Fluid-Flow Approximation in the Analysis of Vast Energy-Aware Networks (original) (raw)
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2018 Winter Simulation Conference (WSC), 2018
As network technologies undergo an exponential growth in terms of bandwidth and topology complexity, the gap is worsened between the performance of network simulation techniques and real network scenarios. Fluid-flow models for network dynamics are a well know option for reducing simulation overhead while offering useful averaged approximations of network metrics. Yet, the methods and tools established in the packet-level simulation community are alien to those used in continuous system modeling by means of differential equations. This hinders the synergy between specialists in both techniques. In this work, we present a novel modeling methodology and simulation tool to unify the experience of designing network simulation models both with fluid-level and packet-level techniques under a single modular and hierarchical formal framework. We verified the efficacy of our approach both in terms of simulation speedups and modeling simplicity for canonical network simulation scenarios.
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Computer Networks, 2004
Design methodologies for TCP/IP based networks is one of the most challenging topic in research on telecommunications networks. The main difficulty consists in modeling congestion control mechanisms because it involves feedback from the network. In this perspective, in this paper we develop an accurate analytical framework for networked TCP applications supporting both Slow Start and Congestion Avoidance algorithms. To this end we enhance the TCP fluid model introduced in the previous literature considering also TCP sources aimed at transmitting a prefixed quantity of data such as file transfer or network browsing. The proposed model addresses a network of routers supporting any Active Queue Management (AQM) techniques, provided that the equations describing the AQM rules implemented in the routers are introduced in the fluid framework. The proposed framework allows designers to study not only the steady-state behavior of the network, but also the transient behavior when a set of TCP sources start to transmit or finish transmitting. Moreover the model results provide the average values of the queue length in each router even when some of them are not bottleneck ones.
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Simulators have been acknowledged as one of the most flexible tool in studying and evaluating network performance. Variuous approaches have been followed in data networks modeling. The present paper explores the range of applicability of a fluid-dynamic model, proposed in [5], able to describe the load evolution of a data network. Looking at intermediate time scale, it is assumed that packets are conserved, and hence the packets density obey to a conservation law. The assumption underlying the model is the behaviour of the information loss probability from which the flux is derived. Here the validity of the above hypothesis and the rules introduced to solve dynamics at nodes are discussed. In particular packet loss estimations using queueing models have been compared with the assumed loss probability. Moreover a TCP throughput simulation is proposed to evaluate the feasibility of the "tent" flux.
Fluid-based Analysis of TCP Flows
openwebsurvey.di.unito.it
In this report, we explore the use of a fluid-based analysis to model the behavior of a large population of TCP flows traversing a network of routers implementing RED (random early detection) and Drop Tail queue management policies. In all cases, we formulate a non-linear problem with the router average queue lengths as unknowns. Once the average queue lengths are obtained, other metrics such as router loss probability, TCP flow throughput, TCP flow end-to-end loss rates, average round trip time, and average session ...
A Large-Scale Wired Network Energy Model for Flow-Level Simulations
Springer eBooks, 2019
The use of simulators to predict network energy consumption is a good way for scientists to improve and develop new algorithms and also to assess them. However, the average size of a network platforms is continuously increasing with the emergence of new technologies like the Internet Of Things and Fog Computing. Packet-level simulators start to reach their limits in terms of performance and this calls for newer solutions in the domain of large-scale platform energy models. In this paper, we propose two energy models for wired networks adapted to flow level simulators in order to estimate the energy consumption of large platforms. An evaluation of these models is proposed and it demonstrates their applicability in practice and their accuracy. Indeed, we obtain simulation results with a relative error lower than 4% compared to an ns-3-based solution, and our flow-based simulation is 120 times faster.
Fluid flow approximation of time-limited TCP/UDP/XCP streams
Bulletin of the Polish Academy of Sciences Technical Sciences, 2014
This article presents the use of fluid flow approximation to model interactions between a set of TCP, UDP and XCP flows in the environment of IP routers using AQM (Active Queue Management) algorithms to control traffic congestion. In contrast to other works, independent UDP and TCP streams are considered and the model allows to start and end data transmissions in TCP, UDP and XCP streams at any time moment. It incorporates several Active Queue Management mechanisms: RED, NLRED, CHOKe.
Internet Performance and Control of Network Systems II, 2001
Fluid flow analytical models have been shown to be able to capture the dynamics of TCP flows and can scale well to solving for networks with a large number of flows. However, accurate closed form solutions are not yet available for wireless networks. Traditional packet-level discrete event simulations provide accurate predictions of network behavior, but their solution time can increase significantly with the number of flows being simulated. Integration of fluid flow models with packet-level simulators appears to offer significant benefits. In this paper, we describe an approach to integrate fluid flow models into QualNet, a scalable packet-level simulator. We validate the mixed model with detailed packet-level simulations for the scenarios considered in this paper. The execution time of the mixed model is significantly impacted by the frequency with which the analytical model must be solved in response to changes in the data rate at the interface of the packet-level and analytical models. We present a time averaging approach to mitigate this impact and present the results of the resulting tradeoff between prediction accuracy and model execution time.
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Performance evaluation of computer networks through traditional packet-level simulation is becoming increasingly difficult as networks grow in size along different dimensions. Due to its higher level of abstraction, fluid simulation is a promising approach for evaluating large-scale network models. In this paper we focus on evaluating and comparing the computational effort required for fluid-and packet-level simulation. To measure the computational effort required by a simulation approach, we introduce the concept of ''simulation event rate'', a measure that is both analytically tractable and adequate. We identify the fundamental factors that contribute to the simulation event rate in fluid-and packet-level simulations and provide an analytical characterization of the simulation event rate for specific network models. Among such factors, we identify the ''ripple effect'' as a significant contributor to the computational effort required by fluid simulation. We also show that the parameter space of a given network model can be divided into different regions where one simulation technique is more efficient than the other. In particular, we consider a realistic large-scale network and demonstrate how the computational effort depends on simulation parameters. Finally, we show that flow aggregation can effectively reduce the impact of the ripple effect and that the ripple effect has less impact when simulating the WFQ scheduling policy.