This paper presents and evaluates two principles for wireless routing protocols. The first is datapath validation: data traffic quickly discovers and fixes routing inconsistencies. The second is adaptive beaconing: extending the Trickle algorithm to routing control traffic reduces route repair latency and sends fewer beacons. We evaluate datapath validation and adaptive beaconing in CTP Noe, a sensor network tree collection protocol. We use 12 different testbeds ranging in size from 20–310 nodes, comprising seven platforms, and six different link layers, on both interference-free and interference-prone channels. In all cases, CTP Noe delivers> 90 % of packets. Many experiments achieve 99.9%. Compared to standard beaconing, CTP Noe sends 73 % fewer beacons while reducing topology repair latency by 99.8%. Finally, when using low-power link layers, CTP Noe has duty cycles of 3 % while supporting aggregate loads of 30 packets/minute.

We undertake a systematic experimental study of the effects of concurrent packet transmissions in low-power wireless networks. Our measurements, conducted with Mica2 motes equipped with CC1000 radios, confirm that guaranteeing successful packet reception with high probability in the presence of concurrent transmissions requires that the signal-to-interference-plus-noise-ratio (SINR) exceed a critical threshold. However, we find a significant variation of about 6 dB in the threshold for groups of radios operating at different transmission powers. We find that it is harder to estimate the level of interference in the presence of multiple interferers. We also find that the measured SINR threshold generally increases with the number of interferers. Our study offers a better understanding of concurrent transmissions and suggests richer interference models and useful guidelines to improve the design and analysis of higher layer protocols.

A substantial percentage of links in wireless networks, especially low-power ones, is asymmetric. For the low-quality direction of asymmetric links, we observe based on testbed experiments that the reliability of synchronous acknowledgments is considerably higher than that of asynchronous messages. Thus the norm of estimating link quality in both directions via asynchronous beacons such as in ETX-based routing potentially underestimates the link reliability of asymmetric links. This leads us to investigate how to exploit asymmetric links in order to improve network functions such as convergecast routing in sensor networks via one-way link estimation. We propose a new one-way link metric ETF (for the expected number of transmissions over forward links) and present a local procedure for its estimation. We use ETF to identify high reliability forward links and use dynamic retransmission thresholding for error control and observe an improvement in convergecast routing over ETX. This is quantified with experimental testbed results with respect to reliability, number of transmissions per packet, latency, duplicates and average hops. We also study the comparative performance improvement of ETF over ETX when no special mechanism is employed to discover asymmetric links.

In the context of IEEE 802.11b network testbeds, we examine the differences between unicast and broadcast link properties, and we show the inherent difficulties in precisely estimating unicast link properties via those of broadcast beacons even if we make the length and transmission rate of beacons be the same as those of data packets. To circumvent the difficulties in link estimation, we propose to estimate unicast link properties directly via data traffic itself without using periodic beacons. To this end, we design a data-driven routing protocol Learn on the Fly (LOF). LOF chooses routes based on ETX/ETT-type metrics, but the metrics are estimated via MAC feedback for unicast data transmission instead of broadcast beacons. Using a realistic sensor network traffic trace and an 802.11b testbed of ∼195 Stargates, we experimentally compare the performance of LOF with that of beacon-based protocols, represented by the geography-unaware ETX and the geography-based PRD. We find that LOF reduces end-to-end MAC latency by a factor of 3, enhances energy efficiency by a factor up to 2.37, and improves network throughput by a factor up to 7.78, which demonstrate the feasibility and the potential benefits of data-driven link estimation and routing.

Abstract—We revisit the problem of computing the path with the minimum cost in terms of the expected number of link layer transmissions (including retransmissions) in wireless mesh networks. Unlike previous efforts, such as the popular ETX, we account for the fact that MAC protocols (including the IEEE 802.11 MAC) incorporate a finite number of transmission attempts per packet. This in turn leads to our key observation: the performance of a path depends not only on the number of the links on the path and the quality of its links, but also, on the relative positions of the links on the path. Based on this observation, we propose ETOP, a path metric that accurately captures the expected number of link layer transmissions required for reliable end-to-end packet delivery. We analytically compute ETOP, which is not trivial, since ETOP is a noncommutative function of the link success probabilities. Although ETOP is a more involved metric, we show that the problem of computing paths with the minimum ETOP cost can be solved by a greedy algorithm. We implement and evaluate a routing approach based on ETOP on a 25-node indoor mesh network. Our experiments show that the path selection with ETOP consistently results in superior TCP goodput (by over 50 % in many cases) compared to path selection based on ETX. We also perform an in-depth analysis of the measurements to better understand why the paths selected by ETOP improve the TCP performance. I.

Abstract Routing in wireless mesh networks has been an active area of research for many years. Among the routing protocols proposed, a large majority selects paths that minimize hop count. Whereas minimum hop count is the most popular metric in wired networks, in wireless networks interference- and energy-related considerations give rise to more complex trade-offs. Therefore, a variety of routing metrics has been proposed for wireless mesh networks providing routing algorithms with high flexibility in the selection of best path and offering a compromise between throughput, end-to-end delay, and energy consumption. In this paper, we present a detailed survey and taxonomy of routing metrics. These metrics can have broadly different optimization objectives (e.g. to optimize application performance, maximize battery lifetime, maximize network throughput), different methods to collect the required information to produce metric values, and different ways to derive the end-to-end route quality out of the individual link quality metrics. The presentation of the metrics is highly comparative, with emphasis on the strengths and the weaknesses of both individual and whole families of metrics. We also discuss the main implications for practitioners and identify open issues for further research in the area. 2 1

Abstract. Execution of wireless sensor network (WSN) applications typically consists of a number of successive phases, such as network reprogramming, localization, power management, health monitoring, and parameter updates. Termination detection of a phase is therefore a critical operation for a network manager to safely execute a new phase on some or all of the network nodes. In this paper, we reformulate the well-known problem of termination detection for WSNs, and present a low-cost solution to the problem. Our algorithm, Reporter, exploits the reactive nature of WSN protocols as well as the broadcast communication model of WSNs. It detects termination accurately and (message) efficiently, using reports from only a small fraction of nodes in the network. It exploits existing network traffic to construct a routing tree to collect these reports at a base station, and thus reduces the control overhead of structure formation. Moreover, it has low computation and memory overhead. We have developed a TinyOS implementation of Reporter, which is easily composed with a number of existing WSN protocols. We provide detailed experimental performance results obtained on an indoor mote testbed which show that Reporter selects as few as 5 % of the total number of nodes in the network for collecting termination reports while preserving accuracy. 1

The wireless network community has become increasingly aware of the benefits of data-driven link estimation and routing as compared with beacon-based approaches, but the issue of biased link sampling (BLS) has not been well studied even though it affects routing convergence in the presence of network and environment dynamics. Focusing on traffic-induced dynamics, we examine the open, unexplored question of how serious the BLS issue is and how to effectively address it when the routing metric ETX is used. For a wide range of traffic patterns and network topologies and using both node-oriented and network-wide analysis and experimentation, we discover that the optimal routing structure remains quite stable even though the properties of individual links and routes vary significantly as traffic pattern changes. In cases where the optimal routing structure does change, data-driven link estimation and routing is either guaranteed to converge to the optimal structure or empirically shown to converge to a close-to-optimal structure. These findings provide the foundation for addressing the BLS issue in the presence of traffic-induced dynamics and suggest approaches other than existing ones. These findings also demonstrate that it is possible to maintain an optimal, stable routing structure despite the fact that the properties of individual links and paths vary in response to network dynamics.

Link asymmetry is one of the characteristic challenges that wireless sensor networks pose in the design of network protocols. We observe, based on testbed experiments, that a substantial percentage of links are asymmetric, many are even unidirectional. We also find that the reliability of synchronous acknowledgments is considerably higher than that of asynchronous messages. Thus the norm of estimating link quality bidirectionally via asynchronous beacons underestimates the link reliability of asymmetric links. This leads us to investigate how to exploit asymmetric links in order to improve network functions such as convergecast routing in sensor networks via oneway link estimation. We propose a new one-way link metric ETF (for the expected number of transmissions over forward links) and present a local procedure for its estimation. We use ETF to identify reliable forward links, and we use dynamic retransmission thresholding for error control. Via experiments on testbeds of CC1000 radios and CC2420 radios (an IEEE 802.15.4-compliant radio), we quantify the performance improvement in ETF as compared with ETX. We also study the performance improvement of ETF over ETX when no special mechanism is employed to discover asymmetric links or to control retransmissions.

Abstract—Link estimation is a basic element of routing in low-power wireless networks, and data-driven link estimation using unicast MAC feedback has been shown to outperform broadcast-beacon based link estimation. Nonetheless, little is known about how different data-driven link estimation methods affect routing behaviors. To address this issue, we classify existing data-driven link estimation methods into two broad categories: L-NT that uses aggregate information about unicast and L-ETX that uses information about the individual unicast-physical transmissions. Through mathematical analysis and experimental measurement in a testbed of 98 XSM motes (an enhanced version of MICA2 motes), we examine the accuracy and stability of L-NT and L-ETX in estimating the ETX routing metric. We also experimentally study the routing performance of L-NT and L-ETX. We discover that these two representative, seemingly similar methods of data-driven link estimation differ significantly in routing behaviors: L-ETX is much more accurate and stable than L-NT in estimating the ETX metric, and, accordingly, L-ETX achieves a higher data delivery reliability and energy efficiency than L-NT (for instance, by 25.18 % and a factor of 3.75 respectively in our testbed). These findings provide new insight into the subtle design issues in data-driven link estimation that significantly impact the reliability, stability, and efficiency of wireless routing, thus shedding light on how to design link estimation methods for mission-critical wireless networks which pose stringent requirements on reliability and predictability. Index Terms—Low-power wireless networks, sensor networks, link estimation and routing, data-driven, beacon-based, distancevector routing, geographic routing I.