4,058 research outputs found
Cloudbus Toolkit for Market-Oriented Cloud Computing
This keynote paper: (1) presents the 21st century vision of computing and
identifies various IT paradigms promising to deliver computing as a utility;
(2) defines the architecture for creating market-oriented Clouds and computing
atmosphere by leveraging technologies such as virtual machines; (3) provides
thoughts on market-based resource management strategies that encompass both
customer-driven service management and computational risk management to sustain
SLA-oriented resource allocation; (4) presents the work carried out as part of
our new Cloud Computing initiative, called Cloudbus: (i) Aneka, a Platform as a
Service software system containing SDK (Software Development Kit) for
construction of Cloud applications and deployment on private or public Clouds,
in addition to supporting market-oriented resource management; (ii)
internetworking of Clouds for dynamic creation of federated computing
environments for scaling of elastic applications; (iii) creation of 3rd party
Cloud brokering services for building content delivery networks and e-Science
applications and their deployment on capabilities of IaaS providers such as
Amazon along with Grid mashups; (iv) CloudSim supporting modelling and
simulation of Clouds for performance studies; (v) Energy Efficient Resource
Allocation Mechanisms and Techniques for creation and management of Green
Clouds; and (vi) pathways for future research.Comment: 21 pages, 6 figures, 2 tables, Conference pape
Notes on Cloud computing principles
This letter provides a review of fundamental distributed systems and economic
Cloud computing principles. These principles are frequently deployed in their
respective fields, but their inter-dependencies are often neglected. Given that
Cloud Computing first and foremost is a new business model, a new model to sell
computational resources, the understanding of these concepts is facilitated by
treating them in unison. Here, we review some of the most important concepts
and how they relate to each other
Security supportive energy-aware scheduling and energy policies for cloud environments
Cloud computing (CC) systems are the most popular computational environments for providing elastic
and scalable services on a massive scale. The nature of such systems often results in energy-related
problems that have to be solved for sustainability, cost reduction, and environment protection.
In this paper we defined and developed a set of performance and energy-aware strategies for resource
allocation, task scheduling, and for the hibernation of virtual machines. The idea behind this model is to
combine energy and performance-aware scheduling policies in order to hibernate those virtual machines
that operate in idle state. The efficiency achieved by applying the proposed models has been tested using
a realistic large-scale CC system simulator. Obtained results show that a balance between low energy
consumption and short makespan can be achieved.
Several security constraints may be considered in this model. Each security constraint is characterized
by: (a) Security Demands (SD) of tasks; and (b) Trust Levels (TL) provided by virtual machines. SD and TL
are computed during the scheduling process in order to provide proper security services.
Experimental results show that the proposed solution reduces up to 45% of the energy consumption
of the CC system. Such significant improvement was achieved by the combination of an energy-aware
scheduler with energy-efficiency policies focused on the hibernation of VMs.COST Action IC140
Chapter Globally Optimised Energy-Efficient Data Centres
A great deal of energy in Information and Communication Technology (ICT) systems can be wasted by software, regardless of how energy-efficient the underlying hardware is. To avoid such waste, programmers need to understand the energy consumption of programs during the development process rather than waiting to measure energy after deployment. Such understanding is hindered by the large conceptual gap from hardware, where energy is consumed, to high-level languages and programming abstractions. The approaches described in this chapter involve two main topics: energy modelling and energy analysis. The purpose of modelling is to attribute energy values to programming constructs, whether at the level of machine instructions, intermediate code or source code. Energy analysis involves inferring the energy consumption of a program from the program semantics along with an energy model. Finally, the chapter discusses how energy analysis and modelling techniques can be incorporated in software engineering tools, including existing compilers, to assist the energy-aware programmer to optimise the energy consumption of code
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