Abstract
Cloud Computing is one of the revolutionized paradigms in the IT industry, which can provide wide variety of services pay-as-you go model to all the customers in different domains like IT industry, Health, education, entertainment etc. These services are provisioned to the user based on the SLA between cloud user and provider virtually. Hypervisors are used to enable the virtualization and to spin up VMs in the cloud paradigm. There are different levels at which virtualization can be implemented, In this book chapter, we are discussing about the overview of cloud computing, different service models, deployment models and different virtualization techniques used for cloud paradigm. For effectiveness of any cloud computing paradigm, a task scheduler is necessary to get seamless services from cloud paradigm. Therefore, in this chapter we have proposed a task scheduling algorithm which uses priorities of tasks and VMs. For this algorithm we have used a nature inspired algorithm chaotic social spider algorithm to model task scheduling algorithm and simulated on CloudSim simulator. Finally, it was compared with existing algorithms PSO and CS and proposed approach is outperformed over existing algorithms with respect to makespan and energy consumption.
| Original language | English |
|---|---|
| Title of host publication | Convergence of Cloud with AI for Big Data Analytics |
| Subtitle of host publication | Foundations and Innovation |
| Publisher | wiley |
| Pages | 13-40 |
| Number of pages | 28 |
| ISBN (Electronic) | 9781119905233 |
| ISBN (Print) | 9781119904885 |
| DOIs | |
| Publication status | Published - 01-01-2024 |
All Science Journal Classification (ASJC) codes
- General Computer Science