Análise de utilização de WLANs universitárias

A recente aposta das universidades europeias nas redes locais sem fios - Wireless Local Area Networks (WLANs), como forma de disponibilizar à comunidade académica um serviço de mobilidade, trouxe inúmeras vantagens, mas é de extrema importância perceber até que ponto é que os seus utilizadores tiram proveito desta tecnologia e qual é o seu comportamento. Neste trabalho foram analisadas as WLANs de dois campi universitários pertencentes às Universidades do Minho e de Vigo. O estudo realizado tem por objectivo identificar padrões de comportamento dos utilizadores e o grau de utilização dos recursos de rede, respondendo à questão: qual a utilização efectiva das WLANs em análise? Os resultados deste trabalho, aqui reportados para o caso da Universidade do Minho, demonstram que o local de acesso tem influência no número de utilizadores associados, no volume de tráfego gerado, no número e duração das sessões, fornecendo importantes indicadores para o planeamento, dimensionamento e investimento nas WLANs universitárias

Hybrid LAN Monitoring and Controlling

Hybrid LAN Monitoring and Controlling is based on the client-server technology which is computer architecture. Client-server technology separates the applications functions into two or more distinct parts. This technology divides function into client and server subsystems for standard communication. Network clients make request to a server by sending messages and server respond to their clients by acting on each request and producing results. With this application each time that you open a file from Windows Explorer or from a standard open/save dialog box, the name of the file that you opened is recorded by the operating system. This utility save name of file into Recent folder and also in Registry

Characterising University WLANs within Eduroam Context

The eduroam initiative is assuming an ever growing relevance in providing a secure, worldwide roaming access within the university WLAN context. Although several studies have focused on educational WLAN traffic characterisation, the increasing variety of devices, mobility scenarios and user applications, motivate assessing the effective use of eduroam in order to sustain consistent network planning and deployment. Based on recent WLAN traffic traces collected at the University of Minho (Portugal) and University of Vigo (Spain), the present work contributes for identifying and characterising patterns of user behaviour regarding, for instance, the location and activity sector of users. The results of data analysis quantify the impact of network access location on the number of associated users, on the number and duration of sessions and corresponding traffic volumes. The results also illustrate to what extent users take advantage of mobility in the WLAN. Complementing the analysis on a monthly basis, a fine grain study of WLAN traffic is provided through the identification of users' behaviour and patterns in small timescales

Groups and frequent visitors shaping the space dynamics

Our research is about a dynamic symbolic space model that is fed with data from the environment by a set of processing modules that receive raw data from sensor networks. For the conducted experiments we have been using data from a WiFi network as it is a widely available infrastructure in our campus. Here we propose two processing modules which will provide more information about the spaces described in the model. The first one tries to implement our human perception of the usual visitors of a place using two measures, the long term and the short term tenant level. The second one detects where groups of users emerge, how many there are and what are their dimensions. Based on this new perspective of the campus we intend to realize how the presence of people shapes the dynamics of a space.Fundação para a Ciência e a Tecnologia (FCT

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

Mining Frequent and Periodic Association Patterns

Profiling the clients\u27 movement behaviors is useful for mobility modeling, anomaly detection, and location prediction. In this paper, we study clients\u27 frequent and periodic movement patterns in a campus wireless network. We use offline data-mining algorithms to discover patterns from clients\u27 association history, and analyze the reported patterns using statistical methods. Many of our results reflect the common characteristics of a typical academic campus, though we also observed some unusual association patterns. There are two challenges: one is to remove noise from data for efficient pattern discovery, and the other is to interpret discovered patterns. We address the first challenge using a heuristic-based approach applying domain knowledge. The second issue is harder to address because we do not have the knowledge of people\u27s activities, but nonetheless we could make reasonable interpretation of the common patterns

Airtime usage control in virtualized multi-cell 802.11 networks

This paper investigates the station (STA)-access point (AP) association and airtime control for virtualized 802.11 networks to provide service customization and fairness across multiple Internet service-providers (ISPs) sharing the common physical infrastructure and network capacity. More specifically, an optimization problem is formulated on the STAs' transmission probabilities to maximize the overall network throughput, while providing airtime usage guarantees for the ISPs. Subsequently, an algorithm to reach the optimal solution is developed by applying monomial approximation and geometric programming iteratively. Illustrative results confirm the superior and robust performance of the developed association and airtime control scheme in terms of both throughput and fairness

AP-STA association control for throughput maximization in virtualized WiFi networks

To manage and enable service customization among multiple internet service providers (ISPs) sharing the common physical infrastructure and network capacity in virtualized Wi-Fi networks, this paper models and optimizes access point-station (STA) association via airtime usage control. More specifically, an optimization problem is formulated on the STAs’ transmission probabilities to maximize the overall network throughput, while providing airtime usage guarantees for the ISPs. As the proposed optimization problem is inherently non-convex, an algorithm to reach the optimal solution is developed by applying monomial approximation and geometric programming iteratively. Based on the proposed 3-D Markov-chain model of the enhanced distributed channel access protocol, the detailed implementation of the optimal transmission probability of each STA is also discussed by manipulating medium access control parameters. The performance of the developed association and airtime control scheme is evaluated through numerical results. For both homogeneous and non-homogeneous STA distributions, numerical results reveal performance gains of the proposed algorithm in improving the throughput and keeping airtime usage guarantees

Analysing the characteristics of VoIP traffic

In this study, the characteristics of VoIP traffic in a deployed Cisco VoIP phone system and a SIP based soft phone system are analysed. Traffic was captured in a soft phone system, through which elementary understanding about a VoIP system was obtained and experimental setup was validated. An advanced experiment was performed in a deployed Cisco VoIP system in the department of Computer Science at the University of Saskatchewan. Three months of traffic trace was collected beginning October 2006, recording address and protocol information for every packet sent and received on the Cisco VoIP network. The trace was analysed to find out the features of Cisco VoIP system and the findings were presented.This work appears to be one of the first real deployment studies of VoIP that does not rely on artificial traffic. The experimental data provided in this study is useful for design and modeling of such systems, from which more useful predictive models can be generated. The analysis method used in this research can be used for developing synthetic workload models. A clear understanding of usage patterns in a real VoIP network is important for network deployment and potential network activities such as integration, optimizations or expansion. The major factors affecting VoIP quality such as delay, jitter and loss were also measured and simulated in this study, which will be helpful in an advanced VoIP quality study. A traffic generator was developed to generate various simulated VoIP traffic. The data used to provide the traffic model parameters was chosen from peak traffic periods in the captured data from University of Saskatchewan deployment. By utilizing the Traffic Trace function in ns2, the simulated VoIP traffic was fed into ns2, and delay, jitter and packet loss were calculated for different scenarios. Two simulation experiments were performed. The first experiment simulated the traffic of multiple calls running on a backbone link. The second experiment simulated a real network environment with different traffic load patterns. It is significant for network expansion and integration

Measurement and analysis of real-world 802.11 mesh networks

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Includes bibliographical references (p. 63-65).Despite many years of work in wireless mesh networks built using 802.11 radios, the performance and behavior of these networks in the wild is not well understood. This is primarily due to a lack of access to data from a wide range of these networks; most researchers have access to only one or two testbeds at any time. In recent years, however, these networks have been deployed commercially and have real users who use the networks in a wide range of conditions. This thesis analyzes data collected from 1407 access points in 110 different commercially deployed Meraki wireless mesh networks, constituting perhaps the largest study of real-world 802.11 mesh networks to date. After analyzing a 24-hour snapshot of data collected from these networks, we answer questions from a variety of active research topics, including the accuracy of SNR-based bit rate adaptation, the impact of opportunistic routing, and the prevalence of hidden terminals. The size and diversity of our data set allow us to analyze claims previously only made in small-scale studies. In particular, we find that the SNR of a link is a good indicator of the optimal bit rate for that link, but that one could not make an SNR-to-bit-rate look-up table that was accurate for an entire network. We also find that an ideal opportunistic routing protocol provides little to no benefit on most paths, and that "hidden triples"-network topologies that can lead to hidden terminals-are more common than suggested in previous work, and increase in proportion as the bit rate increases.by Katrina L. LaCurts.S.M