anilkumar, C., Venkatesh, B., Karrothu, A., Kumar, C.P., & Sasikala, R. (2019). Cloudlet Services for Healthcare Applications in Mobile Cloud Computing. In Proceedings of the 2nd International Conference on Data Engineering and Communication Technology, 2019, pp. 535–543.

  89. Nakahara, F. A., & Beder, D. M. (2018). A context-aware and self-adaptive offloading decision support model for mobile cloud computing system. Journal of Ambient Intelligence and Humanized Computing, 9, 1561–1572.

    Article  Google Scholar 

  90. Mahmoodi, S. E., Subbalakshmi, K., & Uma, R. (2019). Joint Scheduling and Cloud Offloading Using Single Radio. In Spectrum-Aware Mobile Computing. Heidelberg: Springer, 2019, pp. 13–21.

  91. Zhao, J., Li, Q, Gong, Y., & Zhang, K. (2019). Computation Offloading and Resource Allocation for Cloud Assisted Mobile Edge Computing in Vehicular Networks. IEEE Transactions on Vehicular Technology, 2019.

  92. Guo, K., Yang, M., & Zhang, Y. (2018). Computation offloading over a shared communication channel for mobile cloud computing. In IEEE Wireless Communications and Networking Conference (WCNC), 2018, pp 1–6.

  93. Zhou, C., & Tham, C.-K. (2018). Deadline-aware peer-to-peer task offloading in stochastic mobile cloud computing systems. In 2018 15th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), 2018, pp. 1–9.

  94. Jeevan, A. G., & Mohamed, M. M. (2018). DyTO: Dynamic task offloading strategy for mobile cloud computing using surrogate object model. International Journal of Parallel Programming, pp. 1–17, 2018.

  95. Vankadara, S., & Dasari, N. (2019). Energy‐aware dynamic task offloading and collective task execution in mobile cloud computing. International Journal of Communication Systems, p. e3914, 2019.

  96. Qin, A., Cai, C., Wang, Q., Ni, Y., & Zhu, H. (2019). Game Theoretical Multi-user Computation Offloading for Mobile-Edge Cloud Computing. In IEEE Conference on Multimedia Information Processing and Retrieval (MIPR), 2019, 328–332.

  97. Han, D., Chen, W., Bai, B., & Fang, Y. (2019). Offloading Optimization and Bottleneck Analysis for Mobile Cloud Computing. IEEE Transactions on Communications, 2019.

  98. Liu, D., Khoukhi, L., & Hafid, A. (2018). Prediction-based mobile data offloading in mobile cloud computing. IEEE Transactions on Wireless Communications, 17, 4660–4673.

    Article  Google Scholar 

  99. Wu, H., & Huang, D. (2014). Modeling multi-factor multi-site risk-based offloading for mobile cloud computing. In Network and Service Management (CNSM), 2014 10th International Conference on, 2014, pp. 230–235.

  100. Cao, H., & Cai, J. (2018). Distributed multiuser computation offloading for cloudlet-based mobile cloud computing: A game-theoretic machine learning approach. IEEE Transactions on Vehicular Technology, 67, 752–764.

    Article  Google Scholar 

  101. Zheng, J., Cai, Y., Wu, Y., & Shen, X. (2019). Dynamic computation offloading for mobile cloud computing: A stochastic game-theoretic approach. IEEE Transactions on Mobile Computing, 18, 771–786.

    Article  Google Scholar 

  102. Guo, X., Liu, L., Chang, Z., & Ristaniemi, T. (2018). Data offloading and task allocation for cloudlet-assisted ad hoc mobile clouds. Wireless Networks, 24, 79–88.

    Article  Google Scholar 

  103. Ahn, S., Lee, J., Park, S., Newaz, S. S., & Choi, J. K. (2018). Competitive partial computation offloading for maximizing energy efficiency in mobile cloud computing. IEEE Access, 6, 899–912.

    Article  Google Scholar 

  104. Jošilo, S., & Dán, G. (2019). Selfish decentralized computation offloading for mobile cloud computing in dense wireless networks. IEEE Transactions on Mobile Computing, 18, 207–220.

    Article  Google Scholar 

  105. Chen, M.-H., Dong, M., & Liang, B. (2016). Multi-user mobile cloud offloading game with computing access point. In Cloud Networking (Cloudnet), 2016 5th IEEE International Conference on, 2016, pp. 64–69.

  106. Cardellini, V., Personé, V. D. N., Di Valerio, V., Facchinei, F., Grassi, V., Presti, F. L., et al. (2016). A game-theoretic approach to computation offloading in mobile cloud computing. Mathematical Programming, 157, 421–449.

    Article  MathSciNet  MATH  Google Scholar 

  107. Kim, S. (2015). Nested game-based computation offloading scheme for mobile cloud IoT systems. EURASIP Journal on Wireless Communications and Networking, 2015, 229.

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

    Article  Google Scholar 

  109. Zhang, Y., Shi, Y., Shen, F., Yan, F., & Shen, L. (2019). Price-based joint offloading and resource allocation for ad hoc mobile cloud. IEEE Access, 7, 62769–62784.

    Article  Google Scholar 

  110. Li, Y., Liu, J., Li, Q., & Xiao, L. (2015). Mobile cloud offloading for malware detections with learning. In Computer Communications Workshops (INFOCOM WKSHPS). IEEE Conference on, 2015,, pp 197–201.

  111. Zheng, J., Cai, Y., Wu, Y., & Shen, X. (2018). Dynamic computation offloading for mobile cloud computing: A stochastic game-theoretic approach. IEEE Transactions on Mobile Computing, 18, 771–786.

    Article  Google Scholar 

  112. Kuang, Z., Shi, Y., Guo, S., Dan, J., & Xiao, B. (2019). Multi-user offloading game strategy in OFDMA mobile cloud computing system. IEEE Transactions on Vehicular Technology, 68, 12190–12201.

    Article  Google Scholar 

  113. Mahini, H., Rahmani, A. M., & Mousavirad, S. M.. (2020). An evolutionary game approach to IoT task offloading in fog-cloud computing. The Journal of Supercomputing, pp. 1–28, 2020.

  114. Shen, B., Xu, X., Dar, F., Qi, L., Zhang, X., & Dou, W. (2020). Dynamic Task Offloading with Minority Game for Internet of Vehicles in Cloud-Edge Computing. In IEEE International Conference on Web Services (ICWS), 2020, pp 372–379.

  115. Guo, S., Wang, Y., & Wang, H. (2019). Multi-factor based Dynamic Offloading with Coalitional Game in Mobile Cloud Computing. In IEEE/CIC International Conference on Communications in China (ICCC), 2019, pp 863–868.

  116. Wu, H., Wang, Q., & Wolter, K. (2012). Methods of cloud-path selection for offloading in mobile cloud computing systems. In Cloud Computing Technology and Science (CloudCom), 2012 IEEE 4th International Conference on, 2012, pp. 443–448.

  117. Singla, C., & Kaushal, S., (2015). Cloud path selection using fuzzy analytic hierarchy process for offloading in mobile cloud computing. In Recent Advances in Engineering & Computational Sciences (RAECS), 2015 2nd International Conference on, 2015, pp. 1–5.

  118. Shukla,A. K., Pippal, S. K., & Chauhan, S. S. (2019). An empirical evaluation of teaching–learning-based optimization, genetic algorithm and particle swarm optimization," International Journal of Computers and Applications, pp. 1–15, 2019.

  119. Sheikh,. I., & Das, O. (2018). Modeling the effect of parallel execution on multi-site computation offloading in mobile cloud computing, In European Workshop on Performance Engineering, 2018, pp. 219–234.

  120. Guo, S., Wang, Y., Meng, S., & Ma, N. (2018). Delay Optimization for Mobile Cloud Computing Application Offloading in Smart Cities. In International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, 2018, pp. 456–466.

  121. Abd, S. K., Al-Haddad, S. A. R.. Hashim, F., Abdullah, A. B., & Yussof, S. (2017). Energy-aware fault tolerant task offloading of mobile cloud computing. In 2017 5th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud), 2017, pp. 161–164.

  122. Kaushi, N., & Kumar, J. (2014). A computation offloading framework to optimize energy utilisation in mobile cloud computing environment. International Journal of Computer Applications and Information Technology, 5, 61–69.

    Google Scholar 

  123. Roostaei, R., & Movahedi, Z. (2016). Mobility and Context-Aware Offloading in Mobile Cloud Computing. In Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld). Intl IEEE Conferences, 2016,, pp 1144–1148.

  124. Goudarzi, M., Movahedi, Z., & Nazari, M. (2016). Mobile cloud computing: a multisite computation offloading. In Telecommunications (IST), 2016 8th International Symposium on, 2016, pp. 660–665.

  125. Tout, H., Talhi, C., Kara, N., & Mourad, A. (2016). Selective mobile cloud offloading to augment multi-persona performance and viability. IEEE Transactions on Cloud Computing, 2016.

  126. Manukumar, S. T., & Muthuswamy, V. (2019). A Novel Multi-Objective Efficient Offloading Decision Framework in Cloud Computing for Mobile Computing Applications. Wireless Personal Communications, pp. 1–18, 2019.

  127. Wang, Y., Wu, L., Yuan, X., Liu, X., & Li, X. (2019). An Energy-Efficient and Deadline-Aware Task Offloading Strategy Based on Channel Constraint for Mobile Cloud Workflows (May 2019). IEEE Access, 2019.

  128. Alli, A. A., & Alam, M. M. (2019). SecOFF-FCIoT: Machine learning based secure offloading in Fog-Cloud of things for smart city applications. Internet of Things, 7, 100070.

    Article  Google Scholar 

  129. Huang, T., Ruan,F., Xue, S., Qi, L., & Duan, Y. (2019). Computation offloading for multimedia workflows with deadline constraints in cloudlet-based mobile cloud. Wireless Networks, pp. 1–15, 2019.

  130. Adhikari, M., & Gianey, H. (2019). Energy efficient offloading strategy in fog-cloud environment for IoT applications. Internet of Things, 6, 100053.

    Article  Google Scholar 

  131. Xu, X., Liu, Q., Luo, Y., Peng, K., Zhang, X., Meng, S., et al. (2019). A computation offloading method over big data for IoT-enabled cloud-edge computing. Future Generation Computer Systems, 95, 522–533.

    Article  Google Scholar 

  132. Xu, X., Gu, R., Dai, F., Qi, L., & Wan, S. (2019). Multi-objective computation offloading for internet of vehicles in cloud-edge computing. Wireless Networks, pp. 1–19, 2019.

  133. Xu, X., Fu, S., Yuan, Y., Luo, Y., Qi, L., Lin, W., et al. (2019). Multiobjective computation offloading for workflow management in cloudlet-based mobile cloud using NSGA-II. Computational Intelligence, 35, 476–495.

    Article  MathSciNet  Google Scholar 

  134. Chen, S., Wang, Y., & Pedram, M. (2014). Optimal offloading control for a mobile device based on a realistic battery model and semi-Markov decision process. In Proceedings of the 2014 IEEE/ACM International Conference on Computer-Aided Design, 2014, pp. 369–375.

  135. Goudarzi, M., Zamani, M., & Haghighat, A. T. (2017). A fast hybrid multi-site computation offloading for mobile cloud computing. Journal of Network and Computer Applications, 80, 219–231.

    Article  Google Scholar 

  136. Dhanya, N., Kousalya, G., & Balakrishnan, P. (2017). Dynamic mobile cloud offloading prediction based on statistical regression. Journal of Intelligent & Fuzzy Systems, 32, 3081–3089.

    Article  Google Scholar 

  137. Khoda, M. E., Razzaque, M. A., Almogren, A., Hassan, M. M., Alamri, A., & Alelaiwi, A. (2016). Efficient computation offloading decision in mobile cloud computing over 5G network. Mobile Networks and Applications, 21, 777–792.

    Article  Google Scholar 

  138. Xiao, L., Xie, C., Chen, T., Dai, H., & Poor, H. V. (2016). A mobile offloading game against smart attacks. IEEE Access, 4, 2281–2291.

    Article  Google Scholar 

  139. Gao, W., Li, Y., Lu, H., Wang, T., & Liu, C. (2014). On exploiting dynamic execution patterns for workload offloading in mobile cloud applications. In Network Protocols (ICNP), 2014 IEEE 22nd International Conference on, 2014, pp. 1–12.

  140. Wang, Z., Zhong, Z., & Ni, M. (2017). A semi-Markov decision process-based computation offloading strategy in vehicular networks. In Personal, Indoor, and Mobile Radio Communications (PIMRC), 2017 IEEE 28th Annual International Symposium on, 2017, pp. 1–6.

  141. Tong, L., & Gao, W. (2016). Application-aware traffic scheduling for workload offloading in mobile clouds. in INFOCOM 2016-The 35th Annual IEEE International Conference on Computer Communications, IEEE, 2016, pp. 1–9.

  142. Van Le, D., & Tham, C.-K. (2018). Quality of service aware computation offloading in an ad-hoc mobile cloud. IEEE Transactions on Vehicular Technology, 67, 8890–8904.

    Article  Google Scholar 

  143. Chen, X., Wu, C., Zhou, Y., & Zhang, H. (2015). A learning approach for traffic offloading in stochastic heterogeneous cellular networks. In Communications (ICC). IEEE International Conference on, 2015, pp 3347–3351.

  144. Liu, D., Khoukhi, L., & Hafid, A. (2017). Data offloading in mobile cloud computing: A markov decision process approach. In Communications (ICC). IEEE International Conference on, 2017, pp 1–6.

  145. Terefe, M. B., Lee, H., Heo, N., Fox, G. C., & Oh, S. (2016). Energy-efficient multisite offloading policy using Markov decision process for mobile cloud computing. Pervasive and Mobile Computing, 27, 75–89.

    Article  Google Scholar 

  146. Zannat, H., & Hossain, M. S. (2016). A hybrid framework using Markov decision process for mobile code offloading. In Computer and Information Technology (ICCIT), 2016 19th International Conference on, 2016, pp. 31–35.

  147. Truong-Huu, T., Tham, C.-K., & Niyato, D. (2014). To offload or to wait: An opportunistic offloading algorithm for parallel tasks in a mobile cloud. In Cloud Computing Technology and Science (CloudCom), 2014 IEEE 6th International Conference on, 2014, pp. 182–189.

  148. Gao, Z., Hao, W., Zhang, R., & Yang, S. (2020). Markov decision process-based computation offloading algorithm and resource allocation in time constraint for mobile cloud computing. IET Communications, 14, 2068–2078.

    Article  Google Scholar 

  149. Zalat, M. S., Darwish, S. M., & Madbouly, M. M. (2020). An Effective Offloading Model Based on Genetic Markov Process for Cloud Mobile Applications. In International Conference on Advanced Intelligent Systems and Informatics, 2020, pp. 38–50.

  150. Wang, X., Xu, W., & Jin, Z. (2017). A hidden Markov model based dynamic scheduling approach for mobile cloud telemonitoring. In Biomedical & Health Informatics (BHI). IEEE EMBS International Conference on, 2017,pp 273–276.

  151. Wu, H., Sun, Y., & Wolter, K. (2015). Analysis of the energy-response time tradeoff for delayed mobile cloud offloading. ACM SIGMETRICS Performance Evaluation Review, 43, 33–35.

    Article  Google Scholar 

  152. Wu, H., Knottenbelt, W., & Wolter, K. (2015). Analysis of the energy-response time tradeoff for mobile cloud offloading using combined metrics. In Teletraffic Congress (ITC 27), 2015 27th International, 2015, pp. 134–142.

  153. Hyytiä, E., Spyropoulos, T., & Ott, J. (2013). Optimizing offloading strategies in mobile cloud computing. Cryptanalyst, 2013.

  154. Wu, H., Sun, Y., & Wolter, K. (2018). Energy-efficient decision making for mobile cloud offloading. IEEE Transactions on Cloud Computing, 2018.

  155. Zhang, J., Zhou, Z., Li, S., Gan, L., Zhang, X., Qi, L., et al. (2018). Hybrid computation offloading for smart home automation in mobile cloud computing. Personal and Ubiquitous Computing, 22, 121–134.

    Article  Google Scholar 

  156. Wu, H. (2018). Performance Modeling of Delayed Offloading in Mobile Wireless Environments with Failures," IEEE Communications Letters, 2018.

  157. Wang, J., Peng, J., Wei, Y., Liu, D., & Fu, J. (2017). Adaptive application offloading decision and transmission scheduling for mobile cloud computing. China Communications, 14, 169–181.

    Article  Google Scholar 

  158. Salehan, A., Deldari, H., & Abrishami, S. (2019). An online context-aware mechanism for computation offloading in ubiquitous and mobile cloud environments. The Journal of Supercomputing, pp. 1–41, 2019.

  159. Mazouzi, H., Boussetta, K., & Achir, N. (2019). Maximizing mobiles energy saving through tasks optimal offloading placement in two-tier cloud: A theoretical and an experimental study. Computer Communications, 144, 132–148.

    Article  Google Scholar 

  160. Kumari, R., Kaushal, S., & Chilamkurti, N. (2018). Energy conscious multi-site computation offloading for mobile cloud computing. Soft Computing, 22, 6751–6764.

    Article  Google Scholar 

  161. Balakrishnan, P., & Tham, C.-K. (2013). Energy-efficient mapping and scheduling of task interaction graphs for code offloading in mobile cloud computing. In Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing, 2013, pp. 34–41.

  162. Guo, S., Xiao, B., Yang, Y., & Yang, Y. (2016). Energy-efficient dynamic offloading and resource scheduling in mobile cloud computing. In INFOCOM 2016-The 35th Annual IEEE International Conference on Computer Communications, IEEE, 2016, pp. 1–9.

  163. Singh, A., & Madan, N. (2016). A Region Based Offloading Mechanism in Mobile Cloud Computing Environment, 2016.

  164. Farra, N., Raffa, G., Nachman, L., & Hajj, H. (2011). Energy-efficient mobile gesture recognition with computation offloading. In Energy Aware Computing (ICEAC). International Conference on, 2011, pp 1–6.

  165. Kero, A., Khanna, A., Kumar, D., & Agarwal, A. (2019). An adaptive approach towards computation offloading for mobile cloud computing. International Journal of Information Technology and Web Engineering (IJITWE), 14, 52–73.

    Article  Google Scholar 

  166. Dwivedi, S., Vardhan, M., & Tripathi, S. (2020). An Effect of Chaos Grasshopper Optimization Algorithm for Protection of Network Infrastructure. Computer Networks, p. 107251, 2020.

  167. Dwivedi, S., Vardhan, M., & Tripathi, S. (2020). Defense against distributed DoS attack detection by using intelligent evolutionary algorithm. International Journal of Computers and Applications, pp. 1–11, 2020.

  168. Dwivedi, S., Vardhan, M., & Tripathi, S. (2020). Incorporating evolutionary computation for securing wireless network against cyberthreats. The Journal of Supercomputing, pp. 1–38, 2020.

  169. Shukla, A. K., & Singh, P. (2019). Building an effective approach toward intrusion detection using ensemble feature selection. International Journal of Information Security and Privacy (IJISP), 13, 31–47.

    Article  Google Scholar 

  170. Eom, H., Juste, P. S., Figueiredo, R., Tickoo, O., Illikkal, R., & Iyer, R. (2013). Opencl-based remote offloading framework for trusted mobile cloud computing. In Parallel and Distributed Systems (ICPADS). International Conference on, 2013, pp 240–248.

  171. Fadaraliki, D. I.. & Rajendran, S. (2015). Secure mobile cloud computation offloading node privacy and security.

  172. Khayyat, M., Elgendy, I. A., Muthanna, A., Alshahrani, A. S., Alharbi, S., & Koucheryavy, A. (2020). Advanced deep learning-based computational offloading for multilevel vehicular edge-cloud computing networks. IEEE Access, 8, 137052–137062.

    Article  Google Scholar 

  173. Krishna, P. V., Misra, S., Nagaraju, D., Saritha, V., & Obaidat, M. S. (2016). Learning automata based decision making algorithm for task offloading in mobile cloud. In Computer, Information and Telecommunication Systems (CITS). International Conference on, 2016, pp 1–6.

  174. Misra, S., Wolfinger, B. E., Achuthananda, M., Chakraborty, T., Das, S. N., & Das, S. (2019). Auction-based optimal task offloading in Mobile cloud computing. IEEE Systems Journal, 13, 2978–2985.

    Article  Google Scholar 

  175. Zhou, B., Srirama, S. N., & Buyya, R. (2019). An auction-based incentive mechanism for heterogeneous mobile clouds. Journal of Systems and Software, 152, 151–164.

    Article  Google Scholar 

  176. Zhang, D., Tan, L., Ren, J., Awad, M. K., Zhang, S., Zhang, Y., et al. (2019). Near-optimal and truthful online auction for computation offloading in green edge-computing systems. IEEE Transactions on Mobile Computing, 19, 880–893.

    Article  Google Scholar 

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Authors and Affiliations

  1. Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin, 64002, Taiwan, R.O.C.

    Amir Masoud Rahmani

  2. Department of computer science, Khazar University, Baku, Azerbaijan

    Amir Masoud Rahmani

  3. Department of Information Technology, Lebanese French University, Kurdistan Region, Erbil, Iraq

    Mokhtar Mohammadi

  4. Department of Communication and Computer Engineering, Cihan university-Erbil, Kurdistan Region, Erbil, Iraq

    Adil Hussein Mohammed

  5. Computer Department, College of Science, University of Halabja, Halabja, Iraq

    Sarkhel H. Taher Karim

  6. Technical College of Informatics, Computer Networks Department, Sulaimani Polytechnic University, Sulaymaniyah, Iraq

    Sarkhel H. Taher Karim

  7. Science Department: Information Technology, Tishk International University, Erbil, Iraq

    Mohammed Kamal Majeed

  8. Department of computer science, Urmia Branch, Islamic Azad University, Urmia, Iran

    Mohammed Masdari

  9. Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam

    Mehdi Hosseinzadeh

  10. Computer Science, University of Human Development, Sulaimaniyah, Iraq

    Mehdi Hosseinzadeh

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Rahmani, A.M., Mohammadi, M., Mohammed, A.H. et al. Towards Data and Computation Offloading in Mobile Cloud Computing: Taxonomy, Overview, and Future Directions. Wireless Pers Commun 119, 147–185 (2021). https://doi.org/10.1007/s11277-021-08202-y

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