Channel-Specific Wireless Sensor Network Path Data Lance Doherty, William Lindsay, Jonathan Simon Dust Networks Hayward, CA, USA {ldoherty, blindsay, jsimon}@dustnetworks.com Abstract—Channel-specific path data for a 44-node 2.4 GHz wireless sensor network deployed in an industrial setting is presented. Each node generates one data packet every 28 seconds with the number of transmissions, received acknowledgements, average RSSI, and other metrics for a path to a single neighbor on a single channel for every 15 minutes of operation. Twenty-six days of data were recorded, revealing the scale of time-variation of stability throughout the network and how this is a frequency-dependent quantity. Particularly on low-power paths, both RSSI and stability are observed to vary in unpredictable ways that differ from other paths in the same spatial vicinity. A time-varying model is proposed for simulation of networks in low-noise environments. Channel hopping and path diversity succeed in maintaining near-perfect reliability at a delivered rate of 1.0 kb/s despite this time- and frequency-variance. I. INTRODUCTION Wireless sensor networks operating indoors face RF propagation challenges that lead to time-varying signal and interference strength at the receiver. These effects are difficult to predict during the provisioning stage of a network, and in the field of wireless sensor networks, signal strength effects have been studied mainly with the objective of localization [1]. Multi-path effects in particular pose problems as they can have different impacts on different communication channels and can change as humans and machinery alter the RF environment. An example of the severity of multi-path effects in the 900 MHz band over the size scales of interest is presented in [2]. While predictive strategies for determining the number and location of nodes in a network exist, the actual measured performance of a well-planned network can vary significantly from what is predicted in these models. A deployment in an industrial environment [3] was measured to assess the channel characteristics of a small number of paths with the same radio hardware used here and it showed large variation in path stability. Protocols such as ZigBee [4] allow for star-connected single-channel networks to be formed which can result in data loss if this variation is sufficiently large. This paper details an experiment to measure the real time-varying effects on different channels in a monitoring sensor network carrying actual traffic. While behavior averaged over time and frequency channels is easier to monitor, a description of a time-varying model representative of the observed data is given. Simulating using this type of model can yield more realistic network performance estimates and identify the amount of resource over-provisioning required to ensure reliable functionality in the face of time-variance. II. TEST LOCATION Figure 1. An example of the multi-hop network topology. Arrows represent used paths and point towards the gateway in the middle of the figure. The test network was deployed in a printing factory in Berkeley, California, and data was collected over 26 days. The building has a rectangular footprint, measuring 250 feet x 225 feet and is three stories tall. The factory is divided into three distinct areas with different propagation obstacles. The south third contains numerous small job printing cells that process pamphlets, voting ballots, handouts and small catalogs. The central third houses the lithography and digital media center on the ground floor, with two floors of general office space above. The north third houses one large printing machine that takes 5-ton paper rolls in at one end, and pushes completed technical manuals out the other end. Also in this bay are the air-handling motors for the entire facility. There are many obstacles in the work area that could impede RF communication and cause multi-path reflections, but there are no major sources of interference. The network manager is located on the top floor of the office section. 44 radio nodes were deployed throughout the facility, in the manufacturing areas near and around various printing machines, throughout the lithography areas, and in the office areas, in a relatively uniform distribution. The nodes report to the network manager all neighbors within RF range, and from those potential connections the network manager attempts to make the healthiest possible network. Many of these potential paths go unused until they are needed to repair failures. The least connected nodes reported only 4 potential neighbors, while the most connected node reported 26 potential 1-4244-1251-X/07/$25.00 ©2007 IEEE. 89neighbors. The farthest nodes in the resulting self-assembled mesh network had a minimum depth of 3 hops. The average hop depth of all packets for all nodes was 2.48 hops per packet. A snapshot of the connectivity of the network showing only the used paths is given in Figure 1. This topology varied with time. All nodes in the network use the same hardware and software and perform both data generation and routing functions. Nodes use the TI Chipcon CC2420 [5] radio with a power amplifier to increase output power. Output is nominal 15 dBm EIRP and shows device-to-device variation from +12 to +17 dBm at 25 °C. III. NETWORK PROTOCOLS The network deployed was architected to provide high-reliability collection of periodic data from all the sensor nodes and follows link provisioning rules similar to those presented in [6]. The network is many-to-one: all multi-hop data is collected at a gateway node which relays the packets to the network manager and then to the user. The network operates using the Dust Networks Time-Synchronized Mesh Protocol (TSMP, [7]). The centrally-computed TSMP schedule dictates which of the 16 available channels as defined in the 802.15.4 PHY layer specification [8] (starting at 2.40 GHz and with 5 MHz spacing) should be used for each transaction. During a transmit slot, the transmitting node first performs Clear Channel Assessment (CCA) on the specified channel, and if it passes, transmits the packet to the waiting receiver. TSMP does not schedule colliding transmissions so CCA is used solely to avoid interference from outside the network. If the CRC of the packet passes at the receiver, it immediately sends an acknowledgement to the original transmitter on the same channel within the same 31.25 ms time slot.