Name
Title | ||
|---|---|---|
Virtual Network Function Placement in Satellite Edge Computing With a Potential Game Approach |
Abstract | ||
|---|---|---|
Satellite networks, as a supplement to terrestrial networks, can provide effective computing services for Internet of Things (IoT) users in remote areas. Due to the resource limitation of satellites, such as in computing, storage, and energy, a computation task from an IoT user can be divided into several parts and cooperatively accomplished by multiple satellites to improve the overall operational efficiency of satellite networks. Network function virtualization (NFV) is viewed as a new paradigm in allocating network resources on-demand. Satellite edge computing combined with the NFV technology is becoming an emerging topic. In this paper, we propose a potential game approach for virtual network function (VNF) placement in satellite edge computing. The VNF placement problem aims to minimize the deployment cost for each user request, furthermore, we consider that a satellite network should provide computing services for as many user requests as possible. We formulate the VNF placement problem as a potential game to maximize the overall network payoff and analyze the problem by a game-theoretical approach. We implement a decentralized resource allocation algorithm based on a potential game (PGRA) to tackle the VNF placement problem by finding a Nash equilibrium. Finally, we conduct the experiments to evaluate the performance of the proposed PGRA algorithm. The simulation results show that the proposed PGRA algorithm can effectively address the VNF placement problem in satellite edge computing. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TNSM.2022.3141165 | IEEE Transactions on Network and Service Management |
Keywords | DocType | Volume |
Network function virtualization (NFV),satellite edge computing,virtual network function (VNF),resource allocation,potential game | Journal | 19 |
Issue | ISSN | Citations |
2 | 1932-4537 | 0 |
PageRank | References | Authors |
0.34 | 30 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiangqiang Gao | 1 | 0 | 1.69 |
| Rongke Liu | 2 | 127 | 35.79 |
| Aryan Kaushik | 3 | 1 | 0.69 |