Optimal Resource Provisioning and Task Offloading for Network-Aware and Federated Edge Computing
Compared to cloud computing, mobile edge computing (MEC) is a promising solution for delay-sensitive applications due to its proximity to end users. Because of its ability to offload resource-intensive tasks to nearby edge servers, MEC allows a diverse range of compute- and storage-intensive applica...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/22/9200 |
| _version_ | 1797457770985816064 |
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| author | Avilia Kusumaputeri Nugroho Shigeo Shioda Taewoon Kim |
| author_facet | Avilia Kusumaputeri Nugroho Shigeo Shioda Taewoon Kim |
| author_sort | Avilia Kusumaputeri Nugroho |
| collection | DOAJ |
| description | Compared to cloud computing, mobile edge computing (MEC) is a promising solution for delay-sensitive applications due to its proximity to end users. Because of its ability to offload resource-intensive tasks to nearby edge servers, MEC allows a diverse range of compute- and storage-intensive applications to operate on resource-constrained devices. The optimal utilization of MEC can lead to enhanced responsiveness and quality of service, but it requires careful design from the perspective of user-base station association, virtualized resource provisioning, and task distribution. Also, considering the limited exploration of the federation concept in the existing literature, its impacts on the allocation and management of resources still remain not widely recognized. In this paper, we study the network and MEC resource scheduling problem, where some edge servers are federated, limiting resource expansion within the same federations. The integration of network and MEC is crucial, emphasizing the necessity of a joint approach. In this work, we present NAFEOS, a proposed solution formulated as a two-stage algorithm that can effectively integrate association optimization with vertical and horizontal scaling. The Stage-1 problem optimizes the user-base station association and federation assignment so that the edge servers can be utilized in a balanced manner. The following Stage-2 dynamically schedules both vertical and horizontal scaling so that the fluctuating task-offloading demands from users are fulfilled. The extensive evaluations and comparison results show that the proposed approach can effectively achieve optimal resource utilization. |
| first_indexed | 2024-03-09T16:27:45Z |
| format | Article |
| id | doaj.art-b67785a01bab42c29fcea83fd253d319 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T16:27:45Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-b67785a01bab42c29fcea83fd253d3192023-11-24T15:05:43ZengMDPI AGSensors1424-82202023-11-012322920010.3390/s23229200Optimal Resource Provisioning and Task Offloading for Network-Aware and Federated Edge ComputingAvilia Kusumaputeri Nugroho0Shigeo Shioda1Taewoon Kim2School of Computer Science and Engineering, Pusan National University, Busan 46241, Republic of KoreaGraduate School of Engineering, Chiba University, Inage-ku, Chiba 263-8522, JapanSchool of Computer Science and Engineering, Pusan National University, Busan 46241, Republic of KoreaCompared to cloud computing, mobile edge computing (MEC) is a promising solution for delay-sensitive applications due to its proximity to end users. Because of its ability to offload resource-intensive tasks to nearby edge servers, MEC allows a diverse range of compute- and storage-intensive applications to operate on resource-constrained devices. The optimal utilization of MEC can lead to enhanced responsiveness and quality of service, but it requires careful design from the perspective of user-base station association, virtualized resource provisioning, and task distribution. Also, considering the limited exploration of the federation concept in the existing literature, its impacts on the allocation and management of resources still remain not widely recognized. In this paper, we study the network and MEC resource scheduling problem, where some edge servers are federated, limiting resource expansion within the same federations. The integration of network and MEC is crucial, emphasizing the necessity of a joint approach. In this work, we present NAFEOS, a proposed solution formulated as a two-stage algorithm that can effectively integrate association optimization with vertical and horizontal scaling. The Stage-1 problem optimizes the user-base station association and federation assignment so that the edge servers can be utilized in a balanced manner. The following Stage-2 dynamically schedules both vertical and horizontal scaling so that the fluctuating task-offloading demands from users are fulfilled. The extensive evaluations and comparison results show that the proposed approach can effectively achieve optimal resource utilization.https://www.mdpi.com/1424-8220/23/22/9200mobile edge computingtask offloadingoptimal associationvertical scalinghorizontal scaling |
| spellingShingle | Avilia Kusumaputeri Nugroho Shigeo Shioda Taewoon Kim Optimal Resource Provisioning and Task Offloading for Network-Aware and Federated Edge Computing Sensors mobile edge computing task offloading optimal association vertical scaling horizontal scaling |
| title | Optimal Resource Provisioning and Task Offloading for Network-Aware and Federated Edge Computing |
| title_full | Optimal Resource Provisioning and Task Offloading for Network-Aware and Federated Edge Computing |
| title_fullStr | Optimal Resource Provisioning and Task Offloading for Network-Aware and Federated Edge Computing |
| title_full_unstemmed | Optimal Resource Provisioning and Task Offloading for Network-Aware and Federated Edge Computing |
| title_short | Optimal Resource Provisioning and Task Offloading for Network-Aware and Federated Edge Computing |
| title_sort | optimal resource provisioning and task offloading for network aware and federated edge computing |
| topic | mobile edge computing task offloading optimal association vertical scaling horizontal scaling |
| url | https://www.mdpi.com/1424-8220/23/22/9200 |
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