An Auction-Based Mechanism for Optimal Task Allocation and Resource Aware Containerization

TL;DR

This paper introduces AUC-RAC, an auction-based mechanism utilizing Docker swarm for efficient task offloading and resource management among local servers in IoT environments, improving performance and cost-effectiveness.

Contribution

The paper presents a novel auction-based framework for task allocation in IoT cloud containerization, integrating Docker swarm for optimized resource utilization.

Findings

Enhanced task offloading efficiency in IoT environments.

Improved resource utilization among local servers.

Better performance in computation-intensive tasks.

Abstract

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.