An intelligent vertical handoff decision algorithm in next generation wireless networks

Philosophiae Doctor - PhDSeamless mobility is the missing ingredient needed to address the inefficient communication problems faced by the field workforces of service companies that are using field workforce automation solutions to streamline and optimise the operations of their field workforces in an increasingly competitive market place. The key enabling function for achieving seamless mobility and seamless service continuity is seamless handoffs across heterogeneous wireless access networks. A challenging issue in the multi-service next generation wireless network (NGWN) is to design intelligent and optimal vertical handoff decision algorithms, beyond traditional ones that are based on only signal strength, to determine when to perform a handoff and to provide optimal choice of access network technology among all available access networks for users equipped with multimode mobile terminals. The objective of the thesis research is to design such vertical handoff decision algorithms in order for mobile field workers and other mobile users equipped with contemporary multimode mobile devices to communicate seamlessly in the NGWN. In order to tackle this research objective, we used fuzzy logic and fuzzy inference systems to design a suitable handoff initiation algorithm that can handle imprecision and uncertainties in data and process multiple vertical handoff initiation parameters (criteria); used the fuzzy multiple attributes decision making method and context awareness to design a suitable access network selection function that can handle a tradeoff among many handoff metrics including quality of service requirements (such as network conditions and system performance), mobile terminal conditions, power requirements, application types, user preferences, and a price model; used genetic algorithms and simulated annealing to optimise the access network selection function in order to dynamically select the optimal available access network for handoff; and we focused in particular on an interesting use case: vertical handoff decision between mobile WiMAX and UMTS access networks. The implementation of our handoff decision algorithm will provide a network selection mechanism to help mobile users select the best wireless access network among all available wireless access networks, that is, one that provides always best connected services to user

A Multi-Stage Supply Chain Network Optimization Using Genetic Algorithms

In today's global business market place, individual firms no longer compete as independent entities with unique brand names but as integral part of supply chain links. Key to success of any business is satisfying customer's demands on time which may result in cost reductions and increase in service level. In supply chain networks decisions are made with uncertainty about product's demands, costs, prices, lead times, quality in a competitive and collaborative environment. If poor decisions are made, they may lead to excess inventories that are costly or to insufficient inventory that cannot meet customer's demands. In this work we developed a bi-objective model that minimizes system wide costs of the supply chain and delays on delivery of products to distribution centers for a three echelon supply chain. Picking a set of Pareto front for multi-objective optimization problems require robust and efficient methods that can search an entire space. We used evolutionary algorithms to find the set of Pareto fronts which have proved to be effective in finding the entire set of Pareto fronts.Comment: 12 pages, 4 figure

Modeling the Dynamics of Hepatitis C Virus and Immune System during Acute Infection

In this paper, a mathematical model on the interaction between hepatitis c virus (HCV) and immune system has been studied. The paper intends to upgrade the model developed by Avendano et al.(2002) by including death of hepatocytes due to infection and spontaneous clearance of viruses by a noncytolytic process during acute stage of the HCV infection. The next generation matrix method has been applied to compute the basic reproductive number. Also, the stability analysis of the system has been performed for the existence of the disease free and endemic equilibrium states using Meltzer matrix, Routh-Hurwitz and Lyapunov methods. The results indicate that the disease free equilibrium state is locally asymptotically stable if, and unstable if.The endemic equilibrium state is both locally and globally asymptotically stable. We calculated the sensitivity indices of the dynamic threshold relating to each parameter in the model, where we found that the decrease of the rate of infection and the rate of generation of virions have the effect of lessening the infection, which suggests that the disease can be controlled when therapeutic intervention is done on these parameters.Keywords: Hepatitis C virus, Immune system, Basic reproductive number, Disease-free equilibrium state, Endemic equilibrium state

Mathematical Model to Assess Motorcycle Accidents in Tanzania

Motorcycle accident has been one of the paramount road cases in Tanzania. However, when ensuring road safety rules in Tanzania it is important to assess the nature and causes of road accidents in the country. It is also necessary to find out the factors which lead to an obstacle of achieving road safety and regulations. This paper focuses on the assessment of motorcycle accidents in Tanzania and the associated factors such as driving experience, personal status like alcoholic, carelessness, wrong overtaking, speed, mechanical defect and road conditions. The models were formulated by using SPSS software program from the data collected from Kilimanjaro and Arusha regions. By applying multi-linear regression methods, the formulated model solutions were used to analyze the relationship between motorcycle accidents as the dependent variable and other factors such as driving experiences, speed, legal status, personal status, mechanical defects, wrong overtake and rough road, tarmac road as independent variables. Keywords: Multi Linear regression method, Motorcycle accidents, Personal status and   Road condition

Modeling the SBC Tanzania Production-Distribution Logistics Network

The increase in customer expectation in terms of cost and services rendered, coupled with competitive business environment and uncertainty in cost of raw materials have posed challenges on effective supply chain engineering making it essential to do cost-benefit analysis before making final decisions on production distribution logistics. This paper provides a conceptual model that provide guidance in supply chain decision making for business expansion. It presents a mathematical model for production-distribution of an integrated supply chain derived from current operations of SBC Tanzania Ltd which is a major supply chain that manages products' distribution in whole of Tanzania. In addition to finding the optimal cost, we also carried out a sensitivity analysis on the model so as to find ways in which the company can expand at optimal cost, while meeting customers' demands. Genetic algorithms is used to run the simulation for their efficient in solving combinatorial problems

Modeling the SBC Tanzania Production-Distribution Logistics Network

The increase in customer expectation in terms of cost and services rendered, coupled with competitive business environment and uncertainty in cost of raw materials have posed challenges on effective supply chain engineering  making it essential to do cost-benefit analysis before making final decisions on production-distribution logistics. This paper provides a conceptual model that provide guidance in supply chain decision making for business expansion. It presents a mathematical model for production-distribution of an integrated supply chain derived from current operations of SBC Tanzania Ltd which is a major supply chain that manages products' distribution in whole of Tanzania. In addition to finding the optimal cost, we also carried out a sensitivity analysis on the model so as to find ways in which the company can expand at optimal cost, while meeting customers' demands. Genetic algorithms is used to run the simulation for their efficient in solving combinatorial problems. Key words: Business environment, supply chain engineering, production-distribution, genetic algorithms, optimal cost

A Mathematical Model that Estimates Input Demand in Respect to the Costs for Cotton Production

The agricultural sector is the backbone of economic activities to the farmers in Tanzania. Tanzania produces cotton as a commercial crop that is also produced by more than 80 countries in the world particularly those located in the tropics and temperate climate regions. In Tanzania, cotton is mostly grown in the western cotton growing area (WCGA) and eastern cotton growing area (ECGA). The serious problem facing farmers for cotton production is the continuous increasing costs of inputs in Tanzania. The aim of this paper was to build a mathematical model that estimates input demand in respect to the costs for cotton production. The primary data from 2003 to 2014 were collected from cotton farmers at Bariadi in Shinyanga. Moreover, secondary data were collected from the Tanzania Cotton Board, Ukiliguru Agriculture Training Institute, and Shinyanga Regional Commissioners. A mathematical model was estimated after taking out the reasonable statistical tests. The fixed effect and random effect were compared in the Hausman’s specification test. The coefficients (elasticities) in respect to the inputs and other elasticities were estimated by applying Ordinary Least Squares techniques facilitated by STATA 11 and EXCEL

Optimal Control Techniques on a Mathematical Model for the Dynamics of Tungiasis in a Community

Tungiasis is a permanent penetration of female sand flea “Tunga penetrans” into the epidermis of its host. It affects human beings and domestic and sylvatic animals. In this paper, we apply optimal control techniques to a Tungiasis controlled mathematical model to determine the optimal control strategy in order to minimize the number of infested humans, infested animals, and sand flea populations. In an attempt to reduce Tungiasis infestation in human population, the control strategies based on personal protection, personal treatment, educational campaign, environmental sanitation, and insecticidal treatments on the affected parts as well as on animal fur are considered. We prove the existence of optimal control problem, determine the necessary conditions for optimality, and then perform numerical simulations. The numerical results showed that the control strategy comprises all five control measures and that which involves the three control measures of insecticide control, insecticidal dusting on animal furs, and environmental hygiene has the significant impact on Tungiasis transmission. Therefore, fighting against Tungiasis infestation in endemic settings, multidimensional control process should be employed in order to achieve the maximum benefits

Modeling the Effect of Stress and Stigma on the Transmission and Control of Tuberculosis Infection

In this paper a continuous time deterministic model with health education campaign and treatment strategy is formulated to assess the effect of stress and stigma on the transmission and control of Tuberculosis (TB). The effective reproduction number is obtained and used to investigate the impact of health education campaign and treatment strategies. The effective reproduction numbers for health education campaign and treatment considered separately were found not to be effective as compared to a combination of both strategies. Numerical simulation results show that TB can be reduced or eliminated from the community when as treatment is applied. The disease prevalence and incidence are high when stigma is high and decline gradually when the combination of both treatment and health campaign are administered. We recommend that health education campaign to reduce stress among individuals and stigma for infectious individuals should be accompanied by treatment of active TB individuals for improved reduction of TB disease