Design and implementation of a Marking Strategy to Increase the Contactability in the Call Centers, Based on Machine Learning

Jamar is a company that belongs to the furniture sector, which manufactures and sells furniture and accessories for the home. Customer calls are one of the most trusted channels used in contact centers. Currently, the contactability indicator has a goal of 40% and is at 31%. The enemies of the efficiency of this channel are the terrible dimensioning, customers who evade answering these calls by identifying the numbers, non-market numbers in the databases, failures in the technological resources. Therefore, a proposal was made to design and implement a marking strategy in the call center, supported by a statistical model for dimensioning. Likewise, emerging technology such as Machine Learning is performed to help the marking strategy in outbound campaigns, reconfiguration of the dialplan to make it more efficient, and a redundant architecture design in the operators. Basic concepts of Teletraffic are explained, showing its primary functions, relevant for the management of the company's telephone system. In the same way, fundamentals of the Asterisk IP PBX are exposed, one of the most used in our environment due to its versatility and low implementation cost. The methodology of descriptive and applied research is used for the development of the project. The results and discussion show the dialing strategy and some call statistics from previous years, necessary to establish a correct dimensioning of the solution. The proposed solution allows having redundancy management for SIP and trunk operators, to have backup and reliability in case of failure

Using mobile network big data for land use classification CPRsouth 2015

The traditional way of generating insights on land use involve surveys and censuses, which are both infrequent as well as costly. This paper explores the potential of leveraging massive amounts of human mobile phone data to understand the spatiotemporal activity of mass populations, and by extension, provide a useful proxy for activity-based classification of land use. Understanding and monitoring land use characteristics is critical for urban planning. The study demonstrates possibilities for use of mobile network big data, and how it can be leveraged to infer three distinct land use characteristics: commercial/ economic, residential, and mixed-use

Location Management Techniques in Cellular Network: a Novel Approach

Communication had become the necessity of our lives. It is no longer just a way to communicate with each other. It is now a part of our life. Most of this changes are the result of the rapid growth in mobile industry. The number of subscribers are increasing in an exponential manner. At current stage the number of mobile devices had already crossed the total human population of our planet. But this high paced increase in number of subscribers had brought in some new and challenging problems into the eld also. Particularly the problem of ccommodating this huge number of subscribers into the limited amount of spectrum, withoutcompromising the Grade of Service. In this thesis we had tried to address this issue by reducing the spectrum utilization in the location management. Location management are the set of techniques that are used by the telecom provider to determine the current location of the user (location update) and to inform the user regarding an incoming call (paging). Both of this process consumes a huge portion of the available spectrum. This thesis presents a dynamic pro le based location management technique that optimizes both these technology. When simulated using actual user data, the algorithm shows it is 3 times more ecient than the conventional paging and 2 times more ecient compared to other intelligent paging algorithms. Similarly in case of location update, the algorithm shows an improvement of 17% compared to the conventional technique. The thesis also includes a comparison between sequential paging and concurrent paging based on parameters like probability of channel being busy,average waiting time per user etc.The novelty of this work is that it uses CDR (Call Data Record) to pro le the users. And the algorithm is implemented on actual user data rather than any theoretically predicted data. The optimization is done at individual user level. So the optimization achieved through the proposed algorithm is greater compared to other algorithms. The final output shows promising result specically in terms of bandwidth conservatio

A PC-based data acquisition system for sub-atomic physics measurements

Modern particle physics measurements are heavily dependent upon automated data acquisition systems (DAQ) to collect and process experiment-generated information. One research group from the University of Saskatchewan utilizes a DAQ known as the Lucid data acquisition and analysis system. This thesis examines the project undertaken to upgrade the hardware and software components of Lucid. To establish the effectiveness of the system upgrades, several performance metrics were obtained including the system's dead time and input/output bandwidth.Hardware upgrades to Lucid consisted of replacing its aging digitization equipment with modern, faster-converting Versa-Module Eurobus (VME) technology and replacing the instrumentation processing platform with common, PC hardware. The new processor platform is coupled to the instrumentation modules via a fiber-optic bridging-device, the sis1100/3100 from Struck Innovative Systems.The software systems of Lucid were also modified to follow suit with the new hardware. Originally constructed to utilize a proprietary real-time operating system, the data acquisition application was ported to run under the freely available Real-Time Executive for Multiprocessor Systems (RTEMS). The device driver software provided with sis1100/3100 interface also had to be ported for use under the RTEMS-based system. Performance measurements of the upgraded DAQ indicate that the dead time has been reduced from being on the order of milliseconds to being on the order of several tens of microseconds. This increased capability means that Lucid's users may acquire significantly more data in a shorter period of time, thereby decreasing both the statistical uncertainties and data collection duration associated with a given experiment

Location Management Techniques in Cellular Network: a Novel Approach

Communication had become the necessity of our lives. It is no longer just a way to communicate with each other. It is now a part of our life. Most of this changes are the result of the rapid growth in mobile industry. The number of subscribers are increasing in an exponential manner. At current stage the number of mobile devices had already crossed the total human population of our planet. But this high paced increase in number of subscribers had brought in some new and challenging problems into the eld also. Particularly the problem of ccommodating this huge number of subscribers into the limited amount of spectrum, withoutcompromising the Grade of Service. In this thesis we had tried to address this issue by reducing the spectrum utilization in the location management. Location management are the set of techniques that are used by the telecom provider to determine the current location of the user (location update) and to inform the user regarding an incoming call (paging). Both of this process consumes a huge portion of the available spectrum. This thesis presents a dynamic pro le based location management technique that optimizes both these technology. When simulated using actual user data, the algorithm shows it is 3 times more ecient than the conventional paging and 2 times more ecient compared to other intelligent paging algorithms. Similarly in case of location update, the algorithm shows an improvement of 17% compared to the conventional technique. The thesis also includes a comparison between sequential paging and concurrent paging based on parameters like probability of channel being busy,average waiting time per user etc.The novelty of this work is that it uses CDR (Call Data Record) to pro le the users. And the algorithm is implemented on actual user data rather than any theoretically predicted data. The optimization is done at individual user level. So the optimization achieved through the proposed algorithm is greater compared to other algorithms. The final output shows promising result specically in terms of bandwidth conservatio

Edge Computing for Internet of Things

The Internet-of-Things is becoming an established technology, with devices being deployed in homes, workplaces, and public areas at an increasingly rapid rate. IoT devices are the core technology of smart-homes, smart-cities, intelligent transport systems, and promise to optimise travel, reduce energy usage and improve quality of life. With the IoT prevalence, the problem of how to manage the vast volumes of data, wide variety and type of data generated, and erratic generation patterns is becoming increasingly clear and challenging. This Special Issue focuses on solving this problem through the use of edge computing. Edge computing offers a solution to managing IoT data through the processing of IoT data close to the location where the data is being generated. Edge computing allows computation to be performed locally, thus reducing the volume of data that needs to be transmitted to remote data centres and Cloud storage. It also allows decisions to be made locally without having to wait for Cloud servers to respond

Mobile Networks

The growth in the use of mobile networks has come mainly with the third generation systems and voice traffic. With the current third generation and the arrival of the 4G, the number of mobile users in the world will exceed the number of landlines users. Audio and video streaming have had a significant increase, parallel to the requirements of bandwidth and quality of service demanded by those applications. Mobile networks require that the applications and protocols that have worked successfully in fixed networks can be used with the same level of quality in mobile scenarios. Until the third generation of mobile networks, the need to ensure reliable handovers was still an important issue. On the eve of a new generation of access networks (4G) and increased connectivity between networks of different characteristics commonly called hybrid (satellite, ad-hoc, sensors, wired, WIMAX, LAN, etc.), it is necessary to transfer mechanisms of mobility to future generations of networks. In order to achieve this, it is essential to carry out a comprehensive evaluation of the performance of current protocols and the diverse topologies to suit the new mobility conditions

Performance analysis of the interference adaptation dynamic channel allocation technique in wireless communication networks

Dynamic channel allocation (DCA) problem is one of the major research topics in the wireless networking area. The purpose of this technique is to relieve the contradiction between the increasing traffic load in wireless networks and the limited bandwidth resource across the air interface. The challenge of this problem comes from the following facts: a) even the basic DCA problem is shown to be NP-complete (none polynomial complete); b) the size of the state space of the problem is very large; and c) any practical DCA algorithm should run in real-time. Many heuristic DCA schemes have been proposed in the literature. It has been shown through simulation results that the interference adaptive dynamic channel allocation (IA-DCA) scheme is a promising strategy in Time Devision [sic] Multiple Accesss/Frequency Devision [sic] Multiple Accesss [sic] (TDMA/FDMA) based wireless communication systems. However, the analytical work on the IA-DCA strategy in the literature is nearly blank. The performance of a, DCA algorithm in TDMA/FDMA wireless systems is influenced by three factors: representation of the interference, traffic fluctuation, and the processing power of the algorithm. The major obstacle in analyzing IA-DCA is the computation of co-channel interference without the constraint of conventional channel reuse factors. To overcome this difficulty, one needs a representation pattern which can approximate the real interference distribution as accurately as desired, and is also computationally viable. For this purpose, a concept called channel reuse zone (CRZ) is introduced and the methodology of computing the area of a CRZ with an arbitrary, non-trivial channel reuse factor is defined. Based on this new concept, the computation of both downlink and uplink CO-channel interference is investigated with two different propagation models, namely a simplified deterministic model and a shadowing model. For the factor of the processing power, we proposed an idealized Interference Adaptation Maximum Packing (IAMP) scheme, which gives the upper bound of all IA-DCA schemes in terms of the system capacity. The effect of traffic dynamics is delt [sic] with in two steps. First, an asymptotic performance bound for the IA-DCA strategy is derived with the assumption of an arbitrarily large number of channels in the system. Then the performance bound for real wireless systems with the IA-DCA strategy is derived by alleviating this assumption. Our analytical result is compared with the performance bound drawn by Zander and Eriksson for reuse-partitioning DCA1 and some simulation results for IA-DCA in the literature. It turns out that the performance bound obtained in this work is much tighter than Zander and Eriksson\u27s bound and is in agreement with simulation results. 1only available for deterministic propagation model and downlink connection

Modelling and Optimisation of GSM and UMTS Radio Access Networks

The size and complexity of mobile communication networks have increased in the last years making network management a very complicated task. GSM/EDGE Radio Access Network (GERAN) systems are in a mature state now. Thus, non-optimal performance does not come from typical network start-up problems, but, more likely, from the mismatching between traffic, network or propagation models used for network planning, and their real counterparts. Such differences cause network congestion problems both in signalling and data channels. With the aim of maximising the financial benefits on their mature networks, operators do not solve anymore congestion problems by adding new radio resources, as they usually did. Alternatively, two main strategies can be adopted, a) a better assignment of radio resources through a re-planning approach, and/or b) the automatic configuration (optimisation, in a wide sense) of network parameters. Both techniques aim to adapt the network to the actual traffic and propagation conditions. Moreover, a new heterogenous scenario, where several services and Radio Access Technologies (RATs) coexist in the same area, is now common, causing new unbalanced traffic scenarios and congestion problems. In this thesis, several optimisation and modelling methods are proposed to solve congestion problems in data and signalling channels for single- and multi-RAT scenarios