We analyzed the non-Gaussian nature of network traffic using some Internet traffic data. We found that (1) the non-Gaussian nature degrades network performance, (2) it is caused by ‘greedy flows’ that exist with non-negligible probability, and (3) a large majority of ‘greedy flows’ are TCP flows having relatively small hop counts, which correspond to small round-trip times. We conclude that in ...

We introduce a new representation scheme for coalitional games, called coalition-flow networks (CF-NETs), where the formation of effective coalitions in a task-based setting is reduced to the problem of directing flow through a network. We show that our representation is intuitive, fully expressive, and captures certain patterns in a significantly more concise manner compared to the conventiona...

This paper shows that partial differential equations may be a possible area of application of mathematical programming. The solution of Laplace's equation with Neumann's condition is shown to be a minimum cost network flow problem with cost proportional to the arc flow. An algorithm of solving minimum quadratic cost network flow is given.

In this paper, a fuzzy random minimum cost flow problem is presented. In this problem, cost parameters and decision variables are fuzzy random variables and fuzzy numbers respectively. The object of the problem is to find optimal flows of a capacitated network. Then, two algorithms are developed to solve the problem based on Er-expected value of fuzzy random variables and chance-constrained pro...

This paper presents and solves the maximum throughput dynamic network flow problem, an infinite horizon integer programming problem which involves network flows evolving over time. The model is a finite network in which the flow on each arc not only has an associated upper and lower bound but also an associated transit time. Flow is to be sent through the network in each period so as to satisfy...

Let G = (V,E) be a directed graph with two special vertices: a source s and a sink t. Every edge (u, v) has a capacity cap(u, v) ≥ 0. For convenience, we define cap(u, v) = 0 if (u, v) in not an edge. More specifically, we work with a modified set of edges {(u, v) : (u, v) ∈ E or (v, u) ∈ E} with cap(u, v) = 0 if (u, v) 6∈ E. A flow is a real-valued function on edges with three properties: • Sk...

We define a thermal network, which is a network where the flow functionality of a node depends upon its temperature. This model is inspired by several types of real-life networks, and generalizes some conventional network models wherein nodes have fixed capacities and the problem is to maximize the flow through the network. In a thermal network, the temperature of a node increases as traffic mo...

To study mechanisms that cause the nonGaussian nature of network traffic, we analyzed IP flow statistics. For greedy flows in particular, we investigated the hop counts between source and destination nodes, and classified applications by the port number. We found that the main flows contributing to the non-Gaussian nature of network traffic were HTTP flows with relatively small hop counts compa...