Stochastic Dynamic Programming and Stochastic Fluid-Flow Models in the Design and Analysis of Web-Server Farms

A Web-server farm is a specialized facility designed specifically for housing Web servers catering to one or more Internet facing Web sites. In this dissertation, stochastic dynamic programming technique is used to obtain the optimal admission control policy with different classes of customers, and stochastic uid- ow models are used to compute the performance measures in the network. The two types of network traffic considered in this research are streaming (guaranteed bandwidth per connection) and elastic (shares available bandwidth equally among connections). We first obtain the optimal admission control policy using stochastic dynamic programming, in which, based on the number of requests of each type being served, a decision is made whether to allow or deny service to an incoming request. In this subproblem, we consider a xed bandwidth capacity server, which allocates the requested bandwidth to the streaming requests and divides all of the remaining bandwidth equally among all of the elastic requests. The performance metric of interest in this case will be the blocking probability of streaming traffic, which will be computed in order to be able to provide Quality of Service (QoS) guarantees. Next, we obtain bounds on the expected waiting time in the system for elastic requests that enter the system. This will be done at the server level in such a way that the total available bandwidth for the requests is constant. Trace data will be converted to an ON-OFF source and fluid- flow models will be used for this analysis. The results are compared with both the mean waiting time obtained by simulating real data, and the expected waiting time obtained using traditional queueing models. Finally, we consider the network of servers and routers within the Web farm where data from servers flows and merges before getting transmitted to the requesting users via the Internet. We compute the waiting time of the elastic requests at intermediate and edge nodes by obtaining the distribution of the out ow of the upstream node. This out ow distribution is obtained by using a methodology based on minimizing the deviations from the constituent in flows. This analysis also helps us to compute waiting times at different bandwidth capacities, and hence obtain a suitable bandwidth to promise or satisfy the QoS guarantees. This research helps in obtaining performance measures for different traffic classes at a Web-server farm so as to be able to promise or provide QoS guarantees; while at the same time helping in utilizing the resources of the server farms efficiently, thereby reducing the operational costs and increasing energy savings

New utilization criteria for online scheduling

In the classical scheduling problems, it has been assumed that complete knowledge of the problem was available when it was to be solved. However, scheduling problems in the real world face the possibility of the lack of the knowledge. Uncertainties frequently encountered in scheduling environments include the appearance of new jobs and unknown processing times. In this work, we take into account these realistic issues. This thesis deals with the problem of non-preemptive scheduling independent jobs on m identical parallel machines. In our online model, the jobs are submitted over time non-clairvoyantly. Therefore, the processing times of the jobs are unknown until they complete. Further, we assume that the ratio of weight to processing time is equal for all jobs, that is, all jobs have the same priorities. The jobs are assigned to the machines in a nondelay fashion. Our main scheduling objective is to maximize the utilization of the system. We show that the commonly used makespan criterion usually cannot reflect the true utilization of this kind of online scheduling problems. For this reason, it is very important to find another criterion capable of evaluating system utilization. Therefore, we introduce two new alternative criteria that more accurately capture the utilization of the machines. Moreover, we derive competitive factors for both criteria. Those competitive factors are tight for one criterion and almost tight for the other. Finally, we present an experimental investigation to evaluate the performance of the nondelay online algorithm with respect to our criteria. The experimental results show the confirmation of our theoretical results

Optimal policies for ATM cell scheduling and rejection

This paper addresses the following questions related to buffer management schemes for high speed integrated services networks: (i) given the pattern of cell arrivals from different classes of traffic, can buffer control significantly influence the effect of cell loss, and (ii) what are the best policies for selecting cells for transmission from buffers in the network nodes as well as for rejecting cells when the buffers are full. The basic approach to answering these questions is to impute a cost of losing cells which could depend on the class of application, and to minimize this cost over the finite or infinite time horizons. The policies we derive using this cost minimization approach are best in the sense that they minimize linear cost functions of cell losses. at each instant of time during the system\u27s operation. We also show how to construct policies that minimize general cost functions of cell loss rates

Optimal Policies For Atm Cell Scheduling And Rejection

This paper addresses the following questions related to buffer management schemes for high speed integrated services networks: (i) given the pattern of cell arrivals from different classes of traffic, can buffer control significantly influence the effect of cell loss, and (ii) what are the best policies for selecting cells for transmission from buffers in the network nodes as well as for rejecting cells when the buffers are full. The basic approach to answering these questions is to impute a cost of losing cells which could depend on the class of application, and to minimize this cost over the finite or infinite time horizons. The policies we derive using this cost minimization approach are best in the sense that they minimize linear cost functions of cell losses, at each instant of time during the system\u27s operation. We also show how to construct policies that minimize general cost functions of cell loss rates. © 2001 Kluwer Academic Publishers