Utility-driven virtual machine allocation in edge cloud environments using a partheno-genetic algorithm
Abstract Mobile Edge Computing alleviates network congestion and reduces latency by offloading tasks to the network edge. However, fluctuating Quality of Service (QoS) and service compositions significantly challenge service reliability and utility optimization. To address these challenges, this pap...
Saved in:
| Main Authors: | Jie Cao, Cuicui Zhang, Ping Qi, Kekun Hu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-03-01
|
| Series: | Journal of Cloud Computing: Advances, Systems and Applications |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13677-025-00739-8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Research on parallel partheno genetic algorithm based on the immune programming
by: XING Xiao-shuai, et al.
Published: (2007-01-01) -
Device-Driven Service Allocation in Mobile Edge Computing with Location Prediction
by: Qian Zeng, et al.
Published: (2025-05-01) -
Exact and Approximation Algorithms for Task Offloading with Service Caching and Dependency in Mobile Edge Computing
by: Bowen Cui, et al.
Published: (2025-06-01) -
Research on elite hierarchical task offloading strategy based on reinforcement learning in edge-cloud collaboration scenario
by: Juan FANG, et al.
Published: (2022-03-01) -
Joint optimization strategy of service cache and resource allocation in mobile edge network
by: Long LONG, et al.
Published: (2023-01-01)