R
Rajkumar Buyya
Researcher at University of Melbourne
Publications - 1143
Citations - 108162
Rajkumar Buyya is an academic researcher from University of Melbourne. The author has contributed to research in topics: Cloud computing & Grid computing. The author has an hindex of 133, co-authored 1066 publications receiving 95164 citations. Previous affiliations of Rajkumar Buyya include Walter and Eliza Hall Institute of Medical Research & Infosys.
Papers
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Journal ArticleDOI
Energy Efficient Scheduling of Cloud Application Components with Brownout
TL;DR: In this paper, a combined brownout approach is proposed to reduce energy consumption through selectively and dynamically deactivating application optional components, which can also be applied to self-contained microservices.
Proceedings ArticleDOI
An architecture for virtual organization (VO)-based effective peering of content delivery networks
TL;DR: This paper presents an architecture to support peering arrangements among CDN providers, based on a Virtual Organization (VO) model, and shows analytically that significant performance improvement can be achieved through the peering of CDNs.
Book ChapterDOI
Parity Logging Overcoming the Small Write Problem in Redundant Disk Arrays
TL;DR: Parity logging provides performance competitive with mirroring, the best of the alternative single failure tolerating disk array organizations; its overhead cost is close to the minimum offered by RAID level 5; and it can exploit data caching much more effectively than all three alternative approaches.
Journal ArticleDOI
A Deadline-Constrained Multi-Objective Task Scheduling Algorithm in Mobile Cloud Environments
Li Liu,Qi Fan,Rajkumar Buyya +2 more
TL;DR: A heterogeneous earliest finish time (HEFT) using technique for order preference by similarity to an ideal solution method is proposed, which is named as HEFT-T algorithm, which performs better in the criterion of both the optimization for total cost as well as mean load, and the deadline-constraint meeting rate.
Proceedings ArticleDOI
Rescheduling co-allocation requests based on flexible advance reservations and processor remapping
Marco A. S. Netto,Rajkumar Buyya +1 more
TL;DR: The experimental results show that local jobs may not fill all the fragments in the scheduling queues and hence rescheduling co-allocation requests reduces response time of both local and multi-site jobs.