Efficient resource management in the virtualized data center is always a practical concern and has attracted significant attention. In particularly, economic allocation mechanism is desired to maximize the revenue for...
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Efficient resource management in the virtualized data center is always a practical concern and has attracted significant attention. In particularly, economic allocation mechanism is desired to maximize the revenue for commercial cloud providers. This paper uses overbooking from Revenue Management to avoid resource over-provision according to its runtime demand. We propose an economic model to control the overbooking policy while provide users probability based performance guarantee using risk estimation. To cooperate with overbooking policy, we optimize the VM placement with traffic-aware strategy to satisfy application's QoS requirement. We design GreedySelePod algorithm to achieve traffic localization in order to reduce network bandwidth consumption, especially the network bottleneck bandwidth, thus to accept more requests and increase the revenue in the future. The simulation results show that our approach can greatly improve the request acceptance rate and increase the revenue by up to 87% while with acceptable resource confliction.
As the foundation of cloud computing, Server consolidation allows multiple computer infrastructures running as virtual machines in a single physical node. It improves the utilization of most kinds of resource but memo...
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As the foundation of cloud computing, Server consolidation allows multiple computer infrastructures running as virtual machines in a single physical node. It improves the utilization of most kinds of resource but memory under x86 architecture. Because of inaccurate memory usage estimate and the lack of memory resource management, there is much service performance degradation in data centers, even though they have occupied a large amount of memory. Furthermore, memory becomes insufficient for a physical server when a lot of virtual machines depend on it. In order to improve this, we present a dynamic memory scheduling system called DMSS, which can manage memory resources in server consolidation environments and allocate memory among virtual machines on demand. We have designed and implemented the corresponding memory scheduling policy based on Xen virtualization platform to enhance memory efficiency and achieve service level agreement. The benchmark shows that DMSS can make an accurate and rapid response to memory changes and save more than 30% physical memory with less than 5% performance degradation. DMSS actually brings in economic benefits to cloud service providers because more virtual machines can be accommodated at lower costs.
Chemical computing was initially proposed as an intuitive paradigm to capture the essence of parallelcomputing. Within such a model, a program is a solution of information-carrying molecules, that, at run time, colli...
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Chemical computing was initially proposed as an intuitive paradigm to capture the essence of parallelcomputing. Within such a model, a program is a solution of information-carrying molecules, that, at run time, collide non-deterministically to produce new data. Such a paradigm allowed the programmers to focus on the logic of the problem to be solved in parallel, without having to worry about implementation's considerations. Throughout the years, the model has been enriched with various features related to program structure, control and practicability. More importantly, the model was raised to the higher order, increasing again its expressiveness. With the rise of service-orientedcomputing, such models have recently regained a lot of interest. They have been shown to provide adequate abstractions to enhance service-oriented architectures with autonomic properties such as self-adaptation, self-healing, or self-organisation. However, the deployment of chemical programs over large scale distributed platforms is still a widely open problem, hindering the model to be leveraged in practice. This paper studies the possibility of building a distributed execution environment for chemical programs. A generic peer-to-peer-based runtime model and distributed algorithms for large scale chemical computing are discussed. To complete this study, a software prototype was developed and experimented over the Grid'5000 test-bed. Experimental performance results are detailed, allowing for a discussion of the feasibility and performance of such a runtime, thus lifting a barrier towards the enactment of the chemical programming model.
Pervasive computing presents profound privacy risks for end users because its capabilities to monitor, control, and interact with the physical world. As a first step to support early evaluation of potential privacy vi...
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Pervasive computing presents profound privacy risks for end users because its capabilities to monitor, control, and interact with the physical world. As a first step to support early evaluation of potential privacy violations, we introduce PIPER, a framework for the systematic modeling, analysis, and exploration of Privacy Implications in PERvasive computing systems and their physical environments. UML/OCL is used to model important structures and behaviors of these systems as well as data flow properties and privacy requirements. This framework facilitates consideration and explicit specification of the effects of actions in the physical environment and the tracing of data flow through both cyber and physical components of the system. Using this framework, privacy analysts and software engineers can communicate more objectively about privacy-related issues, identify faults in application logic, and examine the impact that changes to either applications or physical environments have on personal privacy in pervasive systems.
This article presents ArCo which is an architecture for managing a digital environment in a context of ambient intelligence. ArCo can integrate all kinds of objects and is totally configurable. Moreover it proposes a ...
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This article presents ArCo which is an architecture for managing a digital environment in a context of ambient intelligence. ArCo can integrate all kinds of objects and is totally configurable. Moreover it proposes a visual programming interface, AmbiProg, which allows controlling each digital object which composes an environment. The objective of this paper is to appraise AmbiProg. An experiment was realized with 16 children around 10 years old. They were asked to realize exercises in a limited period of time. The objective was to determine if programming was easy and how many times they needed to learn scenarios creation. It appeared that they succeed tasks and were able to use AmbiProg. Programming an environment was easy as pie.
An approach in advancing the field of medical robotics is via a more efficient preparation of robotic surgical intervention using accurate simulation. Our intra-operative virtual system for robotic tracheal-oesophagea...
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In the context of parallel and distributed computation, the currently existing numerical libraries do not allow code reuse. Besides, they are not able to exploit the multi-level parallelism offered by many numerical m...
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ISBN:
(纸本)9783642193279
In the context of parallel and distributed computation, the currently existing numerical libraries do not allow code reuse. Besides, they are not able to exploit the multi-level parallelism offered by many numerical methods. A few linear algebra numerical libraries make use of objectoriented approach allowing modularity and extensibility. Nevertheless, those which offer modularity together with sequential and parallel code reuse are almost non-existent. We analyze the lacks in existing libraries and propose a design model based on a component approach and the strict separation between computation operations, data definition and communication control of applications. We present then an implementation of this design using VIAL scientific workflow environment jointly with the objectoriented LAKe (Linear Algebra Kernel) library. Some numerical experiments on GRID5000 platform validate our approach and show its efficiency.
Web software development and cloud computing based on Service-oriented Architecture (SOA) and Service-orientedcomputing (SOC) represent the modern software engineering theories, practices, and technologies. As an arc...
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Current embedded systems offer enough performance to integrate on a single chip jobs that required several distributed devices in the past. The execution environment of such an integrated architecture should satisfy k...
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Modelica is a modern, strongly typed, declarative, equation-based, and object-oriented (EOO) language for modeling and simulation of complex cyber-physical systems. Major features are: ease of use, visual design of mo...
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ISBN:
(纸本)9781424495375
Modelica is a modern, strongly typed, declarative, equation-based, and object-oriented (EOO) language for modeling and simulation of complex cyber-physical systems. Major features are: ease of use, visual design of models with combination of lego-like predefined model building blocks, ability to define model libraries with reusable components, support for modeling and simulation of complex applications involving parts from several application domains, and many more useful facilities. This paper gives an overview of some aspects of the Modelica language and the OpenModelica environment - the most complete Modelica open-source tool for modeling, simulation, and development of Modelica applications. Special features are MetaModeling for efficient model transformations, the ModelicaML profile for UML-Modelica cyber-physical hardware-software modeling, as well as generation of parallel code for multi-core architectures.
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