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.

In this thesis, the radar pulse repetition interval (PRI) tracking with Kalman Filter problem is investigated. The most common types of PRIs are constant PRI, step (jittered) PRI, staggered PRI, sinusoidally modulated PRI. This thesis considers the step (this type of PRI agility is called as constant PRI when the jitter on PRI values is eliminated) and staggered PRI cases. Different algorithms have been developed for tracking step and staggered PRIs cases. Some useful simplifications are obtained in the algorithm developed for step PRI sequence. Two different algorithms robust to the effects of missing pulses obtained for staggered PRI sequence are compared according to estimation performances. Both algorithms have two parts: detection of the period part and a Kalman filter model. The advantages and disadvantages of these algorithms are presented. Simulations are implemented in MATLAB.

In this thesis, performance of the Contribution Reward Routing Protocol with Shapley Value (CAP-SV), a power-aware routing protocol for ad hoc networking is analyzed. Literature study on ad hoc network routing and ower-awareness is given. The overhead induced by the extra packets of the redirection mechanism of CAP-SV is formulized and the factors affecting this overhead are discussed. Then, the power consumption of CAP-SV is analytically analized using a linear power consumption model. It is shown that CAP-SV performs better than AODV regarding power consumption. The analysis validates the simulation results reported in the literature and provides general principles of how protocol and scenario parameters affect the performance.

This study firstly aims to identify facility features of the convention centers and then propose a method in order to identify users&rsquo / priorities and evaluate what extent these were provided by the convention centre. Data has been collected using self-administered questionnaires from three group of users / attendees, employees and meeting planners. The study has been conducted in istanbul L&uuml / tfi Kirdar Convention and Exhibition Center as a case, because of being the most remarkable convention center of Turkey. Each participant will be required to assess this convention center in terms of their priorities of expectations and features provided. The results have been evaluated statistically, and significant differences between the level of importance and performance of the facility features have been presented. This research is expected to be useful for constitution of design criteria of convention centers and effective management of the facilities, in terms of both identifying the features of convention centers and providing a method evaluating the performance of the facilities from the users&rsquo / perspective.

Rail transit investments require highest amount of investment costs of all modes and considering the high cost involved, it is particularly important that their performance justifies this high cost and that expectations from these investments are met. Therefore, in the world, it has become an important field of research to study the performances of rail systems in order to assess whether these expectations are met. In Turkey, there is a growing interest in constructing rail transit systems in the cities. However, there has been limited number of studies on the performance of these investments. There are researches on individual systems / yet, there has not been a comprehensive, systematic and comparative evaluation of the rail transit experience of Turkish cities. It is not clear with what expectations these systems are built or whether these expectations are met. There seems to be an urgent need to study these rail investments, with a particular focus on their planning, investment objectives and outcomes. This thesis analyzes the expectations from the rail transit systems in Turkey and answers the question whether these expectations are met. In order to understand the objectives under the planning and decision making processes in the implementation of Turkish rapid rail transport investments, a sample group was selected among the cities currently operating rail transit systems: &amp / #272 / stanbul, Ankara, &amp / #272 / zmir and Bursa. The study sets the objectives in planning and implementing rail transit systems drawn by the answers in the semi-structured interviews. It compares the expectations with the actual outcomes. As the primary indicators of performance, cost and ridership forecast and outcome data are also collected and considered in the comparison. It is found that the main success in all case study cities was the increase in public transport usage after the opening of the rail transit systems. On the other hand, systems performed rather poor in terms of other expectations, such as attaining ridership forecasts, being built within budget, creating an integrated public transport system, traffic reduction, air pollution reduction, improvement of city image, etc. Hence there is a gap between expectations and outcomes.

Performance analysis is an objective method of gathering the data of performance, and generally transforms these observations into numerical data. Performance indicators, as well as a selection or elements of sucessful outcome, have often been used in order to feedback augmented information in performance analysis systems, but they have rarely been considered within the classification of performance analysis systems based on timing of analysis and feedback. The main aim of this study is to investigate performance indicators used within real-time and lapsed time systems so that the definitions of the performance indicators, the effectiveness of the performance indicators, their reliability and validity within real time analysis systems can be analyzed.

In recent years, Interface Management (IM) practices have been emerging to address the challenges of managing complex capital projects. These challenges include the added complexity and scale of these projects, globalization, geographical distribution and various working cultures, and different internal and external risks. Oil sands, off-shore and nuclear are examples of this class of projects. Despite an emerging consensus on the effectiveness of IM for facilitating complex projects delivery, IM definitions, elements, and the way it has been implemented varies widely across the construction industry. Furthermore, identifying key interface points, integrating IM with the project schedule, and the relationship between IM implementation and project performance are significant questions that owners and contractors wish to have addressed. Therefore, the objectives of this thesis are to develop a workflow driven process for IM, study its current status in the industry, develop an algorithm to identify key interface points and integrate IM with project schedule, and investigate the relationship between IM implementation and project performance. This research is mostly focused on industrial construction, though some data from other sectors is included. In this thesis, the elements and fundamental definitions of Interface Management are proposed. Then, a workflow driven Interface Management System (IMS) is developed, which lays out a strategy to systematically identify and manage stakeholders’ interfaces with the objective of more effective risk management in capital projects. Once the IMS ontology is defined, the current state of IM in the construction industry is studied through data collection on 46 projects by conducting questionnaire based interviews. The interviewed projects are from different sectors of the industry, with various sizes and geographical locations. This study aims at identifying the project characteristics that lead to formal IM implementation in a project, current common IM practices in the industry, and criteria to assess the status and effectiveness of IM. Furthermore, the relationship between IM implementation and project performance in terms of cost and schedule growth is investigated by employing descriptive and statistical analysis tools. One observation was that those projects that implemented IM at a high level experienced lower cost growth and less variation in the cost growth. This thesis also proposes a methodology to identify key interface points by recognizing the interdependency relationships between them and creating the Interface Points Network. By analyzing the network, two types of high impact and risk prone interface points are identified. Once the key interface points are recognized, they are linked to the interface milestones on the project schedule, to integrate the cyclic information of IMS with the conventional, sequential planning, scheduling and control paradigms (e.g. CPM). The proposed algorithms are validated on a representative offshore model project. In summary, the proposed algorithms in this thesis provide a framework to improve project performance through better alignment between stakeholders, enforcement of contract terms, and effective sharing and distribution of risk-related information within formalized interface management framework. The empirical analysis also sets a foundation for construction organizations to assess their IM with regard to the current practices in the industry and a roadmap to improve their IM practices to more mature levels.

Hop count, i.e., the number of wireless hops a packet has to go through to reach the destination, is a fundamental metric in multi-hop wireless ad-hoc networks. Network performance, such as throughput, end-to-end delay, energy consumption, and so on, depends critically on hop count. Previous work on modeling hop count is limited in making unrealistic simplifying assumptions either at the physical or network, or both layers of the communication protocol stack. A key contribution of this thesis is to present an analytical model to derive the probability distribution of hop count under realistic assumptions at both physical and network layers. Specifically, the model considers a log-normal shadowing radio propagation capable of accommodating the random signal fading observed in most wireless communication environments, and the widely used geographic routing at the network layer. Validation of the model is achieved by a comprehensive set of simulation experiments including a trace driven simulation of a real-word vehicular ad-hoc network. The model reveals that the presence of randomness in radio propagation reduces the required number of hops to reach a given destination significantly. To demonstrate the utility of the proposed hop count model, the thesis proposes three new applications which address some of the key challenges in multi-hop wireless networks. The first application derives the per-node packet forwarding load in multi-hop wireless sensor networks and reveals that the nodes in the vicinity of the base station has a significantly less forwarding load than previously thought under simplifying radio propagation and routing assumptions. The second application demonstrates that using hop count as a measure of distance traveled by a data packet, geocasting can be achieved in multi-hop wireless networks in situations when some of the network nodes do not have access to reliable location information. Finally, the proposed hop count model is used to evaluate the performance of the third application which demonstrates that the overhead of geographic routing can be reduced significantly by embracing a position update philosophy which adapts to the mobility and communication patterns of the underlying ad-hoc network.

Hop count, i.e., the number of wireless hops a packet has to go through to reach the destination, is a fundamental metric in multi-hop wireless ad-hoc networks. Network performance, such as throughput, end-to-end delay, energy consumption, and so on, depends critically on hop count. Previous work on modeling hop count is limited in making unrealistic simplifying assumptions either at the physical or network, or both layers of the communication protocol stack. A key contribution of this thesis is to present an analytical model to derive the probability distribution of hop count under realistic assumptions at both physical and network layers. Specifically, the model considers a log-normal shadowing radio propagation capable of accommodating the random signal fading observed in most wireless communication environments, and the widely used geographic routing at the network layer. Validation of the model is achieved by a comprehensive set of simulation experiments including a trace driven simulation of a real-word vehicular ad-hoc network. The model reveals that the presence of randomness in radio propagation reduces the required number of hops to reach a given destination significantly. To demonstrate the utility of the proposed hop count model, the thesis proposes three new applications which address some of the key challenges in multi-hop wireless networks. The first application derives the per-node packet forwarding load in multi-hop wireless sensor networks and reveals that the nodes in the vicinity of the base station has a significantly less forwarding load than previously thought under simplifying radio propagation and routing assumptions. The second application demonstrates that using hop count as a measure of distance traveled by a data packet, geocasting can be achieved in multi-hop wireless networks in situations when some of the network nodes do not have access to reliable location information. Finally, the proposed hop count model is used to evaluate the performance of the third application which demonstrates that the overhead of geographic routing can be reduced significantly by embracing a position update philosophy which adapts to the mobility and communication patterns of the underlying ad-hoc network.

Obtaining an accurate whole program path (WPP) that captures a program’s runtime behaviour in terms of a control-flow trace has a number of well-known benefits, including opportunities for code optimization, bug detection, program analysis refinement, etc. Existing techniques to compute WPPs perform sub-optimal instrumentation resulting in significant space and time overheads. Our goal in this thesis is to minimize these overheads without losing precision. To do so, we design a novel and scalable whole program analysis to determine instrumentation points used to obtain WPPs. Our approach is divided into three components: (a) an efficient summarization technique for inter-procedural path reconstruction, (b) specialized data structures called conflict sets that serve to effectively distinguish between pairs of paths, and (c) an instrumentation algorithm that computes the minimum number of edges to describe a path based on these conflict sets. We show that the overall problem is a variant of the minimum hitting set problem, which is NP-hard, and employ various sound approximation strategies to yield a practical solution. We have implemented our approach and performed elaborate experimentation on Java programs from the DaCapo benchmark suite to demonstrate the efficacy of our approach across multiple dimensions. On average, our approach necessitates instrumenting only 9% of the total number of CFG edges in the program. The average runtime overhead incurred by our approach to collect WPPs is 1.97x, which is only 26% greater than the overhead induced by only instrumenting edges guaranteed to exist in an optimal solution. Furthermore, compared to the state-of-the-art, we observe a reduction in runtime overhead by an average and maximum factor of 2.8 and 5.4, respectively.