Journal ArticleDOI
Resource provisioning and work flow scheduling in clouds using augmented Shuffled Frog Leaping Algorithm
Parmeet Kaur,Shikha Mehta +1 more
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TLDR
An augmented Shuffled Frog Leaping Algorithm (ASFLA) based technique for resource provisioning and workflow scheduling in the Infrastructure as a service (IaaS) cloud environment is presented and outperforms Particle Swarm Optimization and SFLA.About:
This article is published in Journal of Parallel and Distributed Computing.The article was published on 2017-03-01. It has received 107 citations till now. The article focuses on the topics: Provisioning & Scheduling (computing).read more
Citations
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A WOA-Based Optimization Approach for Task Scheduling in Cloud Computing Systems
TL;DR: The proposed Improved WOA for Cloud task scheduling (IWC) has better convergence speed and accuracy in searching for the optimal task scheduling plans, compared to the current metaheuristic algorithms, and can also achieve better performance on system resource utilization.
Journal ArticleDOI
Issues and Challenges of Load Balancing Techniques in Cloud Computing: A Survey
Pawan Kumar,Rakesh Kumar +1 more
TL;DR: A state-of-the-art review of issues and challenges associated with existing load-balancing techniques for researchers to develop more effective algorithms is presented.
Journal ArticleDOI
Host-Based Intrusion Detection System with System Calls: Review and Future Trends
TL;DR: A review of the development of system-call-based HIDS and future research trends is provided, namely, the reduction of the false-positive rate, the improvement of detection efficiency, and the enhancement of collaborative security.
Journal ArticleDOI
Improved many-objective particle swarm optimization algorithm for scientific workflow scheduling in cloud computing
TL;DR: An approach to solve workflow scheduling problem using Improved Many Objective Particle Swarm Optimization algorithm named I_MaOPSO is proposed considering four conflicting objectives namely maximization of reliability and minimization of cost, makespan and energy consumption.
Journal ArticleDOI
Resource provisioning using workload clustering in cloud computing environment: a hybrid approach
TL;DR: This paper presents a hybrid solution to handle the resource provisioning issue using workload analysis in a cloud environment and utilized the Imperialist Competition Algorithm and K-means for clustering the workload submitted by end-users.
References
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Journal ArticleDOI
Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility
TL;DR: This paper defines Cloud computing and provides the architecture for creating Clouds with market-oriented resource allocation by leveraging technologies such as Virtual Machines (VMs), and provides insights on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain Service Level Agreement (SLA) oriented resource allocation.
Journal ArticleDOI
NP-complete scheduling problems
TL;DR: It is shown that the problem of finding an optimal schedule for a set of jobs is NP-complete even in the following two restricted cases, tantamount to showing that the scheduling problems mentioned are intractable.
Journal ArticleDOI
Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization
TL;DR: Experimental results in terms of the likelihood of convergence to a global optimal solution and the solution speed suggest that the SFLA can be an effective tool for solving combinatorial optimization problems.
Proceedings ArticleDOI
A Particle Swarm Optimization-Based Heuristic for Scheduling Workflow Applications in Cloud Computing Environments
TL;DR: This paper presents a particle swarm optimization (PSO) based heuristic to schedule applications to cloud resources that takes into account both computation cost and data transmission cost, and shows that PSO can achieve as much as 3 times cost savings as compared to BRS.
Journal ArticleDOI
Characterizing and profiling scientific workflows
TL;DR: A characterization of workflows from six diverse scientific applications, including astronomy, bioinformatics, earthquake science, and gravitational-wave physics is provided, based on novel workflow profiling tools that provide detailed information about the various computational tasks that are present in the workflow.