Mean Age of Information in Partial Offloading Mobile Edge Computing Networks
The age of information (AoI) performance analysis is essential for evaluating the information freshness in the large-scale mobile edge computing (MEC) networks. This work proposes the earliest analysis of the mean AoI (MAoI) performance of large-scale partial offloading MEC networks. Firstly, we derive and validate the closed-form expressions of MAoI by using queueing theory and stochastic geometry. Based on these expressions, we analyse the effects of computing offloading ratio (COR) and task generation rate (TGR) on the MAoI performance and compare the MAoI performance under the local computing, remote computing, and partial offloading schemes. The results show that by jointly optimising the COR and TGR, the partial offloading scheme outperforms the local and remote computing schemes in terms of the MAoI, which can be improved by up to 51% and 61%, respectively. This encourages the MEC networks to adopt the partial offloading scheme to improve the MAoI performance.
Code (0)
등록된 구현이 없습니다.
Tasks
Edge-computingSimilar Papers 제목 키워드 기반
Cost-Effective Task Offloading Scheduling for Hybrid Mobile Edge-Quantum Computing
In this paper, we aim to address the challenge of hybrid mobile edge-quantum computing (MEQC) for sustainable task offloading scheduling in mobile networks. We develop cost-effective designs for both task offloading mode…
Decision MakingDeep Reinforcement LearningSchedulingSecure Computation Offloading in Blockchain based IoT Networks with Deep Reinforcement Learning
For current and future Internet of Things (IoT) networks, mobile edge-cloud computation offloading (MECCO) has been regarded as a promising means to support delay-sensitive IoT applications. However, offloading mobile ta…
Deep Reinforcement LearningManagementreinforcement-learningReinforcement Learning (RL)Dependency-Aware Computation Offloading in Mobile Edge Computing: A Reinforcement Learning Approach
Mobile edge computing (MobEC) builds an Information Technology (IT) service environment to enable cloud-computing capabilities at the edge of mobile networks. To tackle the restrictions in the battery power and computati…
Cloud ComputingEdge-computingQ-Learningreinforcement-learning+1Learning to Optimize Resource Assignment for Task Offloading in Mobile Edge Computing
In this paper, we consider a multiuser mobile edge computing (MEC) system, where a mixed-integer offloading strategy is used to assist the resource assignment for task offloading. Although the conventional branch and bou…
Edge-computingCache-assisted Mobile Edge Computing over Space-Air-Ground Integrated Networks for Extended Reality Applications
Extended reality-enabled Internet of Things (XRI) provides the new user experience and the sense of immersion by adding virtual elements to the real world through Internet of Things (IoT) devices and emerging 6G technolo…
Edge-computing