Research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis and computer science

This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis, and computer science during the period April l, 1988 through September 30, 1988

Inferring Queueing Network Models from High-precision Location Tracking Data

Stochastic performance models are widely used to analyse the performance and reliability of systems that involve the flow and processing of customers. However, traditional methods of constructing a performance model are typically manual, time-consuming, intrusive and labour-intensive. The limited amount and low quality of manually-collected data often lead to an inaccurate picture of customer flows and poor estimates of model parameters. Driven by advances in wireless sensor technologies, recent real-time location systems (RTLSs) enable the automatic, continuous and unintrusive collection of high-precision location tracking data, in both indoor and outdoor environment. This high-quality data provides an ideal basis for the construction of high-fidelity performance models. This thesis presents a four-stage data processing pipeline which takes as input high-precision location tracking data and automatically constructs a queueing network performance model approximating the underlying system. The first two stages transform raw location traces into high-level “event logs” recording when and for how long a customer entity requests service from a server entity. The third stage infers the customer flow structure and extracts samples of time delays involved in the system; including service time, customer interarrival time and customer travelling time. The fourth stage parameterises the service process and customer arrival process of the final output queueing network model. To collect large-enough location traces for the purpose of inference by conducting physical experiments is expensive, labour-intensive and time-consuming. We thus developed LocTrack- JINQS, an open-source simulation library for constructing simulations with location awareness and generating synthetic location tracking data. Finally we examine the effectiveness of the data processing pipeline through four case studies based on both synthetic and real location tracking data. The results show that the methodology performs with moderate success in inferring multi-class queueing networks composed of single-server queues with FIFO, LIFO and priority-based service disciplines; it is also capable of inferring different routing policies, including simple probabilistic routing, class-based routing and shortest-queue routing

Packet-switched voice and its application to integrated voice / data networks

Imperial Users onl

Approximate solutions for multi-server queuing systems with Erlangian service times and an application to air traffic management

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.Includes bibliographical references (p. 209-213).This thesis is concerned with approximations of certain M(t)/G(t)/n(t)/n(t) + q queueing systems. More specifically, we are interested in such systems under very general conditions such as time-varying demand and capacity, and high utilization, including occasional oversaturation. Conditions such as these cannot be addressed with existing methodologies. We focus on M(t)/G(t)/n(t)/n(t) + q systems that can be approximated fairly well by M(t)/E&(t)/n(t)/n(t) + q systems. The latter have a large number of system states, that increase with the system parameters k, n, q and the utilization ratio, and involve complicated state transition probabilities. We propose numerical methods to solve the corresponding Chapman-Kolmogorov equations, exactly and approximately We first describe the exact solution technique of M(t)/Ek(t)/n(t)/n(t) + q queueing systems. Then, we develop two heuristic solution techniques of M(t)/E&(t)/ndt)/n(t) + q queueing systems, and provide the corresponding complete state descriptions. We compare the exact and approximate results to validate our heuristics and to select the heuristic that best approximates the exact results in steady-state and under stationary conditions. We also propose two algorithms to vary the number of servers in the system, since many real-life problems involve such changes in response to variations in demand. Further results using our ELC heuristic show that our practical approach behaves well under nonstationary conditions, including varying capacity, and during the transient period to steady-state. We conclude that our heuristic approach is an excellent alternative for studying and analyzing M(t)/E&(t)/n(t)/n(t)+q models and, as a by-product, many M(t)/G(t)/n(t)/n(t) +q systems that arise in practice. Finally, we present an application of the M(t)/E&(t)/n(t)/n(t) + q queueing model in the context of Air Traffic Management. This model appears to be a reasonable approach to estimating delays and congestion in an en-route sector in the air traffic system and can be used as an important building block in developing an analytical model of the entire Air Traffic Management system.by Marcos Escobar Fernández de la Vega.Ph.D