Holistic assessment of call centre performance

In modern call centres 60–70% of the operational costs come in the form of the human agents who take the calls. Ensuring that the call centre operates at lowest cost and maximum efficiency involves a trade‐off of the cost of agents against lost revenue and increased customer dissatisfaction due to lost calls. Modelling the performance characteristics of a call centre in terms of the agent queue alone misses key performance influencers, specifically the interaction between channel availability at the media gateway and the time a call is queued. A blocking probability at the media gateway, as low as 0.45%, has a significant impact on the degree of queuing observed and therefore the cost and performance of the call centre. Our analysis also shows how abandonment impacts queuing delay. However, the call centre manager has less control over this than the level of contention at the media gateway. Our commercial assessment provides an evaluation of the balance between abandonment and contention, and shows that the difference in cost between the best and worst strategy is £130K per annum, however this must be balanced against a possible additional £2.98 m exposure in lost calls if abandonment alone is used

Simulation and performance of a statistical multiplexer in an ATM network

This report examines some of the issues arising m the implementation of statistical multiplexing in a broadband Integrated digital services network (B-ISDN) by analysis and simulation The BISDN concept is introduced and described. A review o f the current areas of research is given along with some of the important issues as they relate to telephone traffic. The report then focuses on the problem o f multiplexing voice traffic. A typical voice source is analysed and the traffic characteristics which result are described. The concept of statistical multiplexing is mtroduced. A review of the current literature studies relating to the problems of analysing multiplexed sources is given, with particular reference to the concept of cell level and burst level queues being separate and disparate components requiring different analytical approaches. Several models are mtroduced including the 3-state model not previously described in the literature. The queue behaviour resulting from a large number of superposed lmes is analysed as a simplified Markov process and the results are used to argue that it is not feasible to provide buffers for nodes which multiplex a large number of low intensity sources. The problem of scaling small models up to realistic situations is discussed. An approach to simulating the problem is described along with algorithms for implementing the basic elements. A senes of results derived from the described simulation are presented and analysed. The report concludes that statistical multiplexing is feasible, but with certain limits as to the type of traffic which can be supported

Discrete-time queueing model for responsive network traffic and bottleneck queues

The Internet has been more and more intensively used in recent years. Although network infrastructure has been regularly upgraded, and the ability to manage heavy traffic greatly increased, especially on the core networks, congestion never ceases to appear, as the amount of traffic that flow on the Internet seems to be increasing at an even faster rate. Thus, congestion control mechanisms play a vital role in the functioning of the Internet. Active Queue Management (AQM) is a popular type of congestion control mechanism that is implemented on gateways (most notably routers), which can predict and avoid the congestion before it happens. When properly configured, AQMs can effectively reduce the congestion, and alleviate some of the problems such as global synchronisation and unfairness to bursty traffic. However, there are still many problems regarding AQMs. Most of the AQM schemes are quite sensitive to their parameters setting, and these parameters may be heavily dependent on the network traffic profile, which the administrator may not have intensive knowledge of, and is likely to change over time. When poorly configured, many AQMs perform no better than the basic drop-tail queue. There is currently no effective method to compare the performance of these AQM algorithms, caused by the parameter configuration problem. In this research, the aim is to propose a new analytical model, which mainly uses discrete-time queueing theory. A novel transient modification to the conventional equilibrium-based method is proposed, and it is utilised to further develop a dynamic interactive model of responsive traffic and bottleneck queues. Using step-by-step analysis, it represents the bursty traffic and oscillating queue length behaviour in practical network more accurately. It also provides an effective way of predicting the behaviour of a TCP-AQM system, allowing easier parameter optimisation for AQM schemes. Numerical solution using MATLAB and software simulation using NS-2 are used to extensively validate the proposed models, theories and conclusions

Real-time Traffic Flow Detection and Prediction Algorithm: Data-Driven Analyses on Spatio-Temporal Traffic Dynamics

Traffic flows over time and space. This spatio-temporal dependency of traffic flow should be considered and used to enhance the performance of real-time traffic detection and prediction capabilities. This characteristic has been widely studied and various applications have been developed and enhanced. During the last decade, great attention has been paid to the increases in the number of traffic data sources, the amount of data, and the data-driven analysis methods. There is still room to improve the traffic detection and prediction capabilities through studies on the emerging resources. To this end, this dissertation presents a series of studies on real-time traffic operation for highway facilities focusing on detection and prediction.First, a spatio-temporal traffic data imputation approach was studied to exploit multi-source data. Different types of kriging methods were evaluated to utilize the spatio-temporal characteristic of traffic data with respect to two factors, including missing patterns and use of secondary data. Second, a short-term traffic speed prediction algorithm was proposed that provides accurate prediction results and is scalable for a large road network analysis in real time. The proposed algorithm consists of a data dimension reduction module and a nonparametric multivariate time-series analysis module. Third, a real-time traffic queue detection algorithm was developed based on traffic fundamentals combined with a statistical pattern recognition procedure. This algorithm was designed to detect dynamic queueing conditions in a spatio-temporal domain rather than detect a queue and congestion directly from traffic flow variables. The algorithm was evaluated by using various real congested traffic flow data. Lastly, gray areas in a decision-making process based on quantifiable measures were addressed to cope with uncertainties in modeling outputs. For intersection control type selection, the gray areas were identified and visualized

STOCHASTIC POINT PROCESS MODELING FOR ENGINEERING APPLICATIONS

Hawkes model or self-exciting point process model is a branching point process model. The model classifies the dataset of discrete events to background and offspring events. It has been used to study interconnected events in many fields, but relatively little work exists in applying these concepts to engineering problems. In our research, we use a self-exciting point process model for two engineering applications: (a) To identify secondary crashes from a given traffic data and (b) To quantify the agglomeration state and size of nanoparticles from computationally generated carbon nanotube microstructure using stochastic percolation model and experimentally generated titanium nanoparticle microstructures. We have developed a self-exciting temporal point process to analyze secondary crashes. The model is validated using data on secondary crashes from a data-intensive model from the literature. The model is used to analyze crash incidents on Interstate-4 (I-4) from 2017-2019.The model parameters are optimized using a maximum likelihood estimate. The model is then used to calculate the probability that a given crash from the dataset is a secondary crash. A non-stationary background rate with step and sinusoidal function is introduced to account for the periodic variation of traffic. The results from the model can potentially be utilized to improve the traffic safety especially for first responders. The same approach is used to study nanoparticle agglomeration. The spatial point process model is applied to assess the agglomeration state and size of titanium nanoparticle microstructures generated experimentally. This is accomplished by altering the duration of ultrasonic treatment on solutions with uniform concentrations to achieve varying levels of agglomeration. Similarly, the point process model is used to analyze computationally generated carbon nanotube microstructures, encompassing equiaxed and rope-like morphologies, created through a stochastic microstructure model. We extract nanoparticle locations from these micrographs and apply a point process model for a comprehensive analysis of nanoparticle agglomeration. As an extension of the agglomeration study, a stochastic percolation model was used to investigate the effects of electrical conductivity and resistance on layer-wise inkjet-printed carbon nanotube microstructures. The model was employed to generate microstructures, enabling a parametric exploration of the ink composition, alignment, and agglomeration of CNTs within printed structures affect the sheet resistance with respect to the number of printed layers. A high degree of CNT alignment hindered CNT network formation, resulting in higher resistivity, whereas the partial alignment lowered the network resistivity. In addition, we replicate the microstructure through experimental methods involving sessile drop and twin-line deposition techniques to quantify the resistivity of multilayer CNT structures

Improved performance for network simulation

Over the course of designing and implementing two discrete event simulators, the commercial simulator packages CSIM and DesmoJ were leveraged to allow for rapid development of both wired and wireless network models. However, the two resulting simulators demonstrated poor scalability due to the use of multi-threading to maintain state for simulation elements. By using a simple single-process discrete event simulation engine, the running-time showed a marked decrease when compared to multi-threaded simulators.In one case study, we simulate a simple two-link MPLS network which employs two congestion control mechanisms for inelastic traffic, namely preemption and adaptation. Performance metrics measured include: the per-class blocking probability, customer average fraction of time streams travel on the preferred path, customer average fraction of time at the maximum subscription rate, the customer average rate of adaptation, and the time average rate of preemption. We compare the performance of preemption and adaptation individually and collectively against the base case where neither congestion mechanism is used. At the cost of increased number of rate adaptations and preemption events for a range of regimes, we show that the combined use of preemption and adaptation improves the quality of service and alignment of high priority traffic while increasing the effective network capacity. As a performance enhancement to the simulator developed to conducted these experiments, we switched to a single-process discrete evnt simulation engine in place of multi-threaded simulator. We note a large improvement for the running time as the simulation time and capacity increase.A second case study was conducted on a wireless simulator. In an effort to simplify the simulator and improve performance we again moved from a commercial thread-based simulator (CSIM) to a single-process discrete event simulation engine. Results of the runningtime vs network size for the single-process simulator showed a constant-time improvement over the thread-based simulator. To further improve performance, a complementary technique known as model abstraction is also applied. Model abstraction is a technique that reduces execution time by removing unnecessary simulation detail. In this thesis we propose three abstractions of the IEEE 802.11 protocol. The Goodput Ratio vs Transmission Power and End-to-end delay vs offered load performance metrics are compared against the OPNET commercial simulator.M.S., Computer Engineering -- Drexel University, 200

Statistical Physics of Vehicular Traffic and Some Related Systems

In the so-called "microscopic" models of vehicular traffic, attention is paid explicitly to each individual vehicle each of which is represented by a "particle"; the nature of the "interactions" among these particles is determined by the way the vehicles influence each others' movement. Therefore, vehicular traffic, modeled as a system of interacting "particles" driven far from equilibrium, offers the possibility to study various fundamental aspects of truly nonequilibrium systems which are of current interest in statistical physics. Analytical as well as numerical techniques of statistical physics are being used to study these models to understand rich variety of physical phenomena exhibited by vehicular traffic. Some of these phenomena, observed in vehicular traffic under different circumstances, include transitions from one dynamical phase to another, criticality and self-organized criticality, metastability and hysteresis, phase-segregation, etc. In this critical review, written from the perspective of statistical physics, we explain the guiding principles behind all the main theoretical approaches. But we present detailed discussions on the results obtained mainly from the so-called "particle-hopping" models, particularly emphasizing those which have been formulated in recent years using the language of cellular automata.Comment: 170 pages, Latex, figures include

Experiments with a scheme of data reduction for television signals

Imperial Users onl

Quality of service modeling and analysis for carrier ethernet

Today, Ethernet is moving into the mainstream evolving into a carrier grade technology. Termed as Carrier Ethernet it is expected to overcome most of the\ud shortcomings of native Ethernet. It is envisioned to carry services end-to-end serving corporate data networking and broadband access demands as well as backhauling wireless traffic. As the penetration of Ethernet increases, the offered Quality of Service (QoS) will become increasingly important and a distinguishing factor between different service providers. The challenge is to meet the QoS requirements of end applications such as response times, throughput, delay and jitter by managing the network resources at hand. Since Ethernet was not designed to operate in large public networks it does not possess functionalities to address this issue. In this thesis we propose and analyze mechanisms which improve the QoS performance of Ethernet enabling it to meet the demands of the current and next generation services and applications.\u

ItsBlue: A Distributed Bluetooth-Based Framework for Intelligent Transportation Systems

Inefficiency in transportation networks is having an expanding impact, at a variety of levels. Transportation authorities expect increases in delay hours and in fuel consumption and, consequently, the total cost of congestion. Nowadays, Intelligent Transportation Systems (ITS) have become a necessity in order to alleviate the expensive consequences of the rapid demand on transportation networks. Since the middle of last century, ITS have played a significant role in road safety and comfort enhancements. However, the majority of state of the art ITS are suffering from several drawbacks, among them high deployment costs and complexity of maintenance. Over the last decade, wireless technologies have reached a wide range of daily users. Today\u27s Mobile devices and vehicles are now heavily equipped with wireless communication technologies. Bluetooth is one of the most widely spread wireless technologies in current use. Bluetooth technology has been well studied and is broadly employed to address a variety of challenges due to its cost-effectiveness, data richness, and privacy perverseness, yet Bluetooth utilization in ITS is limited to certain applications. However, Bluetooth technology has a potential far beyond today\u27s ITS applications. In this dissertation, we introduce itsBlue, a novel Bluetooth-based framework that can be used to provide ITS researchers and engineers with desired information. In the itsBlue framework, we utilize Bluetooth technology advantages to collect road user data from unmodified Bluetooth devices, and we extract a variety of traffic statistics and information to satisfy ITS application requirements in an efficient and cost-effective way. The itsBlue framework consists of data collection units and a central computing unit. The itsBlue data collection unit features a compact design that allows for stationary or mobile deployment in order to extend the data collection area. Central computing units aggregate obtained road user data and extract a number of Bluetooth spatial and temporal features. Road users’ Bluetooth features are utilized in a novel way to determine traffic-related information, such as road user context, appearance time, vehicle location and direction, etc. Extracted information is provided to ITS applications to generate the desired transportation services. Applying such a passive approach involves addressing several challenges, like discovering on-board devices, filtering out data received from vehicles out of the target location, or revealing vehicle status and direction. Traffic information provided by the itsBlue framework opens a wide to the development of a wide range of ITS applications. Hence, on top of the itsBlue framework, we develop a pack of intersection management applications that includes pedestrians’ volume and waiting times, as well as vehicle queue lengths and waiting times. Also, we develop a vehicle trajectory reconstruction application. The itsBlue framework and applications are thoroughly evaluated by experiments and simulations. In order to evaluate our work, we develop an enhanced version of the UCBT Network Simulator 2 (NS-2). According to evaluation outcomes, itsBlue framework and applications evaluations show promising results. For instance, the evaluation results show that the itsBlue framework has the ability to reveal road user context with accuracy exceeding 95% in 25s