Characterization of Internet Traffic in UUM Wireless Networks

The development in communication technology and the propagation of mobile devices, lightweight, with built-in, high-speed radio access in wireless are making wireless access to the Internet the popular situation rather than a wire line. Whereas, the growth of the wireless network with additional mobile devices in the UUM and increasing number of users led to slow wireless connection. Therefore, understanding the behavior of traffic analysis helps us to develop, manage WLAN technology, and deploy. It help us to apply our workload analysis results to issues in wireless network deployment, such as capacity planning, and potential network optimizations, such as algorithms for load balancing across multiple Access Points (APs) in a wireless network. The trace composes of two parts: firstly, one that connects to the core switch in computer center which is connected with the distribution switches that link the Access Point (APs) with the wireless network at campus, and secondly, another one for the measurement of bulk data transfers and interactive data exchange between two nodes in UUM library, which had been initiated at that time. This thesis investigates the performance network and users' behavior in UUM wireless network

Predicting the Diffusion of Next Generation 9-1-1 in the Commonwealth of Virginia: An Application Using the Deployment of Wireless E9-1-1 Technologies

This study examines the deployment of Wireless E9-1-1 Phase One and Wireless E9-1-1 Phase Two as a diffusion of innovation. The research method used in this study is a cross-sectional study employing secondary data in a discriminant function analysis. The study population is Virginia units of local governments (95 counties and 39 cities) that had not deployed Wireless E9-1-1 Phase One or Wireless E9-1-1 Phase Two as of January 1, 2001. The period of time included in this study is from 2001 to 2006. The purpose of the study is to assess the overall accuracy of the three principle theories of policy innovation adoption: diffusion, internal determinants, and unified theory, which are variations of the fundamental diffusion theory, in predicting the deployment of wireless E9-1-1 by Virginia units of local government. This assessment was conducted by identifying Virginia specific variables from models associated with these policy innovation theories to determine the best performing model for the deployment of Wireless E9-1-1 throughout the Commonwealth of Virginia. The Virginia specific variables utilized in this study are: Wealth, Population, Fiscal Health, Dedicated Funding, Financial Dependency, Urbanization, Regionalism, and Proximity to Interstate. Dedicated Funding and Regionalism had the largest absolute size of correlation among the predictor variables for the deployment of Wireless E9-1-1 Phase One and Wireless E9-1-1 Phase Two, thus generating the best performing model. This information will provide the basis from which to develop a statewide comprehensive policy and plan for Next Generation 9-1-1 and will help provide an answer to the question of when and how governments get involved in designing and implementing a 9-1-1 emergency service network

Um sistema de recomendação baseado no conceito de internet das coisas

TCC(graduação) - Universidade Federal de Santa Catarina, Campus Araranguá, Tecnologias da Informação e Comunicação.Atualmente as tecnologias de redes sem fio proporcionam ao cenário da Internet das Coisas um ambiente favorável em que usuários, além de consumirem informações, também são os principais responsáveis para a geração de novos conteúdos, uma vez que com a utilização de sensores inteligentes estas interações ocorrem de maneira despercebida. Desta forma, os avanços da tecnologia de sensores sem fio têm provocado um aumento acelerado no volume de informações disponíveis e a consolidação do conceito de Computação Ubíqua. A partir disto, este trabalho reside na proposição de um sistema de recomendação utilizando - se da tecnologia de sensores sem fio para identificar possíveis interesses de usuários por itens em ambientes físicos, através das abordagens de filtragem colaborativa e baseada em conteúdo. Para permitir a avaliação da proposta deste trabalho foi desenvolvido um protótipo, onde o mesmo é aplicado em alguns cenários de uso viabilizando a coleta de dados de modo que estes dados possam ser utilizados em um processo de recomendação. Através da avaliação das informações processadas e geradas com a utilização do protótipo elaborado para este trabalho é possível sugerir itens de interesse aos usuários. Por fim, pode - se concluir que os resultados obtidos no cenário de identificação de interesse dos usuários são consistentes e permitem prover importantes subsídios para guiar usuários em suas escolhas futuras.Nowadays wireless technologies provide to the Internet of Things a favorable environment in which users, in addition to consuming information, are also the main responsible for the generation of new content, since the use of intelligent sensors make such interactions more natural. In this way, advances in wireless sensor technology have accelerated the volume of information available, as well as, the consolidation of the concept of Ubiquitous Computing. From this, this work lies in the proposition of a recommendation system using wireless sensor technology to identify possible user interests for items in physical environments through collaborative filtering and content - based approaches. In order to allow the evaluation of the current work we developed a prototype and applied it in some scenarios of use, making data collection possible aiming to use it in a recommendation process. Through the evaluation of the processed and generated information with the use of the prototype developed in this work, it is possible to suggest items according users interest. Finally, it can be concluded that the results obtained in the scenario of the identification of interest from users are consistent and allow to provide important subsidies to guide users in their future choices

Designs for the Quality of Service Support in Low-Energy Wireless Sensor Network Protocols

A Wireless Sensor Network (WSN) consists of small, low cost, and low energy sensor nodes that cooperatively monitor physical quantities, control actuators, and perform data processing tasks. A network may consist of thousands of randomly deployed self-configurable nodes that operate autonomously to form a multihop topology. This Thesis focuses on Quality of Service (QoS) in low-energy WSNs that aim at several years operation time with small batteries. As a WSN may include both critical and non-critical control and monitoring applications, QoS is needed to make intelligent, content specific trade-offs between energy and network performance. The main research problem is defining and implementing QoS with constrained energy budget, processing power, communication bandwidth, and data and program memories. The problem is approached via protocol designs and algorithms. These are verified with simulations and with measurements in practical deployments. This Thesis defines QoS for WSNs with quantifiable metrics to allow measuring and managing the network performance. The definition is used as a basis for QoS routing protocol and Medium Access Control (MAC) schemes, comprising dynamic capacity allocation algorithm and QoS support layer. Dynamic capacity allocation is targeted at reservation based MACs, whereas the QoS support layer operates on contention based MACs. Instead of optimizing the protocols for a certain use case, the protocols allow configurable QoS based on application specific requirements. Finally, this Thesis designs sensor self-diagnostics and diagnostics analysis tool for verifying network performance. Compared to the related proposals on in-network sensor diagnostics, the diagnostics also detects performance problems and identifies reasons for the issues thus allowing the correction of problems. The results show that the developed protocols allow a clear trade-off between energy, latency, throughput, and reliability aspects of QoS while incurring a minimal overhead. The feasibility of results for extremely resource constrained WSNs is verified with the practical implementation with a prototype hardware platform having only few Million Instructions Per Second (MIPS) of processing power and less than a hundred kBs data and program memories. The results of this Thesis can be used in the WSN research, development, and implementation in general. The developed QoS definition, protocols, and diagnostics tools can be used separately or adapted to other applications and protocols

Energy-Efficient Wireless Network Interface Selection for Mobile Devices

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2014. 2. 조유근.최근 무선 통신 기술과 모바일 컴퓨팅 환경의 발전으로 스마트 폰이나 스마트 패드 와 같이 Wi-Fi, 3G, LTE 네트워크 등을 동시에 지원하는 모바일 장치들이 다양한 분야에 널리 사용되고 있다. 대부분의 모바일 장치들은 제한된 배터리 용량을 갖고 있어 에너지의 효율성은 매우 중요한 요소이다. Wi-Fi, 3G, LTE와 같은 무선 통신 기법은 네트워크 서비스 범위, 통신 속도, 에너지 소모량과 같은 측면에서 매우 다른 특성을 보인다. 따라서 각 네트워크의 특성을 이용하여 모바일 장치의 에너지 및 데이터 전송 효율성을 증대시킬 수 있다. 본 논문에서는 3G와 Wi-Fi 네트워크 인터페이스를 가지는 모바일 장치를 가정 하여 네트워크 탐지 및 선택 주기에 따른 모바일 장치의 에너지 소모량과 데이터 전송 소요 시간을 모델링한다. 제안한 에너지 소모량 모델의 분석을 통해 에너지 소모량을 최소화할 수 있는 네트워크 탐지 및 선택 주기가 존재함을 보인다. 최적의 네트워크 탐지 및 선택 주기는 데이터 전송 요청량이나 Wi-Fi 네트워크의 가용성과 같은 다양한 네트워크 환경 요소에 따라 달라진다. 이를 기반으로 네트워크 탐지 및 선택 주기를 동적으로 조절할 수 있는 에너지 효율적인 네트워크 인터페이스 선택 기법(AWNIS, Adaptive Wireless Network Interface Selection)을 제안한다. 제안 기법은 제안한 에너지 소모 모델을 기반으로 Wi-Fi 네트워크 가용성을 근사화하여 에너지 및 데이터 전송 효율 측면에서 뛰어난 Wi-Fi 네트워크를 사용하기 위한 탐지 및 선택 주기를 동적으로 조절한다. 이를 통해 모바일 장치의 에너지 소모량과 데이터 전송 효율성을 높일 수 있다. 성능 비교 및 분석을 통해 제안 기법이 일정 수준의 데이터 전송 지연 시간을 보장하면서 모바일 장치의 에너지 소모를 감소시킬 수 있음을 보인다. 제안 기법은 3G와 Wi-Fi 네트워크의 특성과 유사한 앞으로 개발되거나 사용이 가능한 근거리와 원거리 네트워크 인터페이스를 동시에 가지는 모바일 장치의 네트워크 인터페이스 선택 기법에 적용이 가능하다.Mobile devices such as smart-phones and smart-pads are widely used not only in our everyday lives but also in various industrial fields by the development of wireless network and mobile computing technologies. Energy efficiency is very important for mobile devices because most of these mobile devices operate on limited battery power. Wireless network technologies such as Wi-Fi, 3G, and LTE have fairly different characteristics in terms of its energy consumption, service area, data transfer rate, and other factors. Efficiencies in terms of energy consumption and data transfer can be improved by leveraging the characteristics of the wireless network technologies. In this dissertation, we assume a mobile device that is equipped with 3G and Wi-Fi network interfaces. We model an energy consumption and data transfer time of the mobile device due to changes in network detection and selection interval. Based on analysis results of the proposed models, we show the existence of the optimal network detection and selection interval which minimizes the energy consumption. The optimal network detection and selection interval changes according to the network environment such as the amount of requested data or availability of Wi-Fi. Based on the above observations, we propose an energy-efficient adaptive wireless network interface-selection scheme, termed AWNIS that can adjust the detection and selection interval dynamically. AWNIS uses a dynamic network selection and detection interval in order to use Wi-Fi network that is more efficient than 3G network in terms of energy consumption and data transfer. When selecting the interval, AWNIS chooses the interval based on the proposed energy consumption model and approximated availability of Wi-Fi network. In this manner, AWNIS improves the energy and data transfer efficiencies of mobile devices. Based on the simulation results, we show that the proposed scheme effectively improves the energy efficiency while guaranteeing a certain level of data transfer delay. Proposed AWNIS also can be applied to mobile devices equipped with future short and long range network interfaces which have similar characteristics compared to 3G and Wi-Fi network interfaces.초 록 i 목 차 ii 표 목 차 v 그 림 목 차 vi 제 1 장 서론 1 1.1 연구 배경 1 1.2 연구 목적 및 범위 3 1.3 연구 성과 요약 4 1.4 논문의 구성 4 제 2 장 관련 연구 6 2.1 TailEnder 6 2.2 CoolSpots 8 2.3 Context-For-Wireless 9 2.4 SALSA 11 2.5 기타 기법 12 제 3 장 에너지 효율적인 무선 네트워크 인터페이스 선택 기법 (AWNIS) 13 3.1 무선 네트워크 인터페이스 선택 주기에 따른 비용 모델링 13 3.1.1 가정 사항 13 3.1.2 3G와 Wi-Fi를 이용한 데이터 전송 14 3.1.3 에너지 소모량 모델링 20 3.1.4 데이터 전송 소요 시간 모델링 25 3.2 무선 네트워크 인터페이스 선택 주기에 따른 비용 분석 29 3.2.1 에너지 소모량 분석 32 3.2.2 데이터 전송 지연 시간 분석 36 3.3 에너지 효율적인 무선 네트워크 인터페이스 선택 알고리즘 38 3.3.1 무선 네트워크 인터페이스 선택 및 탐지 단계 40 3.3.2 3G에서 Wi-Fi로의 네트워크 연결 전환 단계 41 3.3.3 Wi-Fi에서 3G로의 네트워크 연결 전환 단계 42 3.3.4 AWNIS 의 동작의 예 43 3.4 에너지 효율적인 무선 네트워크 인터페이스 선택 알고리즘 분석 44 3.4.1 에너지 소모량 측면 분석 44 3.4.2 데이터 전송 지연 시간 측면 분석 45 제 4 장 성능 분석 및 비교 48 4.1 시뮬레이션 환경 48 4.2 성능 분석 및 비교에 사용된 네트워크 선택 기법 50 4.2.1 AWNIS 의 적용이 가능한 네트워크 선택 기법 51 4.2.2 최적의 네트워크 선택 기법 53 4.2.3 비교 가능한 기존의 네트워크 선택 기법 54 4.3 시뮬레이션 결과 및 분석 54 4.3.1 α에 따른 에너지 소모량 및 데이터 전송 지연 분석 54 4.3.2 합성 워크로드 (Synthetic Workloads)를 이용한 성능 분석 57 4.3.3 현실적인 워크로드 (Realistic Workloads) 를 이용한 성능 분석 63 4.4 AWNIS 알고리즘 개선 및 성능 분석 67 4.4.1 개선된 AWNIS 알고리즘 67 4.4.2 개선된 AWNIS의 성능 분석을 위한 시뮬레이션 환경 71 4.4.3 개선된 AWNIS의 성능 분석 및 비교 71 제 5 장 결론 및 향후 연구 77 5.1 결론 77 5.2 향후 연구 78 참 고 문 헌 80 Abstract 86Docto

Educating the Net Generation

Edited by Diana G. Oblinger and James L. Oblinger. Includes a chapter by former College at Brockport faculty member Joan K. Lippincott: Net generation students and libraries. The Net Generation has grown up with information technology. The aptitudes, attitudes, expectations, and learning styles of Net Gen students reflect the environment in which they were raised—one that is decidedly different from that which existed when faculty and administrators were growing up. This collection explores the Net Gen and the implications for institutions in areas such as teaching, service, learning space design, faculty development, and curriculum. Contributions by educators and students are included.https://digitalcommons.brockport.edu/bookshelf/1278/thumbnail.jp