Sumit Rangwala

A wireless sensor network For structural monitoring

Structural monitoring---the collection and analysis of structural response to ambient or forced excitation--is an important application of networked embedded sensing with significant commercial potential. The first generation of sensor networks for structural monitoring are likely to be data acquisition systems that collect data at a single node for centralized processing. In this paper, we discuss the design and evaluation of a wireless sensor network system (called Wisden for structural data acquisition. Wisden incorporates two novel mechanisms, reliable data transport using a hybrid of end-to-end and hop-by-hop recovery, and low-overhead data time-stamping that does not require global clock synchronization. We also study the applicability of wavelet-based compression techniques to overcome the bandwidth limitations imposed by low-power wireless radios. We describe our implementation of these mechanisms on the Mica-2 motes and evaluate the performance of our implementation. We also report experiences from deploying Wisden on a large structure.

Interference-aware fair rate control in wireless sensor networks

In a wireless sensor network of N nodes transmitting data to a single base station, possibly over multiple hops, what distributed mechanisms should be implemented in order to dynamically allocate fair and efficient transmission rates to each node? Our interferenceaware fair rate control (IFRC) detects incipient congestion at a node by monitoring the average queue length, communicates congestion state to exactly the set of potential interferers using a novel low-overhead congestion sharing mechanism, and converges to a fair and efficient rate using an AIMD control law. We evaluate IFRC extensively on a 40-node wireless sensor network testbed. IFRC achieves a fair and efficient rate allocation that is within 20-40% of the optimal fair rate allocation on some network topologies. Its rate adaptation mechanism is highly effective: we did not observe a single instance of queue overflow in our many experiments. Finally, IFRC can be extended easily to support situations where only a subset of the nodes transmit, where the network has multiple base stations, or where nodes are assigned different transmission weights.

Monitoring civil structures with a wireless sensor network

Structural health monitoring (SHM) is an active area of research devoted to systems that can autonomously and proactively assess the structural integrity of bridges, buildings, and aerospace vehicles. Recent technological advances promise the eventual ability to cover a large civil structure with low-cost wireless sensors that can continuously monitor a buildings structural health, but researchers face several obstacles to reaching this goal, including high data-rate, data-fidelity, and time-synchronization requirements. This article describes two systems the authors recently deployed in real-world structures.

Understanding congestion control in multi-hop wireless mesh networks

Complex interference in static multi-hop wireless mesh networks can adversely affect transport protocol performance. Since TCP does not explicitly account for this, starvation and unfairness can result from the use of TCP over such networks. In this paper, we explore mechanisms for achieving fair and efficient congestion control for multi-hop wireless mesh networks. First, we design an AIMD-based rate-control protocol called Wireless Control Protocol (WCP) which recognizes that wireless congestion is a neighborhood phenomenon, not a node-local one, and appropriately reacts to such congestion. Second, we design a distributed rate controller that estimates the available capacity within each neighborhood, and divides this capacity to contending flows, a scheme we call Wireless Control Protocol with Capacity estimation (WCPCap). Using analysis, simulations, and real deployments, we find that our designs yield rates that are both fair and efficient, and achieve near optimal goodputs for all the topologies that we study. WCP achieves this level of performance while being extremely easy to implement. Moreover, WCPCap achieves the max-min rates for our topologies, while still being distributed and amenable to real implementation.

Neighborhood-centric congestion control for multihop wireless mesh networks

Complex interference in static multihop wireless mesh networks can adversely affect transport protocol performance. Since TCP does not explicitly account for this, starvation and unfairness can result from the use of TCP over such networks. In this paper, we explore mechanisms for achieving fair and efficient congestion control for multihop wireless mesh networks. First, we design an AIMD-based rate-control protocol called Wireless Control Protocol (WCP), which recognizes that wireless congestion is a neighborhood phenomenon, not a node-local one, and appropriately reacts to such congestion. Second, we design a distributed rate controller that estimates the available capacity within each neighborhood and divides this capacity to contending flows, a scheme we call Wireless Control Protocol with Capacity estimation (WCPCap). Using analysis, simulations, and real deployments, we find that our designs yield rates that are both fair and efficient. WCP assigns rates inversely proportional to the number of bottlenecks a flow passes through while remaining extremely easy to implement. An idealized version of WCPCap is max-min fair, whereas a practical implementation of the scheme achieves rates within 15% of the max-min optimal rates while still being distributed and amenable to real implementation.

Quasi-static Centralized Rate Allocation for Sensor Networks

Rate control for congestion mitigation and avoidance has received significant attention in the sensor networks literature. Existing rate control schemes dynamically assign rates in a distributed manner. In this paper, we take a step back and ask: is a near-optimal quasi-static centralized rate allocation even feasible for wireless sensor networks? Intuition would suggest otherwise, since wireless conditions vary dynamically, and optimal centralized rate allocation is known to be computationally intractable. Surprisingly, however, we find that, quasi-static centralized rate allocation performs well at time-scales of tens of minutes on a 40-node testbed. Our approach relies on a relatively simple, lightweight rate allocation heuristic that uses topology and loss rate information, and adapts at relatively long time-scales to channel variability. Extensive experiments on a 40-node wireless testbed show that sensor nodes achieve a goodput very close to their allocated rate, even in harsh wireless conditions. Furthermore, this achieved goodput is nearly 50% higher than that achieved by IFRC, a recently-proposed distributed rate control scheme, and within 13% of an empirically-determined optimal rate. We also evaluate extensions to our heuristic to support weighted fairness and networks with multiple base stations.

Embedded sensing of structures: a reality check

With the advent of miniaturized sensing technology, it has become possible to envision smart structures containing millions of sensors embedded in concrete for autonomously detecting and locating incipient damage. Where are we today in our march towards this vision of autonomous structural health monitoring (SHM) using networked embedded sensing? In this paper, we summarize some of the systems we have developed towards this vision. Wisden is a wireless sensor network that allows continuous monitoring of structures and NetSHM is a programmable system that allows civil engineers to implement and deploy SHM techniques without having to understand the intricacies of wireless sensor networking. We highlight our experiences in developing these systems, and discuss the implications of our experiences on the achievability of the overall vision.