BlueTool: Using a Computing Systems Research Infrastructure Tool to Design and Test Green and Sustainable Data Centers

2013 ◽  
pp. 143-156
Keyword(s):  
Data Centers ◽  
Research Infrastructure ◽  
Computing Systems ◽  
Systems Research

International Virtual Observatory Alliance

2006 ◽  
Vol 2 (14) ◽  
pp. 528-529 ◽  
Author(s):  
Masatoshi Ohishi
Keyword(s):  
21St Century ◽  
Data Centers ◽  
Research Infrastructure ◽  
Technical Development ◽  
Virtual Observatory ◽  
Astronomical Data ◽  
Priority Areas

AbstractThe International Virtual Observatory Alliance is briefly introduced as a concensus-based group to construct International Virtual Observatory – a new, planet-wide research infrastructure for the 21st century astronomy. Standardized protocols by the IVOA were used to interconnect more than 10 astronomical obsrvatories and data centers to provide astronomers with multiwavelength astronomical data. The priority areas for technical development and planned developments are described.

scholarly journals Heuristic algorithms for joint optimization of unicast and anycast traffic in elastic optical network–based large–scale computing systems

2017 ◽  
Vol 27 (3) ◽  
pp. 605-622 ◽  
Author(s):  
Marcin Markowski
Keyword(s):  
Optical Networks ◽  
Wavelength Division Multiplexing ◽  
Data Center ◽  
Large Scale ◽  
Data Centers ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Approximate Solutions ◽  
Computing Systems ◽  
Large Scale Computing

AbstractIn recent years elastic optical networks have been perceived as a prospective choice for future optical networks due to better adjustment and utilization of optical resources than is the case with traditional wavelength division multiplexing networks. In the paper we investigate the elastic architecture as the communication network for distributed data centers. We address the problems of optimization of routing and spectrum assignment for large-scale computing systems based on an elastic optical architecture; particularly, we concentrate on anycast user to data center traffic optimization. We assume that computational resources of data centers are limited. For this offline problems we formulate the integer linear programming model and propose a few heuristics, including a meta-heuristic algorithm based on a tabu search method. We report computational results, presenting the quality of approximate solutions and efficiency of the proposed heuristics, and we also analyze and compare some data center allocation scenarios.

scholarly journals Heuristic-based Approach for Dynamic Consolidation of Software Licenses in Cloud Data Centers

2021 ◽  
Vol 13 (6) ◽  
pp. 1-12
Author(s):  
Leila Helali ◽  
◽  
Mohamed Nazih Omri
Keyword(s):  
Cloud Computing ◽  
Data Centers ◽  
Virtual Machines ◽  
Heuristic Algorithms ◽  
Energy Aware ◽  
Computing Systems ◽  
Cloud Data ◽  
Software Licenses ◽  
Cloud Data Centers ◽  
Distributed Cloud

Since its emergence, cloud computing has continued to evolve thanks to its ability to present computing as consumable services paid by use, and the possibilities of resource scaling that it offers according to client’s needs. Models and appropriate schemes for resource scaling through consolidation service have been considerably investigated,mainly, at the infrastructure level to optimize costs and energy consumption. Consolidation efforts at the SaaS level remain very restrained mostly when proprietary software are in hand. In order to fill this gap and provide software licenses elastically regarding the economic and energy-aware considerations in the context of distributed cloud computing systems, this work deals with dynamic software consolidation in commercial cloud data centers 𝑫𝑺𝟑𝑪. Our solution is based on heuristic algorithms and allows reallocating software licenses at runtime by determining the optimal amount of resources required for their execution and freed unused machines. Simulation results showed the efficiency of our solution in terms of energy by 68.85% savings and costs by 80.01% savings. It allowed to free up to 75% physical machines and 76.5% virtual machines and proved its scalability in terms of average execution time while varying the number of software and the number of licenses alternately.

scholarly journals A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems

2011 ◽  
pp. 47-111 ◽  
Author(s):  
Anton Beloglazov ◽  
Rajkumar Buyya ◽  
Young Choon Lee ◽  
Albert Zomaya
Keyword(s):  
Cloud Computing ◽  
Energy Efficient ◽  
Data Centers ◽  
Computing Systems ◽  
Efficient Data
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