.png){kind=icon}
.png){kind=icon}
Return
Mean Field Evolutionary Dynamics in Dense-User Multi-Access Edge Computing Systems
.png){kind=icon}
PRE
AI
DOI：10.1109/TWC.2020.3016695.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Multi-access edge computing (MEC) can use the distributed computing resources to serve the large numbers of mobile users in the next generation of communication systems. In this new architecture, a limited number of mobile edge servers will serve a relatively large number of mobile users. Heterogeneous servers can provide either single resource or multiple different resources to the massive number of selfish mobile users. To achieve high quality of service (QoS) and low latency under these two cases, we construct two system models and formulate our problems as two non-cooperative population games. Then we apply our proposed mean field evolutionary approach with two different strategy graphs to solve the load balancing problems under those two cases. Finally, to evaluate the performance of our algorithms, we employ the following performance indicators: overall response time (average response time of the whole system), individual response time (response time of each server), and fairness index (equality of users' response time).
Keywords:
Servers
Games
Time factors
Load modeling
Load management
Sociology
Statistics
Mean field evolutionary approach
load balancing
dense-user
MEC
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
10.7
Papers:
1.3W
Citations:
5.3W
Organization
View more organizations