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A straightforward idea to prolong wireless sensor networks network lifetime is to schedule activities of nodes, that will turn into either Active or Passive states during the deployment. Several papers proposed solutions to turn Passive a large subset of nodes. However, only few of those provide information on how to translate this activity state in reality. In this paper, we further improved several activity scheduling mechanisms by introducing a new activity state called Sensing–Only. This new sensor node state concerns formerly Active nodes, all the more reducing the size of this subset. In addition, radio usage being the sensor nodes main source of energy depletion, we also provide a realistic translation of activity states by adjoining to each of those a specific configuration of the medium access control layer. Finally, we validate our approach both by simulation and experimentation over a large set of real sensor nodes.

The Internet of Things (IoT) paradigm aims at connecting any object to the Internet (i.e. to the IP world). Due to the physical constraints (limited energy capacities) and deployment conditions (numerous autonomous devices scattered into an area) of such Things, power management and scalability are key issues in IoT deployments. While the problematics of the IP addressing have been successfully transposed to IoT networks, the dedicated IEEE 802.15.4 Medium Access Control standard lacks of scalability, provides insufficient energy-efficiency and thus fails to fulfill their needs. In this paper, we consider alternative MAC protocols, compatible with IoT specificities. These protocols realize energy gains by asynchronously alternating active and passive periods at the radio scale, thus allowing both energy-efficiency and scalability. For the time being, most real IoT 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, the 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, delays). 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 IoT SensLAB testbed. It demonstrates that our solutions provide up to 61% energy saving, preserve the loss-rate below 10% and guarantee the connectivity of the network. They thus offer a better compromise between energy-efficiency and network performances than any homogeneous MAC configuration.

In this paper, we analyze the IPv6 handover over wireless LANs. Mobile IPv6 is designed to manage mobile nodes movements between wireless IPv6 networks. Nevertheless, a mobile node cannot receive IP packets on its new point of attachment until the handover completes. Therefore, a number of extensions to Mobile IPv6 have been proposed to reduce the handover latency and the number of lost packets. We focus on Fast Mobile IPv6 which is an extension of Mobile IPv6 that allows the use of L2 triggers to anticipate the handover. We compare the handover latency in four specific cases: basic Mobile IPv6, the forwarding method of Mobile IPv6, the Anticipated method, and the Tunnel-Based Handover. The results of the handover latency are calculated with the L2 properties of IEEE 802.11b. In particular, we take into account the L2 handover for different configurations of the wireless network.