Reliability Evaluation of Common-Cause Failures and Other Interdependencies in Large Reconfigurable Networks

This work covers the impact of Interdependencies and CCFs in large repairable networks with possibility of "re-configuration" after a fault and the consequent disconnection of the faulted equipment. Typical networks with these characteristics are the Utilities, e.g. Power Transmission and Distribution Systems, Telecommunication Systems, Gas and Water Utilities, Wi Fi networks. The main issues of the research are: (a) Identification of the specific interdependencies and CCFs in large repairable networks, and (b)Evaluation of their impact on the reliability parameters (load nodes availability, etc.). The research has identified (1) the system and equipment failure modes that are relevant to interdependencies and CCF, and their subsequent effects, and (2) The hidden interdependencies and CCFs relevant to control, supervision and protection systems, and to the automatic change-over systems, that have no impact in normal operation, but that can cause relevant out-of-service when the above automatic systems are called to operate under and after fault conditions. Additionally methods were introduced to include interdependencies and CCFs in the reliability and availability models. The results of the research include a new generalized approach to model the repairable networks for reliability analysis, including Interdependencies/CCFs as a main contributor. The method covers Generalized models for Nodes, Branches and Load nodes; Interdependencies and CCFs on Networks / Components; System Interdependencies/CCFs; Functional Interdependencies/CCFs; Simultaneous and non-simultaneous Interdependencies/CCFs. As an example detailed Interdependency/CCFs analysis and generalized model of an important network structure (a "RING" with load nodes) has been analyzed in detail

Sales Promotion and Consumer Loyalty: A Study of Nigerian Tecommunication Industry

In today’s competitive business world customers are considered to be kings. Customers have several choices to make among alternative products, and they exercise a high level of influence in the market with respect to product size, quality and price. Hence, it is important for producers to meet the needs of customers in order to stay competitive. One of the marketing communication tools that is used in attracting the attention of the customer and build their loyalty is sales promotion. The aim of this paper therefore is to determine the effect of sales promotion on customer loyalty in the telecommunication industry. In this study, the survey method was used in gathering information from the respondents. Simple random sampling was used to select a sample size of 310, while descriptive and inferential statistical analyses were conducted with the aid of SPSS software. Producers spend a large part of their total marketing communication expenses on sales promotion. Hence, this paper attempts to find the effect of sales promotion on customer loyalty using a sample of customers of mobile telecommunication services. The paper found that, there is positive relationship between sales promotion and customer loyalty. More importantly, it was discovered that non-loyal customers are more prone to switch to competing products as a result of sales promotion than loyal customer

Computing the probability mass function of the maximum flow through a reliable network

In this paper we propose a fast state-space enumeration based algorithm called TOP-DOWN capable of computing the probability mass function of the maximum s-t flow through reliable networks. The algorithm computes the probability mass function in the decreasing order of maximum s-t flow values in the network states. This order of enumeration makes this algorithm attractive for commonly observed reliable networks, e.g., in telecommunication networks where link reliabilities are high. We compare the performance of the TOP-DOWN algorithm with a path-based exact algorithm and show that the TOP-DOWN algorithm solves problem much faster and is able to handle much larger problems than existing algorithms.

Stochastic Geometry Modeling of Cellular Networks: Analysis, Simulation and Experimental Validation

Due to the increasing heterogeneity and deployment density of emerging cellular networks, new flexible and scalable approaches for their modeling, simulation, analysis and optimization are needed. Recently, a new approach has been proposed: it is based on the theory of point processes and it leverages tools from stochastic geometry for tractable system-level modeling, performance evaluation and optimization. In this paper, we investigate the accuracy of this emerging abstraction for modeling cellular networks, by explicitly taking realistic base station locations, building footprints, spatial blockages and antenna radiation patterns into account. More specifically, the base station locations and the building footprints are taken from two publicly available databases from the United Kingdom. Our study confirms that the abstraction model based on stochastic geometry is capable of accurately modeling the communication performance of cellular networks in dense urban environments.Comment: submitted for publicatio