Journal ArticleDOI
CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms
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TLDR
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.Abstract:
Cloud computing is a recent advancement wherein IT infrastructure and applications are provided as ‘services’ to end-users under a usage-based payment model. It can leverage virtualized services even on the fly based on requirements (workload patterns and QoS) varying with time. The application services hosted under Cloud computing model have complex provisioning, composition, configuration, and deployment requirements. Evaluating the performance of Cloud provisioning policies, application workload models, and resources performance models in a repeatable manner under varying system and user configurations and requirements is difficult to achieve. To overcome this challenge, we propose CloudSim: an extensible simulation toolkit that enables modeling and simulation of Cloud computing systems and application provisioning environments. The CloudSim toolkit supports both system and behavior modeling of Cloud system components such as data centers, virtual machines (VMs) and resource provisioning policies. It implements generic application provisioning techniques that can be extended with ease and limited effort. Currently, it supports modeling and simulation of Cloud computing environments consisting of both single and inter-networked clouds (federation of clouds). Moreover, it exposes custom interfaces for implementing policies and provisioning techniques for allocation of VMs under inter-networked Cloud computing scenarios. Several researchers from organizations, such as HP Labs in U.S.A., are using CloudSim in their investigation on Cloud resource provisioning and energy-efficient management of data center resources. The usefulness of CloudSim is demonstrated by a case study involving dynamic provisioning of application services in the hybrid federated clouds environment. 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. Copyright © 2010 John Wiley & Sons, Ltd.read more
Citations
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Journal ArticleDOI
Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment.
Syed Hamid Hussain Madni,Syed Hamid Hussain Madni,Muhammad Shafie Abd Latiff,Mohammed Abdullahi,Mohammed Abdullahi,Shafi’i Muhammad Abdulhamid,Mohammed Joda Usman +6 more
TL;DR: Six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput.
Journal ArticleDOI
An improved Lévy based whale optimization algorithm for bandwidth-efficient virtual machine placement in cloud computing environment
TL;DR: This paper focuses on solving VM placement problem with respect to the available bandwidth which is formulated as variable sized bin packing problem and a new bandwidth allocation policy is developed and hybridized with an improved variant of whales optimization algorithm (WOA) called improved Lévy based whale optimization algorithm.
Journal ArticleDOI
MORM: A Multi-objective Optimized Replication Management strategy for cloud storage cluster
TL;DR: Experimental results conclusively demonstrate that the proposed Multi-objective Optimized Replication Management (MORM) is energy effective and outperforms default replication management of HDFS and MOE (Multi-objectives Evolutionary) algorithm in terms of performance and load balancing for large-scale cloud storage cluster.
Journal ArticleDOI
Using Proactive Fault-Tolerance Approach to Enhance Cloud Service Reliability
TL;DR: An initial virtual cluster allocation algorithm is proposed according to the VM characteristics to reduce the total network resource consumption and total energy consumption in the data center and migration VMs from a detected deteriorating PM to some optimal PMs is modeled as an optimization problem that is solved using an improved particle swarm optimization algorithm.
Journal ArticleDOI
A PSO‐based task scheduling algorithm improved using a load‐balancing technique for the cloud computing environment
TL;DR: This paper presents a static task scheduling method based on the particle swarm optimization (PSO) algorithm where the tasks are assumed to be non‐preemptive and independent and is compared with round robin task scheduling, improved PSO task scheduling and a load‐balancing technique.
References
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Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility
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The GRID: Blueprint for a New Computing Infrastructure
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Journal ArticleDOI
GridSim: a toolkit for the modeling and simulation of distributed resource management and scheduling for Grid computing
Rajkumar Buyya,Manzur Murshed +1 more
TL;DR: This work states that clusters, Grids, and peer‐to‐peer (P2P) networks have emerged as popular paradigms for next generation parallel and distributed computing and introduces a number of resource management and application scheduling challenges in the domain of security, resource and policy heterogeneity, fault tolerance, continuously changing resource conditions, and politics.
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