Efficient Binary scheme for Training Heterogeneous Sensor Actor Networks


International audienceSensor networks are expected to evolve into long-lived, autonomous networked systems whose main mission is to provide in-situ users – called actors – with real-time information in support of specific goals supportive of their mission. The network is populated with a heterogeneous set of tiny sensors. The free sensors alternate between sleep and awake periods, under program control in response to computational and communication needs. The periodic sensors alternate between sleep periods and awake periods of predefined lengths, established at the fabrication time. The architectural model of an actor-centric network used in this work comprises in addition to the tiny sensors a set of mobile actors that organize and manage the sensors in their vicinity. We take the view that the sensors deployed are anonymous and unaware of their geographic location. Importantly, the sensors are not, a priori, organized into a network. It is, indeed, the interaction between the actors and the sensor population that organizes the sensors in a disk around each actor into a short-lived, mission-specific, network that exists for the purpose of serving the actor and that will be disbanded when the interaction terminates. The task of setting up this form of actor-centric network involves a training stage where the sensors acquire dynamic coordinates relative to the actor in their vicinity. The main contribution of this work is to propose an energy- efficient training protocol for actor-centric heterogeneous sensor networks. Our protocol outperforms all know training protocols in the number of sleep/awake transitions per sensor needed by the training process. Specifically, in the presence of kk coronas, no sensor will experience more thanlog(k) \lceil log(k)\rceil sleep/awake transitions and awake periods

Similar works

Full text


HAL-Paris 13

Full text is not available
oaioai:HAL:hal-00461925v1Last time updated on 11/11/2016

This paper was published in HAL-Paris 13.

Having an issue?

Is data on this page outdated, violates copyrights or anything else? Report the problem now and we will take corresponding actions after reviewing your request.