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Nasiriasayesh H, Yari A, Nazemi E. Adaptive IWD-based algorithm for deployment of business processes into cloud federations. INTERNATIONAL JOURNAL OF PERVASIVE COMPUTING AND COMMUNICATIONS 2021. [DOI: 10.1108/ijpcc-10-2020-0159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Purpose
The concept of business process (BP) as a service is a new solution in enterprises for the purpose of using specific BPs. BPs represent combinations of software services that must be properly executed by the resources provided by a company’s information technology infrastructure. As the policy requirements are different in each enterprise, processes are constantly evolving and demanding new resources in terms of computation and storage. To support more agility and flexibility, it is common today for enterprises to outsource their processes to clouds and, more recently, to cloud federation environment. Ensuring the optimal allocation of cloud resources to process service during the execution of workflows in accordance with user policy requirements is a major concern. Given the diversity of resources available in a cloud federation environment and the ongoing process changes required based on policies, reallocating cloud resources for service processing may lead to high computational costs and increased overheads in communication costs.
Design/methodology/approach
This paper presents a new adaptive resource allocation approach that uses a novel algorithm extending the natural-based intelligent water drops (IWD) algorithm that optimizes the resource allocation of workflows on the cloud federation which can estimate and optimize final deployment costs. The proposed algorithm is implemented and embedded within the WokflowSim simulation toolkit and tested in different simulated cloud environments with different workflow models.
Findings
The algorithm showed noticeable enhancements over the classical workflow deployment algorithms taking into account the challenges of data transfer. This paper made a comparison between the proposed IWD-based workflow deployment (IWFD) algorithm with other proposed algorithms. IWFD presented considerable improvements in the makespan, cost and data transfer in most situations in the cloud federation environment.
Originality/value
An extension for WorkflowSim to support the implementation of BPs in a federation cloud space regarding BP policy. Optimize workflow execution performance in Federated clouds by means of IWFD algorithm.
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Ran W, Liu H. Cloud service selection based on QoS-aware logistics. Soft comput 2020. [DOI: 10.1007/s00500-019-04196-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Zhang Y, Xiang Y, Zhang LY, Yang LX, Zhou J. Efficiently and securely outsourcing compressed sensing reconstruction to a cloud. Inf Sci (N Y) 2019. [DOI: 10.1016/j.ins.2019.05.024] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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VASILE MA, POP F, NIŢĂ MC, CRISTEA V. MLBox: Machine learning box for asymptotic scheduling. Inf Sci (N Y) 2018. [DOI: 10.1016/j.ins.2017.01.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Elsherbiny S, Eldaydamony E, Alrahmawy M, Reyad AE. An extended Intelligent Water Drops algorithm for workflow scheduling in cloud computing environment. EGYPTIAN INFORMATICS JOURNAL 2018. [DOI: 10.1016/j.eij.2017.07.001] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Pradeep K, Jacob TP. CGSA scheduler: A multi-objective-based hybrid approach for task scheduling in cloud environment. INFORMATION SECURITY JOURNAL: A GLOBAL PERSPECTIVE 2017. [DOI: 10.1080/19393555.2017.1407848] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- K. Pradeep
- Department of Computer Science and Engineering, Sathyabama University, St. Joseph’s College of Engineering, Chennai, Tamilnadu, India
| | - T. Prem Jacob
- Department of Computer Science and Engineering, Sathyabama University, Chennai, Tamilnadu, India
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CS-PSO: chaotic particle swarm optimization algorithm for solving combinatorial optimization problems. Soft comput 2016. [DOI: 10.1007/s00500-016-2383-8] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Babiceanu RF, Seker R. Big Data and virtualization for manufacturing cyber-physical systems: A survey of the current status and future outlook. COMPUT IND 2016. [DOI: 10.1016/j.compind.2016.02.004] [Citation(s) in RCA: 301] [Impact Index Per Article: 33.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Rostami S, Shenfield A. A multi-tier adaptive grid algorithm for the evolutionary multi-objective optimisation of complex problems. Soft comput 2016. [DOI: 10.1007/s00500-016-2227-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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