Resource allocation in multi-user telecommunication networks

This dissertation discussed resource allocation mechanisms in several network topologies including infrastructure wireless network, non-infrastructure wireless network and wire-cum-wireless network. Different networks may have different resource constrains. Based on actual technologies and implementation models, utility function, game theory and a modern control algorithm have been introduced to balance power, bandwidth and customers' satisfaction in the system. ^ In infrastructure wireless networks, utility function was used in the Third Generation (3G) cellular network and the network was trying to maximize the total utility. In this dissertation, revenue maximization was set as an objective. Compared with the previous work on utility maximization, it is more practical to implement revenue maximization by the cellular network operators. The pricing strategies were studied and the algorithms were given to find the optimal price combination of power and rate to maximize the profit without degrading the Quality of Service (QoS) performance. ^ In non-infrastructure wireless networks, power capacity is limited by the small size of the nodes. In such a network, nodes need to transmit traffic not only for themselves but also for their neighbors, so power management become the most important issue for the network overall performance. Our innovative routing algorithm based on utility function, sets up a flexible framework for different users with different concerns in the same network. This algorithm allows users to make trade offs between multiple resource parameters. Its flexibility makes it a suitable solution for the large scale non-infrastructure network. This dissertation also covers non-cooperation problems. Through combining game theory and utility function, equilibrium points could be found among rational users which can enhance the cooperation in the network. ^ Finally, a wire-cum-wireless network architecture was introduced. This network architecture can support multiple services over multiple networks with smart resource allocation methods. Although a SONET-to-WiMAX case was used for the analysis, the mathematic procedure and resource allocation scheme could be universal solutions for all infrastructure, non-infrastructure and combined networks. ^

Interactions between Paramoeba perurans, the causative agent of amoebic gill disease, and the blue mussel, Mytilus edulis

Acknowledgements The authors would like to thank staff at Marine Scotland Science Patricia White, Rebecca McIntosh, Julia Black and Mark Fordyce for their technical assistance and invaluable feedback on the project. Thanks also go to Alex Douglas at the University of Aberdeen for his advice on data analysis and statistics. For feedback on the manuscript thanks to Lesley McEvoy and Rhiannon Inkster at the NAFC Marine Centre. The study was supported by the Marine Collaborations Forum (MarCRF) which aims to develop cross-disciplinary research between the University of Aberdeen and Marine Scotland Science. Finally, thanks are also due to Scottish Fishermen's Trust for a student support bursary.

Multi-Device Selection Scheduling in Non-Identically Distributed Fading Channels

Multiuser selection scheduling concept has been recently proposed in the literature in order to increase the multiuser diversity gain and overcome the significant feedback requirements for the opportunistic scheduling schemes. The main idea is that reducing the feedback overhead saves per-user power that could potentially be added for the data transmission. In this work, the authors propose to integrate the principle of multiuser selection and the proportional fair scheduling scheme. This is aimed especially at power-limited, multi-device systems in non-identically distributed fading channels. For the performance analysis, they derive closed-form expressions for the outage probabilities and the average system rate of the delay-sensitive and the delay-tolerant systems, respectively, and compare them with the full feedback multiuser diversity schemes. The discrete rate region is analytically presented, where the maximum average system rate can be obtained by properly choosing the number of partial devices. They optimise jointly the number of partial devices and the per-device power saving in order to maximise the average system rate under the power requirement. Through the authors’ results, they finally demonstrate that the proposed scheme leveraging the saved feedback power to add for the data transmission can outperform the full feedback multiuser diversity, in non-identical Rayleigh fading of devices’ channels.

Physical Layer Security with Threshold-Based Multiuser Scheduling in Multi-antenna Wireless Networks

In this paper, we consider a multiuser downlink wiretap network consisting of one base station (BS) equipped with AA antennas, NB single-antenna legitimate users, and NE single-antenna eavesdroppers over Nakagami-m fading channels. In particular, we introduce a joint secure transmission scheme that adopts transmit antenna selection (TAS) at the BS and explores threshold-based selection diversity (tSD) scheduling over legitimate users to achieve a good secrecy performance while maintaining low implementation complexity. More specifically, in an effort to quantify the secrecy performance of the considered system, two practical scenarios are investigated, i.e., Scenario I: the eavesdropper’s channel state information (CSI) is unavailable at the BS, and Scenario II: the eavesdropper’s CSI is available at the BS. For Scenario I, novel exact closed-form expressions of the secrecy outage probability are derived, which are valid for general networks with an arbitrary number of legitimate users, antenna configurations, number of eavesdroppers, and the switched threshold. For Scenario II, we take into account the ergodic secrecy rate as the principle performance metric, and derive novel closed-form expressions of the exact ergodic secrecy rate. Additionally, we also provide simple and asymptotic expressions for secrecy outage probability and ergodic secrecy rate under two distinct cases, i.e., Case I: the legitimate user is located close to the BS, and Case II: both the legitimate user and eavesdropper are located close to the BS. Our important findings reveal that the secrecy diversity order is AAmA and the slope of secrecy rate is one under Case I, while the secrecy diversity order and the slope of secrecy rate collapse to zero under Case II, where the secrecy performance floor occurs. Finally, when the switched threshold is carefully selected, the considered scheduling scheme outperforms other well known existing schemes in terms of the secrecy performance and complexity tradeoff

Multi-objective ant colony optimization for requirements selection

The selection of a set of requirements between all the requirements previously defined by customers is an important process, repeated at the beginning of each development step when an incremental or agile software development approach is adopted. The set of selected requirements will be developed during the actual iteration. This selection problem can be reformulated as a search problem, allowing its treatment with metaheuristic optimization techniques. This paper studies how to apply Ant Colony Optimization algorithms to select requirements. First, we describe this problem formally extending an earlier version of the problem, and introduce a method based on Ant Colony System to find a variety of efficient solutions. The performance achieved by the Ant Colony System is compared with that of Greedy Randomized Adaptive Search Procedure and Non-dominated Sorting Genetic Algorithm, by means of computational experiments carried out on two instances of the problem constructed from data provided by the experts.

An identification procedure of multi-input Wiener models for the distortion analysis of nonlinear circuits

In this contribution, a system identification procedure of a two-input Wiener model suitable for the analysis of the disturbance behavior of integrated nonlinear circuits is presented. The identified block model is comprised of two linear dynamic and one static nonlinear block, which are determined using an parameterized approach. In order to characterize the linear blocks, an correlation analysis using a white noise input in combination with a model reduction scheme is adopted. After having characterized the linear blocks, from the output spectrum under single tone excitation at each input a linear set of equations will be set up, whose solution gives the coefficients of the nonlinear block. By this data based black box approach, the distortion behavior of a nonlinear circuit under the influence of an interfering signal at an arbitrary input port can be determined. Such an interfering signal can be, for example, an electromagnetic interference signal which conductively couples into the port of consideration. © 2011 Author(s).

Anticancer and antibacterial secondary metabolites from the endophytic fungus Penicillium sp. CAM64 against multi-drug resistant Gram-negative bacteria.

Background: The emergence of multiple-drug resistance bacteria has become a major threat and thus calls for an urgent need to search for new effective and safe anti-bacterial agents. Objectives: This study aims to evaluate the anticancer and antibacterial activities of secondary metabolites from Penicillium sp. , an endophytic fungus associated with leaves of Garcinia nobilis . Methods: The culture filtrate from the fermentation of Penicillium sp. was extracted and analyzed by liquid chromatography– mass spectrometry, and the major metabolites were isolated and identified by spectroscopic analyses and by comparison with published data. The antibacterial activity of the compounds was assessed by broth microdilution method while the anticancer activity was determined by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. Results: The fractionation of the crude extract afforded penialidin A-C (1-3), citromycetin (4), p-hydroxyphenylglyoxalaldoxime (5) and brefelfin A (6). All of the compounds tested here showed antibacterial activity (MIC = 0.50 – 128 μg/mL) against Gramnegative multi-drug resistance bacteria, Vibrio cholerae (causative agent of dreadful disease cholera) and Shigella flexneri (causative agent of shigellosis), as well as the significant anticancer activity (LC50 = 0.88 – 9.21 μg/mL) against HeLa cells. Conclusion: The results obtained indicate that compounds 1-6 showed good antibacterial and anticancer activities with no toxicity to human red blood cells and normal Vero cells.

Agent based simulation as a novel decision support tool for retail managers

Intelligent agents offer a new and exciting way of understanding the world of work. We apply agent-based simulation to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Our multi-disciplinary research team draws upon expertise from work psychologists and computer scientists. Our research so far has led us to conduct case study work with a top ten UK retailer. Based on our case study experience and data we are developing a simulator that can be used to investigate the impact of management practices (e.g. training, empowerment, teamwork) on customer satisfaction and retail productivity.

Comparing simulation output accuracy of discrete event and agent based models: a quantitative approach

In our research we investigate the output accuracy of discrete event simulation models and agent based simulation models when studying human centric complex systems. In this paper we focus on human reactive behaviour as it is possible in both modelling approaches to implement human reactive behaviour in the model by using standard methods. As a case study we have chosen the retail sector, and here in particular the operations of the fitting room in the women wear department of a large UK department store. In our case study we looked at ways of determining the efficiency of implementing new management policies for the fitting room operation through modelling the reactive behaviour of staff and customers of the department. First, we have carried out a validation experiment in which we compared the results from our models to the performance of the real system. This experiment also allowed us to establish differences in output accuracy between the two modelling methods. In a second step a multi-scenario experiment was carried out to study the behaviour of the models when they are used for the purpose of operational improvement. Overall we have found that for our case study example both, discrete event simulation and agent based simulation have the same potential to support the investigation into the efficiency of implementing new management policies.

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.

Multi-Principal Agency and the Compliance with Professional Guidelines in Health Systems: Economic and Regulatory Perspectives

Amid the trend of rising health expenditure in developed economies, changing the healthcare delivery models is an important point of action for service regulators to contain this trend. Such a change is mostly induced by either financial incentives or regulatory tools issued by the regulators and targeting service providers and patients. This creates a tripartite interaction between service regulators, professionals, and patients that manifests a multi-principal agent relationship, in which professionals are agents to two principals: regulators and patients. This thesis is concerned with such a multi-principal agent relationship in healthcare and attempts to investigate the determinants of the (non-)compliance to regulatory tools in light of this tripartite relationship. In addition, the thesis provides insights into the different institutional, economic, and regulatory settings, which govern the multi-principal agent relationship in healthcare in different countries. Furthermore, the thesis provides and empirically tests a conceptual framework of the possible determinants of (non-)compliance by physicians to regulatory tools issued by the regulator. The main findings of the thesis are first, in a multi-principal agent setting, the utilization of financial incentives to align the objectives of professionals and the regulator is important but not the only solution. This finding is based on the heterogeneity in the financial incentives provided to professionals in different health markets, which does not provide a one-size-fits-all model of financial incentives to influence clinical decisions. Second, soft law tools as clinical practice guidelines (CPGs) are important tools to mitigate the problems of the multi-principal agent setting in health markets as they reduce information asymmetries while preserving the autonomy of professionals. Third, CPGs are complex and heterogeneous and so are the determinants of (non-)compliance to them. Fourth, CPGs work but under conditions. Factors such as intra-professional competition between service providers or practitioners might lead to non-compliance to CPGs – if CPGs are likely to reduce the professional’s utility. Finally, different degrees of soft law mandate have different effects on providers’ compliance. Generally, the stronger the mandate, the stronger the compliance, however, even with a strong mandate, drivers such as intra-professional competition and co-management of patients by different professionals affected the (non-)compliance.

Distributed collision-free traffic management via vertex cover for multi-vehicle systems

In this thesis, we state the collision avoidance problem as a vertex covering problem, then we consider a distributed framework in which a team of cooperating Unmanned Vehicles (UVs) aim to solve this optimization problem cooperatively to guarantee collision avoidance between group members. For this purpose, we implement a distributed control scheme based on a robust Set-Theoretic Model Predictive Control ( ST-MPC) strategy, where the problem involves vehicles with independent dynamics but with coupled constraints, to capture required cooperative behavior.

Graphene And Carbon Nanotube Nanocomposite For Gene Transfection.

Graphene and carbon nanotube nanocomposite (GCN) was synthesised and applied in gene transfection of pIRES plasmid conjugated with green fluorescent protein (GFP) in NIH-3T3 and NG97 cell lines. The tips of the multi-walled carbon nanotubes (MWCNTs) were exfoliated by oxygen plasma etching, which is also known to attach oxygen content groups on the MWCNT surfaces, changing their hydrophobicity. The nanocomposite was characterised by high resolution scanning electron microscopy; energy-dispersive X-ray, Fourier transform infrared and Raman spectroscopies, as well as zeta potential and particle size analyses using dynamic light scattering. BET adsorption isotherms showed the GCN to have an effective surface area of 38.5m(2)/g. The GCN and pIRES plasmid conjugated with the GFP gene, forming π-stacking when dispersed in water by magnetic stirring, resulting in a helical wrap. The measured zeta potential confirmed that the plasmid was connected to the nanocomposite. The NIH-3T3 and NG97 cell lines could phagocytize this wrap. The gene transfection was characterised by fluorescent protein produced in the cells and pictured by fluorescent microscopy. Before application, we studied GCN cell viability in NIH-3T3 and NG97 line cells using both MTT and Neutral Red uptake assays. Our results suggest that GCN has moderate stability behaviour as colloid solution and has great potential as a gene carrier agent in non-viral based therapy, with low cytotoxicity and good transfection efficiency.

Doehlert Design-desirability Function Multi-criteria Optimal Separation Of 17 Phenolic Compounds From Extra-virgin Olive Oil By Capillary Zone Electrophoresis.

In Brazil, the consumption of extra-virgin olive oil (EVOO) is increasing annually, but there are no experimental studies concerning the phenolic compound contents of commercial EVOO. The aim of this work was to optimise the separation of 17 phenolic compounds already detected in EVOO. A Doehlert matrix experimental design was used, evaluating the effects of pH and electrolyte concentration. Resolution, runtime and migration time relative standard deviation values were evaluated. Derringer's desirability function was used to simultaneously optimise all 37 responses. The 17 peaks were separated in 19min using a fused-silica capillary (50μm internal diameter, 72cm of effective length) with an extended light path and 101.3mmolL(-1) of boric acid electrolyte (pH 9.15, 30kV). The method was validated and applied to 15 EVOO samples found in Brazilian supermarkets.

Behavior Of Listeria Monocytogenes In A Multi-species Biofilm With Enterococcus Faecalis And Enterococcus Faecium And Control Through Sanitation Procedures.

The formation of mono-species biofilm (Listeria monocytogenes) and multi-species biofilms (Enterococcus faecium, Enterococcus faecalis, and L. monocytogenes) was evaluated. In addition, the effectiveness of sanitation procedures for the control of the multi-species biofilm also was evaluated. The biofilms were grown on stainless steel coupons at various incubation temperatures (7, 25 and 39°C) and contact times (0, 1, 2, 4, 6 and 8days). In all tests, at 7°C, the microbial counts were below 0.4 log CFU/cm(2) and not characteristic of biofilms. In mono-species biofilm, the counts of L. monocytogenes after 8days of contact were 4.1 and 2.8 log CFU/cm(2) at 25 and 39°C, respectively. In the multi-species biofilms, Enterococcus spp. were present at counts of 8 log CFU/cm(2) at 25 and 39°C after 8days of contact. However, the L. monocytogenes in multi-species biofilms was significantly affected by the presence of Enterococcus spp. and by temperature. At 25°C, the growth of L. monocytogenes biofilms was favored in multi-species cultures, with counts above 6 log CFU/cm(2) after 8days of contact. In contrast, at 39°C, a negative effect was observed for L. monocytogenes biofilm growth in mixed cultures, with a significant reduction in counts over time and values below 0.4 log CFU/cm(2) starting at day 4. Anionic tensioactive cleaning complemented with another procedure (acid cleaning, disinfection or acid cleaning+disinfection) eliminated the multi-species biofilms under all conditions tested (counts of all micro-organisms<0.4 log CFU/cm(2)). Peracetic acid was the most effective disinfectant, eliminating the multi-species biofilms under all tested conditions (counts of the all microorganisms <0.4 log CFU/cm(2)). In contrast, biguanide was the least effective disinfectant, failing to eliminate biofilms under all the test conditions.