{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T19:25:31Z","timestamp":1742930731465,"version":"3.40.3"},"publisher-location":"Cham","reference-count":65,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031080371"},{"type":"electronic","value":"9783031080388"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-08038-8_2","type":"book-chapter","created":{"date-parts":[[2022,10,6]],"date-time":"2022-10-06T09:02:40Z","timestamp":1665046960000},"page":"21-46","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Optimization of Green Mobile Cloud Computing"],"prefix":"10.1007","author":[{"given":"Amir Hossein Jafari","family":"Pozveh","sequence":"first","affiliation":[]},{"given":"Hadi Shahriar","family":"Shahhoseini","sequence":"additional","affiliation":[]},{"given":"Faezeh Arshadi","family":"Soufyani","sequence":"additional","affiliation":[]},{"given":"Morteza","family":"Taheribakhsh","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,10,7]]},"reference":[{"key":"2_CR1","volume-title":"2020 25th International Computer Conference, Computer Society of Iran (CSICC)","author":"M Taheribakhsh","year":"2020","unstructured":"Taheribakhsh, M., et al.: 5G implementation: major issues and challenges. In: 2020 25th International Computer Conference, Computer Society of Iran (CSICC). IEEE (2020)"},{"key":"2_CR2","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1007\/978-3-030-69893-5_6","volume-title":"Mobile Edge Computing","author":"AJ Pozveh","year":"2021","unstructured":"Pozveh, A.J., Shahhoseini, H.S.: IoT integration with MEC. In: Mobile Edge Computing, pp. 111\u2013144. Springer (2021)"},{"issue":"5","key":"2_CR3","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1109\/MWC.001.1900495","volume":"27","author":"J Li","year":"2020","unstructured":"Li, J., Dai, M., Su, Z.: Energy-aware task offloading in the Internet of Things. IEEE Wirel. Commun. 27(5), 112\u2013117 (2020)","journal-title":"IEEE Wirel. Commun."},{"key":"2_CR4","doi-asserted-by":"crossref","unstructured":"Xu, Z., et al.: Energy-aware collaborative service caching in a 5G-enabled MEC with uncertain payoffs. IEEE Trans. Commun. (2021)","DOI":"10.1109\/TCOMM.2021.3125034"},{"issue":"5","key":"2_CR5","doi-asserted-by":"publisher","first-page":"1061","DOI":"10.1109\/LWC.2021.3057114","volume":"10","author":"Y-J Seo","year":"2021","unstructured":"Seo, Y.-J., et al.: A novel joint mobile cache and power management scheme for energy-efficient mobile augmented reality service in mobile edge computing. IEEE Wirel. Commun. Lett. 10(5), 1061\u20131065 (2021)","journal-title":"IEEE Wirel. Commun. Lett."},{"key":"2_CR6","doi-asserted-by":"publisher","first-page":"39390","DOI":"10.1109\/ACCESS.2019.2905589","volume":"7","author":"W Li","year":"2019","unstructured":"Li, W., et al.: A reinforcement learning based smart cache strategy for cache-aided ultra-dense network. IEEE Access. 7, 39390\u201339401 (2019)","journal-title":"IEEE Access"},{"issue":"9","key":"2_CR7","doi-asserted-by":"publisher","first-page":"8157","DOI":"10.1109\/JIOT.2020.2980954","volume":"7","author":"H Wu","year":"2020","unstructured":"Wu, H., et al.: Toward energy-aware caching for intelligent connected vehicles. IEEE Internet Things J. 7(9), 8157\u20138166 (2020)","journal-title":"IEEE Internet Things J."},{"key":"2_CR8","unstructured":"Kabir, A., et al.: Energy-aware caching and collaboration for green communication systems. Acta Montan. Slovaca. 26(1) (2021)"},{"key":"2_CR9","volume-title":"2020 12th International Conference on Communication Software and Networks (ICCSN)","author":"Q Li","year":"2020","unstructured":"Li, Q., et al.: A green DDPG reinforcement learning-based framework for content caching. In: 2020 12th International Conference on Communication Software and Networks (ICCSN). IEEE (2020)"},{"key":"2_CR10","doi-asserted-by":"crossref","unstructured":"Rahmani, A.M., et al.: Towards data and computation offloading in mobile cloud computing: taxonomy, overview, and future directions. Wirel. Pers. Commun., 1\u201339 (2021)","DOI":"10.1007\/s11277-021-08202-y"},{"issue":"5","key":"2_CR11","doi-asserted-by":"publisher","first-page":"4887","DOI":"10.1007\/s11227-020-03476-8","volume":"77","author":"F Jazayeri","year":"2021","unstructured":"Jazayeri, F., Shahidinejad, A., Ghobaei-Arani, M.: A latency-aware and energy-efficient computation offloading in mobile fog computing: a hidden Markov model-based approach. J. Supercomput. 77(5), 4887\u20134916 (2021)","journal-title":"J. Supercomput."},{"key":"2_CR12","volume-title":"Proceedings of 6th International Conference on Recent Trends in Computing: ICRTC 2020","author":"K Anjaria","year":"2020","unstructured":"Anjaria, K., Patel, N.: Attainment of green computing in cloudlet-based mobile cloud computing model using squirrel search algorithm. In: Proceedings of 6th International Conference on Recent Trends in Computing: ICRTC 2020. Springer (2020)"},{"issue":"1","key":"2_CR13","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1016\/j.dcan.2018.10.003","volume":"5","author":"L Huang","year":"2019","unstructured":"Huang, L., et al.: Deep reinforcement learning-based joint task offloading and bandwidth allocation for multi-user mobile edge computing. Digit. Commun. Netw. 5(1), 10\u201317 (2019)","journal-title":"Digit. Commun. Netw."},{"key":"2_CR14","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1016\/j.jpdc.2018.03.004","volume":"132","author":"R Mahmud","year":"2019","unstructured":"Mahmud, R., et al.: Quality of Experience (QoE)-aware placement of applications in Fog computing environments. J. Parallel Distrib. Comput. 132, 190\u2013203 (2019)","journal-title":"J. Parallel Distrib. Comput."},{"key":"2_CR15","volume-title":"2018 10th International Conference on Wireless Communications and Signal Processing (WCSP)","author":"S Wu","year":"2018","unstructured":"Wu, S., et al.: An efficient offloading algorithm based on support vector machine for mobile edge computing in vehicular networks. In: 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP). IEEE (2018)"},{"key":"2_CR16","doi-asserted-by":"publisher","first-page":"63840","DOI":"10.1109\/ACCESS.2020.2982669","volume":"8","author":"MIA Zahed","year":"2020","unstructured":"Zahed, M.I.A., et al.: Green and secure computation offloading for cache-enabled IoT networks. IEEE Access. 8, 63840\u201363855 (2020)","journal-title":"IEEE Access"},{"issue":"13","key":"2_CR17","doi-asserted-by":"publisher","first-page":"4527","DOI":"10.3390\/s21134527","volume":"21","author":"A Ali","year":"2021","unstructured":"Ali, A., et al.: An efficient dynamic-decision based task scheduler for task offloading optimization and energy management in mobile cloud computing. Sensors. 21(13), 4527 (2021)","journal-title":"Sensors"},{"key":"2_CR18","volume-title":"International Conference on Simulation Tools and Techniques","author":"N Xing","year":"2020","unstructured":"Xing, N., et al.: A network energy efficiency measurement method for cloud-edge communication networks. In: International Conference on Simulation Tools and Techniques. Springer (2020)"},{"key":"2_CR19","doi-asserted-by":"publisher","first-page":"134742","DOI":"10.1109\/ACCESS.2019.2942052","volume":"7","author":"S Pan","year":"2019","unstructured":"Pan, S., et al.: Dependency-aware computation offloading in mobile edge computing: a reinforcement learning approach. IEEE Access. 7, 134742\u2013134753 (2019)","journal-title":"IEEE Access"},{"key":"2_CR20","volume":"31","author":"Y Hao","year":"2021","unstructured":"Hao, Y., et al.: Energy-aware offloading based on priority in mobile cloud computing. Sustain. Comput. Inform. Syst. 31, 100563 (2021)","journal-title":"Sustain. Comput. Inform. Syst."},{"issue":"1","key":"2_CR21","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1007\/s10844-018-0527-2","volume":"54","author":"LO Colombo-Mendoza","year":"2020","unstructured":"Colombo-Mendoza, L.O., et al.: A knowledge-based multi-criteria collaborative filtering approach for discovering services in mobile cloud computing platforms. J. Intell. Inf. Syst. 54(1), 179\u2013203 (2020)","journal-title":"J. Intell. Inf. Syst."},{"key":"2_CR22","doi-asserted-by":"crossref","unstructured":"Aliyu, A., et al.: Mobile cloud computing: taxonomy and challenges. J. Comput. Netw. Commun. 2020 (2020)","DOI":"10.1155\/2020\/2547921"},{"issue":"18","key":"2_CR23","doi-asserted-by":"crossref","DOI":"10.1002\/dac.4636","volume":"33","author":"J Kumar","year":"2020","unstructured":"Kumar, J., Rani, A., Dhurandher, S.K.: Convergence of user and service provider perspectives in mobile cloud computing environment: taxonomy and challenges. Int. J. Commun. Syst. 33(18), e4636 (2020)","journal-title":"Int. J. Commun. Syst."},{"key":"2_CR24","doi-asserted-by":"crossref","unstructured":"Nugroho, K., et al.: Mobile cloud learning based on user acceptance using DeLone and McLean model for higher education. Int. J. Adv. Comput. Sci. Appl. 11(1) (2020)","DOI":"10.14569\/IJACSA.2020.0110122"},{"key":"2_CR25","doi-asserted-by":"crossref","unstructured":"Zhu, X., Zhou, M.C.: Multi-objective optimized cloudlet deployment and task offloading for Mobile edge computing. IEEE Internet Things J. (2021)","DOI":"10.1109\/JIOT.2021.3073113"},{"key":"2_CR26","doi-asserted-by":"crossref","unstructured":"Liu, Q., et al.: Multi-objective resource allocation in mobile edge computing using PAES for Internet of Things. Wirel. Netw, 1\u201313 (2020)","DOI":"10.1007\/s11276-020-02409-w"},{"key":"2_CR27","volume-title":"International Conference on Advanced Intelligent Systems and Informatics","author":"MS Zalat","year":"2020","unstructured":"Zalat, M.S., Darwish, S.M., Madbouly, M.M.: An effective offloading model based on genetic Markov process for cloud mobile applications. In: International Conference on Advanced Intelligent Systems and Informatics. Springer (2020)"},{"key":"2_CR28","volume-title":"Energy-Delay Tradeoff for Virtual Machine Placement in Virtualized Multi-Access Edge Computing: A Two-Sided Matching Approach","author":"L Zhang","year":"2021","unstructured":"Zhang, L., et al., Energy-Delay Tradeoff for Virtual Machine Placement in Virtualized Multi-Access Edge Computing: A Two-Sided Matching Approach 2021"},{"issue":"1","key":"2_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13638-019-1526-x","volume":"2019","author":"K Peng","year":"2019","unstructured":"Peng, K., et al.: An energy-and cost-aware computation offloading method for workflow applications in mobile edge computing. EURASIP J. Wirel. Commun. Netw. 2019(1), 1\u201315 (2019)","journal-title":"EURASIP J. Wirel. Commun. Netw."},{"key":"2_CR30","unstructured":"Power and performance efficient SDN-enabled fog architecture. arxiv (2021)"},{"issue":"5","key":"2_CR31","doi-asserted-by":"publisher","first-page":"734","DOI":"10.3390\/sym13050734","volume":"13","author":"A Alomari","year":"2021","unstructured":"Alomari, A., et al.: Resource management in SDN-based cloud and SDN-based fog computing: taxonomy study. Symmetry. 13(5), 734 (2021)","journal-title":"Symmetry"},{"key":"2_CR32","volume":"30","author":"A Singh","year":"2021","unstructured":"Singh, A., Aujla, G.S., Bali, R.S.: Container-based load balancing for energy efficiency in software-defined edge computing environment. Sustain. Comput. Inform. Syst. 30, 100463 (2021)","journal-title":"Sustain. Comput. Inform. Syst."},{"key":"2_CR33","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1016\/j.apenergy.2017.10.106","volume":"210","author":"A Ehsan","year":"2018","unstructured":"Ehsan, A., Yang, Q.: Optimal integration and planning of renewable distributed generation in the power distribution networks: a review of analytical techniques. Appl. Energy. 210, 44\u201359 (2018)","journal-title":"Appl. Energy"},{"issue":"9","key":"2_CR34","doi-asserted-by":"publisher","first-page":"3315","DOI":"10.3390\/su10093315","volume":"10","author":"X Jianzhong","year":"2018","unstructured":"Jianzhong, X., Assenova, A., Erokhin, V.: Renewable energy and sustainable development in a resource-abundant country: challenges of wind power generation in Kazakhstan. Sustainability. 10(9), 3315 (2018)","journal-title":"Sustainability"},{"key":"2_CR35","doi-asserted-by":"publisher","first-page":"212709","DOI":"10.1109\/ACCESS.2020.3040958","volume":"8","author":"MIA Zahed","year":"2020","unstructured":"Zahed, M.I.A., et al.: A review on green caching strategies for next generation communication networks. IEEE Access. 8, 212709\u2013212737 (2020)","journal-title":"IEEE Access"},{"issue":"1","key":"2_CR36","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1109\/MNET.2014.6724106","volume":"28","author":"W Deng","year":"2014","unstructured":"Deng, W., et al.: Harnessing renewable energy in cloud datacenters: opportunities and challenges. IEEE Netw. 28(1), 48\u201355 (2014)","journal-title":"IEEE Netw."},{"key":"2_CR37","volume-title":"2019 IEEE Global Communications Conference (GLOBECOM)","author":"MS Munir","year":"2019","unstructured":"Munir, M.S., et al.: A multi-agent system toward the green edge computing with microgrid. In: 2019 IEEE Global Communications Conference (GLOBECOM). IEEE (2019)"},{"key":"2_CR38","doi-asserted-by":"crossref","unstructured":"Perin, G., et al.: EASE: energy-aware job scheduling for vehicular Edge networks with renewable energy resources. arXiv preprint arXiv, 2111.02186 (2021)","DOI":"10.1109\/TGCN.2022.3199171"},{"key":"2_CR39","doi-asserted-by":"publisher","first-page":"82672","DOI":"10.1109\/ACCESS.2019.2924085","volume":"7","author":"MIK Khalil","year":"2019","unstructured":"Khalil, M.I.K., Ahmad, I., Almazroi, A.A.: Energy efficient indivisible workload distribution in geographically distributed data centers. IEEE Access. 7, 82672\u201382680 (2019)","journal-title":"IEEE Access"},{"key":"2_CR40","volume-title":"ICC 2019-2019 IEEE International Conference on Communications (ICC)","author":"C Yang","year":"2019","unstructured":"Yang, C., et al.: Efficient task offloading and resource allocation for edge computing-based smart grid networks. In: ICC 2019-2019 IEEE International Conference on Communications (ICC). IEEE (2019)"},{"issue":"9","key":"2_CR41","doi-asserted-by":"publisher","first-page":"8419","DOI":"10.1109\/JIOT.2020.2992522","volume":"7","author":"Y Chen","year":"2020","unstructured":"Chen, Y., et al.: Joint task scheduling and energy management for heterogeneous mobile edge computing with hybrid energy supply. IEEE Internet Things J. 7(9), 8419\u20138429 (2020)","journal-title":"IEEE Internet Things J."},{"key":"2_CR42","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2021.108100","volume":"192","author":"G Vallero","year":"2021","unstructured":"Vallero, G., et al.: Base Station switching and edge caching optimisation in high energy-efficiency wireless access network. Comput. Netw. 192, 108100 (2021)","journal-title":"Comput. Netw."},{"key":"2_CR43","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1016\/j.future.2019.11.041","volume":"105","author":"MIA Zahed","year":"2020","unstructured":"Zahed, M.I.A., et al.: Proactive content caching using surplus renewable energy: a win\u2013win solution for both network service and energy providers. Futur. Gener. Comput. Syst. 105, 210\u2013221 (2020)","journal-title":"Futur. Gener. Comput. Syst."},{"issue":"11","key":"2_CR44","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1109\/MCOM.2017.1700129","volume":"55","author":"S Zhang","year":"2017","unstructured":"Zhang, S., et al.: Self-sustaining caching stations: toward cost-effective 5G-enabled vehicular networks. IEEE Commun. Mag. 55(11), 202\u2013208 (2017)","journal-title":"IEEE Commun. Mag."},{"issue":"10","key":"2_CR45","doi-asserted-by":"publisher","first-page":"2819","DOI":"10.1109\/TMC.2017.2652464","volume":"16","author":"T Han","year":"2017","unstructured":"Han, T., Ansari, N.: Network utility aware traffic load balancing in backhaul-constrained cache-enabled small cell networks with hybrid power supplies. IEEE Trans. Mob. Comput. 16(10), 2819\u20132832 (2017)","journal-title":"IEEE Trans. Mob. Comput."},{"key":"2_CR46","volume-title":"2017 9th International Conference on Wireless Communications and Signal Processing (WCSP)","author":"D Xu","year":"2017","unstructured":"Xu, D., et al.: Joint caching and sleep-active scheduling for energy-harvesting based small cells. In: 2017 9th International Conference on Wireless Communications and Signal Processing (WCSP). IEEE (2017)"},{"issue":"1","key":"2_CR47","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1109\/TNSM.2019.2944402","volume":"17","author":"MIA Zahed","year":"2019","unstructured":"Zahed, M.I.A., et al.: A cooperative green content caching technique for next generation communication networks. IEEE Trans. Netw. Serv. Manag. 17(1), 375\u2013388 (2019)","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"key":"2_CR48","doi-asserted-by":"crossref","unstructured":"Zhao, F., et al.: Dynamic offloading and resource scheduling for mobile edge computing with energy harvesting devices. IEEE Trans. Netw. Serv. Manag. (2021)","DOI":"10.1109\/TNSM.2021.3069993"},{"issue":"6","key":"2_CR49","doi-asserted-by":"publisher","first-page":"4668","DOI":"10.1109\/JIOT.2020.3027506","volume":"8","author":"H Xu","year":"2020","unstructured":"Xu, H., et al.: Priority-aware reinforcement-learning-based integrated design of networking and control for industrial Internet of Things. IEEE Internet Things J. 8(6), 4668\u20134680 (2020)","journal-title":"IEEE Internet Things J."},{"key":"2_CR50","volume-title":"2015 IEEE International Conference on Communication Workshop (ICCW)","author":"Y Li","year":"2015","unstructured":"Li, Y., et al.: Smart duty cycle control with reinforcement learning for machine to machine communications. In: 2015 IEEE International Conference on Communication Workshop (ICCW). IEEE (2015)"},{"key":"2_CR51","unstructured":"AI based service management for 6G green communications. arXiv (2021)"},{"issue":"2","key":"2_CR52","first-page":"70","volume":"66","author":"AH Jafari","year":"2015","unstructured":"Jafari, A.H., Shahhoseini, H.S.: A reinforcement routing algorithm with access selection in the multi-hop multi-Interface networks. J. Electr. Eng. 66(2), 70 (2015)","journal-title":"J. Electr. Eng."},{"key":"2_CR53","doi-asserted-by":"crossref","unstructured":"Suryadevara, N.K.: Energy and latency reductions at the fog gateway using a machine learning classifier. Sustain. Comput. Inform. Syst., 100582 (2021)","DOI":"10.1016\/j.suscom.2021.100582"},{"issue":"1","key":"2_CR54","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1007\/s10845-020-01570-5","volume":"32","author":"C Xu","year":"2021","unstructured":"Xu, C., Zhu, G.: Intelligent manufacturing lie group machine learning: real-time and efficient inspection system based on fog computing. J. Intell. Manuf. 32(1), 237\u2013249 (2021)","journal-title":"J. Intell. Manuf."},{"key":"2_CR55","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/j.pmcj.2019.05.001","volume":"57","author":"P Nawrocki","year":"2019","unstructured":"Nawrocki, P., Sniezynski, B., Slojewski, H.: Adaptable mobile cloud computing environment with code transfer based on machine learning. Pervasive Mobile Comput. 57, 49\u201363 (2019)","journal-title":"Pervasive Mobile Comput."},{"key":"2_CR56","doi-asserted-by":"publisher","DOI":"10.21203\/rs.3.rs-372831\/v1","volume-title":"Unsupervised Deep Learning for Binary Offloading in Mobile Edge Computation Network","author":"X Chen","year":"2021","unstructured":"Chen, X., et al., Unsupervised Deep Learning for Binary Offloading in Mobile Edge Computation Network. 2021"},{"issue":"3","key":"2_CR57","doi-asserted-by":"publisher","first-page":"1839","DOI":"10.1007\/s11277-020-07657-9","volume":"115","author":"P Nawrocki","year":"2020","unstructured":"Nawrocki, P., Sniezynski, B.: Adaptive context-aware energy optimization for services on mobile devices with use of machine learning. Wirel. Pers. Commun. 115(3), 1839\u20131867 (2020)","journal-title":"Wirel. Pers. Commun."},{"key":"2_CR58","volume-title":"2020 20th IEEE\/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID)","author":"P Nawrocki","year":"2020","unstructured":"Nawrocki, P., et al.: Adaptive context-aware energy optimization for services on mobile devices with use of machine learning considering security aspects. In: 2020 20th IEEE\/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID). IEEE (2020)"},{"key":"2_CR59","doi-asserted-by":"crossref","unstructured":"Kilcioglu, E., et al.: An energy-efficient fine-grained deep neural network partitioning scheme for wireless collaborative fog computing. IEEE Access. (2021)","DOI":"10.1109\/ACCESS.2021.3084689"},{"key":"2_CR60","unstructured":"Eshratifar, A.E., Abrishami, M.S., Pedram, M.: JointDNN: an efficient training and inference engine for intelligent mobile cloud computing services. IEEE Trans. Mob. Comput. (2019)"},{"key":"2_CR61","doi-asserted-by":"publisher","first-page":"149623","DOI":"10.1109\/ACCESS.2019.2947053","volume":"7","author":"Z Ali","year":"2019","unstructured":"Ali, Z., et al.: A deep learning approach for energy efficient computational offloading in mobile edge computing. IEEE Access. 7, 149623\u2013149633 (2019)","journal-title":"IEEE Access"},{"key":"2_CR62","doi-asserted-by":"crossref","unstructured":"Ale, L., et al.: Delay-aware and energy-efficient computation offloading in mobile edge computing using deep reinforcement learning. IEEE Trans. Cognit. Commun. Netw. (2021)","DOI":"10.1109\/TCCN.2021.3066619"},{"key":"2_CR63","doi-asserted-by":"crossref","unstructured":"Bi, S., et al.: Lyapunov-guided deep reinforcement learning for stable online computation offloading in mobile-edge computing networks. IEEE Trans. Wirel. Commun. (2021)","DOI":"10.1109\/TWC.2021.3085319"},{"key":"2_CR64","doi-asserted-by":"crossref","unstructured":"Wang, L., et al.: Deep reinforcement learning based dynamic trajectory control for UAV-assisted mobile edge computing. IEEE Trans. Mob. Comput. (2021)","DOI":"10.1109\/TCCN.2020.3027695"},{"issue":"5","key":"2_CR65","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1109\/MNET.001.1900561","volume":"34","author":"S Gong","year":"2020","unstructured":"Gong, S., et al.: Deep reinforcement learning for backscatter-aided data offloading in mobile edge computing. IEEE Netw. 34(5), 106\u2013113 (2020)","journal-title":"IEEE Netw."}],"container-title":["Green Mobile Cloud Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-08038-8_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,28]],"date-time":"2023-11-28T14:27:40Z","timestamp":1701181660000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-08038-8_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031080371","9783031080388"],"references-count":65,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-08038-8_2","relation":{},"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"7 October 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}