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.
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.
We propose a new method, called closed multidimensional sequential pattern mining, for mining multidimensional sequential patterns. The new method is an integration of closed sequential pattern mining and closed items...
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We propose a new method, called closed multidimensional sequential pattern mining, for mining multidimensional sequential patterns. The new method is an integration of closed sequential pattern mining and closed itemset pattern mining. Based on this method, we show that (1) the number of complete closed multidimensional sequential patterns is not larger than the number of complete multidimensional sequential patterns (2) the set of complete closed multidimensional sequential patterns covers the complete resulting set of multidimensional sequential patterns. In addition, mining using closed itemset pattern mining on multidimensional information would mine only multidimensional information associated with mined closed sequential patterns, and mining using closed sequential pattern mining on sequences would mine only sequences associated with mined closed itemset patterns
When transacting and interacting through open computer networks, traditional methods used in the physical world for establishing trust can no longer be used. Creating virtual network substitutes with which people, org...
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The change in the softwaresystems is inevitable if the system is to remain useful. The change in business requirements sometimes is such that the old and new requirements have to be met simultaneously, i.e. old and n...
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The change in the softwaresystems is inevitable if the system is to remain useful. The change in business requirements sometimes is such that the old and new requirements have to be met simultaneously, i.e. old and new business rules are needed to exist concurrently. Accommodating more than one rule in the existing entities, leads to the change in the operational system, which involves risk. The evolution in the system impacts the business rules as well as the data model of the system. The evolution step incorporating the change in business rule requires changes to be carried out in the application architecture in terms of addition or modification of process as well as data components and also the alterations in the relationships among the components. The evolution problem of coexistence of business rules can be considered as incremental change to the existing architectural design of the system to nullify the risk of change to the software. In this paper we propose the framework, where temporal aspects of process as well as data components and concurrent validity of multiple business rules, with multiple versions of the components can be effectively implemented. The framework supports evolution without disturbing existing architecture and functionality. This framework is consistent in application to systems irrespective of the design methodology followed for the same.
An algorithm for time division multiple access (TDMA) is found to be applicable in converting existing distributed algorithms into a model that is consistent with sensor networks. Such a TDMA service needs to be self-...
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Long-duration surface missions to the Moon and Mars will require bases to accommodate habitats for the astronauts, as well as indoor laboratory facilities, in-situ resource plants, power plants, and scientific/surface...
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ISBN:
(纸本)0784408300
Long-duration surface missions to the Moon and Mars will require bases to accommodate habitats for the astronauts, as well as indoor laboratory facilities, in-situ resource plants, power plants, and scientific/surface mobility equipment. Transporting the materials and equipment required to build the necessary habitats would be costly and difficult. However, the use of planetary resources to produce construction materials, or even as naturally found (such as lunar regolith utilized as an outer layer for radiation shielding, or regolith in bags as wall structure), could drastically reduce the upmass for habitats. The materials chosen for the habitat walls play a direct role in protection against each of the mentioned hazards. Choosing the best materials, their configuration, and the amount required is extremely difficult due to the immense size of the design region. For example a 3-layer habitat wall created from 20 possible materials all with varying thicknesses would have #number of layers(possible material types)∧(possible thicknesses) = 320∧inf possible solutions. Clearly, an optimization method is warranted for habitat wall design. Standard optimization techniques are not suitable for problems with such large search spaces. To overcome the large search regions, a habitat wall design tool using genetic algorithms has been developed. GAs use a "survival of the fittest" philosophy, where the most fit individuals are more likely to survive and reproduce, therefore transmitting their genes to the next generation. This paper focuses on finding optimal GA parameters for the habitat optimization tool. This tool is a multiobjective formulation of structural analysis, heat loss, radiation, and meteoroid protection. Some of the constraint calculations (i.e. safety factor, deflection, and heat loss) require long computation times. Even though each material has a designated thickness range, the number of different values within that range is near infinite;therefore, the searc
Connectors are used to realize component interactions in component systems. Apart from their primary function, which is mediating the communication, their implementation can also support additional features that, whil...
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Taking advantage of the Grid workflow, scientists and engineers are building more and more complex decision support applications to process large data sets, and coordinate scheduling distributed decision resources. Su...
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Taking advantage of the Grid workflow, scientists and engineers are building more and more complex decision support applications to process large data sets, and coordinate scheduling distributed decision resources. Such decision resource scheduling processes require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow scheduling systems for decision resource coordinate scheduling on Grid environment. In this paper, we investigates the emerging need for Grid workflow to aid decision support on the Grid and proposes a Grid workflow for decision resource scheduling that is a Petri net-based graph model and incorporates a reasoning system designed to perform such a task. It effectively hides the heterogeneity of decision resources with good intelligence, scalability and adaptability.
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