energy, and resource usage cost while offloading tasks in a CoMEC network. A task offloading framework based on greyWOLf optimization that exploitsVERtical collaborationINEdge computing, namelyWOLVERINEsystem is devised to solve the problem. The WOLVERINE stands out from other task-offloading frameworks ...
Experiment results validate that our approach not only leads to the improvement of key system performance indicators, but also ensures the comprehensive exploitation of the computing resources of mobile vehicles.Huaming WuAnqi GuYonghui LiangVehicular Technology, IEEE Transactions on...
The integration of new Internet of Things (IoT) applications and services heavily relies on task offloading to external devices due to the constrained computing and battery resources of IoT devices. Up to now, Cloud Computing (CC) paradigm has been a good approach for tasks where latency is not...
According to the practical experiment of [22] we can set the value as xn=10−27{Pnlc}2. From Eqs. (1) & (2) the total cost of local computing can be shown as (3)(TC)nlc=WntTnlc+WneEnlc, Here, Wnt and Wne are representing the weights of time and Rn is representing the ...
The experiment in this paper is to partition the regional power grid A1 and A2 reasonably by using the decomposition and coordination algorithm, and then configure the virtual machine by using the two-stage heuristic algorithm to meet the needs of local regional task computing. In order to clearl...
Edge computing task scheduling blockchain task caching industrial security 1. Introduction In recent years, the world has started the fourth industrial revolution represented by the industrial internet, and the current manufacturing industry is developing in the direction of personalization, service, interco...
By offloading dynamic workloads, fog computing can extend resource-limited limitations and improve computational and communication latency for latency-sensitive IoT applications. In layered computing architecture, task priority and offload layers are also prioritized to reduce service latency. The study [23...
offloading solutions developed for MAR tasks suffer from high migration overhead, poor scalability, and short-sightedness when applied in provisioning multi-user MAR services. To address these issues, a MAR service-oriented task offloading scheme is designed and evaluated in edge-cloud computing ...
Experiment evaluation To evaluate the performance of the offloading algorithm proposed in this study, we elaborate on the experiments we performed. In the experiments, we use the WorkflowSim framework to simulate the industrial devices, edge computing, and cloud computing layers, and use WorkflowGenerat...
2, task uninstallation uses two distinct techniques to move computing jobs from mobile devices to edge servers for processing. Partial offloading refers to the transfer of part of the calculation of the task to the edge server for processing, while the rest is still executed on the mobile ...