Distributed computing has enabled cooperation between multiple computing devices for the simultaneous execution of resource-hungry tasks. Such execution also plays a pivotal role in the parallel execution of numerous tasks in the Internet of Things (IoT) environment. Leveraging the computing resources of multiple devices, the offloading and processing of computationintensive tasks can be carried out more efficiently. However, managing resources and optimizing costs remain challenging for successfully executing tasks in cloud-based containerization for IoT. This paper proposes AUC-RAC, an auction-based mechanism for efficient offloading of computation tasks among multiple local servers in the context of IoT devices. The approach leverages the concept of Docker swarm, which connects multiple local servers in the form of Manager Node (MN) and Worker Nodes (WNs). It uses Docker containerization to execute tasks simultaneously. In this system, IoT devices send tasks to the MN, which then sends the task details to all its WNs to participate in the auction-based bidding process. The auctionbased bidding process optimizes the allocation of computation tasks among multiple systems, considering their resource sufficiency. The experimental analysis establishes that the approach offers improved offloading and computation-intensive services for IoT devices by enabling cooperation between local servers.

翻译：分布式计算使得多个计算设备能够协同执行资源密集型任务。这种执行方式在物联网环境中对大量任务的并行处理也起着关键作用。通过利用多设备的计算资源，计算密集型任务的卸载与处理能够更高效地完成。然而，在基于云的物联网容器化环境中，资源管理与成本优化仍是成功执行任务所面临的挑战。本文提出AUC-RAC——一种面向物联网设备场景、基于拍卖机制的多本地服务器间计算任务高效卸载方法。该方法利用Docker swarm的概念，以管理节点和工作者节点的形式连接多个本地服务器，并采用Docker容器化技术实现任务并行执行。在该系统中，物联网设备将任务发送至管理节点，管理节点随后将任务详情发送至所有工作者节点以参与基于拍卖的竞价流程。该竞价流程在考虑各系统资源充足度的前提下，优化了计算任务在多个系统间的分配。实验分析表明，通过实现本地服务器间的协同合作，该方法为物联网设备提供了更优的卸载与计算密集型服务能力。