Journal ArticleDOI
Dependency-Aware Task Scheduling in Vehicular Edge Computing
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TLDR
An efficient task scheduling algorithm is developed to prioritize multiple applications and prioritize multiple tasks so as to guarantee the completion time constraints of applications and the processing dependency requirements of tasks.Abstract:
Vehicular edge computing (VEC) offers a new paradigm to improve vehicular services and augment the capabilities of vehicles. In this article, we study the problem of task scheduling in VEC, where multiple computation-intensive vehicular applications can be offloaded to roadside units (RSUs) and each application can be further divided into multiple tasks with task dependency. The tasks can be scheduled to different mobile-edge computing servers on RSUs for execution to minimize the average completion time of multiple applications. Considering the completion time constraint of each application and the processing dependency of multiple tasks belonging to the same application, we formulate the multiple tasks scheduling problem as an optimization problem that is NP-hard. To solve the optimization problem, we develop an efficient task scheduling algorithm. The basic idea is to prioritize multiple applications and prioritize multiple tasks so as to guarantee the completion time constraints of applications and the processing dependency requirements of tasks. The numerical results demonstrate that our proposed algorithm can significantly reduce the average completion time of multiple applications compared with benchmark algorithms.read more
Citations
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Journal ArticleDOI
Collaborative Learning of Communication Routes in Edge-Enabled Multi-Access Vehicular Environment
TL;DR: A collaborative learning-based routing scheme for multi-access vehicular edge computing environment that employs a reinforcement learning algorithm based on end-edge-cloud collaboration to find routes in a proactive manner with a low communication overhead and is preemptively changed based on the learned information.
Journal ArticleDOI
Offloading Time Optimization via Markov Decision Process in Mobile-Edge Computing
TL;DR: This work first investigates a MEC system consisting of mobile devices and heterogeneous edge severs that support various radio access technologies, and proposes an optimal offloading node selection strategy formulated as a Markov decision process (MDP), and solved by employing the value iteration algorithm (VIA).
Journal ArticleDOI
Computation Offloading for Vehicular Environments: A Survey
Alisson Barbosa de Souza,Paulo A. L. Rego,Tiago Carneiro,Jardel das C. Rodrigues,Pedro Pedrosa Rebouças Filho,José Neuman de Souza,Vinay Chamola,Victor Hugo C. de Albuquerque,Biplab Sikdar +8 more
TL;DR: This survey aims to review and organize the computation offloading literature in vehicular environments, demystify some concepts, propose a taxonomy with the most important aspects and classify most works in the area according to each category.
Journal ArticleDOI
Adaptive Computing Scheduling for Edge-Assisted Autonomous Driving
TL;DR: The proposed indexed-based scheme avoids the time-consuming policy exploration common in DRL scheduling approaches and makes effectual decisions with low complexity while adapting to time-variant vehicle mobility.
Journal ArticleDOI
Multi-Hop Multi-Task Partial Computation Offloading in Collaborative Edge Computing
TL;DR: A joint partial offloading and flow scheduling heuristic (JPOFH) that decidespartial offloading ratio by considering both waiting times at the devices and start time of network flows is proposed.
References
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Journal ArticleDOI
A Survey on Mobile Edge Computing: The Communication Perspective
TL;DR: A comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management is provided in this paper, where a set of issues, challenges, and future research directions for MEC are discussed.
Journal ArticleDOI
Performance-effective and low-complexity task scheduling for heterogeneous computing
TL;DR: Two novel scheduling algorithms for a bounded number of heterogeneous processors with an objective to simultaneously meet high performance and fast scheduling time are presented, called the Heterogeneous Earliest-Finish-Time (HEFT) algorithm and the Critical-Path-on-a-Processor (CPOP) algorithm.
Posted Content
A Survey on Mobile Edge Computing: The Communication Perspective
TL;DR: A comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management and recent standardization efforts on MEC are introduced.
Journal ArticleDOI
Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing
TL;DR: In this article, a game theoretic approach for computation offloading in a distributed manner was adopted to solve the multi-user offloading problem in a multi-channel wireless interference environment.
Journal ArticleDOI
Mobile Edge Computing: A Survey on Architecture and Computation Offloading
Pavel Mach,Zdenek Becvar +1 more
TL;DR: This paper describes major use cases and reference scenarios where the mobile edge computing (MEC) is applicable and surveys existing concepts integrating MEC functionalities to the mobile networks and discusses current advancement in standardization of the MEC.