Multiobjective network topology design

The cable industry has begun testing and deploying high speed cable modems for data delivery. However, practical network designs require the estimation and prediction of performance under realistic traffic models and must consider the dominant factors that affect packet loss probabilities and offered load. In this paper we evaluate the use of a stochastic model of WWW client-server transactions as a tool for network design and analysis. Specifically, a sensitivity analysis of the model is performed to identify the impact various model parameters have on predicted packet loss probabilities in an Internet access network utilizing CATV transport. The traffic model used is a self-similar traffic model in which the inter-arrival times of document requests generated by each source is based on a two-state ON-OFF source model described and the length of each document is given by a Pareto distribution. We investigate the results of using such a model in predicting a number of network performance parameters including buffer requirements and achieved channel utilization. We also evaluate the number of WWW users that a head-end can support for a specific bandwidth. The effects of multiplexing, decreasing the inter-arrival times, increasing the length of the ON period, changing the tail of the document size distribution, and increasing the buffer size are all considered. We also identify which parameters most affect the packet loss probability and the offered load on the system. Such parameters will be the dominant factors that need to be used in network and capacity planning for CATV data delivery systems.

Traditional Ethernet is not suitable for application in industry field which has strict requirements for real-time because of its indeterminacy. A real-time Ethernet media access control (MAC) protocol is proposed. This protocol provides a predictable upper bound for the sum of queuing and transmission delay of real-time frames. The protocol of non-real-time nodes does not need to change and it is compatible with traditional Ethernet MAC protocol. The non-real-time nodes can directly access network without any modification. The arrival of data frames was assumed to be satisfied Poisson distribution in previous network simulations, but it does not reflect the actual situation of networks. So a self-similar traffic model is proposed and the new real-time MAC protocol is simulated under the model. The feasibility and effectiveness of this protocol is verified by simulation results.

This paper deals with an efficient dynamic bandwidth allocation technique is presented based on traffic prediction. In particular, the self-similar traffic modeling is herein considered and the accuracy of several prediction techniques is taken into account. With the aim of improving the overall system performance a corrective factor is introduced applying it to predicted traffic level. This approach is then applied to a satellite IP network based on the DVB-RCS standard highlighting the noticeable advantages of the proposed allocation policy in terms of link delay both in the case of a single traffic class and in a multiclass environment based on the DiffServ model.

The notion of self-similarity has been shown to apply to wide-area and local-area network traffic. We show evidence that the subset of network traffic that is due to World Wide Web (WWW) transfers can show characteristics that are consistent with self-similarity, and we present a hypothesized explanation for that self-similarity. Using a set of traces of actual user executions of NCSA Mosaic, we examine the dependence structure of WWW traffic. First, we show evidence that WWW traffic exhibits behavior that is consistent with self-similar traffic models. Then we show that the self-similarity in such traffic can be explained based on the underlying distributions of WWW document sizes, the effects of caching and user preference in file transfer, the effect of user "think time", and the superimposition of many such transfers in a local-area network. To do this, we rely on empirically measured distributions both from client traces and from data independently collected at WWW servers.

Most of the proposed self-similar traffic models are asymptotic in nature. Hence, they are less effective in queueing-based performance evaluation when the buffer sizes are small. In this paper, we propose a short range dependent (SRD) process modelling by a generalized variance-based Markovian fitting to provide effective queueing-based performance measures when buffer sizes are small. The proposed method is to match the variance of the exact second-order self-similar processes. The fitting procedure determines the related parameters in an exact and straightforward way. The resultant traffic model essentially consists of a superposition of several two-state Markov-modulated Poisson processes (MMPPs) with distinct modulating parameters. We present how well the resultant MMPP could emulate the variance of original self-similar traffic in the range of the specified time scale, and could provide more accurate bounds for the queueing-based performance measures, namely tail probability, mean waiting time and loss probability. Numerical results show that both the second-order statistics and queueing-based performance measures when buffer capacity is small are more accurate than that of the variance-based fitting where the modulating parameters of each superposed two-state MMPP are equal. We then investigate the relationship between time scale and the number of superposed two-state MMPPs. We found that when the performance measures pertaining to larger time scales are not better than that of smaller ones, we need to increase the number of superposed two-state MMPPs to maintain the accurate and reliable queueing-based performance measures. We then conclude from the extensive numerical examples that an exact second-order self-similar traffic can be well represented by the proposed model.

Recently the notion of self-similarity has been shown to apply to wide-area and local-area network traffic. In this paper we examine the mechanisms that give rise to the self-similarity of network traffic. We present a hypothesized explanation for the possible self-similarity of traffic by using a particular subset of wide area traffic: traffic due to the World Wide Web (WWW). Using an extensive set of traces of actual user executions of NCSA Mosaic, reflecting over half a million requests for WWW documents, we examine the dependence structure of WWW traffic. While our measurements are not conclusive, we show evidence that WWW traffic exhibits behavior that is consistent with self-similar traffic models. Then we show that the self-similarity in such traffic can be explained based on the underlying distributions of WWW document sizes, the effects of caching and user preference in file transfer, the effect of user "think time", and the superimposition of many such transfers in a local area network. To do this we rely on empirically measured distributions both from our traces and from data independently collected at over thirty WWW sites.

Recent results from packet measurement analysis have shown that packet traffic exhibits fractal properties such as self-similarity (or its concomitant, long-range dependence) which are fundamentally different from features found in circuit switched voice traffic and captured by commonly used packet traffic models such as batch-Poisson and Markov modulated Poisson process (MMPP). These fractal properties are associated with the well-known burstiness of packet traffic, and self-similar traffic models (e.g., fractional Brownian motion (FBM)) permit parsimonious descriptions of packet traffic. The FBM model requires only 3 parameters: mean rate, peakedness (a measure of the fluctuations about the mean rate), and the Hurst parameter (characterizing long-range dependence). From the viewpoint of applying such models in practice, the estimation of these parameters is of crucial importance. We use a semi-parametric periodogram-based algorithm (SPA) to estimate the Hurst parameter and the peakedness. The algorithm is based on the fact that the power spectral density (PSD) of long-range dependent processes obey a power-law near the origin (i.e., 1/f-noise). We apply SPA to estimate the traffic parameters of both synthetically generated FBM traces as well as real Ethernet traces. Our analysis indicates that, compared with other methods SPA offers several advantages: (i) the marginals of the traffic time series are not required to be Gaussian (ii) it is computationally efficient (iii) it can estimate the peakedness factor as well as the Hurst parameter.

In the past few decades, there has been a large amount of work on algorithms for linear network flow problems, special classes of network problems such as assignment problems (linear and quadratic), Steiner tree problems, topology network design and nonconvex cost network flow problems. Network optimization problems find numerous applications in transportation, in communication network design, in production and inventory planning, in facilities location and allocation, and in VLSI design. The purpose of this book is to cover a spectrum of recent developments in network optimization problems, from linear networks to general nonconvex network flow problems.

We present the first constant-factor approximation algorithms for the following problem. Given a metric space ( V , c ), a finite set D ⊆ V of terminals/customers with demands d : D → R + , a facility opening cost f ∈ R + and a capacity u ∈R + , find a partition D = D 1 ⊍…⊍ D k and Steiner trees T i for D i ( i = 1, …, k ) with c ( E ( T i )) + d ( D i ) ≤ u for i = 1,…, k such that Σ i = 1 k c ( E ( T i )) + kf is minimum. This problem arises in VLSI design. It generalizes the bin-packing problem and the Steiner tree problem. In contrast to other network design and facility location problems, it has the additional feature of upper bounds on the service cost that each facility can handle. Among other results, we obtain a 4.1-approximation in polynomial time, a 4.5-approximation in cubic time, and a 5-approximation as fast as computing a minimum spanning tree on ( D , c ).

In this paper we tackle the design problem of the trunk group (TG) overlay in wide area ATM networks under reliability constraints. The TGs are composed of virtual paths (VPs) that the soft-permanent virtual connections (S-PVCs) can ride on. The private network-network interface (PNNI) routing standard is used to route these connections. The design problem consists to find the capacity and the administrative weight (AW) of each TG that ensure the successful rerouting of the S-PVCs for all failure scenarios of interest to the network planner. The objective is to minimize the cost of the TG overlay. An optimization model is proposed as well as a tabu search algorithm. A detailed TG overlay design example is performed and tested. The results showed that the tabu-based algorithm has improved the solution by 9.80%.

We consider the Minimum Elmore Delay Steiner Tree Problem, which is a key problem in VLSI design: We are given a set of pins which have to be connected by a Steiner tree. One of the pins is the source. Challenging timing constraints impose tight bounds on the delay of propagating a signal from the source to the other pins. The commonly used measure is Elmore delay (Elmore in J Appl Phys 19:55---63, 1948). We consider two variants: minimizing the maximum Elmore delay or a weighted sum of Elmore delays. Both variants are strongly NP-hard even for very restricted special cases. Although it is a central problem in VLSI design (Kahng and Robins in On optimal interconnections for VLSI. Kluwer, Boston, 1995; Korte and Vygen in Building bridges--between mathematics and computer science. Springer, Berlin, pp 333---368, 2008), no approximation algorithms were known so far. In this work, we give the first constant-factor approximation algorithm. It works for both variants. The algorithm achieves an approximation ratio of 3.39 in the rectilinear plane and 4.11 in general metric spaces. We can show that our algorithm is best possible in a certain sense. We also demonstrate that our algorithm leads to improvements on real world VLSI instances compared to the currently used standard method of computing short Steiner trees.

In this work we introduce a mixed integer linear program (MILP) for multi-layer networks with demand uncertainty. The goal is to minimize the overall network equipment costs containing basic node costs and interface costs while guarding against variations of the traffic demand. Multi-layer network design requires technological feasible inter-layer connections. We present and evaluate two layering configurations, top-bottom and variable. The first layering configuration utilizes all layers allowing shortcuts and the second enables layer-skipping. Technological capabilities like router-offloading and layers able to multiplex traffic demand are also included in the model. Several case studies are carried out applying the Γ-robustness concept to take into account the demand uncertainties. We investigate the dependency of the robustness parameter Γ on the overall costs and possible cost savings by enabling layer-skipping.

An algorithm with different exploration mechanisms: Experimental results to capacitated facility location/network design problem

Dimensionality problems in design of water quality networks arise from the multiple variables measured, which may be generated by different physical, chemical, and biological processes, and from the multiple spatial and temporal dimensions of the processes generating the measurements. The problem is further complicated by the range of objectives which a network may be required to meet. The designer is almost inevitably constrained by budget considerations to employ the same network to measure an array of variables, often for more than one objective. These considerations serve to pose serious difficulties in arriving at an analytical formulation of the problem, far less to solve it, with the result that almost all existing water quality networks have been designed on an ad hoc basis. Although no one approach is likely to be universally applicable, several techniques have been employed in particular situations. Included are state estimation, time series analysis, probability theory, and the theory of regionalized variables. Several promising applications of these techniques to water quality network design are reviewed, and suggestions for future research directions are advanced.

To support multicast communications for live media, the authors propose a group synchronization mechanism and enhance an intra-stream/inter-stream synchronization mechanism which they previously proposed for live media. The proposed method employs estimates of network delays for adjustment of the output timing among the destinations. The authors have implemented the mechanisms on a lip-synch experimental system. Live video of a speaker and his voice captured at a source are multicast, and then they are synchronized and output at the destinations. This paper also presents the system performance such as coefficient of variation of output interval, total pause time, mean square error of synchronization, average output rate, and average delay.