Tania Jimenez

A survey on networking games in telecommunications

In this survey, we summarize different modeling and solution concepts of networking games, as well as a number of different applications in telecommunications that make use of or can make use of networking games. We identify some of the mathematical challenges and methodologies that are involved in these problems. We include here work that has relevance to networking games in telecommunications from other areas, in particular from transportation planning.

Competitive routing in networks with polynomial costs

We study a class of noncooperative general topology networks shared by N users. Each user has a given flow which it has to ship from a source to a destination. We consider a class of polynomial link cost functions adopted originally in the context of road traffic modeling, and show that these costs have appealing properties that lead to predictable and efficient network flows. In particular, we show that the Nash equilibrium is unique, and is moreover efficient. These properties make the polynomial cost structure attractive for traffic regulation and link pricing in telecommunication networks. We finally discuss the computation of the equilibrium in the special case of the affine cost structure for a topology of parallel links.

Novel Delayed ACK Techniques for Improving TCP Performance in Multihop Wireless Networks

We study in this paper TCP performance over a static multihop network that uses IEEE 802.11 protocol for access. For such networks it has been shown in [6] that TCP performance is mainly determined by the hidden terminal effects (and not by drop probabilities at buffers) which limits the number of packets that can be transmitted simultaneously in the network. We propose new approaches for improving the performance based on thinning the ACK streams that competes over the same radio resources as the TCP packets. In particular, we propose a new delayed ACK scheme in which the delay coefficient varies with the sequence number of the TCP packet. Through simulations we show that the ACK thinning allows to increase TCP throughput substantially more than previous improvement methods.

Slotted Aloha as a game with partial information

This paper studies distributed choice of retransmission probabilities in slotted ALOHA. Both the cooperative team problem as well as the noncooperative game problem are considered. Unlike some previous work, we assume that mobiles do not know the number of backlogged packets at other nodes. A Markov chain analysis is used to obtain optimal and equilibrium retransmission probabilities and throughput. We then investigate the impact of adding retransmission costs (which may represent the disutility for power consumption) on the equilibrium and show how this pricing can be used to make the equilibrium throughput coincide with the optimal team throughput.

Competitive routing in networks with polynomial cost

We study a class of noncooperative general topology networks shared by N users. Each user has a given flow which it has to ship from a source to a destination. We consider a class of polynomial link cost functions, adopted originally in the context of road traffic modeling, and show that these costs have appealing properties that lead to predictable and efficient network flows. In particular, we show that the Nash equilibrium is unique, and is moreover efficient, i.e., it coincides with the solution of a corresponding global optimization problem with a single user. These properties make the cost structure attractive for traffic regulation and link pricing in telecommunication networks. We finally discuss the computation of the equilibrium in the special case of the affine cost structure for a topology of parallel links.

Routing into Two Parallel Links

We study a class of noncooperative networks where N users send traffic to a destination node over two links with given capacities in such a way that a Nash equilibrium is achieved. Under a linear cost structure for the individual users, we obtain several dynamic policy adjustment schemes for the online computation of the Nash equilibrium and study their local convergence properties. These policy adjustment schemes require minimum information on the part of each user regarding the cost?utility functions of the others.

A game theoretic approach for delay minimization in slotted ALOHA

This paper studies distributed choice of retransmission probabilities in slotted ALOHA. Both the cooperative team problem as well as the noncooperative game problem is considered. In previous work that has focused on the maximization of throughput, it was shown that in heavy load, this maximization is obtained at the cost of a huge delay of backlogged packets. This motivates us to investigate the delay minimization problem as well as the multicriterion problem of minimizing the average expected delay (or maximizing the throughput) subject to constraints on the expected delay of backlogged packets. A Markov chain analysis is used to obtain optimal and equilibrium retransmission probabilities and expected delays analysis.

ON THE COMPARISON OF QUEUEING SYSTEMS WITH THEIR FLUID LIMITS

In this article, we study a method to compare queueing systems and their fluid limits. For a certain class of queueing systems, it is shown that the expected workload (and certain functions of the workload) is higher in the queueing system than in the fluid approximation. This class is characterized by convexity of the value function in the state component(s) where external arrivals occur. The main example that we consider is a tandem of multiserver queues with general service times and Markov-modulated arrivals. The analysis is based on dynamic programming and the use of phase-type distributions. Numerical examples to illustrate the results are also given.

Probabilistic analysis of buffer starvation in Markovian queues

Our purpose in this paper is to obtain the exact distribution of the number of buffer starvations within a sequence of N consecutive packet arrivals. The buffer is modeled as an M/M/1 queue. When the buffer is empty, the service restarts after a certain amount of packets are prefetched. With this goal, we propose two approaches, one of which is based on Ballot theorem, and the other uses recursive equations. The Ballot theorem approach gives an explicit solution, but at the cost of the high complexity order in certain circumstances. The recursive approach, though not offering an explicit result, needs fewer computations. We further propose a fluid analysis of starvation probability on the file level, given the distribution of file size and the traffic intensity. The starvation probabilities of this paper have many potential applications. We apply them to optimize the quality of experience (QoE) of media streaming service, by exploiting the tradeoff between the start-up delay and the starvation.

Analysis of Buffer Starvation With Application to Objective QoE Optimization of Streaming Services

Our purpose in this paper is to characterize buffer starvations for streaming services. The buffer is modeled as a FIFO queue with exponential service time and Poisson arrivals. When the buffer is empty, the service restarts after a certain amount of packets are prefetched. With this goal, we propose two approaches to obtain exact distribution of the number of buffer starvations, one of which is based on Ballot theorem, and the other uses recursive equations. The Ballot theorem approach gives an explicit result. We extend this approach to the scenario with a constant playback rate using Tàkacs Ballot theorem. The recursive approach, though not offering an explicit result, allows us to obtain the distribution of starvations with non-independent and identically distributed (i.i.d.) arrival process in which an ON/OFF bursty arrival process is considered. We further compute the starvation probability as a function of the amount of prefetched packets for a large number of files via a fluid analysis. Among many potential applications of starvation analysis, we show how to apply it to optimize objective quality of experience (QoE) of media streaming, by exploiting the tradeoff between startup/rebuffering delay and starvations.