Jigsaw

Abstract

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.

From MAP to DIST: The Evolution of a Large-Scale WLAN Monitoring System

“…We address each group in turn. Table 1 compares the scale of MAP and Jigsaw [10] to DIST. It can be seen that DIST's scale is much larger than that of either MAP or Jigsaw.…”

“…Table 2 provides a detailed comparison between Saluki and other well-known passive network sniffing programs, such as tcpdump [21], wireshark [22], Kismet [23], dingo [6], and Jigdump [10]. In this table, only Saluki provides the complete feature set to address DIST's efficiency, scalability, and security challenges.…”

“…In the event of an ongoing network attack, the higher fidelity stream of frames may allow MAP to confirm the attack or locate the attacker. We refer interested readers to our previous work [6] for more thorough information about MAP and its comparison to Jigsaw [10], DAIR [11], DOMINO [16], and Wit [17].…”

“…have been collected in conference events, a building floor and even a whole building; several distributed WLAN monitoring systems, such as DAIR [11], Jigsaw [10], MAP [6], and AirLab [12] have been successfully built and used for WLAN security and management research.…”

Mobile Autonomous Router System for Dynamic (Re)formation of Wireless Relay Networks

“…There have been numerous link-quality measurement studies and techniques in wireless mesh networks, large-scale WLANs, and wireless sensor networks [18], [19], [20], [21], [22]. Their insights and solutions, however, focus on stationary networks where the physical space of measurements is fixed.…”