Browsing by Author "Yeo, Jihwang"
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Item Capacity and Variability Analysis of the IEEE 802.11 MAC Protocol(2004-04-19) Yeo, Jihwang; Agrawala, Ashok{\em Packet error} in the IEEE 802.11 network %which is due to non-ideal channel condition and wireless device variability, is one source of performance degradation and its variability. %Therefore the effect of packet errors, along with {\em collision %avoidance} and {\em hidden terminals}, is among the most important %considerations in performance anaylsis of the 802.11 MAC protocol. Most of the previous works study how {\em collision avoidance} and {\em hidden terminals} affect 802.11 performance metrics, such as probability of a collision and saturation throughput. In this paper we focus on the effect of packet errors on capacity and variability of the 802.11 MAC protocol. We develope a new analytical model, called $p_e$-Model, by extending the existing model (Tay and Chua's model) to incorporate {\em packet error probability} $p_e$. With $p_e$-Model, we successfully analyze capacity and variability of the 802.11 MAC protocol. The variability analysis shows that increasing packet error probability by $\Delta p_e$ has more effect on saturation throughput, than adding $0.5 W \Delta p_e$ stations, where $W$ is the minimum contention window size, We also show the numerical validation of $p_e$-Model with 802.11 MAC-level simulator. (UMIACS-TR-2003-45)Item Characterizing the IEEE 802.11 Traffic: The Wireless Side(2004-04-19) Yeo, Jihwang; Youssef, Moustafa; Agrawala, AshokMany studies on measurement and characterization of wireless LANs have been performed recently. Most of these measurements have been conducted from the wired portion of the network based on wired monitoring or SNMP statistics. In this paper we argue that traffic measurements from a wireless vantage point in the network are more appropriate than wired measurements or SNMP statistics, to expose the wireless medium characteristics and their impact on the traffic patterns. While it is easier to make consistent measurements in the wired part of a network, such measurements can not observe the significant vagaries present in the wireless medium itself. As a consequence constructing an accurate measurement system from a wireless vantage point is important but usually quite difficult due to the noisy wireless channel. In our work we have explored the various issues in implementing such a system to monitor traffic in an IEEE 802.11 based wireless network. We show the effectiveness of the wireless monitoring by quantitatively comparing it with SNMP and measurements at wired vantage points. We also show the analysis of a typical computer science department network traffic using the wireless monitoring technique. Our analysis reveals rich information about the PHY/MAC layers of the IEEE 802.11 protocol such as the typical traffic mix of different frame types, their temporal characteristics, correlation with the user activities and the error characteristics of the wireless medium. Moreover, we identify anomalies in the operation of the IEEE 802.11 MAC protocol. Our results show excessive retransmissions of some management frame types reducing the useful throughput of the wireless network. We also find that some features of the protocol, which were designed to reduce the retransmission errors, are not used. In addition, most of the clients fail to adapt the data rate according to the signal condition between them and the access point, which further reduce the useful throughput. (UMIACS-TR-2004-15)Item Measuring Traffic on the Wireless Medium: Experience and Pitfalls(2003-01-21) Yeo, Jihwang; Banerjee, Suman; Agrawala, AshokA number of measurement studies have examined traffic characteristics in wireless networks. Most of these measurements have been conducted from the wired portion of the network. In this paper we argue that such measurements are not sufficient to expose either the characteristics of the wireless medium or how such characteristics impact traffic patterns. While it is easier to make consistent measurements in the wired part of a network, such measurements can not observe the significant vagaries present in the wireless medium itself. As a consequence constructing an efficient and accurate measurement system from a wireless vantage point is important but usually quite difficult. In our work we have explored the various issues in implementing such a system to monitor traffic in an 802.11 based wireless network. We identify different challenges in making such measurements and provide detailed experimental evidence in their supports. Our work shows that the wireless measurement allows us to infer much richer information about the medium characteristics than is possible with a measurements made on the wired part of the network. We apply our measurement technique to study the end-to-end wireless network delay. We show that wireless monitoring can effectively identify the causes of end-to-end delays. (UMIACS-TR-2002-101)Item Multiscale Analysis for Wireless LAN Traffic Characterization(2004-04-19) Yeo, Jihwang; Agrawala, AshokIn this survey paper, we overview the various network traffic models, especially focusing on the multiscale analysis. By multiscale analysis we mean wavelet-based self-similar and multifractal analysis. Multiscale analysis is advantageous in that it can reveal the scaling behavior of the traffic on large time scale, at the same time characterize small-scale irregularity. We also discuss how we can apply this analysis technique to wireless LAN traffic characterization. (UMIACS-TR-2004-16)Item WLAN Workload Characterization(2005-08-25) Yeo, Jihwang; Agrawala, Ashok K; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In this dissertation, we address the problem of workload characterization in a wireless LAN (WLAN). Workload is generated by applications and users trying to carry out some of their functions. We attempt to capture such application- and user-level characteristics from the information gathered at the MAC level. Developing an understandable description of the workload requires making some abstractions at the application- and user-level. Our approach is to consider the workload in terms of ``sessions", where a session is an application- and user-level sequence of exchanges. We attempt to capture the session by considering an inactive duration in the activities between a wireless end-point and the network. We consider workload to consist of a population of sessions for which a probability distribution function can be defined. Considering this distribution function to be a mixture distribution, we attempt to find the components by using non-parametric clustering technique. As the number of types of user level activities is not likely to be very large, we expect that we can associate a distinct activity with each such component. In this work, we identify such components and analyze the traffic and protocol characteristics of each component. Moreover, we empirically show that the identified workload components can effectively represent the actual WLAN workload and its daily variations.