Barbara Panicucci
University of Pisa
21 Papers
248 Citations
Barbara Panicucci is an academic researcher from University of Pisa. The author has contributed to research in topics: Variational inequality & Cloud computing. The author has an hindex of 14, co-authored 21 publications. Previous affiliations of Barbara Panicucci include Polytechnic University of Milan & University of Modena and Reggio Emilia.
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Papers
Energy-Aware Autonomic Resource Allocation in Multitier Virtualized Environments
TL;DR: The main novelty of the approach is to address-in a unifying framework-service centers resource management by exploiting as actuation mechanisms allocation of virtual machines to servers, load balancing, capacity allocation, server power state tuning, and dynamic voltage/frequency scaling.
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Generalized Nash Equilibria for the Service Provisioning Problem in Multi-Cloud Systems
TL;DR: This paper model the service provisioning problem as a generalized Nash game and shows the existence of equilibria for such game, and proposes and proves two solution methods based on the best-reply dynamics that can improve the efficiency of the cloud system evaluated in terms of Price of Anarchy.
A game theoretic formulation of the service provisioning problem in cloud systems
Danilo Ardagna,Barbara Panicucci,Mauro Passacantando +2 more
- 28 Mar 2011
TL;DR: This paper model the service provisioning problem as a Generalized Nash game, and proposes an efficient algorithm for the run time management and allocation of IaaS resources to competing SaaSs.
A Hierarchical Approach for the Resource Management of Very Large Cloud Platforms
TL;DR: A scalable distributed hierarchical framework based on a mixed-integer nonlinear optimization of resource management acting at multiple timescales is presented to devise resource allocation policies for virtualized cloud environments that satisfy performance and availability guarantees and minimize energy costs in very large cloud service centers.
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Dual time-scale distributed capacity allocation and load redirect algorithms for cloud systems
TL;DR: A distributed solution which integrates workload prediction and distributed non-linear optimization techniques to minimize the costs of allocated resources in terms of virtual machines, while guaranteeing SLA constraints expressed as a threshold on the average response time is proposed.
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