Abstract not found

The advent of fast tunable optical transceivers makes it feasible to dynamically update the connectivity of multihop WDM networks to accommodate traffic demands that vary over time. Of major concern in such design is how the connectivity should react to changes in traffic patterns. We formulate the problem as a Markovian Decision Process, and we develop heuristics to obtain good reconfiguration policies and manage the state and decision space explosion.

Telecommunications network planning is concerned with the design and maintenance of large networks at reasonable cost, to deliver high capacity and speed. Loosely interpreted, "reliability" is a key requirement. In this paper, reliability and performability are discussed in this context. A brief review of current tools is given, and some thoughts about future research are outlined. 1 TELECOMMUNICATIONS NETWORKS Given a set of geographically distributed sites, information about the traffic between them, and information about the means by which they can be connected (links), the network design problem is to select some of the candidate connections. The goals in this selection typically include keeping the cost within a specified budget and providing sufficient connections to support the traffic offered at a specified capacity, speed, or throughput. Of course, the wide variety of traffic types and patterns, and of means of connection, results in a significant range of network design prob...

this paper, we propose an algorithm that orders network partitionings in decreasing order of probability. This algorithm is similar to the Most Probable State Enumeration (MPSE) algorithm proposed by Li and Silvester. By looking at only the most probable partitionings, a good estimate of the performance of the network may be obtained. This approach also gives bounds on the network performance. Two distinct goals, both equally important, have been attained in this paper. First we have proposed an algorithm Order-P, to generate network partitionings in the order of their decreasing probabilities of occurrence. We are not aware of any other algorithm that specifically orders network partitionings. However, three algorithms (Order, Order-II, and NewOrder) that generate network states in order of their decreasing state probabilities are known, for dual-mode (up/down) components. We improvised these algorithms to generate the most probable network partitionings and then made a comparison with algorithm Order-P. Order-P has a lower computational complexity than all of the three improvised algorithms. The second goal has been to apply the algorithm in the real world and demonstrate its value in performance modeling of distributed systems. We believe that with the development of this algorithm, performance modeling of fairly large systems, hitherto unattempted due to large computational costs will be feasible. Although the obtained probabilities of occurrence of various partitionings using Order-P, are estimates of their real values, we claim that the approximation is close enough and substantiate this claim with an example. A methodology to compute performance measures under conditions of network partitioning has also been proposed, and corroborated with examples in the domain ...

A problem encountered in the analysis of telecommunication and other distribution systems is evaluating the performance of the system in meeting user demands with available resources. We consider the case in which user demands and available resources are only known stochastically, and connecting links can operate at various levels. This situation can be modeled as a stochastic network flow problem, in which each edge of the network assumes a finite number of values (corresponding to different capacity levels) with known probabilities. Each state of the network corresponds to a specification of supplies, demands, and link capacities in the given system. For any such state we are interested in whether overall demand can be met using the present supply of resources. If not, we are interested in the maximum demand that can be met using the best allocation of resources. The approach used here to estimate the probability of unmet demand, as well as the average unmet demand, involves generating only high leverage states of the systemstates having high probability and/or high values of unmet demand. A new method is proposed for generating such states in monotone order, either by probability or unmet demand. Various bounds on performance measures for the system are investigated. 2 1.

Network reduction techniques are mainly used with exact approaches such as factoring to compute network reliability. However, exact computation of network reliability is feasible only for small sized networks. Simulation is an alternative approach to estimate network reliability. This paper discuses the effect of using network reductions before estimating network reliability using a simulation. Theoretical and empirical results are provided to understand the source of variance reduction in simulation due to network reductions. 1