.png){kind=icon}
返回
Adaptive Resource Allocation for Computation Offloading: A Control-Theoretic Approach
.png){kind=icon}
OA
AI
DOI：10.1145/3284553.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Although mobile devices today have powerful hardware and networking capabilities, they fall short when it comes to executing compute-intensive applications. Computation offloading (i.e., delegating resource-consuming tasks to servers located at the edge of the network) contributes toward moving to a mobile cloud computing paradigm. In this work, a two-level resource allocation and admission control mechanism for a cluster of edge servers offers an alternative choice to mobile users for executing their tasks. At the lower level, the behavior of edge servers is modeled by a set of linear systems, and linear controllers are designed to meet the system's constraints and quality of service metrics, whereas at the upper level, an optimizer tackles the problems of load balancing and application placement toward the maximization of the number the offloaded requests. The evaluation illustrates the effectiveness of the proposed offloading mechanism regarding the performance indicators, such as application average response time, and the optimal utilization of the computational resources of edge servers.
Keyword:
Edge computing
linear modeling
feedback control
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.1
论文数:
896
被引数:
1.9K
机构
引用论文
.png){kind=icon}
Load following operation of NAS battery by setting statistic margins to avoid risks通过设置统计裕度来避免风险，对NAS电池进行负载跟踪操作
PREAI
分享收藏分享收藏
查看更多内容