Proceedings ArticleDOI
A novel architecture for task scheduling based on Dynamic Queues and Particle Swarm Optimization in cloud computing
Hicham Ben Alla,Said Ben Alla,Abdellah Ezzati +2 more
- pp 108-114
TLDR
A novel architecture to schedule the tasks in cloud computing on the basis of a new Dynamic Dispatch Queues Algorithm (DDQA) and Particle Swarm Optimization (PSO) algorithm is proposed.Abstract:
Task scheduling is one of the most challenging aspects in cloud computing nowadays, which plays an important role to improve the overall performance and services of the cloud such as response time, cost, makespan, throughput etc. Mostly a non-optimal task scheduling algorithm can be a key tool in over utilization or under utilization of cloud resources. In order to solve these problems, this paper proposes a novel architecture to schedule the tasks in cloud computing on the basis of a new Dynamic Dispatch Queues Algorithm (DDQA) and Particle Swarm Optimization (PSO) algorithm. The proposed algorithm DDQA-PSO gives full consideration to the dynamic characteristics of the cloud computing environment. The experimental results based on CloudSim simulator show that the proposed architecture can effectively achieve good performance, load balancing, and improve the resource utilization.read more
Citations
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Journal ArticleDOI
Task Scheduling in Cloud Computing based on Meta-heuristics: Review, Taxonomy, Open Challenges, and Future Trends
TL;DR: In this paper, the authors provide a brief on traditional and heuristic scheduling methods before diving deeply into the most popular meta-heuristics for cloud task scheduling followed by a detailed systematic review featuring a novel taxonomy of those techniques, along with their advantages and limitations.
Journal ArticleDOI
Task Scheduling Based on a Hybrid Heuristic Algorithm for Smart Production Line with Fog Computing.
Juan Wang,Di Li +1 more
TL;DR: A task scheduling strategy based on a hybrid heuristic (HH) algorithm is proposed that mainly solves the problem of terminal devices with limited computing resources and high energy consumption and makes the scheme feasible for real-time and efficient processing tasks of terminal device.
Journal ArticleDOI
Ranging and tuning based particle swarm optimization with bat algorithm for task scheduling in cloud computing
R. Valarmathi,T. Sheela +1 more
TL;DR: A ranging function and tuning function based PSO (RTPSO) based on data locality is introduced in this paper for solving the inertia weight assignment problem in existing PSO algorithm for task scheduling.
Proceedings ArticleDOI
A multi-Agent based model for task scheduling in cloud-fog computing platform
TL;DR: This paper considers task scheduling in a cloud-fog computing platform, and proposes a multi-agent based model that aims at serving the most important task first, taking into consideration the task priority, its wait time, its status and the resources required to complete it successfully.
Book ChapterDOI
A Priority Based Task Scheduling in Cloud Computing Using a Hybrid MCDM Model
TL;DR: This paper proposes a new Dynamic Priority-Queue (DPQ) approach based on a hybrid multi-criteria decision making (MCDM) namely ELECTRE III and Differential Evolution and introduces a hybrid meta-heuristic algorithm based on Particle Swarm Optimization and Simulated Annealing.
References
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Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
ReportDOI
The NIST Definition of Cloud Computing
Peter Mell,Timothy Grance +1 more
TL;DR: This cloud model promotes availability and is composed of five essential characteristics, three service models, and four deployment models.
Journal ArticleDOI
The particle swarm - explosion, stability, and convergence in a multidimensional complex space
M. Clerc,James Kennedy +1 more
TL;DR: This paper analyzes a particle's trajectory as it moves in discrete time, then progresses to the view of it in continuous time, leading to a generalized model of the algorithm, containing a set of coefficients to control the system's convergence tendencies.
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.
Proceedings ArticleDOI
A discrete binary version of the particle swarm algorithm
TL;DR: The paper reports a reworking of the particle swarm algorithm to operate on discrete binary variables, where trajectories are changes in the probability that a coordinate will take on a zero or one value.