A call center is a service network in which agents provide telephone-based services. Customers who seek these services are delayed in tele-queues. This article summarizes an analysis of a unique record of call center operations. The data comprise a complete operational history of a small banking call center, call by call, over a full year. Taking the perspective of queueing theory, we decompose the service process into three fundamental components: arrivals, customer patience, and service durations. Each component involves different basic mathematical structures and requires a different style of statistical analysis. Some of the key empirical results are sketched, along with descriptions of the varied techniques required. Several statistical techniques are developed for analysis of the basic components. One of these techniques is a test that a point process is a Poisson process. Another involves estimation of the mean function in a nonparametric regression with lognormal errors. A new graphical technique is introduced for nonparametric hazard rate estimation with censored data. Models are developed and implemented for forecasting of Poisson arrival rates. Finally, the article surveys how the characteristics deduced from the statistical analyses form the building blocks for theoretically interesting and practically useful mathematical models for call center operations.

We investigate the scheduling of matrix computations expressed as directed acyclic graphs for shared-memory parallelism. Because of the data granularity in this problem domain, even slight variations in load balance or data locality can greatly affect performance. Well-known scheduling algorithms such as work stealing have proven time and space bounds, but these bounds do not provide a discernable indicator of performance between different scheduling algorithms and heuristics. We provide a flexible framework for scheduling matrix computations, which we use to empirically quantify different scheduling algorithms. By building software solutions based on hardware techniques through leveraging a cache coherence protocol, we develop a scheduling algorithm that addresses both load balance and data locality simultaneously and show its performance benefits.

Abstract—Telco providers are in the phase of migrating their services from PSTN to so called Next Generation Networks (NGNs) based on standard IP connectivity. This switch is expected to produce a cost degression of 50 % for CAPEX, while OPEX remains fairly stable due to network management and energy costs. At the same time we are expecting a big increase of the load of a telco provider at the core level due to the istantiation of new telco services (VoIP, video conferencing etc) and to the support of third parties services (such as support to smart phone applications, etc.). The goal of this work is to show how management and energy costs can be effectively reduced by leveraging autonomic approaches to move some NGN services toward the telco network edge while still providing QoS levels comparable with those provided by a traditional fully-managed infrastructure. This is done taking into consideration the increase of the load of such services that is expected to raise of one order of magnitude in the close future. Specifically, we propose a hybrid architecture letting Telco administrators reduce the number of servers in the provider managed network by exploiting home devices in the computation and by organizing them in a selfconfiguring P2P system; in this way it is possible to reduce the overall system and operational costs. Our claims are supported by an experimental study based on both simulations and theoretical models that analyze the trade-off between the number of servers and home devices in order to guarantee a service within QoS constraints. Experiments are carried out on a realistic model that abstracts the lookup procedures within the NGN of a big telco provider (i.e., finding the IP address of a given unique user profile). I.

Modern networks have become increasingly complex over the past years in terms of control algorithms, applications and service expectations. Since classical theories for the analysis of telephone networks were found inadequate to cope with these complexities, new analytical tools have been conceived as of late. Among these, the stochastic network calculus has given rise to the optimism that it can emerge as an elegant mathematical tool for assessing network performance. This thesis argues that the stochastic network calculus can provide new analytical insight into the scaling properties of network performance metrics. In this sense it is shown that end-to-end delays grow as Θ(H log H) in the number of network nodes H, as opposed to the Θ(H) order of growth predicted by other theories under simplifying assumptions. It is also shown a comparison between delay bounds obtained with the stochastic network calculus and exact results available in some product-form queueing networks. The main technical contribution of this thesis is a construction of a statistical network service curve that expresses the service given to a flow by a network as if the flow traversed a single node only. This network service curve enables the proof of the O(H log H) scaling

This course is 100 % exam. 3 4 Reading List The course is based primarily on Bertsekas and Gallager [1992]. The relevant parts of the book are as follows.

Abstract: The Amoroso distribution is the natural unification of the gamma and extreme value families of distributions. Over 50 distinct, named distributions (and twice as many synonyms) occur as special cases or limiting forms. Consequently, this single simple functional form encapsulates and systematizes an extensive menagerie of interesting and common probability distributions.

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Abstract—Increasingly ubiquitous communication networks and connectivity via portable devices have engendered a host of applications in which sources, for example people and environmental sensors, send updates of their status to interested recipients. These applications desire status updates at the recipients to be as timely as possible; however, this is typically constrained by limited network resources. In this paper, we employ a timeaverage age metric for the performance evaluation of status update systems. We derive general methods for calculating the age metric that can be applied to a broad class of service systems. We apply these methods to queue-theoretic system abstractions consisting of a source, a service facility and monitors, with the model of the service facility (physical constraints) a given. The queue discipline of first-come-first-served (FCFS) is explored. We show the existence of an optimal rate at which a source must generate its information to keep its status as timely as possible at all its monitors. This rate differs from those that maximize utilization (throughput) or minimize status packet delivery delay. While our abstractions are simpler than their real-world counterparts, the insights obtained, we believe, are a useful starting point in understanding and designing systems that support real time status updates. I.

Abstract In the last few years telco providers are striving to migrate their services from the traditional Public Switch Telephone Network (PSTN) to so called Next Generation Networks (NGNs) based on standard IP connectivity. This switch is expected to produce a cost degression of 50 % for CAPital EXpenditure (CAPEX), while OPerating EXpences (OPEX) remains fairly stable due to network management and energy costs. At the same time, the instantiation of new telco services (Voice over IP (VoIP), video conferencing, etc.) and the support of third party applications (such as support to smartphone applications, etc.) are expected to produce a big increase of the load of a telco provider at the core level. The goal of this work is to show how management and energy costs can be effectively reduced by leveraging autonomic approaches to move some NGN services toward the telco network edge while still providing Quality of Service (QoS) levels comparable with those provided by a traditional fully-managed infrastructure. This is done by taking into consideration the increase of the load of such services that is expected to raise by one order of magnitude in the near future. Specifically, we propose a hybrid architecture letting telco administrators reduce the number of servers in the provider managed network by exploiting home devices in the computation and by organizing them in a self-configuring Peer to Peer (P2P) system; in this way it is possible to reduce the overall system and operational costs. Our claims are supported by an experimental study based on both simulations and theoretical models that analyze the trade-off between the number of servers and home devices in order to guarantee a service within QoS constraints. Experiments are carried out on a realistic model that abstracts the lookup procedures within