PERFORMANCE EVOLUTION OF PEER TO PEER NETWORKS

This thesis work concerns about the Performance evolution of peer to peer networks, where we used different distribution technique’s of peer distribution like Weibull, Lognormal and Pareto distribution process. Then we used a network simulator to evaluate the performance of these three distribution techniques.During the last decade the Internet has expanded into a world-wide network connecting millions of hosts and users and providing services for everyone. Many emerging applications are bandwidth-intensive in their nature; the size of downloaded files including music and videos can be huge, from ten megabits to many gigabits. The efficient use of network resources is thus crucial for the survivability of the Internet. Traffic engineering (TE) covers a range of mechanisms for optimizing operational networks from the traffic perspective. The time scale in traffic engineering varies from the short-term network control to network planning over a longer time period.Here in this thesis work we considered the peer distribution technique in-order to minimise the peer arrival and service process with three different techniques, where we calculated the congestion parameters like blocking time for each peer before entering into the service process, waiting time for a peers while the other peer has been served in the service block and the delay time for each peer. Then calculated the average of each process and graphs have been plotted using Matlab to analyse the results

Combined solar and pellet heating systems for single-family houses : How to achieve decreased electricity usage, increased system efficiency and increased solar gains

In Sweden, there are about 0.5 million single-family houses that are heated by electricity alone, and rising electricity costs force the conversion to other heating sources such as heat pumps and wood pellet heating systems. Pellet heating systems for single-family houses are currently a strongly growing market. Future lack of wood fuels is possible even in Sweden, and combining wood pellet heating with solar heating will help to save the bio-fuel resources. The objectives of this thesis are to investigate how the electrically heated single-family houses can be converted to pellet and solar heating systems, and how the annual efficiency and solar gains can be increased in such systems. The possible reduction of CO-emissions by combining pellet heating with solar heating has also been investigated. Systems with pellet stoves (both with and without a water jacket), pellet boilers and solar heating have been simulated. Different system concepts have been compared in order to investigate the most promising solutions. Modifications in system design and control strategies have been carried out in order to increase the system efficiency and the solar gains. Possibilities for increasing the solar gains have been limited to investigation of DHW-units for hot water production and the use of hot water for heating of dishwashers and washing machines via a heat exchanger instead of electricity (heat-fed appliances). Computer models of pellet stoves, boilers, DHW-units and heat-fed appliances have been developed and the parameters for the models have been identified from measurements on real components. The conformity between the models and the measurements has been checked. The systems with wood pellet stoves have been simulated in three different multi-zone buildings, simulated in detail with heat distribution through door openings between the zones. For the other simulations, either a single-zone house model or a load file has been used. Simulations were carried out for Stockholm, Sweden, but for the simulations with heat-fed machines also for Miami, USA. The foremost result of this thesis is the increased understanding of the dynamic operation of combined pellet and solar heating systems for single-family houses. The results show that electricity savings and annual system efficiency is strongly affected by the system design and the control strategy. Large reductions in pellet consumption are possible by combining pellet boilers with solar heating (a reduction larger than the solar gains if the system is properly designed). In addition, large reductions in carbon monoxide emissions are possible. To achieve these reductions it is required that the hot water production and the connection of the radiator circuit is moved to a well insulated, solar heated buffer store so that the boiler can be turned off during the periods when the solar collectors cover the heating demand. The amount of electricity replaced using systems with pellet stoves is very dependant on the house plan, the system design, if internal doors are open or closed and the comfort requirements. Proper system design and control strategies are crucial to obtain high electricity savings and high comfort with pellet stove systems. The investigated technologies for increasing the solar gains (DHW-units and heat-fed appliances) significantly increase the solar gains, but for the heat-fed appliances the market introduction is difficult due to the limited financial savings and the need for a new heat distribution system. The applications closest to market introduction could be for communal laundries and for use in sunny climates where the dominating part of the heat can be covered by solar heating. The DHW-unit is economical but competes with the internal finned-tube heat exchanger which is the totally dominating technology for hot water preparation in solar combisystems for single-family houses.

Big Data Analysis in Social Networks : Extracting Food Preferences of Vegans from Twitter

Market research is often conducted through conventional methods such as surveys, focus groups and interviews. But the drawbacks of these methods are that they can be costly and timeconsuming. This study develops a new method, based on a combination of standard techniques like sentiment analysis and normalisation, to conduct market research in a manner that is free and quick. The method can be used in many application-areas, but this study focuses mainly on the veganism market to identify vegan food preferences in the form of a profile. Several food words are identified, along with their distribution between positive and negative sentiments in the profile. Surprisingly, non-vegan foods such as cheese, cake, milk, pizza and chicken dominate the profile, indicating that there is a significant market for vegan-suitable alternatives for such foods. Meanwhile, vegan-suitable foods such as coconut, potato, blueberries, kale and tofu also make strong appearances in the profile. Validation is performed by using the method on Volkswagen vehicle data to identify positive and negative sentiment across five car models. Some results were found to be consistent with sales figures and expert reviews, while others were inconsistent. The reliability of the method is therefore questionable, so the results should be used with caution.