Journal ArticleDOI
A metaheuristic method for joint task scheduling and virtual machine placement in cloud data centers
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TLDR
Simulation results show that optimizing joint task scheduling and VM placement leads to better overall results in terms of minimizing execution cost, makespan and degree of imbalance and maximizing PHs resource utilization.About:
This article is published in Future Generation Computer Systems.The article was published on 2021-02-01. It has received 43 citations till now. The article focuses on the topics: Job shop scheduling & Metaheuristic.read more
Citations
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Journal ArticleDOI
Binary Aquila Optimizer for Selecting Effective Features from Medical Data: A COVID-19 Case Study
TL;DR: A wrapper feature selection approach is presented on the basis of the newly proposed Aquila optimizer (AO) in this work, demonstrating that using both proposed BAO variants can improve the classification accuracy on these medical datasets.
Journal ArticleDOI
Reliability-aware task scheduling for energy efficiency on heterogeneous multiprocessor systems
TL;DR: An improved whale optimization algorithm (WOA) deploying opposition-based learning and individual selection strategy, which can balance the exploration and exploitation ability, and a constrained rank-based method which retains some infeasible individuals in the population is proposed.
Journal ArticleDOI
Chaotic Salp Swarm Optimization-Based Energy-Aware VMP Technique for Cloud Data Centers
S. Parthiban,A. Harshavardhan,S. Neelakandan,Vempaty Prashanthi,Abdul-Rasheed Akeji Alhassan Alolo,Selvam Velmurugan +5 more
TL;DR: A novel energy-aware VMP technique for CDCs that is founded on the Disordered Salp Swarm Optimization Algorithm and is enhanced for energy efficiency (EAVMP-CSSA), which attempts to reduce CDC energy ingesting by dropping the quantity of active servers supporting virtual machines.
Journal ArticleDOI
A latency-aware task scheduling algorithm for allocating virtual machines in a cost-effective and time-sensitive fog-cloud architecture
TL;DR: An infrastructure for smart home energy management with minimum hardware cost using cloud and fog computing is designed and a latency-aware scheduling algorithm based on virtual machine matching using meta-heuristics is proposed that outperforms the Tabu search, genetic algorithm, PSO, and simulated annealing methods.
Journal ArticleDOI
CCSA: Hybrid Cuckoo Crow Search Algorithm for Task Scheduling in Cloud Computing
TL;DR: An efficient hybridized scheduling algorithm that replicates the parasitic behaviour of the cuckoo and food gathering habit of the crow bird, named Cuckoo Crow Search Algorithm (CCSA) had been presented for improvising the task scheduling process.
References
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Book ChapterDOI
Individual Comparisons by Ranking Methods
TL;DR: The comparison of two treatments generally falls into one of the following two categories: (a) a number of replications for each of the two treatments, which are unpaired, or (b) we may have a series of paired comparisons, some of which may be positive and some negative as mentioned in this paper.
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
CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms
TL;DR: The result of this case study proves that the federated Cloud computing model significantly improves the application QoS requirements under fluctuating resource and service demand patterns.
Journal ArticleDOI
Genetic Algorithms and the Optimal Allocation of Trials
TL;DR: This study gives a formal setting to the difficult optimization problems characterized by the conjunction of substantial complexity and initial uncertainty, and the necessity of acquiring new models to solve these problems.
Proceedings ArticleDOI
Dynamic Placement of Virtual Machines for Managing SLA Violations
TL;DR: A dynamic server migration and consolidation algorithm is introduced and is shown to provide substantial improvement over static server consolidation in reducing the amount of required capacity and the rate of service level agreement violations.
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