This paper is principally concerned with resource allocation for connections tolerating statistical quality of service (QoS) guarantees in a public wide-area ATM network. Our aim is to sketch a ...framework, based on effective bandwidths, for call admission schemes that are sensitive to individual QoS requirements and account for statistical multiplexing. Results approximating the effective bandwidth required by heterogeneous streams sharing buffered links, including results for the packetized generalized processor sharing service discipline, are described. Extensions to networks follow via the concept of decoupling bandwidths, motivated by a study of the input-output properties of queues. Based on these results we claim that networks with sufficient routing diversity will inherently satisfy nodal decoupling. We then discuss on-line methods for estimating the effective bandwidth of connection. Using this type of traffic monitoring we propose an approach to usage parameter control (i.e., policing) for effective bandwidth descriptors. Finally, we suggest how on-line monitoring might be combined with admission control to exploit unknown statistical multiplexing gains and thus increase utilization.< >
At each instant of time we are required to sample a fixed number m \geq 1 out of N i.i.d, processes whose distributions belong to a family suitably parameterized by a real number \theta . The ...objective is to maximize the long run total expected value of the samples. Following Lai and Robbins, the learning loss of a sampling scheme corresponding to a configuration of parameters C = (\theta_{1},..., \theta_{N}) is quantified by the regret R_{n}(C) . This is the difference between the maximum expected reward at time n that could be achieved if C were known and the expected reward actually obtained by the sampling scheme. We provide a lower bound for the regret associated with any uniformly good scheme, and construct a scheme which attains the lower bound for every configuration C . The lower bound is given explicitly in terms of the Kullback-Liebler number between pairs of distributions. Part II of this paper considers the same problem when the reward processes are Markovian.
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.< >
By focusing on the convergence of the telephone, computer networking, cable TV, and wireless industries, this fully revised second edition explains current and emerging networking technologies. The ...authors proceed from fundamental principles to develop a comprehensive understanding of network architectures, protocols, control, performance, and economics. Communications engineers, computer scientists, and network administrators and managers will appreciate the book for its perspectives on the innovations that impact their work. Students will be enriched by the descriptive and thorough coverage of networking, giving them the knowledge to explore rewarding career opportunities.* Provides the most recent information on * wide and local area networks, including WDM and optical networks, Fast and Gigabit Ethernets* access networks, such as cable modems and DSL;* approaches for quality-differentiated services in IP and ATM networks.* Examines the Internet, including proposed advances for improved performance and quality of service.* Presents a comprehensive discussion of wireless networks for voice and data.* Explains the economic factors and technical tradeoffs that guide network development.* Derives (in self-contained sections) the most important mathematical results of network performance.
Addresses the issue of call acceptance and routing in ATM networks. The goal is to design an algorithm that guarantees bounds on the fraction of cells lost by a call. The method proposed for call ...acceptance and routing does not require models describing the traffic. Each switch estimates the additional fraction of cells that would be lost if new calls were routed through the switch. The routing algorithm uses these estimates. The estimates are obtained by monitoring the switch operations and extrapolating to the situation where more calls are routed through the switch. The extrapolation is justified by a scaling property. To reduce the variance of the estimates, the switches calculate the cell loss that would occur with virtual buffers. A way to choose the sizes of the virtual buffers in order to minimize the variance is discussed. Thus, the switches constantly estimate their spare capacity. Simulations were performed using Markov fluid sources to test the validity of the approach.< >
At each instant of time we are required to sample a fixed number m \geq 1 out of N Markov chains whose stationary transition probability matrices belong to a family suitably parameterized by a real ...number \theta . The objective is to maximize the long run expected value of the samples. The learning loss of a sampling scheme corresponding to a parameters configuration C = (\theta_{1}, ..., \theta_{N}) is quantified by the regret R_{n}(C) . This is the difference between the maximum expected reward that could be achieved if C were known and the expected reward actually achieved. We provide a lower bound for the regret associated with any uniformly good scheme, and construct a sampling scheme which attains the lower bound for every C . The lower bound is given explicitly in terms of the Kullback-Liebler number between pairs of transition probabilities.
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