Wireless Local Area Networks (WLANs) are now commonplace on many academic and corporate campuses. As "Wi-Fi" technology becomes ubiquitous, it is increasingly important to understand trends in the usage of these networks.

The combination of unlicensed spectrum, cheap wireless interfaces and the inherent convenience of untethered computing have made 802.11-based networks ubiquitous in the enterprise. Modern universities, corporate campuses and government offices routinely deploy scores of access points to blanket their sites with wireless Internet access. However, while the fine-grained behavior of the 802.11 protocol itself has been well studied, our understanding of how large 802.11 networks behave in their full empirical complexity is surprisingly limited. In this paper, we present a system called Jigsaw that uses multiple monitors to provide a single unified view of all physical, link, network and transport-layer activity on an 802.11 network. To drive this analysis, we have deployed an infrastructure of over 150 radio monitors that simultaneously capture all 802.11b and 802.11g activity in a large university building (1M+ cubic feet). We describe the challenges posed by both the scale and ambiguity inherent in such an architecture, and explain the algorithms and inference techniques we developed to address them. Finally, using a 24-hour distributed trace containing more than 1.5 billion events, we use Jigsaw’s global cross-layer viewpoint to isolate performance artifacts, both explicit, such as management inefficiencies, and implicit, such as co-channel interference. We believe this is the first analysis combining this scale and level of detail for a production 802.11 network.

In this paper, we analyze the mobility patterns of users of wireless handheld PDAs in a campus wireless network using an 11 week trace of wireless network activity. Our study has three goals. First, we characterize the high-level mobility and access patterns of handheld PDA users and compare these characteristics to previous workload mobility studies focused on laptop users. Second, we develop two wireless network topology models for use in wireless mobility studies: an evolutionary topology model based on user proximity and a campus waypoint model that serves as a trace-based complement to the random waypoint model. Finally, we use our wireless network topology models as a case study to evaluate ad-hoc routing algorithms on the network topologies created by the access and mobility patterns of users of modern wireless PDAs.

We present Wit, a non-intrusive tool that builds on passive monitoring to analyze the detailed MAC-level behavior of operational wireless networks. Wit uses three processing steps to construct an enhanced trace of system activity. First, a robust merging procedure combines the necessarily incomplete views from multiple, independent monitors into a single, more complete trace of wireless activity. Next, a novel inference engine based on formal language methods reconstructs packets that were not captured by any monitor and determines whether each packet was received by its destination. Finally, Wit derives network performance measures from this enhanced trace; we show how to estimate the number of stations competing for the medium. We assess Wit with a mix of real traces and simulation tests. We find that merging and inference both significantly enhance the originally captured trace. We apply Wit to multi-monitor traces from a live network to show how it facilitates 802.11 MAC analyses that would otherwise be difficult or rely on less accurate heuristics.

Abstract – We analyze wireless measurements taken during the SIGCOMM 2004 conference to understand how well 802.11 operates in real deployments. We find that the overhead of 802.11 is high, with only 40 % of the transmission time spent in sending original data. Most of the remaining time is consumed by retransmissions due to packet losses that are caused by both contention and transmission errors. Our analysis also shows that wireless nodes adapt their transmission rates with an extremely high frequency. We comment on the difficulties and opportunities of working with wireless traces, rather than the wired traces of wireless activity that are presently more common. Categories and Subject Descriptors:

Many studies on measurement and characterization of wireless LANs (WLANs) have been performed recently. Most of these measurements have been conducted from the wired portion of the network based on wired monitoring (e.g. sniffer at some wired point) or SNMP statistics. More recently, wireless monitoring, the traffic measurement from a wireless vantage point, is also widely adopted in both wireless research and commercial WLAN management product development. Wireless monitoring technique can provide detailed PHY/MAC information on wireless medium. For the network diagnosis purpose (e.g. anomaly detection and security monitoring) such detailed wireless information is more useful than the information provided by SNMP or wired monitoring. In this paper we have explored various issues in implementing the wireless monitoring system for an IEEE 802.11 based wireless network. We identify the pitfalls that such system needs to be aware of,

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The growing popularity of wireless networks has led to cases of heavy utilization and congestion. In heavily utilized wireless networks, the wireless portion of the network is a major performance bottleneck. Understanding the behavior of the wireless portion of such networks is critical to ensure their robust operation. This understanding can also help optimize network performance. In this paper, we use link layer information collected from an operational, large-scale, and heavily utilized IEEE 802.11b wireless network deployed at the 62 nd Internet Engineering Task Force (IETF) meeting to study congestion in wireless networks. We motivate the use of channel busy-time as a direct measure of channel utilization and show how channel utilization along with network throughput and goodput can be used to define highly congested, moderately congested, and uncongested network states. Our study correlates network congestion and its effect on link-layer performance. Based on these correlations we find that (1) current rate adaptation implementations make scarce use of the 2 Mbps and 5.5 Mbps data rates, (2) the use of Request-to-Send/Clear-to-Send (RTS–CTS) prevents nodes from gaining fair access to a heavily congested channel, and (3) the use of rate adaptation, as a response to congestion, is detrimental to network performance. 1

The growing deployment and concomitant rise in wireless network usage necessitates the comprehensive understanding of its behavior. More importantly, as networks grow in size and number of users, congestion in the wireless portion of the network is likely to increase. We believe there is a strong need to understand the intricacies of the wireless portion of a congested network by interpreting information collected from the network. Congestion in a wireless network can be best analyzed by studying the transmission of frames at the link layer. To this end, we use vicinity sniffing techniques to analyze the link layer in an operational IEEE 802.11b wireless network. In this paper, we discuss how congestion in a network can be estimated using point-to-point link reliability. We then show how link reliability is correlated with the behavior of link-layer properties such as frame retransmissions, frame sizes, and data rates. Based on the results from these correlations, our hypothesis is that the performance of the link layer in congested networks can be improved by (1) sending smaller frames, and/or (2) using higher data rates with a fewer number of frames sent.

Abstract—Wireless LAN administrators often have to deal with the problem of sporadic client congestion in popular locations within the network. Existing approaches that relieve congestion by balancing the traffic load are encumbered by the modifications that are required to both access points and clients. We propose Cell Breathing, a well-known concept in cellular telephony, as a load balancing mechanism to handle client congestion in a wireless LAN. We develop power management algorithms for controlling the coverage of access points to handle dynamic changes in client workloads. We further incorporate hand-off costs and manufacturer specified power level constraints into our algorithms. Our approach does not require modification to clients or to the standard. It only changes the transmission power of beacon packets and does not change the transmission power of data packets to avoid the interactions with autorating. We analyze the worst-case bounds of the algorithms and show that they are either optimal or close to optimal. In addition, we evaluate our algorithms empirically using synthetic and real wireless LAN traces. Our results show that cell breathing significantly outperforms the commonly used fixed power scheme and performs at par with sophisticated load balancing schemes that require changes to both the client and access points. Index Terms—Wireless LAN, power control, cell breathing, algorithms. 1