Joint Routing and STDMA-based Scheduling to Minimize Delays in Grid Wireless Sensor Networks

In this report, we study the issue of delay optimization and energy efficiency in grid wireless sensor networks (WSNs). We focus on STDMA (Spatial Reuse TDMA)) scheduling, where a predefined cycle is repeated, and where each node has fixed transmission opportunities during specific slots (defined by colors). We assume a STDMA algorithm that takes advantage of the regularity of grid topology to also provide a spatially periodic coloring ("tiling" of the same color pattern). In this setting, the key challenges are: 1) minimizing the average routing delay by ordering the slots in the cycle 2) being energy efficient. Our work follows two directions: first, the baseline performance is evaluated when nothing specific is done and the colors are randomly ordered in the STDMA cycle. Then, we propose a solution, ORCHID that deliberately constructs an efficient STDMA schedule. It proceeds in two steps. In the first step, ORCHID starts form a colored grid and builds a hierarchical routing based on these colors. In the second step, ORCHID builds a color ordering, by considering jointly both routing and scheduling so as to ensure that any node will reach a sink in a single STDMA cycle. We study the performance of these solutions by means of simulations and modeling. Results show the excellent performance of ORCHID in terms of delays and energy compared to a shortest path routing that uses the delay as a heuristic. We also present the adaptation of ORCHID to general networks under the SINR interference model

Connectivity-Based Self-Localization in WSNs

Efficient localization methods are among the major challenges in wireless sensor networks today. In this paper, we present our so-called connectivity based approach i.e, based on local connectivity information, to tackle this problem. At first the method fragments the network into larger groups labeled as packs. Based on the mutual connectivity relations with their surrounding packs, we identify border nodes as well as the central node. As this first approach requires some a-priori knowledge on the network topology, we also present a novel segment-based fragmentation method to estimate the central pack of the network as well as detecting so-called corner packs without any a-priori knowledge. Based on these detected points, the network is fragmented into a set of even larger elements, so-called segments built on top of the packs, supporting even more localization information as they all reach the central node

A mosaic of eyes

Autonomous navigation is a traditional research topic in intelligent robotics and vehicles, which requires a robot to perceive its environment through onboard sensors such as cameras or laser scanners, to enable it to drive to its goal. Most research to date has focused on the development of a large and smart brain to gain autonomous capability for robots. There are three fundamental questions to be answered by an autonomous mobile robot: 1) Where am I going? 2) Where am I? and 3) How do I get there? To answer these basic questions, a robot requires a massive spatial memory and considerable computational resources to accomplish perception, localization, path planning, and control. It is not yet possible to deliver the centralized intelligence required for our real-life applications, such as autonomous ground vehicles and wheelchairs in care centers. In fact, most autonomous robots try to mimic how humans navigate, interpreting images taken by cameras and then taking decisions accordingly. They may encounter the following difficulties

On Mobility Management in Multi-Sink Sensor Networks for Geocasting of Queries

In order to efficiently deal with location dependent messages in multi-sink wireless sensor networks (WSNs), it is key that the network informs sinks what geographical area is covered by which sink. The sinks are then able to efficiently route messages which are only valid in particular regions of the deployment. In our previous work (see the 5th and 6th cited documents), we proposed a combined coverage area reporting and geographical routing protocol for location dependent messages, for example, queries that are injected by sinks. In this paper, we study the case where we have static sinks and mobile sensor nodes in the network. To provide up-to-date coverage areas to sinks, we focus on handling node mobility in the network. We discuss what is a better method for updating the routing structure (i.e., routing trees and coverage areas) to handle mobility efficiently: periodic global updates initiated from sinks or local updates triggered by mobile sensors. Simulation results show that local updating perform very well in terms of query delivery ratio. Local updating has a better scalability to increasing network size. It is also more energy efficient than ourpreviously proposed approach, where global updating in networks have medium mobility rate and speed

AWARE: Platform for Autonomous self-deploying and operation of Wireless sensor-actuator networks cooperating with unmanned AeRial vehiclEs

This paper presents the AWARE platform that seeks to enable the cooperation of autonomous aerial vehicles with ground wireless sensor-actuator networks comprising both static and mobile nodes carried by vehicles or people. Particularly, the paper presents the middleware, the wireless sensor network, the node deployment by means of an autonomous helicopter, and the surveillance and tracking functionalities of the platform. Furthermore, the paper presents the first general experiments of the AWARE project that took place in March 2007 with the assistance of the Seville fire brigades