Meeting Deadlines Using Artificial Bee Colony (ABC) Based Resource Mechanism in Public Clouds with Task Replication in Large-Scale Biomedical Data

Ramathilagam, A.; Vijayalakshmi, K.

doi:10.1166/jctn.2018.7168

Cited by 1 publication

(1 citation statement)

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“…The QoS satisfaction is a major trouble which can be found in task scheduling process in cloud computing environment. And this trouble is discussed by an improved Artificial Bee Colony (ABC) based on IaaS Cloud Partial Critical Path (IC‐PCP) with Replication algorithm that is proposed by Ramathilagam et al 13 and it is known as EAIPR. It is utilized to increase the possibility of finishing the execution of a technical application execution within a user‐defined target in a cloud infrastructure.…”

Section: Related Workmentioning

confidence: 99%

Workflow scheduling in cloud environment using a novel metaheuristic optimization algorithm

Ramathilagam¹,

Vijayalakshmi²

2021

Int J Communication

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Summary Workflow scheduling is the most focused research issue in the on‐demand clouds where the user satisfaction like cost and bandwidth is more difficult. Several research works have been conducted earlier towards performing reliable workflow scheduling with the aim of reducing cost or execution time. However, those works lack to produce better result by compromising any attributes for attaining the goal. The existing work lacks from the security where the tasks might get corrupted during execution. To resolve this problem, an Enhanced Artificial Fish Swarm Algorithm (EAFSA)‐based IaaS Cloud Partial Critical Path (IC‐PCP) Replication and Hyper Elliptic Curve Cryptography (EAFSAIPR with HECC) is proposed. The main goal is to perform better workflow scheduling which can complete the task execution before deadline given by the users. This is done by predicting the early start time and latest finish time using EAFSA algorithm, so that task replication can be made to meet the soft deadline constraint. The task authentication is done efficiently using HEEC algorithm, so that corruption from malicious users can be avoided. The task replication is done securely using the cryptographic algorithm. The proposed EAFSAIPR with HECC algorithm uses idle time of provisioned resources to replicate workflow tasks optimally. The proposed EAFSAIPR algorithm scheduler focused to ensure the lowest cost while serving a deadline set by the user. The experimental results show that the scheduler can find good schedules of deadlines being met and reduces the total execution time of applications as the budget available for replication increases.

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Section: Related Workmentioning

confidence: 99%