Jean Walrand

Achieving 100% throughput in an input-queued switch

It is well known that head-of-line blocking limits the throughput of an input-queued switch with first-in-first-out (FIFO) queues. Under certain conditions, the throughput can be shown to be limited to approximately 58.6%. It is also known that if non-FIFO queueing policies are used, the throughput can be increased. However, it has not been previously shown that if a suitable queueing policy and scheduling algorithm are used, then it is possible to achieve 100% throughput for all independent arrival processes. In this paper we prove this to be the case using a simple linear programming argument and quadratic Lyapunov function. In particular, we assume that each input maintains a separate FIFO queue for each output and that the switch is scheduled using a maximum weight bipartite matching algorithm. We introduce two maximum weight matching algorithms: longest queue first (LQF) and oldest cell first (OCF). Both algorithms achieve 100% throughput for all independent arrival processes. LQF favors queues with larger occupancy, ensuring that larger queues will eventually be served. However, we find that LQF can lead to the permanent starvation of short queues. OCF overcomes this limitation by favoring cells with large waiting times.

Automated vehicle control developments in the PATH program

The accomplishments to date on the development of automatic vehicle control technology in the Program on Advanced Technology for the Highway (PATH) at the University of California, Berkeley, are summarized. The basic principles and assumptions underlying the PATH work are identified, and the work on automating vehicle lateral (steering) and longitudinal (spacing and speed) control is explained. For both lateral and longitudinal control, the modeling of plant dynamics is described, and the development of the additional subsystems needed (communications, reference/sensor systems) and the derivation of the control laws are presented. Plans for testing on vehicles in both near and long term are discussed. >

Effective bandwidths for multiclass Markov fluids and other ATM sources

The authors show the existence of effective bandwidths for multiclass Markov fluids and other types of sources that are used to model ATM traffic. More precisely, it is shown that when such sources share a buffer with deterministic service rate, a constraint on the tail of the buffer occupancy distribution is a linear constraint on the number of sources. That is, for a small loss probability one can assume that each source transmits at a fixed rate called its effective bandwidth. When traffic parameters are known, effective bandwidths can be calculated and may be used to obtain a circuit-switched style call acceptance and routing algorithm for ATM networks. The important feature of the effective bandwidth of a source is that it is a characteristic of that source and the acceptable loss probability only. Thus, the effective bandwidth of a source does not depend on the number of sources sharing the buffer or the model parameters of other types of sources sharing the buffer. >

A distributed CSMA algorithm for throughput and utility maximization in wireless networks

In multihop wireless networks, designing distributed scheduling algorithms to achieve the maximal throughput is a challenging problem because of the complex interference constraints among different links. Traditional maximal-weight scheduling (MWS), although throughput-optimal, is difficult to implement in distributed networks. On the other hand, a distributed greedy protocol similar to IEEE 802.11 does not guarantee the maximal throughput. In this paper, we introduce an adaptive carrier sense multiple access (CSMA) scheduling algorithm that can achieve the maximal throughput distributively. Some of the major advantages of the algorithm are that it applies to a very general interference model and that it is simple, distributed, and asynchronous. Furthermore, the algorithm is combined with congestion control to achieve the optimal utility and fairness of competing flows. Simulations verify the effectiveness of the algorithm. Also, the adaptive CSMA scheduling is a modular MAC-layer algorithm that can be combined with various protocols in the transport layer and network layer. Finally, the paper explores some implementation issues in the setting of 802.11 networks.

Comparison of Multichannel MAC Protocols

This paper compares, through analysis and simulation, a number of multichannel MAC protocols. We first classify these protocols into four categories based on their principles of operation: dedicated control channel, common hopping, split phase, and parallel rendezvous protocols. We then examine the effects of the number of channels and devices, channel switching times, and traffic patterns on the throughput and delay of the protocols. Here are some of the conclusions of our study: (1) parallel rendezvous protocols generally perform better than single rendezvous protocols, (2) the dedicated control channel protocol can be a good approach with its simplicity when the number of channels is high and the packets are long, and (3) the split phase protocol is very sensitive to the durations of the control and data phases. Our study focuses on a single collision domain.

Analysis and comparison of TCP Reno and Vegas

We propose some improvements of TCP Vegas and compare its performance characteristics with TCP Reno. We argue through analysis that TCP Vegas, with its better bandwidth estimation scheme, uses the network resources more efficiently and fairly than TCP Reno. Simulation results are given that support the results of the analysis.

A simple dynamic routing problem

As jobs arrive they have to be routed to one of two similar exponential servers. It is shown that if the queue lengths at both servers are observed then the Optimal decision is to route jobs to the shorter queue, whereas if the queue lenths are not observed then it is best to alternate between queues, provided the initial distribution of the two queue sizes is the same. The optimality of these routing strategies is independent of the statistics of the job arrivals.

A quick simulation method for excessive backlogs in networks of queues

Excessive backlogs in stable open Jackson networks are studied. Although these events occur rarely, they can be critical, since they can impair the functioning of the network. The use of simulation to estimate their probability is attempted. Since a direct simulation of a rare event takes a very long time, a method is discussed for changing the network to speed up the simulation, using a heuristic method. It is shown by examples that the method can be several orders of magnitude faster than direct simulations. >

Sufficient conditions for stability of longest-queue-first scheduling: second-order properties using fluid limits

We consider the stability of the longest-queue-first scheduling policy (LQF), a natural and low-complexity scheduling policy, for a generalized switch model. Unlike that of common scheduling policies, the stability of LQF depends on the variance of the arrival processes in addition to their average intensities. We identify new sufficient conditions for LQF to be throughput optimal for independent, identically distributed arrival processes. Deterministic fluid analogs, proved to be powerful in the analysis of stability in queueing networks, do not adequately characterize the stability of LQF. We combine properties of diffusion-scaled sample path functionals and local fluid limits into a sharper characterization of stability.

Extensions of the multiarmed bandit problem: The discounted case

There are N independent machines. Machine i is described by a sequence {X^{i}(s), F^{i}(s)} where X^{i}(s) is the immediate reward and F^{i}(s) is the information available before i is operated for the sth lime. At each time one operates exacfiy one machine; idle machines remain frozen. The problem is to schedule the operation of the machines so as to maximize the expected total discounted sequence of rewards. An elementary proof shows that to each machine is associated an index, and the optimal policy operates the machine with the largest current index. When the machines are completely observed Markov chains, this coincides with the well-known Gittins index rule, and new algorithms are given for calculating the index. A reformulation of the bandit problem yields the tax problem, which includes, as a special case, Klimovs waiting time problem. Using the concept of superprocess, an index rule is derived for the case where new machines arrive randomly. Finally, continuous time versions of these problems are considered for both preemptive and nonpreemptive disciplines.