A locality-based replication manager for data cloud

Sookhtsaraei, Reza; Artin, Javad; Ghorbani, Ali A.; Faraahi, Ahmad; Adineh, Hadi

doi:10.1631/fitee.1500391

Cited by 6 publications

(1 citation statement)

References 14 publications

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“…7 It is a complex optimization problem that needs to consider different criteria that can meet huge quality of service (QoS) requirements. 8 Many efforts have been made to develop workflow management systems for task scheduling algorithms in grid 9 and cloud [10][11][12] environments. They all contribute to QoS of applications by mapping all instance-intensive tasks in various hardware platforms.…”

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confidence: 99%

Near‐optimal dynamic priority scheduling strategy for instance‐intensive business workflows in cloud computing

Wang

Huang

et al. 2017

Concurrency and Computation

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Summary Utilization of cloud computing resources has made a fast growth in e‐business. Business and government agencies often need to handle large volume of service requests, the so‐called instance‐intensive business processes in a constrained period. On‐time completion for instance‐intensive business processes within the constrained time is a very important issue. In the past few years, traditional optimal task scheduling has been well researched and proven to be a nondeterministic polynomial (NP) time–complete problem. So many heuristic and metaheuristic algorithms are put forward to solve the issue with near‐optimal solutions. However, most of them just treat a single workflow instance as a multistep task without considering that steps within a task can be different types of activities. To explain multistep features of business workflows, a typical motivating instance‐intensive business example of security exchange and a multistep scheduling model for business workflows are introduced in this paper. Then our near‐optimal dynamic priority scheduling (DPS) strategy is proposed on the basis of the idea of Min‐Min heuristic algorithm and greedy philosophy. Compared to the first come first served and constrained Min‐Min by makespan and standard deviation, DPS can make a more optimized choice in each round of scheduling towards overall outcome. To show the effectiveness of DPS, theoretical minimum execution time (METtheory) is used as a benchmark for evaluation based on simulation. The results show that the ratios between METtheory and DPS are more than 98.5% by scheduling different orders of magnitude tasks from 1000 to 1 000 000. In particular, the ratio between METtheory and DPS is nearly 99.9% with 1 000 000 tasks, which means that our DPS can get the near‐optimal result when scheduling large number of tasks.

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confidence: 99%

Near‐optimal dynamic priority scheduling strategy for instance‐intensive business workflows in cloud computing

Wang

Huang

et al. 2017

Concurrency and Computation

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Optimized Data Replication in Cloud Using Hybrid Optimization Approach

Rambabu,

Govardhan

2024

Trans Emerging Tel Tech

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Cloud computing (CC), in contrast to traditional high‐performance computing environments, is a group of imaginary and networked resources of computing that are controlled by one unified maximum‐performance computing power. Here, this work aims to develop a novel data replication method in the cloud. The data replication is carried out with a new multi‐objective technique that considers constraints like cost, the distance between data centers, trust, and risk. Moreover, for optimal data replication, a new hybrid algorithm termed poor rich strategy assisted grasshopper optimization (PRS‐GO) is introduced. To increase the accessibility of the system, the data used continuously should be duplicated in various areas. A minimal mean value of 0.66 is gained with the PRS‐GO scheme, whereas Particle Swarm Optimization‐Tabu Search (PSO + TS), Receding Horizon Control (RHC), Sun Flower Optimization (SFO), Cat Mouse‐Based Optimization (CMBO), Hunger Games Search Optimization (HGSO), Seagull Optimization (SGO), Poor And Rich Optimization (PRO), and Grasshopper Optimization Algorithm (GOA) have got a high mean value of 0.722, 0.71, 0.71, 0.71, 0.7, 0.7, 0.7, and 0.69.

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An Intensive Review of Data Replication Algorithms for Cloud Systems

Dabas

Aggarwal

2019

Emerging Research in Computing, Information, Communication and Applications

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A locality-based replication manager for data cloud

Cited by 6 publications

References 14 publications

Near‐optimal dynamic priority scheduling strategy for instance‐intensive business workflows in cloud computing

Near‐optimal dynamic priority scheduling strategy for instance‐intensive business workflows in cloud computing

Optimized Data Replication in Cloud Using Hybrid Optimization Approach

An Intensive Review of Data Replication Algorithms for Cloud Systems

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