Efficient scheduling is a key concern for the effectual execution of performance driven Grid applications, such as workflows. Many list heuristics have been developed for scheduling workflows in centralized Grid envir...
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Efficient scheduling is a key concern for the effectual execution of performance driven Grid applications, such as workflows. Many list heuristics have been developed for scheduling workflows in centralized Grid environment. However, in this paper, we present a distributed list heuristic for decentralized scheduling of workflow applications in global Grids. The simulation results show that the proposed scheduling approach is scalable with respect to increased workload on the system.
In this paper a possible application of a novel adaptive control approach is reported that fits to the 'traditional line of thinking' according to which in the most practical cases neither very precise, nor ev...
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In this paper, we present an efficient and robust subspace learning based object tracking algorithm with special illumination handling. Illumination variances pose a great challenge to most of object tracking algorith...
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ISBN:
(纸本)9781424452378
In this paper, we present an efficient and robust subspace learning based object tracking algorithm with special illumination handling. Illumination variances pose a great challenge to most of object tracking algorithms. In this paper, an edge orientation based feature has been proposed and proven to approximately invariant to illumination changes. Besides, we utilize the incremental subspace learning based particle filter framework which is effective to handle various appearance changes. To reduce the amount of computation when the particle number is large, a new layer of preprocessing step has been added to the particle filter framework with the help of edge orientation features. From the experimental m results, it is obvious that our proposed algorithm achieves promising performance especially in the scenarios with large illumination changes.
Peering of Content Delivery Networks (CDNs) allow providers to rapidly scale-out to meet both flash crowds and anticipated increases in demand. Recent trends foster the need for a utility model for content delivery se...
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Peering of Content Delivery Networks (CDNs) allow providers to rapidly scale-out to meet both flash crowds and anticipated increases in demand. Recent trends foster the need for a utility model for content delivery services to provide transparency, high availability, reduced investment cost, and improved content delivery performance. Analysis of prior work reveals only a modest progress in evaluating the utility for peering CDNs. In this paper, we introduce a utility model and measure the content-serving ability of the peering CDNs system. Our model assists in providing a customer view of the system's health for different traffic types. Our model also captures the traffic activities in the system and helps to reveal the true propensities of participating CDNs to cooperate in peering. Through extensive simulations we unveil many interesting observations on how the utility of the peering CDNs system is varied for different system parameters and provide incentives for their exploitation in the system design.
Cloud resource providers in a market face dynamic and unpredictable consumer behavior. The way, how prices are set in a dynamic environment, can influence the demand behavior of price sensitive customers. A cloud reso...
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ISBN:
(纸本)9781424446469;9780769537559
Cloud resource providers in a market face dynamic and unpredictable consumer behavior. The way, how prices are set in a dynamic environment, can influence the demand behavior of price sensitive customers. A cloud resource provider has to decide on how to allocate his scarce resources in order to maximize his profit. The application of bid price control for evaluating incoming service requests is a common approach for capacity control in network revenue management. In this paper we introduce a customized version of the concept of self-adjusting bid prices and apply it to the area of cloud computing. Furthermore, we perform a simulation in order to test the efficiency of the proposed model.
In numerous practical applications precise control of a subsystem passively connected to a precisely controllable subsystem by elastic connection is needed. As typical example is a crane carrying its payload swinging ...
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In numerous practical applications precise control of a subsystem passively connected to a precisely controllable subsystem by elastic connection is needed. As typical example is a crane carrying its payload swinging on an elastic string can be mentioned. From the point of view of control technology this task is interesting since the connected degree of freedom has little damping and it is apt to keep swinging accordingly. The traditional approaches apply the input shaping technology to assist the human operator responsible for the manipulation task. In the present paper a novel adaptive approach applying fixed point transformations based iterations having local basin of attraction is proposed for simultaneously tackle the problems originating from the imprecisions of the available dynamic model of the system to be controlled and the swinging phenomenon. In the simulation investigations presented a simple model consisting of two connected masspoints is considered: one of them can directly by controlled by control forces, the other one (in the role of the payload) is dragged by the controlled point via an elastic spring. The control considers the 4th time-derivative of the trajectory of the dragged system.
The modified DAC version with thermal quadrupoles can be considered an interesting alternative to thermal contrast computations since it provides an automated tool for depth retrieval and eliminates the need of select...
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In this paper, we use EEG signals to classify two emotions-happiness and sadness. These emotions are evoked by showing subjects pictures of smile and cry facial expressions. We propose a frequency band searching metho...
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In this paper, we use EEG signals to classify two emotions-happiness and sadness. These emotions are evoked by showing subjects pictures of smile and cry facial expressions. We propose a frequency band searching method to choose an optimal band into which the recorded EEG signal is filtered. We use common spatial patterns (CSP) and linear-SVM to classify these two emotions. To investigate the time resolution of classification, we explore two kinds of trials with lengths of 3s and 1s. Classification accuracies of 93.5% plusmn 6.7% and 93.0%plusmn6.2% are achieved on 10 subjects for 3s-trials and 1s-trials, respectively. Our experimental results indicate that the gamma band (roughly 30-100 Hz) is suitable for EEG-based emotion classification.
Nowadays enterprise information and knowledge systems provide technical platforms for the integration and collaboration of business processes among multi-organizations of enterprises. However, software systems support...
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Nowadays enterprise information and knowledge systems provide technical platforms for the integration and collaboration of business processes among multi-organizations of enterprises. However, software systems supporting enterprise business processes are hard to be adapted and deployed to satisfy the ever-changing requirements of enterprises. In this paper we put forward an adaptable enterprise information system framework in which we use four levels of abstractions. At the meta-meta model level, the ontology schema is used which provides the specification language for other more specific levels. At the meta-model level, the extended OSM model is used, and the generic elements obtained from analyzing the commonality of requirements are included. At the model level, the commonalities of sub-domains, such as the patterns of tasks in a specific domain are analyzed and generalized for future reuse. The intermediate specifications of the business processes and work flows are used in this level. At the application level, specific elements and requirements of the applications will be added and customized via the tools developed at the abstracted levels. A case study of knowledge management system based on this four level abstraction is discussed.
We present a computational model of creative design based on collaborative interactive genetic algorithms. We test our model on floorplanning. We guide the evolution of floorplans based on subjective and objective cri...
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We present a computational model of creative design based on collaborative interactive genetic algorithms. We test our model on floorplanning. We guide the evolution of floorplans based on subjective and objective criteria. The subjective criteria consists of designers picking the floorplan they like the best from a population of floorplans, and the objective criteria consists of coded architectural guidelines. We support collaboration by allowing individual designers to view each others' designs during the evolutionary process and the sharing of designs via case injection. This methodology supports team design, and reflects the view of creativity that collaboration accounts for much of our intelligence and creativity. We present a description of the model and a comparative study of floorplans created individually versus collaboratively. Our results show that floorplans created collaboratively were considered to be more ldquorevolutionaryrdquo and ldquooriginalrdquo than those created individually.
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