This paper presents the HTTP request global distribution using the fuzzy-neural decision making mechanism. Two efficient algorithms GARDiB and GARDiB2 are proposed to support HTTP request routing to the Websites. The ...
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Abstract This paper presents self-stabilizing statistical algorithm for validation and optimisation of communication channel. There is usually a need to transmit data describing some industrial process for purpose of ...
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Abstract This paper presents self-stabilizing statistical algorithm for validation and optimisation of communication channel. There is usually a need to transmit data describing some industrial process for purpose of archiving and/or remote evaluation of system performance quality. The communication self-stabilization is possible in multi-agent system (MAS) when certain data loss for remote user is acceptable. Communication overload especially in case of wireless transmission may cause unpredictable data loss. System may self-organize and reach some stable equilibrium point where communication load level and data loss is optimal. Perturbation in system usually does not change structure of the MAS but change equilibrium point that guarantees optimal performance.
This paper presents a new approach to rejection of sinusoidal disturbances acting at the output of a discrete-time complex-valued linear stable plant (e.g. acoustic channel) with unknown and possibly time-varying dyna...
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ISBN:
(纸本)9781424423538
This paper presents a new approach to rejection of sinusoidal disturbances acting at the output of a discrete-time complex-valued linear stable plant (e.g. acoustic channel) with unknown and possibly time-varying dynamics. It is assumed that the instantaneous frequency of the sinusoidal disturbance may be slowly varying with time and that the output signal is contaminated with wideband measurement noise. It is not assumed that a reference signal, correlated with the disturbance, is available. The proposed disturbance rejection algorithm automatically adjusts its adaptation gains to the rate of system and/or disturbance variation.
This paper describes the application of a Parallel Genetic Algorithm that solves the weekly timetable construction problem for elementary schools. Timetable construction is NPcomplete and highly constrained problem, a...
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Complex applications are describing using work-flows. Execution of these workflows in Grid environments require optimized assignment of tasks on available resources according with different constrains. This paper pres...
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Complex applications are describing using work-flows. Execution of these workflows in Grid environments require optimized assignment of tasks on available resources according with different constrains. This paper presents a decentralized scheduling algorithm based on genetic algorithms for the problem of DAG scheduling. The genetic algorithm presents a powerful method for optimization and could consider multiple criteria in optimization process. Also, we describe in this paper the integration platform for the proposed algorithm in Grid systems. We make a comparative evaluation with other existing DAG scheduling solution: Cluster ready Children First, Earliest Time First, Highest Level First with Estimated Times, Improved Critical Path with Descendant Prediction) and Hybrid Remapper. We carry out our experiments using a simulation tool with various scheduling scenarios and with heterogeneous input tasks and computation resources. We present several experimental results that offer a support for near-optimal algorithm selection.
The execution of applications in dependable system requires a high level of instrumentation for automaticcontrol. We present in this paper a monitoring solution for complex application execution. The monitoring solut...
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ISBN:
(纸本)9781424444106
The execution of applications in dependable system requires a high level of instrumentation for automaticcontrol. We present in this paper a monitoring solution for complex application execution. The monitoring solution is dynamic, offering real-time information about systems and applications. The complex applications are described using workflows. We show that the management process for application execution is improved using monitoring information. The environment is represented by distributed dependable systems that offer a flexible support for complex application execution. Our experimental results highlight the performance of the proposed monitoring tool, the MonALISA framework.
This paper presents a simulation tool to test concepts related to Distributed Artificial Intelligence (DAI), multi agent systems (MAS) and agent oriented programming (AOP), such as cooperation and coordination within ...
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This paper presents a simulation tool to test concepts related to Distributed Artificial Intelligence (DAI), multi agent systems (MAS) and agent oriented programming (AOP), such as cooperation and coordination within an MAS, degrees of autonomy both in a flat agent architecture, as well as in a layered architecture of supervisory control. As a case study suitable to an agent oriented approach, the tool implements an application of exploring and mapping an unknown space, allowing the study of agent behaviour and emergent system behaviour in a variety of test conditions. This simulation software will be subsequently extended to include a module for interfacing mobile robots which will exhibit the behaviours tested in simulation, as physical counterparts of the simulated agents.
Nowadays, we have to deal with a large quantity of unstructured data, produced by a number of sources. For example, clustering web pages is essential to getting structured information in response to user queries. In t...
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Nowadays, we have to deal with a large quantity of unstructured data, produced by a number of sources. For example, clustering web pages is essential to getting structured information in response to user queries. In this paper, we intend to test the results of a new clustering technique - clustering by compression - when applied to heterogeneous sets of data. The clustering by compression procedure is based on a parameter-free, universal, similarity distance, the normalized compression distance or NCD, computed from the lengths of compressed data files (singly and in pair-wise concatenation). Compression algorithms allow defining a similarity measure based on the degree of common information, whereas clustering methods allow clustering similar data without any previous knowledge.
The paper describes a new MLF (Mostly Loaded First) method of HTTP requests scheduling and distribution in a cluster-based Web system. Its application enables keeping the quality of the Web service on the required lev...
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The paper describes a new MLF (Mostly Loaded First) method of HTTP requests scheduling and distribution in a cluster-based Web system. Its application enables keeping the quality of the Web service on the required level and makes the Web service behave in a predictable way, opposite to other Web services offering unpredictable and unreliable services of best-effort type. MLF method helps to keep the page response time within established bounds, so that at a heavy workload, servicing both small and simple or more complex pages, would not exceed the imposed time limit. In the method presented, appropriate mechanisms of HTTP requests scheduling have been applied, as well as a new algorithm of the requests distribution has been proposed. In the paper, the method, the testbed and results obtained, which indicate desirability of further research on the MLF method, are presented.
Generalized adaptive notch filters (GANFs) are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters...
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Generalized adaptive notch filters (GANFs) are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. The tracking properties of a GANF algorithm depend on two adaptation gains, which should be chosen so as to match the degree of nonstationarity of the identified system. First, an analytical study of a tracking performance of a real-valued GANF algorithm is presented. Then, based on the obtained theoretical results, a self-optimizing algorithm is proposed, capable of automatic tuning of its adaptation gains. The paper is an extension of the previous work devoted to complex-valued GANF algorithms.
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