François Ingelrest

SensorScope: Out-of-the-Box Environmental Monitoring

Environmental monitoring constitutes an important field of application for wireless sensor networks. Given the severity of potential climate changes, environmental impact on cities, and pollution, it is a domain where sensor networks can have great impact and as such, is getting more and more attention. Current data collection techniques are indeed rather limited and make use of very expensive sensing stations, leading to a lack of appropriate observations. In this paper, we present SensorScope, a collaborative project between environmental and network researchers, that aims at providing an efficient and inexpensive out-of-the-box environmental monitoring system, based on a wireless sensor network. We especially focus on data gathering and present the hardware and network architecture of SensorScope. We also describe a real-world deployment, which took place on a rock glacier in Switzerland, as well as the results we obtained.

The hitchhiker's guide to successful wireless sensor network deployments

The successful deployment of a wireless sensor network is a difficult task, littered with traps and pitfalls. Even a functional network does not guarantee gathering meaningful data. In SensorScope, with its multiple campaigns in various environments (e.g., urban, high-mountain), we have acquired much knowledge in planning, conducting, and managing real-world sensor network deployments. In this paper, we share our experience by stepping through the entire process, from the preparatory hard- and software development to the actual field deployment. Illustrated by numerous real-life examples, excerpted from our own experience, we point out many potential problems along this way and their possible solutions. We also indicate the importance of a close interaction with the end-user community in planning and running the network, and finally exploiting the data.

SensorScope: Application-specific sensor network for environmental monitoring

SensorScope is a turnkey solution for environmental monitoring systems, based on a wireless sensor network and resulting from a collaboration between environmental and network researchers. Given the interest in climate change, environmental monitoring is a domain where sensor networks will have great impact by providing high resolution spatio-temporal data for long periods of time. SensorScope is such a system, which has already been successfully deployed multiple times in various environments (e.g., mountainous, urban). Here, we describe the overall hardware and software architectures and especially focus on the sensor network itself. We also describe one of our most prominent deployments, on top of a rock glacier in Switzerland, which resulted in the description of a micro-climate phenomenon leading to cold air release from a rock-covered glacier in a region of high alpine risks. Another focus of this paper is the description of what happened behind the scenes to turn SensorScope from a laboratory experiment into successful outdoor deployments in harsh environments. Illustrated by various examples, we point out many lessons learned while working on the project. We indicate the importance of simple code, well suited to the application, as well as the value of close interaction with end-users in planning and running the network and finally exploiting the data.

Wireless Sensor Networks for Environmental Monitoring: The SensorScope Experience

While wireless sensor networks have been extensively studied in the past few years, most results are of theoretical nature and were obtained outside of a practical context. This can be problematic for real applications, especially in the area of environmental monitoring where many factors, such as harsh weather conditions, can greatly influence the performance of such a network, while reliable delivery and high-quality measurements are required. SensorScope is an interdisciplinary project, elaborated by environmental and networking researchers, that aims at narrowing the gap between theory and practice. Several successful real-world deployments have already been undertaken in rugged environments. In this paper, we analyze the particular requirements of environmental monitoring and how these requirements have been met in the SensorScope project. We also present an application example of a deployment, undertaken in a harsh mountain environment.

Hydrologic response of an alpine watershed: Application of a meteorological wireless sensor network to understand streamflow generation

A field measurement campaign was conducted from June to October 2009 in a 20 km2 catchment of the Swiss Alps with a wireless network of 12 weather stations and river discharge monitoring. The objective was to investigate the spatial variability of meteorological forcing and to assess its impact on streamflow generation. The analysis of the runoff dynamics highlighted the important contribution of snowmelt from spring to early summer. During the entire experimental period, the streamflow discharge was dominated by base flow contributions with temporal variations due to occasional rainfall-runoff events and a regular contribution from glacier melt. Given the importance of snow and ice melt runoff in this catchment, patterns of near-surface air temperatures were studied in detail. Statistical data analyses revealed that meteorological variables inside the watershed exhibit spatial variability. Air temperatures were influenced by topographic effects such as slope, aspect, and elevation. Rainfall was found to be spatially variable inside the catchment. The impact of this variability on streamflow generation was assessed using a lumped degree-day model. Despite the variability within the watershed, the streamflow discharge could be described using the lumped model. The novelty of this work mainly consists in quantifying spatial variability for a small watershed and showing to which extent this is important. When the focus is on aggregated outputs, such as streamflow discharge, average values of meteorological forcing can be adequately used. On the contrary, when the focus is on distributed fields such as evaporation or soil moisture, their estimate can benefit from distributed measurements.

A Turnover based Adaptive HELLO Protocol for Mobile Ad Hoc and Sensor Networks

We present a turnover based adaptive HELLO protocol (TAP), which enables nodes in mobile networks to dynamically adjust their HELLO messages frequency depending on the current speed of nodes. To the best of our knowledge, all existing solutions are based on specific assumptions (e.g., slotted networks) and/or require specific hardware (e.g., GPS) for speed evaluation. One of the key aspects of our solution is that no additional hardware is required since it does not need this speed information. TAP may be used in any kind of mobile networks that rely on HELLO messages to maintain neighborhood tables and is thus highly relevant in the context of ad hoc and sensor networks. In our solution, each node has to monitor its neighborhood table to count new neighbors whenever a HELLO is sent. This turnover is then used to adjust HELLO frequency. To evaluate our solution, we propose a theoretical analysis based on some given assumptions that provides the optimal turnover when these assumptions hold. Our experimental results demonstrate that when this optimal value is used as the targeted turnover in TAP, the HELLO frequency is correctly adjusted and provides a good accuracy with regards to the neighborhood tables.

Potentials of Opportunistic Routing in Energy-Constrained Wireless Sensor Networks

The low quality of wireless links leads to perpetual packet losses. While an acknowledgment mechanism is generally used to cope with these losses, multiple retransmissions nevertheless occur. Opportunistic routing limits these retransmissions by taking advantage of the broadcast nature of the wireless channel: sending packets to multiple receivers at once, and only then, based on the outcome, choosing the actual next hop [1]. In this paper, we first study the potentials of opportunistic routing in energy-constrained wireless sensor networks. In particular, the reduction of retransmissions due to the broadcast advantage is balanced with the arising need for coordination to avoid duplicate packets. We then propose Coordinated Anypath Routing, an opportunistic routing protocol designed for wireless sensor networks, in which the coordination between receivers is handled by an overhearing-based acknowledgment scheme. Our protocol may be used to minimize either retransmissions or power consumption, and our simulation results show that, with lossy links, energy savings go up to 7%, even for small networks of 20 nodes.

Localized broadcast incremental power protocol for wireless ad hoc networks

As broadcasting is widely used for miscellaneous maintenance operations in wireless ad hoc networks, where energy is a scarce resource, an efficient broadcasting protocol is of prime importance. One of the best known algorithm, named BIP (broadcast incremental power), constructs a spanning tree rooted at a given node. This protocol offers very good results in terms of energy savings, but its computation is unfortunately centralized, as the source node needs to know the entire topology of the network to compute the tree. Many localized protocols have since been proposed, but none of them has ever reached the performances of BIP. Even distributed versions of the latter have been proposed, but they require a huge transmission overhead for information exchange and thus waste energy savings obtained thanks to the efficiency of the tree, in this paper, we propose and analyze a localized version of this protocol. In our method, each node is aware of the position of all the hosts in the set of its 2-hop neighborhood and compute the BIP tree on this set, based on information provided by the node from which it got the packet. That is, a tree is incrementally built thanks to information passed from node to node in the broadcast packet. Only the source node computes an initially empty tree to initiate the process. We also provide experimental results showing that this new protocol has performances very close to other good ones for low densities, and is very energy-efficient for higher densities with performances that equal the ones of BIP.

Target transmission radius over LMST for energy-efficient broadcast protocol in ad hoc networks

We investigate minimum energy broadcasting problem where mobile nodes have the capability to adjust their transmission range. The power consumption for two nodes at distance r is r/sup /spl alpha// + c, where /spl alpha/ /spl ges/ 2 and c is a constant that includes signal processing and minimal reception power. We show that, for c > 0 (which is realistic assumption), it is not optimal to minimize transmission range. Furthermore, we demonstrate that there exists an optimal radius, computed with a hexagonal tiling of the network area that minimizes the power consumption. For /spl alpha/ > 2 and c > 0, the optimal radius is r = /spl alpha//spl radic/(2c//spl alpha/-2), which is derived theoretically, and confirmed experimentally. We propose also a localized broadcast algorithm TR-LBOP that takes this optimal radius into account. This protocol is experimentally shown to be efficient compared to existing localized protocol LBOP and globalized BIP protocol. Most importantly, TR-LBOP is shown to have limited energy overhead with respect to BIP for all network densities, which is not the case with LBOP whose overhead explodes for higher densities.

Localized minimum spanning tree based multicast routing with energy-efficient guaranteed delivery in ad hoc and sensor networks

We present a localized geographic multicast scheme, MSTEAM, based on the construction of local minimum spanning trees (MSTs), that requires information only on 1-hop neighbors. A message replication occurs when the MST spanning the current node and the set of destinations has multiple edges originated at the current node. Destinations spanned by these edges are grouped together, and for each of these subsets the best neighbor is selected as the next hop. This selection is based on a cost over progress metric, where the progress is approximated by subtracting the weight of the MST over a given neighbor and the subset of destinations to the weight of the MST over the current node and the subset of destinations. Since such greedy scheme may lead the message to a void area (i.e., no neighbor providing positive progress), we propose a new multicast generalization of the well-known face recovery mechanism. We provide a theoretical analysis proving that MSTEAM is loop-free, and achieves delivery of the multicast message as long as a path to the destinations exists. Our results demonstrate that MSTEAM outperforms the best existing localized multicast scheme, and is almost as efficient as a centralized scheme in high densities.