Network traffic simulation

About: Network traffic simulation is a research topic. Over the lifetime, 4535 publications have been published within this topic receiving 74606 citations.

Does Traffic Consolidation Always Lead to Network Energy Savings

Abstract: In this paper we study the behavior of a general optimization model for reducing the power consumption of core networks employing energy-aware network equipment. Specifically, we assess how the energy profiles of the devices affect the outcome of the optimization model and hence determine the general power saving policy. The computational analysis performed on several real topologies shows that the widespread traffic consolidation strategy does not always provide the best results. In fact, for devices presenting a cubic (convex in general) energy profile, the highest energy savings are achieved by spreading the traffic on the network.

Multi-scale integrated information and telecommunications system (MIITS): first results from a large-scale end-to-end network simulator

Abstract: Performing realistic simulations of Internet packet traffic on a national or global level is a daunting task from both the modeling and the computational perspective. We present the MIITS (Multi-scale Integrated Information and Telecommunications System) tool that implements a novel approach to network simulation and report first scaling results from a realistic Internet scenario. MIITS' end-to-end approach to network simulation relies on modules for (i) accurate network topology and capacity representation, (ii) realistic communication session generation based on the activities of an agent population that is statistically equivalent to the population in a large metropolitan area, (iii) the actual scalable packet-level network simulation that is based on distributed event?driven technology, and (iv) analysis of large amounts of simulation output data. We present a sample simulation of a Los Angeles network as an intermediate step toward the vision of national-level simulation.

Anomaly detection for network servers using digital signature of network segment

Abstract: Network anomaly detection is essential for rapid fault recovery and increasing network reliability. The paper presents results of the utilization of the digital signatures of network segments (DSNS) for network servers to characterize the traffic that flows through the network servers. An alarm system model is also presented that uses the network servers' traffic characterization generated by DSNS. The obtained results validate the experiment and show, in practice, significant advantages in network management.

Design and Dimensioning of a WDM Mesh Network to Groom Dynamically Varying Traffic

Abstract: In this paper, we address the traffic grooming problem in WDM mesh networks when the offered traffic is characterized by a set of traffic matrices—a variant of dynamically changing traffic. We justify the need to address this problem in mesh networks and also argue for the validity of our approach to solve this problem. Our primary objective is to design the network in terms of the number of wavelengths and transceivers required to support any offered traffic matrix. We provide a simple and generic framework to minimize the number of transceivers needed in the network. Simulation results have been presented in contrast with a possible approach, to enable comparison with our solution strategy. An ILP formulation of our approach is also presented.

Robust network design

Abstract: In this paper, we address the problem of robust network design. Robustness is defined as the minimizing variations in network performance, such as average delay and throughput, due to the perturbations in the network, e.g. topology, demand and community of interest. We pose an optimization problem is cast in the form of minimizing a new robustness metric that is a function of network routing, capacities and external traffic demand distributions. We use the correspondence between packet flows in a network and random walk models. We use Markov chain sensitivity analysis to derive a new measure and prove its robustness property. We show that the node robustness factor, along with the Kemeny constant, plays a critical role in the robustness of a network. We evaluate the proposed robust optimization method by comparing to conventional network design approaches.