In wireless sensor networks (WSNs), the base station (BS) is a critical sensor node whose failure causes severe data losses. Deploying multiple fixed BSs improves the robustness, yet requires all BSs to be installed with large batteries and large energy-harvesting devices due to the high energy consumption of BSs. In this paper, we propose a scheme to coordinate the multiple deployed BSs such that the energy supplies required by individual BSs can be substantially reduced. In this scheme, only one BS is selected to be active at a time and the other BSs act as regular sensor nodes. We first present the basic architecture of our system, including how we keep the network running with only one active BS and how we manage the handover of the role of the active BS. Then, we propose an algorithm for adaptively selecting the active BS under the spatial and temporal variations of energy resources. This algorithm is simple to implement but is also asymptotically optimal under mild conditions. Finally, by running simulations and real experiments on an outdoor testbed, we verify that the proposed scheme is energy-efficient, has low communication overhead and reacts rapidly to network changes.

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.

SensorScope is a collaborative project between network, signal processing, and environmental researchers that aims at providing a cheap and out-of-the-box environmental monitoring system based on a wireless sensor network. It has been successfully used in a number of deployments to gather hundreds of megabytes of environmental data. With data gathering techniques well mastered, the efficient processing of the huge amounts of the acquired information to allow for useful exploitation has become an increasingly important issue. In this paper, we present a number of challenging and relevant signal processing tasks that arise from the SensorScope project. We believe the resolution of these problems will benefit from a better understanding of the underlying physical processes. We show an example to demonstrate how physical correlations between different sensing modalities can help reduce the sampling rate.

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 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.

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.

We consider the problem of activity scheduling and area coverage in sensor networks, and especially focus on problems that arise when using a more realistic physical layer. Indeed, most of the previous work in this area has been studied within an ideal environment, where messages are always correctly received. In this paper, we argue that protocols developed with such an assumption can hardly provide satisfying results in a more realistic world. To show this, we replace the classic unit disk graph model by the lognormal shadowing one. The results show that either the resulting area coverage is not sufficient or the percentage of active nodes is very high. We thus present an original method, where a node decides to turn off when there exists in its vicinity a sufficiently reliable covering set of neighbors. We show that our solution is very efficient as it preserves area coverage while minimizing the quantity of active nodes.

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.

We investigate the problem of minimum energy broadcasting in ad hoc networks where nodes have capability to adjust their transmission range. The minimal transmission energy needed for correct reception by neighbor at distance r is proportional to r/sup /spl alpha//+c/sub e/, /spl alpha/ and c/sub e/ being two environment-dependent constants. We demonstrate the existence of an optimal transmission radius, computed with a hexagonal tiling of the network area, that minimizes the total power consumption for a broadcasting task. This theoretically computed value is experimentally confirmed. The existing localized protocols are inferior to existing centralized protocols for dense networks. We present two localized broadcasting protocols, based on derived "target" radius, that remain competitive for all network densities. The first one, TR-LBOP, computes the minimal radius needed for connectivity and increases it up to the target one after having applied a neighbor elimination scheme on a reduced subset of direct neighbors. In the second one, TRDS, each node first considers only neighbors whose distance is no greater than the target radius (which depends on the power consumption model used), and neighbors in a localized connected topological structure such as RNG or LMST. Then, a connected dominating set is constructed using this subgraph. Nodes not selected for the set may be sent to sleep mode. Nodes in selected dominating set apply TR-LBOP. This protocol is the first one to consider both activity scheduling and minimum energy consumption as one combined problem. Finally, some experimental results for both protocols are given, as well as comparisons with other existing protocols. Our analysis and protocols remain valid if energy needed for packet receptions is charged.

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.

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.