Framework Models for Theme Park Design: Incorporating Transportability Models and Visitor Preferences

Analyzing human movement is crucial for evaluating designs in transportation and urban planning. Our expertise lies in the realm of designing and assessing wireless networks and services tailored for cutting-edge theme park experiences. The effectiveness of specific wireless networks, such as mobile ad hoc networks, is significantly impacted by human mobility. In response to this challenge, we've developed an advanced program known as ParkSim, dedicated to replicating the intricate motion patterns of guests within a theme park environment. ParkSim utilizes an activity-based mobility model, influenced by the diverse activities guests engage in throughout the park. The calibration of this tool is based on GPS data collected from an amusement theme park, ensuring its accuracy and reliability. It has undergone rigorous verification against various performance metrics relevant to wireless ad hoc networks. Our primary goal is to enhance ParkSim further, enabling it to evaluate innovative strategies for equitably distributing visitors across different sections of the theme park. This expansion will provide valuable insights into optimizing wireless network performance and enhancing the overall theme park experience for guests

A Classification and Performance Comparison of Mobility Models for Ad Hoc Networks

Abstract. In mobile ad hoc network research, simulation plays an important role in determining the network characteristics and measuring performance. On the other hand, unrealistic simulation conditions may be misleading, instead of being explanatory. For this reason, constructing simulation models closer to the real circumstances is very significant. Movement behavior of mobile entities is one of the most important concepts for the realistic simulation scenarios in mo-bile ad hoc networks. In this study, we first provide a survey and a new hybrid classification of existing mobility models in the literature. We implemented the random direction and boundless simulation area models on Scalable Wireless Ad Hoc Network Simulator (SWANS) and conducted simulations of Ad Hoc On-Demand Distance Vector (AODV) protocol for these as well as the random walk and random waypoint models. Our comparative results for the mobility models are discussed on a variety of simulation settings and parameters.

Persim - Simulator for Human Activities in Pervasive Spaces

Activity recognition research relies heavily on test data to verify the modeling technique and the performance of the activity recognition algorithm. But data from real deployments are expensive and time consuming to obtain. And even if cost is not an issue, regulatory limitations on the use of human subjects prohibit the collection of extensive datasets that can test all scenarios, under all circumstances. A powerful and verifiable simulation tool is needed to accelerate research on human activity recognition. We present Persim, an event driven simulator of human activities in pervasive spaces. Persim is capable of capturing elements of space, sensors, behaviors (activities), and their inter-relationships. We focus on presenting the five main use cases for Persim addressing dataset synthesis, reuse and extension of existing datasets, sharing of data and simulation projects, as well as data validation. © 2011 IEEE

A survey on mobility models for performance analysis in tactical mobile networks, Journal of Telecommunications and Information Technology, 2008, nr 2

In scenarios of military operations and catastrophes – even when there is no infrastructure available or left – there is a need for communication. Due to the specific context the communication systems used in these tactical scenarios need to be as reliable as possible. Thus, the performance of these systems has to be evaluated. Beside field-tests, computer simulations are an interesting alternative concerning costs, scalability, etc. Results of simulative performance evaluation strongly depend on the models used. Since tactical networks consist of, or, at least, contain mobile devices, the mobility model used has a decisive impact. However, in common performance evaluations mainly simple random-based models are used. In the paper we will provide classification and survey of existing mobility models. Furthermore, we will review these models concerning the requirements for tactical scenarios

Processing continuous range queries with spatiotemporal tolerance

Continuous queries are often employed to monitor the locations of mobile objects (MOs), which are determined by sensing devices like GPS receivers. In this paper, we tackle two challenges in processing continuous range queries (CRQs): coping with data uncertainty inherently associated with location data, and reducing the energy consumption of battery-powered MOs. We propose the concept of spatiotemporal tolerance for CRQ to relax a query's accuracy requirements in terms of a maximal acceptable error. Unlike previous works, our definition considers tolerance in both the spatial and temporal dimensions, which offers applications more flexibility in specifying their individual accuracy requirements. As we will show, these tolerance bounds can provide well-defined query semantics in spite of different sources of data uncertainty. In addition, we present efficient algorithms that carefully control when an MO should sense or report a location, while satisfying these tolerances. Thereby, we particularly reduce the number of position sensing operations substantially, which constitute a considerable source of energy consumption. Extensive simulations confirm that the proposed algorithms result in large energy savings compared to nontolerant query processing. © 2006 IEEE.published_or_final_versio

Analysis of User Mobility Models Based on Outdoor Measurement Data and Literature Surveys

The main objectives of the presented work are to study the various existing human mobility models based on literature reviews and to select an appropriate and simplified mobility model fit to the available measurement data. This thesis work is mainly processing a part of “Big Data” that was collected from large number of people, known as Mobile Data Challenge (MDC). MDC is large scale data collection from Smartphone based research. The thesis also addressed the fact that appropriate mobility models could be utilized in many important practical applications, such as in public health care units, for elderly care and monitoring, to improve the localization algorithms, in cellular communications networks to avoid traffic congestion, for designing of such systems that can predict prior users location, in economic forecasting, for public transportation systems and for developing social mobile applications. Basically, mobility models indicate the movement patterns of users and how their position, velocity and acceleration vary with respect to time. Such models can be widely used in the investigation of advanced communication and navigation techniques. These human mobility models are normally classified into two main models, namely; entity mobility models and group mobility models. The presented work focuses on the entity mobility models. The analysis was done in Matlab, based on the measurement data available in MDC database, the several parameters of Global Positioning System (GPS) data were extracted, such as time, latitude, longitude, altitude, speed, horizontal accuracy, horizontal Dilution of Precision (DOP), vertical accuracy, vertical DOP, speed accuracy etc. Parts of these parameters, namely the time, latitude, longitude, altitude and speed were further investigated in the context of basic random walk mobility model. The data extracted from the measurements was compared with the 2-D random walk mobility model. The main findings of the thesis are that the random walk model is not a perfect fit for the available user measurement data, but can be used as a starting point in analyzing the user mobility models

Investigations of outdoor mobility patterns of taxicabs in urban scenarios

This thesis investigates various outdoor mobility patterns of taxicabs in urban environments based on open-data real traces and it proposes a suitable outdoor mobility model to fit the provided measurement data. This thesis is processing user traces of taxicabs of two major cities: Rome and San Francisco downloaded from CRAWDAD open-source repository, which is responsible for sharing data from real networks and real mobile users across the various research communities around the world. There are numerous sources of collecting traces of users in a city, such as mobile devices, vehicles, smart cards, floating sensors etc. This thesis presents a comparative analysis of the mobility patterns of various taxicabs from Rome and San Francisco cities based on data collected via GPS-enabled mobile devices. Finding suitable mobility models of taxicabs to represent the travelling patterns of users moving from one location to another with respect to their varying time, location and speed can be quite helpful for the advanced researches in the diverse fields of wireless communications, such as better network planning, more efficient smart city design, improved traffic flows in cities. Also other applications such as weather forecasting, cellular coverage planning, e-health services, prediction of tourist areas, intelligent transport systems can benefit from the information hidden in user traces and from being able to find out statistically valid mobility models. The work here focused on extracting various mobility parameters from the crowdsourced open-source data and trying to model them according to various mobility models existing in the literature. The measurement analysis of this thesis work was completed in Matlab

Investigations of outdoor mobility patterns of taxicabs in urban scenarios

This thesis investigates various outdoor mobility patterns of taxicabs in urban environments based on open-data real traces and it proposes a suitable outdoor mobility model to fit the provided measurement data. This thesis is processing user traces of taxicabs of two major cities: Rome and San Francisco downloaded from CRAWDAD open-source repository, which is responsible for sharing data from real networks and real mobile users across the various research communities around the world. There are numerous sources of collecting traces of users in a city, such as mobile devices, vehicles, smart cards, floating sensors etc. This thesis presents a comparative analysis of the mobility patterns of various taxicabs from Rome and San Francisco cities based on data collected via GPS-enabled mobile devices. Finding suitable mobility models of taxicabs to represent the travelling patterns of users moving from one location to another with respect to their varying time, location and speed can be quite helpful for the advanced researches in the diverse fields of wireless communications, such as better network planning, more efficient smart city design, improved traffic flows in cities. Also other applications such as weather forecasting, cellular coverage planning, e-health services, prediction of tourist areas, intelligent transport systems can benefit from the information hidden in user traces and from being able to find out statistically valid mobility models. The work here focused on extracting various mobility parameters from the crowdsourced open-source data and trying to model them according to various mobility models existing in the literature. The measurement analysis of this thesis work was completed in Matlab

Impacts of Mobility Models on RPL-Based Mobile IoT Infrastructures: An Evaluative Comparison and Survey

With the widespread use of IoT applications and the increasing trend in the number of connected smart devices, the concept of routing has become very challenging. In this regard, the IPv6 Routing Protocol for Low-power and Lossy Networks (PRL) was standardized to be adopted in IoT networks. Nevertheless, while mobile IoT domains have gained significant popularity in recent years, since RPL was fundamentally designed for stationary IoT applications, it could not well adjust with the dynamic fluctuations in mobile applications. While there have been a number of studies on tuning RPL for mobile IoT applications, but still there is a high demand for more efforts to reach a standard version of this protocol for such applications. Accordingly, in this survey, we try to conduct a precise and comprehensive experimental study on the impact of various mobility models on the performance of a mobility-aware RPL to help this process. In this regard, a complete and scrutinized survey of the mobility models has been presented to be able to fairly justify and compare the outcome results. A significant set of evaluations has been conducted via precise IoT simulation tools to monitor and compare the performance of the network and its IoT devices in mobile RPL-based IoT applications under the presence of different mobility models from different perspectives including power consumption, reliability, latency, and control packet overhead. This will pave the way for researchers in both academia and industry to be able to compare the impact of various mobility models on the functionality of RPL, and consequently to design and implement application-specific and even a standard version of this protocol, which is capable of being employed in mobile IoT applications

Journal of Telecommunications and Information Technology, 2008, nr 2

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