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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
Numerical Computation of Differential-Algebraic Equations for Non-Linear Dynamics of Multibody Systems Involving Contact Forces
TL;DR: In this article, the Euler-Lagrange equations of motion for constrained variational problems are derived using the principle of virtual work, which are used in the modelling of multibody systems and result in differential-algebraic equations of high index.
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Dynamical Service Deployment and Replacement in Resource-Constrained Edges
TL;DR: A prototype of service provisioning system that simulates the behaviors between users and servers is designed and an approach to deploy services on edge servers before the launching of these servers is proposed, and the result shows that this approach can improve the performance of service Provisioning systems.
Journal ArticleDOI
DronePrint: Acoustic Signatures for Open-set Drone Detection and Identification with Online Data
Harini Kolamunna,Thilini Dahanayaka,Junye Li,Suranga Seneviratne,Kanchana Thilakaratne,Albert Y. Zomaya,Aruna Seneviratne +6 more
TL;DR: In this paper, the authors used drone acoustic signatures to detect the presence of a drone and identify the make and the model of the drone, which achieved 96% accuracy in a closed-set scenario, and 86% accuracy for a more challenging open-set case.
Proceedings ArticleDOI
Just Satisfactory Resource Provisioning for Parallel Applications in the Cloud
TL;DR: The paper discusses a resource management method at the cloud tenant level that makes initial resource leasing plan based on client request profile and performance targets in service level agreements (SLAs) and dynamically adjusts resource allocation based on monitoring data.
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A Multi-objective Optimization Scheme for Job Scheduling in Sustainable Cloud Data Centers
TL;DR: A multi-objective optimization problem for job scheduling and VM placement is formulated with respect to parameters such as service level agreement (SLA), energy cost, carbon footprint rate (CFR), and availability of RES and is solved using an enhanced heuristic approach based on a greedy strategy.