Grid computing has emerged as an effective means of facilitating the sharing of distributed heterogeneous resources, enabling collaboration in large scale environments. However, the nature of grid systems coupled with...
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Grid computing has emerged as an effective means of facilitating the sharing of distributed heterogeneous resources, enabling collaboration in large scale environments. However, the nature of grid systems coupled with the overabundance and fragmentation of information, makes it difficult to monitor resources, services, and computations in order to plan and make decisions. In this paper we present Gridscape II, a customisable portal component that can be used on its own or plugged-in to compliment existing grid portals. Gridscape II manages the gathering of information from arbitrary, heterogeneous and distributed sources and presents them together seamlessly within a single interface. It also leverages the Google Maps API in order to provide a highly interactive user interface. Gridscape II is simple and easy to use, providing a solution to those users who do not wish to invest heavily in developing their own monitoring portal from scratch, and also for those users who want something easy to customise and extend for their specific needs
The advent of service-oriented grid computing has resulted in the need for grid resources such as clusters to enforce user-specific service needs and expectations. Service level agreements (SLAs) define conditions whi...
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The advent of service-oriented grid computing has resulted in the need for grid resources such as clusters to enforce user-specific service needs and expectations. Service level agreements (SLAs) define conditions which a cluster needs to fulfill for various jobs. An example of SLA requirement is the deadline by which a job has to be completed. In addition, these clusters implement job admission control so that overall service performance does not deteriorate due to accepting exceeding amount of jobs. However, their effectiveness is highly dependent on accurate runtime estimates of jobs. This paper thus examines the adverse impact of inaccurate runtime estimates for deadline constrained job admission control in clusters using the earliest deadline first (EDF) strategy and a deadline-based proportional processor share strategy called Libra. Simulation results show that an enhancement called LibraRisk can manage the risk of inaccurate runtime estimates better than EDF and Libra by considering the risk of deadline delay
This paper presents interfacing techniques to integrate a virtual environment (VE), computer graphics, image-based modeling, and other technologies in a networked system for robot control. Technologies such as network...
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As the Unified Modeling Language (UML) and modeldriven development (MDD) become increasingly common in industry, many developers are faced with the difficult task of understanding how an existing UML model realizes sy...
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As the Unified Modeling Language (UML) and modeldriven development (MDD) become increasingly common in industry, many developers are faced with the difficult task of understanding how an existing UML model realizes system requirements. Essentially, developers are required to understand the structure and behavior of UML models that they may have not created. Understanding these relationships is non-trivial, because the interactions in the model are not readily apparent. Commonly, the only means to elicit these relationships is visual inspection and guided simulation. This paper describes an alternative approach termed REVU (Requirements Visualization of UML), a process for visualizing functional requirements in terms of behavioral interactions in a UML model. We illustrate the use of this process with the visualization of scenarios for an adaptive light control system.
In this paper we propose a smart repeater that consumes less energy and is suitable for driving global interconnections in nanometre technologies. When there is coupling between interconnects, the effective capacitanc...
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ISBN:
(纸本)1595932550
In this paper we propose a smart repeater that consumes less energy and is suitable for driving global interconnections in nanometre technologies. When there is coupling between interconnects, the effective capacitance of a given wire is a function not only of the physical geometry, but also the relative switching pattern described by the bits on the wire in question (the victim) and the adjacent wires (aggressors). The drive strength of a traditional repeater is static, resulting in a spread of the propagation delay, with the repeater strength being essentially too much for every bit pattern other than the worst-case pattern. In the proposed SMART repeater, the drive strength is dynamically altered depending on the relative bit pattern, by partitioning it into a Main Driver and Assistant Driver. For a higher effective load capacitance both drivers switch, while for a lower effective capacitance the assistant driver is quiet. By disconnecting part of the repeater when it is not needed, the total load capacitance to the previous stage is reduced, resulting in reduced energy consumption for those instances. It is shown that the potential average saving in energy can be as much 15% with a 18% jitter reduction over a traditional repeater for typical global wire lengths in nanometre technologies. Copyright 2006 ACM.
This paper presents a component oriented modeling environment for building hybrid dynamic models of physical system. The modeling environment is created using the generic modeling environment (GME), a meta programmabl...
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This paper presents a component oriented modeling environment for building hybrid dynamic models of physical system. The modeling environment is created using the generic modeling environment (GME), a meta programmable visual modeling application developed at the Institute for software Integrated systems (ISIS). The core of the modeling language itself is a hybrid extension of the bond graph modeling language. The advantages of an object-oriented approach to physical system modeling combined with the advanced features of GME for managing model complexity are illustrated by building a library of hydraulic system components. A simulation model can be automatically generated from the physical system model using a model translator. As an example application we use the component library to build the model of a coupled multi-tank system with controlled and autonomous hybrid behaviors, and illustrate this with a simulation example
In this study, a novel approach is used to identify nondominated solutions to multiobjective optimization problems. The method is composed of a Particle Swarm Optimizer (PSO) coupled with a neural network. The PSO is ...
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In this study, a novel approach is used to identify nondominated solutions to multiobjective optimization problems. The method is composed of a Particle Swarm Optimizer (PSO) coupled with a neural network. The PSO is used to find an initial set of nondominated solutions. These nondominated solutions are then used to construct a general regression neural network that generates a considerably larger set of nondominated solutions. Our neural network enhancement process is demonstrated on a test suite of six instances of bi-criteria semidesirable facility location problems. Results show that the set of nondominated solutions developed by the neural network is, on average, 25 times larger than the initial set found by PSO, and in many instances dominate those identified by PSO. The method developed within is straightforward and general and is a new alternative to multiobjective optimization with decision variables in continuous space.
Fault diagnosis of coupled mobile robots requires a large number of measurements to be communicated either between the robots or from the robots to a central diagnoser. As computational complexity increases with the n...
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Fault diagnosis of coupled mobile robots requires a large number of measurements to be communicated either between the robots or from the robots to a central diagnoser. As computational complexity increases with the number of measurements, centralized algorithms become inefficient. This paper presents a distributed approach for qualitative fault diagnosis of coupled mobile robots. The approach is based on a bond graph modeling framework which incorporates local and distributed control algorithms, multiple sensor types, and both actuator and sensor faults. Relative measurement orderings are introduced to discriminate faults by exploiting the temporal order of the measurement deviations. This increases the discriminatory power of a set of measurements and results in a more efficient qualitative diagnosis algorithm. Distributed diagnosers are designed and applied to coupled mobile robots. Experimental results for a system consisting of two robots pushing a box demonstrate the improvement in both discriminatory power of the measurements and efficiency of the distributed diagnosis approach
Checkpointing is widely used in robust fault-tolerant applications. We present an efficient incremental checkpointing mechanism. It requires to record only the state changes and not the complete state. After the creat...
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ISBN:
(纸本)9781424405015
Checkpointing is widely used in robust fault-tolerant applications. We present an efficient incremental checkpointing mechanism. It requires to record only the state changes and not the complete state. After the creation of a checkpoint, state changes are logged incrementally as records in memory, with which an application can spontaneously roll back later. This incrementalism allows us to implement checkpointing with high performance. Only small constant time is required for checkpoint creation and state recording. Rollback requires linear time in the number of recorded state changes, which is bounded by the number of state variables times the number of checkpoints. We implement a Java source transformer that automatically converts an existing application into a behavior-preserving one with checkpointing functionality. This transformation is application-independent and application-transparent. A wide range of applications can benefit from this technique. Currently, it has been used for distributed discrete event simulation using the time warp technique
Over the last few years, grid technologies have progressed towards a service-oriented paradigm that enables a new way of service provisioning based on utility computing models. Users consume these services based on th...
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Over the last few years, grid technologies have progressed towards a service-oriented paradigm that enables a new way of service provisioning based on utility computing models. Users consume these services based on their QoS (quality of service) requirements. In such “pay-per-use” grids, workflow execution cost must be considered during scheduling based on users' QoS constraints. In this paper, we propose a budget constraint based scheduling, which minimizes execution time while meeting a specified budget for delivering results. A new type of genetic algorithm is developed to solve the scheduling optimization problem and we test the scheduling algorithm in a simulated grid testbed.
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