Auswahl der wissenschaftlichen Literatur zum Thema „Edge server placement“
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Zeitschriftenartikel zum Thema "Edge server placement"
Ma, Rong. „Edge Server Placement for Service Offloading in Internet of Things“. Security and Communication Networks 2021 (30.09.2021): 1–16. http://dx.doi.org/10.1155/2021/5109163.
Der volle Inhalt der QuelleLuo, Fei, Shuai Zheng, Weichao Ding, Joel Fuentes und Yong Li. „An Edge Server Placement Method Based on Reinforcement Learning“. Entropy 24, Nr. 3 (23.02.2022): 317. http://dx.doi.org/10.3390/e24030317.
Der volle Inhalt der QuelleZhang, Qiyang, Shangguang Wang, Ao Zhou und Xiao Ma. „Cost-aware edge server placement“. International Journal of Web and Grid Services 18, Nr. 1 (2022): 83. http://dx.doi.org/10.1504/ijwgs.2022.119275.
Der volle Inhalt der QuelleMa, Xiao, Ao Zhou, Qiyang Zhang und Shangguang Wang. „Cost-aware edge server placement“. International Journal of Web and Grid Services 18, Nr. 1 (2022): 83. http://dx.doi.org/10.1504/ijwgs.2022.10042204.
Der volle Inhalt der QuelleWang, Shangguang, Yali Zhao, Jinlinag Xu, Jie Yuan und Ching-Hsien Hsu. „Edge server placement in mobile edge computing“. Journal of Parallel and Distributed Computing 127 (Mai 2019): 160–68. http://dx.doi.org/10.1016/j.jpdc.2018.06.008.
Der volle Inhalt der QuelleYin, Hao, Xu Zhang, Hongqiang H. Liu, Yan Luo, Chen Tian, Shuoyao Zhao und Feng Li. „Edge Provisioning with Flexible Server Placement“. IEEE Transactions on Parallel and Distributed Systems 28, Nr. 4 (01.04.2017): 1031–45. http://dx.doi.org/10.1109/tpds.2016.2604803.
Der volle Inhalt der QuelleGuo, Feiyan, Bing Tang und Jiaming Zhang. „Mobile edge server placement based on meta-heuristic algorithm“. Journal of Intelligent & Fuzzy Systems 40, Nr. 5 (22.04.2021): 8883–97. http://dx.doi.org/10.3233/jifs-200933.
Der volle Inhalt der QuelleKasi, Mumraiz Khan, Sarah Abu Ghazalah, Raja Naeem Akram und Damien Sauveron. „Secure Mobile Edge Server Placement Using Multi-Agent Reinforcement Learning“. Electronics 10, Nr. 17 (30.08.2021): 2098. http://dx.doi.org/10.3390/electronics10172098.
Der volle Inhalt der QuelleShao, Yanling, Zhen Shen, Siliang Gong und Hanyao Huang. „Cost-Aware Placement Optimization of Edge Servers for IoT Services in Wireless Metropolitan Area Networks“. Wireless Communications and Mobile Computing 2022 (27.07.2022): 1–17. http://dx.doi.org/10.1155/2022/8936576.
Der volle Inhalt der QuelleLähderanta, Tero, Teemu Leppänen, Leena Ruha, Lauri Lovén, Erkki Harjula, Mika Ylianttila, Jukka Riekki und Mikko J. Sillanpää. „Edge computing server placement with capacitated location allocation“. Journal of Parallel and Distributed Computing 153 (Juli 2021): 130–49. http://dx.doi.org/10.1016/j.jpdc.2021.03.007.
Der volle Inhalt der QuelleDissertationen zum Thema "Edge server placement"
Khamari, Sabri. „Architectures et protocoles pour les véhicules connectés“. Electronic Thesis or Diss., Bordeaux, 2023. http://www.theses.fr/2023BORD0483.
Der volle Inhalt der QuelleThe advent of Intelligent Transportation Systems (ITS) marks a paradigm shift in the approach to managing and optimizing transportation infrastructures. Rooted in the integration of state-of-the-art communication technologies, ITS encompass a variety of applications aimed at enhancing road safety, traffic efficiency, and driving comfort. However, the execution of these increasingly computation-intensive applications raises inherent challenges related to latency, data processing, and service continuity. The emergence of Edge Computing stands as a transformative advancement poised to redefine the efficacy of vehicular applications in Intelligent Transportation Systems (ITS). Contrasting with conventional cloud computing paradigms, which frequently encounter latency issues attributable to the remote nature of data processing, Edge Computing decentralizes computational tasks to be nearer to the point of data generation. This proximity drastically diminishes latency, optimizes data aggregation, and enhances overall resource utilization. Consequently, Edge Computing is uniquely positioned to address and potentially mitigate the limitations that have previously impeded the optimization of ITS functionalities. Nevertheless, the incorporation of Edge Computing into vehicular networks unveils a unique array of complexities, ranging from the strategic placement of edge servers and efficient data offloading techniques to the implementation of robust service migration protocols and safeguarding privacy and security measures.This thesis investigates the problems of edge server placement and service migration in vehicular networks. Our contributions in this thesis are threefold. First, we introduce "ESIAS," an Edge-based Safety Intersection Assistance System, specifically designed to improve safety intersections. The system aims to proactively distribute precise warning messages to drivers, mitigating the risk of common intersection-related accidents. Second, we tackle the challenge of optimal Edge server placement in vehicular networks, employing integer linear programming to find the most effective solutions. The methodology considers latency, cost, and server capacity in real-world traffic conditions. The proposed framework aims not only to minimize the overall deployment cost but also to balance the computational workloads among Edge servers, all while maintaining latency within acceptable thresholds. Finally, we delve into the complex issue of service migration in MEC-enabled vehicular networks, addressing the quandary of maintaining quality of service (QoS) while minimizing migration costs. As vehicles move through different regions, maintaining service quality requires strategic service migration, which poses challenges in terms of timing and location. To resolve this problem, we formulate it as a Markov Decision Process (MDP) and apply deep reinforcement learning techniques, specifically Deep Q-Networks (DQN), to discover optimal migration strategies tailored to each service's requirements. The resulting framework ensures seamless service continuity even within high-mobility constraints, achieving an optimal balance between latency and migration costs
Gupta, Devyani. „Optimal Placement and Traffic Steering of VNFs and Edge Servers using Column Generation in Data Center Networks“. Thesis, 2022. https://etd.iisc.ac.in/handle/2005/5974.
Der volle Inhalt der QuelleBuchteile zum Thema "Edge server placement"
Xu, Xiaolong, Yuan Xue, Lianyong Qi, Xuyun Zhang, Shaohua Wan, Wanchun Dou und Victor Chang. „Load-Aware Edge Server Placement for Mobile Edge Computing in 5G Networks“. In Service-Oriented Computing, 494–507. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33702-5_38.
Der volle Inhalt der QuelleWang, Lijuan, Yingya Guo, Jiangyuan Yao und Siyu Zhou. „SCESP: An Edge Server Placement Method Based on Spectral Clustering in Mobile Edge Computing“. In Advances in Artificial Intelligence and Security, 527–39. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06761-7_42.
Der volle Inhalt der QuelleGuo, Feiyan, Bing Tang, Linyao Kang und Li Zhang. „Mobile Edge Server Placement Based on Bionic Swarm Intelligent Optimization Algorithm“. In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 95–111. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67540-0_6.
Der volle Inhalt der QuelleMoorthy, Rajalakshmi Shenbaga, K. S. Arikumar und B. Sahaya Beni Prathiba. „An Improved Whale Optimization Algorithm for Optimal Placement of Edge Server“. In Lecture Notes in Networks and Systems, 89–100. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1203-2_8.
Der volle Inhalt der QuelleZhang, Chaoyue, Bin Lin, Lin X. Cai, Liping Qian, Yuan Wu und Shuang Qi. „Joint Edge Server Deployment and Service Placement for Edge Computing-Enabled Maritime Internet of Things“. In Wireless Algorithms, Systems, and Applications, 541–53. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19211-1_44.
Der volle Inhalt der QuelleYan, Xuan, Zhanyang Xu, Mohammad R. Khosravi, Lianyong Qi und Xiaolong Xu. „An NPGA-II-Based Multi-objective Edge Server Placement Strategy for IoV“. In Advances in Parallel & Distributed Processing, and Applications, 541–55. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69984-0_39.
Der volle Inhalt der QuelleZhang, Xing, Jielin Jiang, Lianyong Qi und Xiaolong Xu. „An Edge Server Placement Method with Cyber-Physical-Social Systems in 5G“. In Simulation Tools and Techniques, 127–39. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72795-6_11.
Der volle Inhalt der QuelleHu, Haiquan, Jifu Chen und Chengying Mao. „HR-kESP: A Heuristic Algorithm for Robustness-Oriented k Edge Server Placement“. In Algorithms and Architectures for Parallel Processing, 17–33. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-0862-8_2.
Der volle Inhalt der QuelleBakshi, Mohana, Moumita Roy, Ujjwal Maulik und Chandreyee Chowdhury. „An Optimal Edge Server Placement Algorithm Based on Glowworm Swarm Optimization Technique“. In Proceedings of 4th International Conference on Frontiers in Computing and Systems, 3–12. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-2614-1_1.
Der volle Inhalt der QuelleHuang, Tao, Fengmei Chen, Shengjun Xue, Zheng Li, Yachong Tian und Xianyi Cheng. „OPECE: Optimal Placement of Edge Servers in Cloud Environment“. In Green, Pervasive, and Cloud Computing, 3–16. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-9896-8_1.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Edge server placement"
Wang, Futian, Xingxiang Huang, Hongfang Nian, Qiang He, Yun Yang und Cheng Zhang. „Cost-Effective Edge Server Placement in Edge Computing“. In ICSCC 2019: 2019 5th International Conference on Systems, Control and Communications. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3377458.3377461.
Der volle Inhalt der QuelleCui, Guangming, Qiang He, Xiaoyu Xia, Feifei Chen, Hai Jin und Yun Yang. „Robustness-oriented k Edge Server Placement“. In 2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID). IEEE, 2020. http://dx.doi.org/10.1109/ccgrid49817.2020.00-85.
Der volle Inhalt der QuelleLu, Dongyu, Yuben Qu, Fan Wu, Haipeng Dai, Chao Dong und Guihai Chen. „Robust Server Placement for Edge Computing“. In 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS). IEEE, 2020. http://dx.doi.org/10.1109/ipdps47924.2020.00038.
Der volle Inhalt der QuelleLi, Yuanzhe, und Shangguang Wang. „An Energy-Aware Edge Server Placement Algorithm in Mobile Edge Computing“. In 2018 IEEE International Conference on Edge Computing (EDGE). IEEE, 2018. http://dx.doi.org/10.1109/edge.2018.00016.
Der volle Inhalt der QuelleChen, Xiao, Wei Liu, Jing Chen und Jin Zhou. „An Edge Server Placement Algorithm in Edge Computing Environment“. In 2020 12th International Conference on Advanced Infocomm Technology (ICAIT). IEEE, 2020. http://dx.doi.org/10.1109/icait51223.2020.9315526.
Der volle Inhalt der QuelleGong, Yadong. „Optimal Edge Server and Service Placement in Mobile Edge Computing“. In 2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC). IEEE, 2020. http://dx.doi.org/10.1109/itaic49862.2020.9339180.
Der volle Inhalt der QuelleTakeda, Ayaka, Tomotaka Kimura und Kouji Hirata. „Evaluation of edge cloud server placement for edge computing environments“. In 2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW). IEEE, 2019. http://dx.doi.org/10.1109/icce-tw46550.2019.8991970.
Der volle Inhalt der QuelleLi, Wenyao, Jingduo Zhang und Zhijie Han. „Workload balance-aware edge server placement in mobile edge computing“. In 2023 2nd International Conference on Applied Statistics, Computational Mathematics and Software Engineering (ASCMSE 2023), herausgegeben von Paulo Batista und Yudong Zhang. SPIE, 2023. http://dx.doi.org/10.1117/12.2692001.
Der volle Inhalt der QuelleZheng, Danyang, Chengzong Peng und Xiaojun Cao. „On the Placement of Edge Server for Mobile Edge Computing“. In 2021 7th International Conference on Computer and Communications (ICCC). IEEE, 2021. http://dx.doi.org/10.1109/iccc54389.2021.9674609.
Der volle Inhalt der QuelleYeom, Sungwoong, Shivani Sanjay Kolekar und Kyungbaek Kim. „Effective Edge Server Placement for Efficient Federated Clustering“. In 2022 23rd Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 2022. http://dx.doi.org/10.23919/apnoms56106.2022.9919936.
Der volle Inhalt der QuelleBerichte der Organisationen zum Thema "Edge server placement"
Ginzel. L51748 Detection of Stress Corrosion Induced Toe Cracks-Advancement of the Developed Technique. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), März 1996. http://dx.doi.org/10.55274/r0010659.
Der volle Inhalt der QuelleBriggs, Nicholas E., Robert Bailey Bond und Jerome F. Hajjar. Cyclic Behavior of Steel Headed Stud Anchors in Concrete-filled Steel Deck Diaphragms through Push-out Tests. Northeastern University. Department of Civil and Environmental Engineering., Februar 2023. http://dx.doi.org/10.17760/d20476962.
Der volle Inhalt der QuelleBriggs, Nicholas E., und Jerome F. Hajjar. Cyclic Seismic Behavior of Concrete-filled Steel Deck Diaphragms. Department of Civil and Environmental Engineering, Northeastern University, September 2023. http://dx.doi.org/10.17760/d20593269.
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