Cloud computing has created a shift from the use of physical hardware and locally managed software-enabled platforms to that of virtualized cloud-hosted services. Cloud assembles large networks of virtual services, including hardware (CPU, storage, and network) and software resources (databases, message queuing systems, monitoring systems, and load-balancers). As Cloud continues to revolutionize applications in academia, industry, government, and many other fields, the transition to this efficient and flexible platform presents serious challenges at both theoretical and practical levelsones that will often require new approaches and practices in all areas. Comprehensive and timely, Cloud Computing: Methodology, Systems, and Applications summarizes progress in state-of-the-art research and offers step-by-step instruction on how to implement it. Summarizes Cloud Developments, Identifies Research Challenges, and Outlines Future Directions Ideal for a broad audience that includes researchers, engineers, IT professionals, and graduate students, this book is designed in three sections: Fundamentals of Cloud Computing: Concept, Methodology, and Overview Cloud Computing Functionalities and Provisioning Case Studies, Applications, and Future Directions It addresses the obvious technical aspects of using Cloud but goes beyond, exploring the cultural/social and regulatory/legal challenges that are quickly coming to the forefront of discussion. Properly applied as part of an overall IT strategy, Cloud can help small and medium business enterprises (SMEs) and governments in optimizing expenditure on application-hosting infrastructure. This material outlines a strategy for using Cloud to exploit opportunities in areas including, but not limited to, government, research, business, high-performance computing, web hosting, social networking, and multimedia. With contributions from a host of internationally recognized researchers, this reference delves into everything from necessary changes in users initial mindset to actual physical requirements for the successful integration of Cloud into existing in-house infrastructure. Using case studies throughout to reinforce concepts, this book also addresses recent advances and future directions in methodologies, taxonomies, IaaS/SaaS, data management and processing, programming models, and applications.
Cited By
- Garg S, Aryal J, Wang H, Shah T, Kecskemeti G and Ranjan R (2018). Cloud computing based bushfire prediction for cyberphysical emergency applications, Future Generation Computer Systems, 79:P1, (354-363), Online publication date: 1-Feb-2018.
- Li K (2018). Energy constrained scheduling of stochastic tasks, The Journal of Supercomputing, 74:1, (485-508), Online publication date: 1-Jan-2018.
- Weerasiri D, Barukh M, Benatallah B, Sheng Q and Ranjan R (2017). A Taxonomy and Survey of Cloud Resource Orchestration Techniques, ACM Computing Surveys, 50:2, (1-41), Online publication date: 31-Mar-2018.
- Zeng X, Garg S, Strazdins P, Jayaraman P, Georgakopoulos D and Ranjan R (2017). IOTSim, Journal of Systems Architecture: the EUROMICRO Journal, 72:C, (93-107), Online publication date: 1-Jan-2017.
- Zeng X, Ranjan R, Strazdins P, Garg S and Wang L Cross-layer SLA management for cloud-hosted big data analytics applications Proceedings of the 15th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, (765-768)
- Cao Y, Lu H, Shi X and Duan P Evaluation Model of the Cloud Systems Based on Queuing Petri Net Proceedings of the ICA3PP International Workshops and Symposiums on Algorithms and Architectures for Parallel Processing - Volume 9532, (413-423)
- Chaudhuri A, Maity S and Ghosh S QoS prediction for network data traffic using hierarchical modified regularized least squares rough support vector regression Proceedings of the 30th Annual ACM Symposium on Applied Computing, (659-661)
- Gupte N and Wang J Securely outsourcing power grid simulation on cloud Proceedings of the 24th edition of the great lakes symposium on VLSI, (225-226)
- Zhang M, Ranjan R, Nepal S, Menzel M and Haller A A declarative recommender system for cloud infrastructure services selection Proceedings of the 9th international conference on Economics of Grids, Clouds, Systems, and Services, (102-113)