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Albert Y. Zomaya
Researcher at University of Sydney
Publications - 1020
Citations - 30827
Albert Y. Zomaya is an academic researcher from University of Sydney. The author has contributed to research in topics: Cloud computing & Scheduling (computing). The author has an hindex of 75, co-authored 946 publications receiving 24637 citations. Previous affiliations of Albert Y. Zomaya include University of Alabama & University of Sheffield.
Papers
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Journal ArticleDOI
A note on advances in scheduling algorithms for Cyber-Physical-Social workflows
TL;DR: This includes one research survey paper that gives an interesting overview of the privacy aspects in cyber physical social environments and three papers related to scheduling algorithms and techniques for CPS-DS workflow applications.
Book ChapterDOI
Local Resource Consumption Shaping: A Case for MapReduce
TL;DR: In this paper, the authors consider the problem of local resource consumption shaping, an alternative to fair resource sharing at the local node/core level, to improve the performance of MapReduce.
Journal ArticleDOI
A Weighted Optimal Scheduling Scheme for Congestion Control in Cloud Data Center Networks
TL;DR: Wang et al. as mentioned in this paper proposed a weighted optimal scheduling scheme WSPR for congestion control in cloud data center networks which prevents the congestion in advance with the global view so that it can make good use of vacant network resources.
Posted Content
Privacy Knowledge Modelling for Internet of Things: A Look Back
TL;DR: This paper reviews how privacy knowledge has been modelled and used in the past in different domains, and appreciates their findings and discusses their applicability towards the IoT.
Proceedings ArticleDOI
Dynamic Control of CPU Cap Allocations in Stream Processing and Data-Flow Platforms
TL;DR: A technique to define CPU resource allocation (i.e., CPU capping) with the goal to improve response time latency in such type of applications with different quality of service (QoS) level, as they are concurrently running in a shared multi-core computing system with unknown and volatile demand.