A general task offloading and resources allocation strategy for multi-RSUs with load unbalance and priority awareness

IF 4.4 3区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Dun Cao , WenQian Wang , Meihua Wu , Shuo Cai , Fayez Alqahtani , Jin Wang
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引用次数: 0

Abstract

Vehicular Edge Computing is a new computing paradigm that enables real-time response to vehicular applications and servers by performing data processing on edge computing devices near the vehicle. However, on the one hand, the random distribution and the mobility of vehicles may lead to load unbalance among different Roadside Units (RSUs), and some tasks may not be able to get timely response due to inadequate computing resources and communication resources in the high-load RSU areas. On the other hand, considering the different urgency of the tasks, the service quality of the system will be seriously affected if these tasks are not treated indistinguishably. To address the above challenges, this paper constructs a priority-aware task offloading and computing&communication resources allocation problem in a general scenario of unbalanced load among multi-RSUs, aiming at minimising the average delay. In the problem, considering the absence of communication resources, the relay vehicle is used to offload the subtasks of splittable tasks to the RSUs that are in the neighbouring and low-load. Moreover, to take full advantage of computing resources, the task can be reasonably split into at most four parts and processed in parallel on a relay vehicle, a current RSU, a neighbouring RSU and a local vehicle. To solve the problem, a Split-Hop Offloading and Resources Allocation Strategy (SHORAS) based on an improved particle swarm optimisation algorithm is proposed, which uses a penalty function to incline resources towards high priority tasks. Simulation results show that SHORAS improves 24% in terms of the total system delay and effectively reduces the processing delay in the high-load areas compared to other strategies, while ensuring the delay requirements of high priority tasks.
具有负载不平衡和优先级意识的多 RSU 的一般任务卸载和资源分配策略
车载边缘计算是一种新的计算模式,通过在车辆附近的边缘计算设备上执行数据处理,实现对车载应用和服务器的实时响应。然而,一方面,车辆的随机分布和流动性可能导致不同路侧单元(RSU)之间的负载不平衡,在高负载的 RSU 区域,由于计算资源和通信资源不足,一些任务可能无法得到及时响应。另一方面,考虑到任务的紧迫性不同,如果不对这些任务进行区别对待,将严重影响系统的服务质量。针对上述挑战,本文构建了一个在多 RSU 负载不平衡的一般场景下的优先级感知任务卸载和计算&通信资源分配问题,旨在最小化平均延迟。在该问题中,考虑到通信资源的缺失,利用中继车将可分拆任务的子任务卸载到邻近且负载较低的 RSU 上。此外,为了充分利用计算资源,任务最多可合理地拆分为四个部分,并在中继车、当前 RSU、邻近 RSU 和本地车上并行处理。为解决这一问题,提出了一种基于改进的粒子群优化算法的分跳卸载和资源分配策略(SHORAS),该策略使用惩罚函数将资源向高优先级任务倾斜。仿真结果表明,与其他策略相比,SHORAS 在确保高优先级任务延迟要求的前提下,将系统总延迟提高了 24%,并有效减少了高负载区域的处理延迟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Ad Hoc Networks
Ad Hoc Networks 工程技术-电信学
CiteScore
10.20
自引率
4.20%
发文量
131
审稿时长
4.8 months
期刊介绍: The Ad Hoc Networks is an international and archival journal providing a publication vehicle for complete coverage of all topics of interest to those involved in ad hoc and sensor networking areas. The Ad Hoc Networks considers original, high quality and unpublished contributions addressing all aspects of ad hoc and sensor networks. Specific areas of interest include, but are not limited to: Mobile and Wireless Ad Hoc Networks Sensor Networks Wireless Local and Personal Area Networks Home Networks Ad Hoc Networks of Autonomous Intelligent Systems Novel Architectures for Ad Hoc and Sensor Networks Self-organizing Network Architectures and Protocols Transport Layer Protocols Routing protocols (unicast, multicast, geocast, etc.) Media Access Control Techniques Error Control Schemes Power-Aware, Low-Power and Energy-Efficient Designs Synchronization and Scheduling Issues Mobility Management Mobility-Tolerant Communication Protocols Location Tracking and Location-based Services Resource and Information Management Security and Fault-Tolerance Issues Hardware and Software Platforms, Systems, and Testbeds Experimental and Prototype Results Quality-of-Service Issues Cross-Layer Interactions Scalability Issues Performance Analysis and Simulation of Protocols.
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