Prediction Techniques in Internet of Things (IoT) Environment: A Comparative Study

Socialization and Personalization in Internet of Things (IOT) environment are the current trends in computing research. Most of the research work stresses the importance of predicting the service & providing socialized and personalized services. This paper presents a survey report on different techniques used for predicting user intention in wide variety of IOT based applications like smart mobile, smart television, web mining, weather forecasting, health-care/medical, robotics, road-traffic, educational data mining, natural calamities, retail banking, e-commerce, wireless networks & social networking. As per the survey made the prediction techniques are used for: predicting the application that can be accessed by the mobile user, predicting the next page to be accessed by web user, predicting the users favorite TV program, predicting user navigational patterns and usage needs on websites & also to extract the users browsing behavior, predicting future climate conditions, predicting whether a patient is suffering from a disease, predicting user intention to make implicit and human-like interactions possible by accepting implicit commands, predicting the amount of traffic occurring at a particular location, predicting student performance in schools & colleges, predicting & estimating the frequency of natural calamities occurrences like floods, earthquakes over a long period of time & also to take precautionary measures, predicting & detecting false user trying to make transaction in the name of genuine user, predicting the actions performed by the user to improve the business, predicting & detecting the intruder acting in the network, predicting the mood transition information of the user by using context history, etc. This paper also discusses different techniques like Decision Tree algorithm, Artificial Intelligence and Data Mining based Machine learning techniques, Content and Collaborative based Recommender algorithms used for prediction

A Human Driver Model for Autonomous Lane Changing in Highways: Predictive Fuzzy Markov Game Driving Strategy

This study presents an integrated hybrid solution to mandatory lane changing problem to deal with accident avoidance by choosing a safe gap in highway driving. To manage this, a comprehensive treatment to a lane change active safety design is proposed from dynamics, control, and decision making aspects. My effort first goes on driver behaviors and relating human reasoning of threat in driving for modeling a decision making strategy. It consists of two main parts; threat assessment in traffic participants, (TV s) states, and decision making. The first part utilizes an complementary threat assessment of TV s, relative to the subject vehicle, SV , by evaluating the traffic quantities. Then I propose a decision strategy, which is based on Markov decision processes (MDPs) that abstract the traffic environment with a set of actions, transition probabilities, and corresponding utility rewards. Further, the interactions of the TV s are employed to set up a real traffic condition by using game theoretic approach. The question to be addressed here is that how an autonomous vehicle optimally interacts with the surrounding vehicles for a gap selection so that more effective performance of the overall traffic flow can be captured. Finding a safe gap is performed via maximizing an objective function among several candidates. A future prediction engine thus is embedded in the design, which simulates and seeks for a solution such that the objective function is maximized at each time step over a horizon. The combined system therefore forms a predictive fuzzy Markov game (FMG) since it is to perform a predictive interactive driving strategy to avoid accidents for a given traffic environment. I show the effect of interactions in decision making process by proposing both cooperative and non-cooperative Markov game strategies for enhanced traffic safety and mobility. This level is called the higher level controller. I further focus on generating a driver controller to complement the automated car’s safe driving. To compute this, model predictive controller (MPC) is utilized. The success of the combined decision process and trajectory generation is evaluated with a set of different traffic scenarios in dSPACE virtual driving environment. Next, I consider designing an active front steering (AFS) and direct yaw moment control (DYC) as the lower level controller that performs a lane change task with enhanced handling performance in the presence of varying front and rear cornering stiffnesses. I propose a new control scheme that integrates active front steering and the direct yaw moment control to enhance the vehicle handling and stability. I obtain the nonlinear tire forces with Pacejka model, and convert the nonlinear tire stiffnesses to parameter space to design a linear parameter varying controller (LPV) for combined AFS and DYC to perform a commanded lane change task. Further, the nonlinear vehicle lateral dynamics is modeled with Takagi-Sugeno (T-S) framework. A state-feedback fuzzy H∞ controller is designed for both stability and tracking reference. Simulation study confirms that the performance of the proposed methods is quite satisfactory

The Internet-Wide Impact of P2P Traffic Localization on ISP Profitability

We conduct a detailed simulation study to examine how localizing P2P traffic within network boundaries impacts the profitability of an ISP. A distinguishing aspect of our work is the focus on Internet-wide implications, i.e., how adoption of localization within an ISP affects both itself and other ISPs. Our simulations are based on detailed models that estimate inter-autonomous-system (AS) P2P traffic and inter-AS routing, localization models that predict the extent to which P2P traffic is reduced, and pricing models that predict the impact of changes in traffic on the profit of an ISP. We evaluate our models by using a large-scale crawl of BitTorrent containing over 138 million users sharing 2.75 million files. Our results show that the benefits of localization must not be taken for granted. Some of our key findings include: 1) residential ISPs can actually lose money when localization is employed, and some of them will not see increased profitability until other ISPs employ localization; 2) the reduction in costs due to localization will be limited for small ISPs and tends to grow only logarithmically with client population; and 3) some ISPs can better increase profitability through alternate strategies to localization by taking advantage of the business relationships they have with other ISP

SIMULATION AND ANALYSIS OF VEHICULAR AD-HOC NETWORKS IN URBAN AND RURAL AREAS

According to the American National Highway Traffic Safety Administration, in 2010, there were an estimated 5,419,000 police-reported traffic crashes, in which 32,885 people were killed and 2,239,000 people were injured in the US alone. Vehicular Ad-Hoc Network (VANET) is an emerging technology which promises to decrease car accidents by providing several safety related services such as blind spot, forward collision and sudden braking ahead warnings. Unfortunately, research of VANET is hindered by the extremely high cost and complexity of field testing. Hence it becomes important to simulate VANET protocols and applications thoroughly before attempting to implement them. This thesis studies the feasibility of common mobility and wireless channel models in VANET simulation and provides a general overview of the currently available VANET simulators and their features. Six different simulation scenarios are performed to evaluate the performance of AODV, DSDV, DSR and OLSR Ad-Hoc routing protocols with UDP and TCP packets. Simulation results indicate that reactive protocols are more robust and suitable for the highly dynamic VANET networks. Furthermore, TCP is found to be more suitable for VANET safety applications due to the high delay and packet drop of UDP packets.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Impacto de las estrategias para incentivar el uso de la bicicleta en viajes al trabajo : un estudio de caso con empleados de la Companhia Riograndense de Saneamento

This study identifies the most valued factors for potential bicycle users on work trips and evaluate the impact of implementing different strategies to improve bicycle use. We applied an online stated-preference survey from 127 Companhia Riograndense de Saneamento (CORSAN) employees in Porto Alegre (Brazil). Then, we formulated hybrid ordered logit models to estimate the probability of bicycle use under different hypothetical scenarios. The results showed that locker rooms, bicycle parking, bike-sharing systems (bike loaner programs run by the company), training for employees in bicycle use and the presence of bike paths for access to CORSAN all encourage bicycle use. The availability of locker rooms proved to be the most important variable. The joint implementation of locker rooms, bicycle parking and bike-sharing systems (loaner programs) would increase demand by 66%. The strategies discussed in this article can easily be adapted to other contexts where there is a desire to increase shared bicycle commuting to workplaces.Los objetivos de este estudio son identificar los factores más importantes para estimular el uso de la bicicleta en viajes al trabajo y evaluar el impacto de la implantación de diferentes medidas. Los empleados de la Companhia Riograndense de Saneamento (CORSAN) fueron utilizados como estudio de caso en Porto Alegre (Brasil), a través de una encuesta de preferencia declarada. La probabilidad de uso de la bicicleta en diferentes escenarios se estimó mediante modelos híbridos logit ordenados. Los resultados mostraron que la implantación de vestuarios, estacionamiento de bicicletas, sistemas de bicicletas compartidas (programa de préstamos de bicicletas realizado por la empresa), capacitación de los empleados en relación al uso de bicicleta y la presencia de ciclovías para el acceso a CORSAN, fomentan el uso de la bicicleta. La disponibilidad de vestuarios resultó ser la variable más importante. La implementación conjunta de vestuarios, estacionamiento de bicicletas y sistemas de bicicletas compartidas (programas de préstamo) aumentaría la demanda en un 66% en este caso. Los procedimientos adoptados podrían aplicarse fácilmente en otros contextos donde se desee incrementar la proporción de viajes hacia los lugares de trabajo

SURVEY STUDY FOR VEHICULAR AD HOC NETWORKS PERFORMANCE IN CITY AND URBAN RESIDENTIAL AREAS

This thesis it survey study for VANET (Vehicular Ad-Hoc Networks) and it performance in city and urban residential areas, when the the number of vehicles on roads is increasing annually, due to the higher amount of traffic, there are more accidents associated with road traffic complexity. VANET can be used to detect dangerous situations which are forwarded to the driver assistant system by monitoring the traffic status.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Book of abstracts of the 24th Euro Working Group on Transportation Meeting

Sem resumo disponível.publishe