1,421 research outputs found

    Versatile Markovian models for networks with asymmetric TCP sources

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    In this paper we use Stochastic Petri Nets (SPNs) to study the interaction of multiple TCP sources that share one or two buffers, thereby considerably extending earlier work. We first consider two sources sharing a buffer and investigate the consequences of two popular assumptions for the loss process in terms of fairness and link utilization. The results obtained by our model are in agreement with existing analytic models or are closer to results obtained by ns-2 simulations. We then study a network consisting of three sources and two buffers and provide evidence that link sharing is approximately minimum-potential-delay-fair in case of equal round-trip times. \u

    A Markovian model of the RED mechanism solved with a cluster of computers

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    The paper presents a working example of distributed application which can be used to find stationary probabilities of states for queuing models - by generating a transition rate matrix and solving a linear system. The presented example is connected to the RED mechanism which can be used in the TCP/IP protocol to control packets flow. The paper also shows efficiency of the application with the use of a various number of computers connected with Ethernet

    Communication-efficient Distributed Multi-resource Allocation

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    In several smart city applications, multiple resources must be allocated among competing agents that are coupled through such shared resources and are constrained --- either through limitations of communication infrastructure or privacy considerations. We propose a distributed algorithm to solve such distributed multi-resource allocation problems with no direct inter-agent communication. We do so by extending a recently introduced additive-increase multiplicative-decrease (AIMD) algorithm, which only uses very little communication between the system and agents. Namely, a control unit broadcasts a one-bit signal to agents whenever one of the allocated resources exceeds capacity. Agents then respond to this signal in a probabilistic manner. In the proposed algorithm, each agent makes decision of its resource demand locally and an agent is unaware of the resource allocation of other agents. In empirical results, we observe that the average allocations converge over time to optimal allocations.Comment: To appear in IEEE International Smart Cities Conference (ISC2 2018), Kansas City, USA, September, 2018. arXiv admin note: substantial text overlap with arXiv:1711.0197

    A Study of V2V Communication on VANET: Characteristic, Challenges and Research Trends

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    Vehicle to Vehicle (V2V) communication is a specific type of communication on Vehicular Ad Hoc Network (VANET)  that attracts the great interest of researchers, industries, and government attention in due to its essential application to improve safety driving purposes for the next generation of vehicles. Our paper is a systematic study of V2V communication in VANET that cover the particular research issue, and trends from the recent works of literature. We begin the article with a brief V2V communication concept and the V2V application to safety purposes and non-safety purposes; then, we analyze several problems of V2V communication for VANET related to safety issues and non-safety issues. Next, we provide the trends of the V2V communication application for VANET. Finally, provide SWOT analysis as a discussion to identify opportunities and challenges of V2V communication for VANET in the future. The paper does not include a technical explanation. Still, the article describes the general perspective of VANET to the reader, especially for the beginner reader, who intends to learn about the topic

    Distributed flow optimization and cascading effects in weighted complex networks

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    We investigate the effect of a specific edge weighting scheme (kikj)β\sim (k_i k_j)^{\beta} on distributed flow efficiency and robustness to cascading failures in scale-free networks. In particular, we analyze a simple, yet fundamental distributed flow model: current flow in random resistor networks. By the tuning of control parameter β\beta and by considering two general cases of relative node processing capabilities as well as the effect of bandwidth, we show the dependence of transport efficiency upon the correlations between the topology and weights. By studying the severity of cascades for different control parameter β\beta, we find that network resilience to cascading overloads and network throughput is optimal for the same value of β\beta over the range of node capacities and available bandwidth

    Exploring MultiPath TCP Through Discrete Event Simulation

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    Postponed access: the file will be accessible after 2022-06-01Global internet usage is rapidly becoming more mobile. Devices are, as a consequence, equipped with multiple network interfaces to meet the demand for mobility. With the emergence of 5G-technology, this trend will most likely continue. However, most internet traffic makes use of standard TCP. TCP does not allow a connection to span several interfaces, even though multiple network interfaces are available. MPTCP is a proposed protocol that enables the use of several interfaces. By distributing data through several paths, MPTCP aims at making internet usage more robust while providing higher throughput and multihoming features. In this thesis, we develop a discrete event simulator to simulate a network. Using this simulator, we analyze and evaluate the performance of MPTCP in various situations. Our findings show that MPTCP has several pitfalls and highlight possible mitigationsMasteroppgave i informatikkINF399MAMN-INFMAMN-PRO

    Derandomized Distributed Multi-resource Allocation with Little Communication Overhead

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    We study a class of distributed optimization problems for multiple shared resource allocation in Internet-connected devices. We propose a derandomized version of an existing stochastic additive-increase and multiplicative-decrease (AIMD) algorithm. The proposed solution uses one bit feedback signal for each resource between the system and the Internet-connected devices and does not require inter-device communication. Additionally, the Internet-connected devices do not compromise their privacy and the solution does not dependent on the number of participating devices. In the system, each Internet-connected device has private cost functions which are strictly convex, twice continuously differentiable and increasing. We show empirically that the long-term average allocations of multiple shared resources converge to optimal allocations and the system achieves minimum social cost. Furthermore, we show that the proposed derandomized AIMD algorithm converges faster than the stochastic AIMD algorithm and both the approaches provide approximately same solutions
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