Genetic Algorithm Based QoS-aware Service Composition in Multi-cloud

2015 ◽  
Author(s):  
Miao Zhang ◽  
Li Liu ◽  
Songtao Liu
Keyword(s):  
Genetic Algorithm ◽  
Service Composition ◽  
Multi Cloud

A memetic grouping genetic algorithm for cost efficient VM placement in multi-cloud environment

2019 ◽  
Vol 23 (2) ◽  
pp. 797-836 ◽  
Author(s):  
Seyedeh Yasaman Rashida ◽  
Masoud Sabaei ◽  
Mohammad Mehdi Ebadzadeh ◽  
Amir Masoud Rahmani
Keyword(s):  
Genetic Algorithm ◽  
Cloud Environment ◽  
Vm Placement ◽  
Grouping Genetic Algorithm ◽  
Cost Efficient ◽  
Multi Cloud

scholarly journals Service Composition in IoT using Genetic algorithm and Particle swarm optimization

2020 ◽  
Vol 10 (1) ◽  
pp. 56-64 ◽  
Author(s):  
Neeti Kashyap ◽  
A. Charan Kumari ◽  
Rita Chhikara
Keyword(s):  
Genetic Algorithm ◽  
Quality Of Service ◽  
Particle Swarm Optimization ◽  
Service Composition ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Pso Algorithm ◽  
Critical Issue ◽  
Swarm Optimization

AbstractWeb service compositions are commendable in structuring innovative applications for different Internet-based business solutions. The existing services can be reused by the other applications via the web. Due to the availability of services that can serve similar functionality, suitable Service Composition (SC) is required. There is a set of candidates for each service in SC from which a suitable candidate service is picked based on certain criteria. Quality of service (QoS) is one of the criteria to select the appropriate service. A standout amongst the most important functionality presented by services in the Internet of Things (IoT) based system is the dynamic composability. In this paper, two of the metaheuristic algorithms namely Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are utilized to tackle QoS based service composition issues. QoS has turned into a critical issue in the management of web services because of the immense number of services that furnish similar functionality yet with various characteristics. Quality of service in service composition comprises of different non-functional factors, for example, service cost, execution time, availability, throughput, and reliability. Choosing appropriate SC for IoT based applications in order to optimize the QoS parameters with the fulfillment of user’s necessities has turned into a critical issue that is addressed in this paper. To obtain results via simulation, the PSO algorithm is used to solve the SC problem in IoT. This is further assessed and contrasted with GA. Experimental results demonstrate that GA can enhance the proficiency of solutions for SC problem in IoT. It can also help in identifying the optimal solution and also shows preferable outcomes over PSO.

scholarly journals MultiCuckoo: Multi-Cloud Service Composition Using a Cuckoo-Inspired Algorithm for the Internet of Things Applications

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 56737-56749 ◽  
Author(s):  
Heba Kurdi ◽  
Fadwa Ezzat ◽  
Lina Altoaimy ◽  
Syed Hassan Ahmed ◽  
Kamal Youcef-Toumi
Keyword(s):  
Internet Of Things ◽  
Service Composition ◽  
Cloud Service ◽  
The Internet ◽  
Cloud Service Composition ◽  
The Internet Of Things ◽  
Multi Cloud

scholarly journals An Efficient Multi-Cloud Service Composition Using A Distributed Multiagent-based, Memory-driven Approach

2019 ◽  
pp. 1-1 ◽  
Author(s):  
Phillip Kendrick ◽  
Thar Baker ◽  
Zakaria Maamar ◽  
Abir Hussain ◽  
Rajkumar Buyya ◽  
...  
Keyword(s):  
Service Composition ◽  
Cloud Service ◽  
Cloud Service Composition ◽  
Multi Cloud
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