Load balancing solution and evaluation of F5 content switch equipment

The Thesis focused on hardware based Load balancing solution of web traffic through a load balancer F5 content switch. In this project, the implemented scenario for distributing HTTPtraffic load is based on different CPU usages (processing speed) of multiple member servers.Two widely used load balancing algorithms Round Robin (RR) and Ratio model (weighted Round Robin) are implemented through F5 load balancer. For evaluating the performance of F5 content switch, some experimental tests has been taken on implemented scenarios using RR and Ratio model load balancing algorithms. The performance is examined in terms of throughput (bits/sec) and Response time of member servers in a load balancing pool. From these experiments we have observed that Ratio Model load balancing algorithm is most suitable in the environment of load balancing servers with different CPU usages as it allows assigning the weight according to CPU usage both in static and dynamic load balancing of servers.

A Unified Load Generator for Geographically Distributed Generation ofNetwork Traffic

During the last decade, the Internet usage has been growing at an enormous rate which has beenaccompanied by the developments of network applications (e.g., video conference, audio/videostreaming, E-learning, E-Commerce and real-time applications) and allows several types ofinformation including data, voice, picture and media streaming. While end-users are demandingvery high quality of service (QoS) from their service providers, network undergoes a complex trafficwhich leads the transmission bottlenecks. Considerable effort has been made to study thecharacteristics and the behavior of the Internet. Simulation modeling of computer networkcongestion is a profitable and effective technique which fulfills the requirements to evaluate theperformance and QoS of networks. To simulate a single congested link, simulation is run with asingle load generator while for a larger simulation with complex traffic, where the nodes are spreadacross different geographical locations generating distributed artificial loads is indispensable. Onesolution is to elaborate a load generation system based on master/slave architecture.

Signal Processing and patternrecognition algorithm for monitoringParkinson’s disease.

This masters thesis describes the development of signal processing and patternrecognition in monitoring Parkison’s disease. It involves the development of a signalprocess algorithm and passing it into a pattern recogniton algorithm also. Thesealgorithms are used to determine , predict and make a conclusion on the study ofparkison’s disease. We get to understand the nature of how the parkinson’s disease isin humans.

Solving the Vehicle Routing Problem with Genetic ALgorithm and Simulated Annealing

This Thesis Work will concentrate on a very interesting problem, the Vehicle Routing Problem (VRP). In this problem, customers or cities have to be visited and packages have to be transported to each of them, starting from a basis point on the map. The goal is to solve the transportation problem, to be able to deliver the packages-on time for the customers,-enough package for each Customer,-using the available resources- and – of course - to be so effective as it is possible.Although this problem seems to be very easy to solve with a small number of cities or customers, it is not. In this problem the algorithm have to face with several constraints, for example opening hours, package delivery times, truck capacities, etc. This makes this problem a so called Multi Constraint Optimization Problem (MCOP). What’s more, this problem is intractable with current amount of computational power which is available for most of us. As the number of customers grow, the calculations to be done grows exponential fast, because all constraints have to be solved for each customers and it should not be forgotten that the goal is to find a solution, what is best enough, before the time for the calculation is up. This problem is introduced in the first chapter: form its basics, the Traveling Salesman Problem, using some theoretical and mathematical background it is shown, why is it so hard to optimize this problem, and although it is so hard, and there is no best algorithm known for huge number of customers, why is it a worth to deal with it. Just think about a huge transportation company with ten thousands of trucks, millions of customers: how much money could be saved if we would know the optimal path for all our packages.Although there is no best algorithm is known for this kind of optimization problems, we are trying to give an acceptable solution for it in the second and third chapter, where two algorithms are described: the Genetic Algorithm and the Simulated Annealing. Both of them are based on obtaining the processes of nature and material science. These algorithms will hardly ever be able to find the best solution for the problem, but they are able to give a very good solution in special cases within acceptable calculation time.In these chapters (2nd and 3rd) the Genetic Algorithm and Simulated Annealing is described in details, from their basis in the “real world” through their terminology and finally the basic implementation of them. The work will put a stress on the limits of these algorithms, their advantages and disadvantages, and also the comparison of them to each other.Finally, after all of these theories are shown, a simulation will be executed on an artificial environment of the VRP, with both Simulated Annealing and Genetic Algorithm. They will both solve the same problem in the same environment and are going to be compared to each other. The environment and the implementation are also described here, so as the test results obtained.Finally the possible improvements of these algorithms are discussed, and the work will try to answer the “big” question, “Which algorithm is better?”, if this question even exists.

A Genetic Algorithm for Solar Boat

Genetic algorithm has been widely used in different areas of optimization problems. Ithas been combined with renewable energy domain, photovoltaic system, in this thesis.To participate and win the solar boat race, a control program is needed and C++ hasbeen chosen for programming. To implement the program, the mathematic model hasbeen built. Besides, the approaches to calculate the boundaries related to conditionhave been explained. Afterward, the processing of the prediction and real time controlfunction are offered. The program has been simulated and the results proved thatgenetic algorithm is helpful to get the good results but it does not improve the resultstoo much since the particularity of the solar driven boat project such as the limitationof energy production

Branch and Bound Algorithm for Multiprocessor Scheduling

The multiprocessor task graph scheduling problem has been extensively studied asacademic optimization problem which occurs in optimizing the execution time of parallelalgorithm with parallel computer. The problem is already being known as one of the NPhardproblems. There are many good approaches made with many optimizing algorithmto find out the optimum solution for this problem with less computational time. One ofthem is branch and bound algorithm.In this paper, we propose a branch and bound algorithm for the multiprocessor schedulingproblem. We investigate the algorithm by comparing two different lower bounds withtheir computational costs and the size of the pruned tree.Several experiments are made with small set of problems and results are compared indifferent sections.

University Scheduling using Genetic Algorithm

The automated timetabling and scheduling is one of the hardest problem areas. This isbecause of constraints and satisfying those constraints to get the feasible and optimizedschedule, and it is already proved as an NP Complete (1) [1]. The basic idea behind this studyis to investigate the performance of Genetic Algorithm on general scheduling problem underpredefined constraints and check the validity of results, and then having comparative analysiswith other available approaches like Tabu search, simulated annealing, direct and indirectheuristics [2] and expert system. It is observed that Genetic Algorithm is good solutiontechnique for solving such problems and later analysis will prove this argument. The programis written in C++ and analysis is done by using variation in various parameters.

University Timetabling using Genetic Algorithm

The field of automated timetabling and scheduling meeting all the requirementsthat we call constraints is always difficult task and already proved as NPComplete. The idea behind my research is to implement Genetic Algorithm ongeneral scheduling problem under predefined constraints and check the validityof results, and then I will explain the possible usage of other approaches likeexpert systems, direct heuristics, network flows, simulated annealing and someother approaches. It is observed that Genetic Algorithm is good solutiontechnique for solving such problems. The program written in C++ and analysisis done with using various tools explained in details later.

Load and Season Adapted Solar Collectors

In Sweden solar irradiation and space heating loads are unevenly distributed over the year. Domestic hot water loads may be nearly constant. Test results on solar collector performance are often reported as yearly output of a certain collector at fixed temperatures, e g 25, 50 and 75 C. These data are not suitable for dimensioning of solar systems, because the actual performance of the collector depends heavily on solar fraction and load distribution over the year.At higher latitudes it is difficult to attain high solar fractions for buildings, due to overheating in summer and small marginal output for added collector area. Solar collectors with internal reflectors offer possibilities to evade overheating problems and deliver more energy at seasons when the load is higher. There are methods for estimating the yearly angular irradiation distribution, but there is a lack of methods for describing the load and the storage in such a way as to enable optical design of season and load adapted collectors.This report describes two methods for estimation of solar system performance with relevance for season and load adaption. Results regarding attainable solar fractions as a function of collector features, load profiles, load levels and storage characteristics are reported. The first method uses monthly collector output data at fixed temperatures from the simulation program MINSUN for estimating solar fractions for different load profiles and load levels. The load level is defined as estimated yearly collector output at constant collector temperature divided be yearly load. This table may examplify the results:CollectorLoadLoadSolar Improvementtypeprofile levelfractionover flat plateFlat plateDHW 75 %59 %Load adaptedDHW 75 %66 %12 %Flat plateSpace heating 50 %22 %Load adaptedSpace heating 50 %28 %29 %The second method utilises simulations with one-hour timesteps for collectors connected to a simplified storage and a variable load. Collector output, optical and thermal losses, heat overproduction, load level and storage temperature are presented as functions of solar incidence angles. These data are suitable for optical design of load adapted solar collectors. Results for a Stockholm location indicate that a solar combisystem with a solar fraction around 30 % should have collectors that reduce heat production at solar heights above 30 degrees and have optimum efficiency for solar heights between 8 and 30 degrees.

Load Adapted Solar Thermal Combisystems - Optical Analysis and Systems Optimization

In a northern European climate a typical solar combisystem for a single family house normally saves between 10 and 30 % of the auxiliary energy needed for space heating and domestic water heating. It is considered uneconomical to dimension systems for higher energy savings. Overheating problems may also occur. One way of avoiding these problems is to use a collector that is designed so that it has a low optical efficiency in summer, when the solar elevation is high and the load is small, and a high optical efficiency in early spring and late fall when the solar elevation is low and the load is large.The study investigates the possibilities to design the system and, in particular, the collector optics, in order to match the system performance with the yearly variations of the heating load and the solar irradiation. It seems possible to design practically viable load adapted collectors, and to use them for whole roofs ( 40 m2) without causing more overheating stress on the system than with a standard 10 m2 system. The load adapted collectors collect roughly as much energy per unit area as flat plate collectors, but they may be produced at a lower cost due to lower material costs. There is an additional potential for a cost reduction since it is possible to design the load adapted collector for low stagnation temperatures making it possible to use less expensive materials. One and the same collector design is suitable for a wide range of system sizes and roof inclinations. The report contains descriptions of optimized collector designs, properties of realistic collectors, and results of calculations of system output, stagnation performance and cost performance. Appropriate computer tools for optical analysis, optimization of collectors in systems and a very fast simulation model have been developed.

Solvärmesystem för hög täckningsgrad - Load adapted concentrating collectors for high solar fractions

Dagens kombisolvärmesystem för enfamiljshus har i storleksordningen 10 m2 solfångare och kan täcka i runda tal 10 ? 30 % av det årliga värmebehovet. Ökar man solfångarytan för att öka solvärmetäckningsgraden uppstår det vanligtvis en överproduktion av värme sommartid viket kan orsaka problem i form av termisk utmattning av material, att material förstörs eller att säkerhetsventiler utlöses med driftsstopp som följd. Vidare förkortas glykolens livslängd radikalt och detta kan ge följdskador såsom korrosion, beläggningar i rören och t o m igensättning av systemet. Ett sätt att undvika problemen med överhettning i solvärmesystem med hög täckningsgrad är att använda lastanpassade solfångare. Med detta menas solfångare som har en verkningsgrad som är beroende av solhöjden och varierar över året. Verkningsgraden är hög när värmelasten är hög (vanligtvis sen höst, vinter och tidig vår) medan verkningsgraden är låg då värmelasten är låg (vanligtvis sen vår, sommar och tidig höst). I denna rapport visas att det är möjligt att bygga lastanpassade solfångarsystem med hög täckningsgrad för enfamiljshus med solfångarytor som täcker hela villatak (>= 40 m2), utan att den termiska påfrestningen på systemet blir större än för vanliga solvärmesystem med 10 m2 plana solfångare. Detta kan göras med samma systemkomponenter som finns i system med plana solfångare. De lastanpassade solfångarna levererar ungefär samma energimängd per m2 som plana solfångare, men de bör kunna bli billigare, på grund av lägre materialkostnad. Det finns även en potential att konstruera lastanpassade solvärmesystem med begränsad stagnationstemperatur, vilket kan möjliggöra användandet av billigare material. En och samma solfångartyp är lämplig för såväl stora som små system och för olika takvinklar. I rapporten redovisas optimerade solfångargeometrier för lastanpassade solvärmesystem, geometrier och optiska egenskaper för praktiskt möjliga solfångare samt beräkningar av förväntat årsutbyte, stagnationstemperaturer, stagnationstider och kostnader. Testresultat för två prototyper av lastanpassade solfångare presenteras. Optimeringsalgoritmer för design av optiken för lastanpassade solfångare i system samt ett ray-tracingverktyg och snabba men ändå tillräckligt noggranna simuleringsverktyg har utvecklats.

Intelligent Algorithms for a Hybrid FuelCell/Photovoltaic Standalone System : Simulation Of Hybrid FuelCell/Photovoltaic Standalone System

The Intelligent Algorithm is designed for theusing a Battery source. The main function is to automate the Hybrid System through anintelligent Algorithm so that it takes the decision according to the environmental conditionsfor utilizing the Photovoltaic/Solar Energy and in the absence of this, Fuel Cell energy isused. To enhance the performance of the Fuel Cell and Photovoltaic Cell we used batterybank which acts like a buffer and supply the current continuous to the load. To develop the main System whlogic based controller was used. Fuzzy Logic based controller used to develop this system,because they are chosen to be feasible for both controlling the decision process and predictingthe availability of the available energy on the basis of current Photovoltaic and Battery conditions. The Intelligent Algorithm is designed to optimize the performance of the system and to selectthe best available energy source(s) in regard of the input parameters. The enhance function of these Intelligent Controller is to predict the use of available energy resources and turn on thatparticular source for efficient energy utilization. A fuzzy controller was chosen to take thedecisions for the efficient energy utilization from the given resources. The fuzzy logic basedcontroller is designed in the Matlab-Simulink environment. Initially, the fuzzy based ruleswere built. Then MATLAB based simulation system was designed and implemented. Thenthis whole proposed model is simulated and tested for the accuracy of design and performanceof the system.