Section: New Results

Wireless Sensor Networks

Participants : Cédric Adjih, Aline Carneiro Viana, Emmanuel Baccelli, Thomas Clausen, Philippe Jacquet, Pascale Minet, Ichrak Amdouni, Ridha Soua, Erwan Livolant, Paul Mühlethaler, Yasser Toor.

Executive summary

In wireless sensor networks, we focus more particularly on:

• Spatial reuse of the bandwidth,

• Routing according to a cross-layering approach,

• Security,

• Energy efficiency,

• IPv6 support.

Scientific achievements

Cryptographic Protocols to Fight Sinkhole Attacks on Tree-based Routing in Wireless Sensor Networks

Wireless Sensor Networks (WSN) are penetrating more and more in our daily life. As a consequence, security has become an important matter for these networks. We introduce two new cryptographic protocols of different complexity and strength in limiting network degradation caused by sinkhole attacks on tree-based routing topologies in Wireless Sensor Networks (WSNs). The main goal of both protocols is to provide continuous operation by improving resilience against, rather than detection of, these attacks. The main benefit of providing resilience is that it allows operating (or graceful degradation) in the presence of attacks. Furthermore, while resilience mechanisms do not dismiss detection mechanisms, detection mechanisms often introduce more complexity and so, more weaknesses to the system, which might not justify their benefits. More specifically our two RESIlient and Simple Topology-based reconfiguration protocols are: RESIST-1 and RESIST-0. RESIST-1 prevents a malicious node from modifying its advertised distance to the sink by more than one hop, while RESIST-0 does not allow such lying at the cost of additional complexity.

IPv6 Protocol suite for Sensor Networks

Wireless sensor networking is a key element of the Internet of Things (IoT), a substantial part of the billions of smart objects that are soon to blend into the global IP network, from actuators to home appliances, from smart meters, to smart dust. Sensor nodes are devices used for distributed and automated monitoring of various parameters such as temperature, movement, noise or radioactivity levels etc. Sensors are scattered with minimum planning with respect to their precise physical position (including the central role of the sink, if any), and the set of peers with which a sensor can directly communicate through its wireless interface may change rapidly over time due to asynchronous sleep mode strategies, fluctuations in the radio environment, device failure or mobility. Through its wireless interface, a sensor thus connects to a communication link with undetermined connectivity properties. Sensor networks are a challenge to current IP standards, since on the one hand these protocols were designed to work on wired links and on the other hand these protocols were designed to work on machines that do not have drastic constraints in terms of CPU, power capacities, and memory, as sensor nodes do. In consequence, several key standard protocols (including TCP, UDP, DHCP, NDP, SLAAC, and OSPF) do not function correctly in this environment. Nevertheless, IPv6-based sensor networking is a viable long term goal because it would enable generic, large scale, seamless integration of millions of sensing devices using heterogeneous radio technologies, at a low cost, and in a future-proof manner.The Internet Engineering Task Force (IETF) is currently engaged into multiple efforts addressing the limitations of existing standards concerning wireless sensor IP networking. Some of the standards under construction aim at fitting IP formats, especially IPv6 formats, to direct wireless communications using low power radio technologies such as IEEE 802.15.4, which require IP format compression. Other standards in development aim at providing multi-hop wireless sensor communication with IPv6, which requires specific routing protocols, efforts in which we actively participate, prompting numerous joint publications with both industrial and academic partners.

Coloring in wireless sensor networks

Graph coloring is used in wireless networks to optimize network resources: bandwidth and energy. We focus on grid topologies that constitute regular topologies for large or dense wireless networks. We consider various transmission ranges and identify a color pattern that can be reproduced to color the whole grid with the optimal number of colors. We obtain an optimal periodic coloring of the grid for the considered transmission range. We then evaluate the performance of a 3-hop distributed coloring algorithm, called SERENA. Through simulation results, we highlight the impact of node priority assignment on the number of colors obtained for any network and grids in particular. We then compare these optimal results on grids with those obtained by SERENA and identify directions to improve SERENA.

Coloring algorithm optimized for dense wireless networks

In 2011, we also designed OSERENA "Optimized SchEduling RoutEr Node Activity", a distributed coloring algorithm optimized for dense wireless networks. Network density has an extremely reduced impact on the size of the messages exchanged to color the network. Furthermore, the number of colors used to color the network is not impacted by this optimization. We describe the properties of the algorithm and prove its correctness and termination. Simulation results point out the considerable gains in bandwidth.

Multichannel access in wireless sensor networks

In 2011 we started a research activity on multichannel access in wireless sensor networks. A state of the art has been published at the IFIP Wireless Days 2011 Conference.

Collaborations

• Many contractual collaborations:

  • Hitachi (Vehicular applications, OLSRv2),

  • OCARI2 project (industrial wireless sensor network, QoS, cross layer, energy efficiency, routing, node activity scheduling),

  • SAHARA project (wireless sensor network embedded in aircrafts),

  • STIC INRIA-Tunisian Universities: the team of Prof. Leila Saidane at ENSI (Performance improvement in a wireless sensor network),

• Non contractual:

  • BAE (OLSRv2),

  • Freie Universitaet (sensor networks, DHT),

  • Deutsche Telekom Labs/TU-Berlin, Germany,

  • University of Athens, Greece.