In traditional routing protocols designed for Wireless Sensor Networks, each sensor node is related to one or more neighbors that will forward its readings up to the sink. This technique performs well for static topologies with homogeneous configurations, but usually fails to cope with network dynamics such as mobility and node failures. Opportunistic routing is an approach to address this particular problem. In this context, the data packets are addressed to a set of potential forwarders and then forwarded by the neighbor that first acknowledges the message. Yet, several former studies demonstrated that in some cases, a single packet may be forwarded by multiple neighbors simultaneously. This situation leads to packet duplication and consequently to increased channel occupancy and energy consumption in the network. In this paper, we study to what extent the previously reported phenomenon depends on both the topology density and the nodes MAC configuration. We then introduce a mechanism that handles the potential deafness in the network through heterogeneous configuration among the nodes in the network. We do so through local, dynamic and automatic MAC parameters adaptation, in order to reduce unnecessary traffic, channel occupancy and energy consumption due to packet duplication in opportunistic networks. Finally, we provide both theoretical analysis and experimental campaign to detail the benefits of our approach.

Due to their physical constraints and deployment conditions, power management is a key issue in Wireless Sensor Networks. The radio component being the most responsible for energy wastage, controlling medium access is of prime importance in order to obtain desired network lifetime. Several existing mechanisms realize energy gains by alternating active and passive periods at the radio scale and most real WSN deployments implement static and homogeneous duty-cycling (i.e. invariant and identical for each node in the network). Although preventing any node isolation, such method fails to address the dynamics of the network efficiently. We propose a strategy to enable heterogeneous MAC duty-cycle configurations among nodes in the network. We aim at granting each node a specific sleep-depth, according to criteria specific to the deployment (e.g. applicative criteria, location in the routing structure). To implement this idea, sensor nodes are divided into disjoint subsets, each of them standing for a given duty-cycle configuration and leading to a network performance managed at its best (e.g. energy consumption, loss rate). We detail to what extent our approach preserves network connectivity with coherent heterogeneous duty-cycling, thus reaching a compromise between energy consumption and reactivity. The presented experimental campaign was led over the SensLAB testbed. It demonstrates that our solutions provide up to 61% energy saving, yet preserving the loss-rate below 10%, and guaranteeing the connectivity of the network.

Validation of protocols and mechanisms is an essential step to the development of object networks in critical domains. Most papers still provide evaluation either obtained through theoretical analysis or simulations campaigns. Yet, simulators and formal models fail to precisely reproduce the unique specificities of the deployment environments those networks have to evolve in. Also, by putting no limits to code complexity and execution, those tools prevent users to apprehend the actual limits of WSN nodes and to propose realistic communication protocols and applications. In this paper, we highlight to what extent the addition of experimentations can significantly improve the value of performance evaluation campaigns. Along with the recent tendency to have algorithmic and protocol proposals facing real environments, it is questionable whether the so obtained results should be considered as scientific or empirical ones. In the former case, reproducibility, stability over time, topology management to cite a few, are a must have for testbeds and real deployments that are used. In the latter, the results should be viewed as a proof-of-concept only, far from independent of the used hardware and encountered conditions at the experimentation time but still critical from the development cycle standpoint. Through some experiments over the IoT-LAB testbed, we aim at demonstrating to what extent some of the simulation setup and conditions from reality could be emulated. We also provide insight on how to obtain the best out of it in a quick and efficient manner. We show that such testbeds would satisfy many expectations (e.g. scientific tool and proof-of-concept validator), thus minding and bridging some of the gaps between theory and practice in WSN. To this end, we here give an overview of available simulation tools, and guidelines on how to transpose simulation setups to the open large-scale IoT-LAB platform.

Wireless sensor networks (WSN) require pertinent and reliable data collection schemes in order to provide information about their deployment area. This article aims at detailing our contribution for message loss avoidance along prone-to-failure paths that monitoring reports would follow from sensors to sink stations. While many researchers have tackled this issue by focusing on particular layers of the embedded communication stack (e.g. medium access control or routing protocol), we propose an original layer-independent scheme. The key aspect of our solution is to create fake data sources that have acted as storage nodes during the failure of links leading to the sink station. Few control messages are required during our gradual recovery phase, thus maintaining a negligible overhead in terms of message complexity and energy consumption, and also resulting in much improved data delivery ratio.

In this paper, we briefly describe an interactive roulette game enabled over a wireless sensor network platform. It basically consists in a train speeding in one way (the spinning roulette) and in a message hopping along some deployed sensors in the other way (the wheeling ball). This demonstration aims at illustrating in an interactive manner the high radio channel randomness in dense wireless sensor networks, as well as its impact on the communication protocols.