Enhancing Cloud-Based Task Scheduling: A Novel Approach Integrating Named Data Network And Smart Contracts For Optimal Blockchain Network Selection

Abstract

The optimization in task scheduling within a network system in computational resources is utilized to execute a collection of tasks with varying computational requirements. The existing system operates in a networking environment, where tasks compete for execution across machines with differing execution times. The scheduling problem is formulated as a model focusing on the minimizing makespan known to be the total time spent on task execution. In proposing an enhanced system, introduce a novel approach involving a Named Data Network (NDN) coupled with smart contracts for task scheduling by selecting optimal Blockchain network. The envisioned system aims to leverage the benefits of NDN architecture and smart contract technology to optimize the assignment of tasks to machines within the cloud environment. By employing a non-preemptive scheduling model and considering a range of task properties, including execution time and machine suitability, the proposed system seeks to enhance the efficiency and effectiveness of task scheduling. The task Scheduling Problem emphasizes the importance of minimizing makespan as a key metric. The proposed Named Data Network with smart contracts introduces a paradigm shift in task scheduling, offering a potential solution to the challenges posed by the dynamic nature of task scheduling environments and the need for efficient block selection in Blockchain allocation. Through the formalization of the existing model, this research contributes to the ongoing discourse on optimal task scheduling strategies within complex computational environments.