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The paper introduces AUC-RAC, an auction-based mechanism for optimizing task allocation and resource utilization in IoT environments using Docker Swarm. It addresses the challenge of efficiently offloading computation-intensive tasks to multiple local servers by employing an auction-based bidding process among worker nodes managed by a manager node. Experimental results demonstrate improved offloading and computation performance through optimized resource allocation.
Ditch static task assignment: this auction-based system dynamically allocates IoT tasks to servers based on real-time resource availability, boosting efficiency.
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.