The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Cloud-TM: An Elastic, Self-Tuning Transactional Store for the Cloud
Abstract
By shifting data and computation away from local servers towards very large scale, world-wide spread data centers, Cloud Computing promises very compelling benefits for both cloud consumers and cloud service providers: freeing corporations from large IT capital investments via usage-based pricing schemes, drastically lowering barriers to entry and capital costs; leveraging the economies of scale for both services providers and users of the cloud; facilitating deployment of services; attaining unprecedented scalability levels. However, the promise of infinite scalability catalyzing much of the recent hype about Cloud Computing is still menaced by one major pitfall: the lack of programming paradigms and abstractions capable of bringing the power of parallel programming into the hands of ordinary programmers. This chapter describes Cloud-TM, a self-optimizing middleware platform aimed at simplifying the development and administration of applications deployed on large scale Cloud Computing infrastructures.
Related Content
Dina Darwish.
© 2024.
43 pages.
|
Kassim Kalinaki, Musau Abdullatif, Sempala Abdul-Karim Nasser, Ronald Nsubuga, Julius Kugonza.
© 2024.
23 pages.
|
Yogita Yashveer Raghav, Ramesh Kait.
© 2024.
17 pages.
|
Renuka Devi Saravanan, Shyamala Loganathan, Saraswathi Shunmuganathan.
© 2024.
21 pages.
|
Veera Talukdar, Ardhariksa Zukhruf Kurniullah, Palak Keshwani, Huma Khan, Sabyasachi Pramanik, Ankur Gupta, Digvijay Pandey.
© 2024.
30 pages.
|
Dharmesh Dhabliya, Sukhvinder Singh Dari, Nitin N. Sakhare, Anish Kumar Dhablia, Digvijay Pandey, Balakumar Muniandi, A. Shaji George, A. Shahul Hameed, Pankaj Dadheech.
© 2024.
9 pages.
|
Avtar Singh, Shobhana Kashyap.
© 2024.
11 pages.
|
|
|