3,176 research outputs found

    TCP over High Speed Variable Capacity Links: A Simulation Study for Bandwidth Allocation

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    New optical network technologies provide opportunities for fast, controllable bandwidth management. These technologies can now explicitly provide resources to data paths, creating demand driven bandwidth reservation across networks where an applications bandwidth needs can be meet almost exactly. Dynamic synchronous Transfer Mode (DTM) is a gigabit network technology that provides channels with dynamically adjustable capacity. TCP is a reliable end-to-end transport protocol that adapts its rate to the available capacity. Both TCP and the DTM bandwidth can react to changes in the network load, creating a complex system with inter-dependent feedback mechanisms. The contribution of this work is an assessment of a bandwidth allocation scheme for TCP flows on variable capacity technologies. We have created a simulation environment using ns-2 and our results indicate that the allocation of bandwidth maximises TCP throughput for most flows, thus saving valuable capacity when compared to a scheme such as link over-provisioning. We highlight one situation where the allocation scheme might have some deficiencies against the static reservation of resources, and describe its causes. This type of situation warrants further investigation to understand how the algorithm can be modified to achieve performance similar to that of the fixed bandwidth case

    The co-evolutionary dynamics of directed network of spin market agents

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    The spin market model [S. Bornholdt, Int.J.Mod.Phys. C 12 (2001) 667] is extended into co-evolutionary version, where strategies of interacting and competitive traders are represented by local and global couplings between the nodes of dynamic directed stochastic network. The co-evolutionary principles are applied in the frame of Bak - Sneppen self-organized dynamics [P. Bak, K. Sneppen, Phys. Rev. Letter 71 (1993) 4083] that includes the processes of selection and extinction actuated by the local (node) fitness. The local fitness is related to orientation of spin agent with respect to instant magnetization. The stationary regime characterized by a fat tailed distribution of the log-price returns with index α3.6\alpha\simeq 3.6 (out of the Levy range) is identified numerically. The non-trivial consequence of the extremal dynamics is the partially power-law decay (an effective exponent varies between -0.3 and -0.6) of the autocorrelation function of volatility. Broad-scale network topology with node degree distribution characterized by the exponent γ=1.8\gamma=1.8 from the range of social networks is obtained.Comment: 10 pages, 4 figures. accepted for publication in Physica

    DTMsim - DTM channel simulation in ns

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    Dynamic Transfer Mode (DTM) is a ring based MAN technology that provides a channel abstraction with a dynamically adjustable capacity. TCP is a reliable end to end transport protocol capable of adjusting its rate. The primary goal of this work is investigate the coupling of dynamically allocating bandwidth to TCP flows with the affect this has on the congestion control mechanism of TCP. In particular we wanted to find scenerios where this scheme does not work, where either all the link capacity is allocated to TCP or congestion collapse occurs and no capacity is allocated to TCP. We have created a simulation environment using ns-2 to investigate TCP over networks which have a variable capacity link. We begin with a single TCP Tahoe flow over a fixed bandwidth link and progressively add more complexity to understand the behaviour of dynamically adjusting link capacity to TCP and vice versa

    Distributed top-k aggregation queries at large

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    Top-k query processing is a fundamental building block for efficient ranking in a large number of applications. Efficiency is a central issue, especially for distributed settings, when the data is spread across different nodes in a network. This paper introduces novel optimization methods for top-k aggregation queries in such distributed environments. The optimizations can be applied to all algorithms that fall into the frameworks of the prior TPUT and KLEE methods. The optimizations address three degrees of freedom: 1) hierarchically grouping input lists into top-k operator trees and optimizing the tree structure, 2) computing data-adaptive scan depths for different input sources, and 3) data-adaptive sampling of a small subset of input sources in scenarios with hundreds or thousands of query-relevant network nodes. All optimizations are based on a statistical cost model that utilizes local synopses, e.g., in the form of histograms, efficiently computed convolutions, and estimators based on order statistics. The paper presents comprehensive experiments, with three different real-life datasets and using the ns-2 network simulator for a packet-level simulation of a large Internet-style network

    STRATEGY MANAGEMENT IN A MULTI-AGENT SYSTEM USING NEURAL NETWORKS FOR INDUCTIVE AND EXPERIENCE-BASED LEARNING

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    Intelligent agents and multi-agent systems prove to be a promising paradigm for solving problems in a distributed, cooperative way. Neural networks are a classical solution for ensuring the learning ability of agents. In this paper, we analyse a multi-agent system where agents use different training algorithms and different topologies for their neural networks, which they use to solve classification and regression problems provided by a user. Out of the three training algorithms under investigation, Backpropagation, Quickprop and Rprop, the first demonstrates inferior performance to the other two when considered in isolation. However, by optimizing the strategy of accepting or rejecting tasks, Backpropagation agents succeed in outperforming the other types of agents in terms of the total utility gained. This strategy is learned also with a neural network, by processing the results of past experiences. Therefore, we show a way in which agents can use neural network models for both external purposes and internal ones.agents, learning, neural networks, strategy management multi-agent system.

    Performance Portability Through Semi-explicit Placement in Distributed Erlang

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    We consider the problem of adapting distributed Erlang applications to large or heterogeneous architectures to achieve good performance in a portable way. In many architectures, and especially large architectures, the communication latency between pairs of virtual machines (nodes) is no longer uniform. We propose two language-level methods that enable programs to automatically adapt to heterogeneity and non-uniform communication latencies, and both provide information enabling a program to identify an appropriate node when spawning a process. We provide a means of recording node attributes describing the hardware and software capabilities of nodes, and mechanisms that allow an application to examine the attributes of remote nodes. We provide an abstraction of communication distances that enables an application to select nodes to facilitate efficient communication. We have developed open source libraries that implement these ideas. We show that the use of attributes for node selection can lead to significant performance improvements if different components of the application have different processing requirements. We report a detailed empirical investigation of non-uniform communication times in several representative architectures, and show that our abstract model provides a good description of the hierarchy of communication times

    Toward a Formal Semantics for Autonomic Components

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    Autonomic management can improve the QoS provided by parallel/ distributed applications. Within the CoreGRID Component Model, the autonomic management is tailored to the automatic - monitoring-driven - alteration of the component assembly and, therefore, is defined as the effect of (distributed) management code. This work yields a semantics based on hypergraph rewriting suitable to model the dynamic evolution and non-functional aspects of Service Oriented Architectures and component-based autonomic applications. In this regard, our main goal is to provide a formal description of adaptation operations that are typically only informally specified. We contend that our approach makes easier to raise the level of abstraction of management code in autonomic and adaptive applications.Comment: 11 pages + cover pag

    Simulator Development - Annual Report Year 3

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    This document describes the progress of the simulator development with in the third year of the CATNETS project. The refinement of the simulator as well as a detailed guide to conducting simulations is presented. --Grid Computing
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