Analysis and Evaluation of EndpointSecurity Solutions

The main objective for this degree project was to analyze the Endpoint Security Solutions developed by Cisco, Microsoft and a third minor company solution represented by InfoExpress. The different solutions proposed are Cisco Network Admission Control, Microsoft Network Access Protection and InfoExpress CyberGatekeeper. An explanation of each solution functioning is proposed as well as an analysis of the differences between those solutions. This thesis work also proposes a tutorial for the installation of Cisco Network Admission Control for an easier implementation. The research was done by reading articles on the internet and by experimenting the Cisco Network Admission Control solution. My background knowledge about Cisco routing and ACL was also used. Based on the actual analysis done in this thesis, a conclusion was drawn that all existing solutions are not yet ready for large-scale use in corporate networks. Moreover all solutions are proprietary and incompatible. The future possible standard for Endpoint solution might be driven by Cisco and Microsoft and a rude competition begins between those two giants.

Print quality study of a laboratory offset press

PAPRO operates within the Forest Research company and their mission is to develop value-addingindustry solutions. At present there are no good ways for mills to easily test the printing quality on newsprintpaper. There is a great need for a fast way to do this on different paper qualities; with a laboratory-offset press this can be both a time and money saving method. At PAPRO Forest Research, NewZealand, a laboratory offset press has been developed and designed, during the past seven years, concerningthis issue. Earlier projects were made concerning the press, e.g. to establish the optimal settings.The mission with this project was to partly determine the present variability of the print quality andto evaluate if the fountain solution, distilled water and 2% Diol green concentrate, used at the momentmixed with different percentages of Isopropanol could decrease the variability and contribute to morestabile results. Throughout the whole project the print quality showed a high variation and was evenmore variable when the Isopropanol was added. All in all 50 print rounds times twelve printed paperstrips was carried out through the project divided into three parts. To analyse the print quality, amicroscope with an image capture camera has been used. Data from the taken images was analysedand inserted into charts to see the variations.The conclusions of the whole project are not satisfying because no final evaluations were possible tomake. Main conclusions are that the additive of Isopropanol to the ordinary fountain solution, used atpresent, only contributed to more unstable results of the print quality. And it seems to be difficult toget some stable results from the lab press as long as the room where it is placed is not fully conditionedas required for the process of offset printing. And the fact that the airbrush which applies theamount of fountain solution is also variable, as shown in earlier projects, which contributes to unstableresults as well. For further work more exact parameters as a conditioned room are required and thepossibility to further design the laboratory press to use waterless offset printing instead.

Implementation and role of device management Solutions to the end users

This research is based on consumer complaints with respect to recently purchased consumer electronics. This research document will investigate the instances of development and device management as a tool used to aid consumer and manage consumer’s mobile products in order to resolve issues in or before the consumers is aware one exists. The problem at the present time is that mobile devices are becoming very advanced pieces of technology, and not all manufacturers and network providers have kept up the support element of End users. As such, the subject of the research is to investigate how device management could possibly be used as a method to promote research and development of mobile devices, and provide a better experience for the consumer. The wireless world is becoming increasingly complex as revenue opportunities are driven by new and innovative data services. We can no longer expect the customer to have the knowledge or ability to configure their own device. Device Management platforms can address the challenges of device configuration and support through new enabling technologies. Leveraging these technologies will allow a network operator to reduce the cost of subscriber ownership, drive increased ARPU (Average Revenue per User) by removing barriers to adoption, reduce churn by improving the customer experience and increase customer loyalty. DM technologies provide a flexible and powerful management method but are managing the same device features that have historically been configured manually through call centers or by the end user making changes directly on the device. For this reason DM technologies must be treated as part of a wider support solution. The traditional requirement for discovery, fault finding, troubleshooting and diagnosis are still as relevant with DM as they are in the current human support environment yet the current generation of solutions do little to address this problem. In the deployment of an effective Device Management solution the network operator must consider the integration of the DM platform, interfacing with many areas of the business, supported by knowledge of the relationship between devices, applications, solutions and services maintained on an ongoing basis. Complementing the DM solution with published device information, setup guides, training material and web based tools will ensure the quality of the customer experience, ensuring that problems are completely resolved, driving data usage by focusing customer education on the use of the wireless service In this way device management becomes a tool used both internally within the network or device vendor and by the customer themselves, with each user empowered to effectively manage the device without any prior knowledge or experience, confident that changes they apply will be relevant, accurate, stable and compatible. The value offered by an effective DM solution with an expert knowledge service will become a significant differentiator for the network operator in an ever competitive wireless market. This research document is intended to highlight some of the issues the industry faces as device management technologies become more prevalent, and offers some potential solutions to simplify the increasingly complex task of managing devices on the network, where device management can be used as a tool to aid customer relations and manage customer’s mobile products in order to resolve issues before the user is aware one exists. The research is broken down into the following, Customer Relationship Management, Device management, the role of knowledge with the DM, Companies that have successfully implemented device management, and the future of device management and CRM. And it also consists of questionnaires aimed at technical support agents and mobile device users. Interview was carried out with CRM managers within support centre to further the evidence gathered. To conclude, the document is to consider the advantages and disadvantages of device management and attempt to determine the influence it will have over customer support centre, and what methods could be used to implement it.

Electricity Supply Solutions for an Educational Center in Tanzania

The aim of this study was to investigate electricity supply solutions for an educationalcenter that is being built in Chonyonyo Tanzania. Off-grid power generation solutions andfurther optimization possibilities were studied for the case.The study was done for Engineers Without Borders in Sweden. Who are working withMavuno Project on the educational center. The school is set to start operating in year 2015with 40 girl students in the beginning. The educational center will help to improve genderequality by offering high quality education in a safe environment for girls in rural area.It is important for the system to be economically and environmentally sustainable. Thearea has great potential for photovoltaic power generation. Thus PV was considered as theprimary power generation and a diesel generator as a reliable backup. The system sizeoptimization was done with HOMER. For the simulations HOMER required componentdata, weather data and load data. Common components were chose with standardproperties, the loads were based on load estimations from year 2011 and the weather datawas acquired from NASA database. The system size optimization result for this base casewas a system with 26 kW PW; 5.5 kW diesel generator, 15 kW converter and 112 T-105batteries. The initial cost of the system was 55 875 €, the total net present cost 92 121 €and the levelized cost of electricity 0.264 €/kWh.In addition three optimization possibilities were studied. First it was studied how thesystem should be designed and how it would affect the system size to have night loads(security lights) use DC and could the system then be extended in blocks. As a result it wasfound out that the system size could be decreased as the inverter losses would be avoided.Also the system extension in blocks was found to be possible. The second study was aboutinverter stacking where multiple inverters can work as one unit. This type of connectionallows only the required number of inverters to run while shutting down the excess ones.This would allow the converter-unit to run with higher efficiency and lower powerconsumption could be achieved. In future with higher loads the system could be easilyextendable by connecting more inverters either in parallel or series depending on what isneeded. Multiple inverters would also offer higher reliability than using one centralizedinverter. The third study examined how the choice of location for a centralized powergeneration affects the cable sizing for the system. As a result it was found that centralizedpower generation should be located close to high loads in order to avoid long runs of thickcables. Future loads should also be considered when choosing the location. For theeducational center the potential locations for centralized power generation were found outto be close to the school buildings and close to the dormitories.

Statistical bound of genetic solutions to quadratic assignment problems

Quadratic assignment problems (QAPs) are commonly solved by heuristic methods, where the optimum is sought iteratively. Heuristics are known to provide good solutions but the quality of the solutions, i.e., the confidence interval of the solution is unknown. This paper uses statistical optimum estimation techniques (SOETs) to assess the quality of Genetic algorithm solutions for QAPs. We examine the functioning of different SOETs regarding biasness, coverage rate and length of interval, and then we compare the SOET lower bound with deterministic ones. The commonly used deterministic bounds are confined to only a few algorithms. We show that, the Jackknife estimators have better performance than Weibull estimators, and when the number of heuristic solutions is as large as 100, higher order JK-estimators perform better than lower order ones. Compared with the deterministic bounds, the SOET lower bound performs significantly better than most deterministic lower bounds and is comparable with the best deterministic ones. 

On statistical bounds of heuristic solutions to location problems

Solutions to combinatorial optimization problems, such as problems of locating facilities, frequently rely on heuristics to minimize the objective function. The optimum is sought iteratively and a criterion is needed to decide when the procedure (almost) attains it. Pre-setting the number of iterations dominates in OR applications, which implies that the quality of the solution cannot be ascertained. A small, almost dormant, branch of the literature suggests using statistical principles to estimate the minimum and its bounds as a tool to decide upon stopping and evaluating the quality of the solution. In this paper we examine the functioning of statistical bounds obtained from four different estimators by using simulated annealing on p-median test problems taken from Beasley’s OR-library. We find the Weibull estimator and the 2nd order Jackknife estimator preferable and the requirement of sample size to be about 10 being much less than the current recommendation. However, reliable statistical bounds are found to depend critically on a sample of heuristic solutions of high quality and we give a simple statistic useful for checking the quality. We end the paper with an illustration on using statistical bounds in a problem of locating some 70 distribution centers of the Swedish Post in one Swedish region. 

Confidence in heuristic solutions?

Solutions to combinatorial optimization problems frequently rely on heuristics to minimize an objective function. The optimum is sought iteratively and pre-setting the number of iterations dominates in operations research applications, which implies that the quality of the solution cannot be ascertained. Deterministic bounds offer a mean of ascertaining the quality, but such bounds are available for only a limited number of heuristics and the length of the interval may be difficult to control in an application. A small, almost dormant, branch of the literature suggests using statistical principles to derive statistical bounds for the optimum. We discuss alternative approaches to derive statistical bounds. We also assess their performance by testing them on 40 test p-median problems on facility location, taken from Beasley’s OR-library, for which the optimum is known. We consider three popular heuristics for solving such location problems; simulated annealing, vertex substitution, and Lagrangian relaxation where only the last offers deterministic bounds. Moreover, we illustrate statistical bounds in the location of 71 regional delivery points of the Swedish Post. We find statistical bounds reliable and much more efficient than deterministic bounds provided that the heuristic solutions are sampled close to the optimum. Statistical bounds are also found computationally affordable.

Optimization heuristic solutions, how good can they be? : With empirical applications in location problems

Combinatorial optimization problems, are one of the most important types of problems in operational research. Heuristic and metaheuristics algorithms are widely applied to find a good solution. However, a common problem is that these algorithms do not guarantee that the solution will coincide with the optimum and, hence, many solutions to real world OR-problems are afflicted with an uncertainty about the quality of the solution. The main aim of this thesis is to investigate the usability of statistical bounds to evaluate the quality of heuristic solutions applied to large combinatorial problems. The contributions of this thesis are both methodological and empirical. From a methodological point of view, the usefulness of statistical bounds on p-median problems is thoroughly investigated. The statistical bounds have good performance in providing informative quality assessment under appropriate parameter settings. Also, they outperform the commonly used Lagrangian bounds. It is demonstrated that the statistical bounds are shown to be comparable with the deterministic bounds in quadratic assignment problems. As to empirical research, environment pollution has become a worldwide problem, and transportation can cause a great amount of pollution. A new method for calculating and comparing the CO2-emissions of online and brick-and-mortar retailing is proposed. It leads to the conclusion that online retailing has significantly lesser CO2-emissions. Another problem is that the Swedish regional division is under revision and the border effect to public service accessibility is concerned of both residents and politicians. After analysis, it is shown that borders hinder the optimal location of public services and consequently the highest achievable economic and social utility may not be attained.

How does the use of different road networks effect the optimal location of facilities in rural areas?

The p-median problem is often used to locate P service facilities in a geographically distributed population. Important for the performance of such a model is the distance measure. Distance measure can vary if the accuracy of the road network varies. The rst aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the road network is alternated. It is hard to nd an exact optimal solution for p-median problems. Therefore, in this study two heuristic solutions are applied, simulating annealing and a classic heuristic. The secondary aim is to compare the optimal location solutions using dierent algorithms for large p-median problem. The investigation is conducted by the means of a case study in a rural region with an asymmetrically distributed population, Dalecarlia. The study shows that the use of more accurate road networks gives better solutions for optimal location, regardless what algorithm that is used and regardless how many service facilities that is optimized for. It is also shown that the simulated annealing algorithm not just is much faster than the classic heuristic used here, but also in most cases gives better location solutions.

How does data quality in a network affect heuristic solutions?

To have good data quality with high complexity is often seen to be important. Intuition says that the higher accuracy and complexity the data have the better the analytic solutions becomes if it is possible to handle the increasing computing time. However, for most of the practical computational problems, high complexity data means that computational times become too long or that heuristics used to solve the problem have difficulties to reach good solutions. This is even further stressed when the size of the combinatorial problem increases. Consequently, we often need a simplified data to deal with complex combinatorial problems. In this study we stress the question of how the complexity and accuracy in a network affect the quality of the heuristic solutions for different sizes of the combinatorial problem. We evaluate this question by applying the commonly used p-median model, which is used to find optimal locations in a network of p supply points that serve n demand points. To evaluate this, we vary both the accuracy (the number of nodes) of the network and the size of the combinatorial problem (p). The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 supply points we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000 (which is aggregated from the 1.5 million nodes). To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when the accuracy in the road network increase and the combinatorial problem (low p) is simple. When the combinatorial problem is complex (large p) the improvements of increasing the accuracy in the road network are much larger. The results also show that choice of the best accuracy of the network depends on the complexity of the combinatorial (varying p) problem.

A computational comparison of different algorithms for very large p-median problems

In this paper, we propose a new method for solving large scale p-median problem instances based on real data. We compare different approaches in terms of runtime, memory footprint and quality of solutions obtained. In order to test the different methods on real data, we introduce a new benchmark for the p-median problem based on real Swedish data. Because of the size of the problem addressed, up to 1938 candidate nodes, a number of algorithms, both exact and heuristic, are considered. We also propose an improved hybrid version of a genetic algorithm called impGA. Experiments show that impGA behaves as well as other methods for the standard set of medium-size problems taken from Beasley’s benchmark, but produces comparatively good results in terms of quality, runtime and memory footprint on our specific benchmark based on real Swedish data.

Optimization of cable cycles : a trade-off between reliability and cost

This paper elaborates the routing of cable cycle through available routes in a building in order to link a set of devices, in a most reasonable way. Despite of the similarities to other NP-hard routing problems, the only goal is not only to minimize the cost (length of the cycle) but also to increase the reliability of the path (in case of a cable cut) which is assessed by a risk factor. Since there is often a trade-off between the risk and length factors, a criterion for ranking candidates and deciding the most reasonable solution is defined. A set of techniques is proposed to perform an efficient and exact search among candidates. A novel graph is introduced to reduce the search-space, and navigate the search toward feasible and desirable solutions. Moreover, admissible heuristic length estimation helps to early detection of partial cycles which lead to unreasonable solutions. The results show that the method provides solutions which are both technically and financially reasonable. Furthermore, it is proved that the proposed techniques are very efficient in reducing the computational time of the search to a reasonable amount.