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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
Mobility-aware Offloading and Resource Allocation for Distributed Services Collaboration
Haowei Chen,Shuguang Deng,Hongbo Zhu,Hailiang Zhao,Rong Jiang,Schahram Dustdar,Albert Y. Zomaya +6 more
TL;DR: This work study the service collaboration with master-slave dependency among service chains of MUs and formulate this combinational optimization problem as a mix integer non-linear programming (MINLP) problem and derive the closed-form expression of resource allocation solution by convex optimization and transform it to integer linear programming (ILP) problem.
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Resilient virtual communication networks using multi-commodity flow based local optimal mapping
TL;DR: A novel virtual network restoration approach, MFP-VNMH, is presented, which could enhance the VN mapping and service restoration subject to the physical link failure in the physical substrate whilst avoiding the remapping of the overall VNs.
Journal Article
Coevolution and evolving parallel cellular automata-based scheduling algorithms
TL;DR: In this article, an approach called a selected neighborhood is used to design a structure of cellular automata (CAs) for a given program graph, and a Coevolutionary Genetic Algorithm (GA) to discover rules of parallel CAs, suitable for solving the scheduling problem is proposed.
Journal ArticleDOI
Note on the Hankel matrix
V. Sreeram,Albert Y. Zomaya +1 more
TL;DR: In this paper, a new property of Hankel matrix is presented which can be used to compute the characteristic polynomial of the system from the measurements of its impulse response data.
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Computing Hierarchical Summary from Two-Dimensional Big Data Streams
TL;DR: A new concept, which can capture the sequential nature of the relationship between pairs of hierarchical items at multiple concept levels and can capture local contextual patterns within the context of the global patterns, is introduced.