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Passive monitoring is an important tool for measuring, troubleshooting, and protecting modern wireless networks. To date, WiFi monitoring has focused primarily on indoor settings or ephemeral outdoor studies though wardriving. We present Argos, the first urban-scale wireless sensor network designed explicitly to support measurement of ambient WiFi traffic across an entire city. Urban-scale wireless monitoring presents unique challenges due to limited packet-capture ability, heterogeneous traffic loads, and limited backhaul capacity between sensor nodes. Argos addresses these through in-network traffic merging and processing, plus an intelligent approach to coordinated channel sampling by multiple sniffers. Argos provides a rich query interface allowing users to study the complex dynamics of ambient wireless traffic. We present a detailed evaluation of a 26-node Argos network deployed on streetlights and rooftops around a city, demonstrating its ability to detect and classify wireless access points and clients; monitor Web page usage; detect malicious traffic; track the mobility of WiFi-equipped public transport vehicles; and fingerprint individual users through 802.11 probe request packets.

Desynchronization is a novel primitive for sensor networks: it implies that nodes perfectly interleave periodic events to occur in a round-robin schedule. This primitive can be used to evenly distribute sampling burden in a group of nodes, schedule sleep cycles, or organize a collision-free TDMA schedule for transmitting wireless messages. Here we present Desync, a biologically-inspired self-maintaining algorithm for desynchronization in a single-hop network. We present (1) theoretical results showing convergence, (2) experimental results on TinyOS-based Telos sensor motes, and (3) a Desync-based TDMA protocol. Desync-TDMA addresses two weaknesses of traditional TDMA: it does not require a global clock and it automatically adjusts to the number of participating nodes, so that bandwidth is always fully utilized. Experimental results show a reduction in message loss under high contention from approximately 58% to less than 1%, as well as a 25% increase in throughput over the default Telos MAC protocol.

Abstract. Desynchronization is a recently introduced primitive for sensor networks: it implies that nodes perfectly interleave periodic events to occur in a round-robin schedule. This primitive can be used to evenly distribute sampling burden in a group of nodes, schedule sleep cycles, or organize a collision-free TDMA schedule for transmitting wireless messages. Here we present a summary 1 of Desync, a biologically-inspired self-maintaining algorithm for desynchronization in a single-hop network. We also describe Desync-TDMA, a self-adjusting TDMA protocol that addresses two weaknesses of traditional TDMA: it does not require a global clock and it automatically adjusts to the number of participating nodes, so that bandwidth is always fully utilized.

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