Reliability Analysis of Sensor Networks

To Integrate the capacity of sensing, communication, computing, and actuating, one of the compelling technological advances of these years has been the appearance of distributed wireless sensor network (DSN) for information gathering tasks. In order to save the energy, multi-hop routing between the sensor nodes and the sink node is necessary because of limited resource. In addition, the unpredictable conditional factors make the sensor nodes unreliable. In this paper, the reliability of routing designed for sensor network and some dependability issues of DSN, such as MTTF (mean time to failure) and the probability of connectivity between the sensor nodes and the sink node are analyzed. Unfortunately, we could not obtain the accurate result for the arbitrary network topology, which is #P-hard problem. And the reliability analysis of restricted topologies clustering-based is given. The method proposed in this paper will show us a constructive idea about how to place energy-constrained sensor nodes in the network efficiently from the prospective of reliability.

Cooperative Localization and Tracking in Distributed Robot-Sensor Networks

This paper addresses the problem of real-time position and orientation estimation of networked mobile robots in two-dimensional Euclidean space with simultaneous tracking of a rigid unknown object based on exteroceptive sensory information extracted from distributed vision systems. The sufficient and necessary conditions for team localization are proposed. A localization and object tracking approach based on statistical operators and graph searching algorithms is presented for a team of robots localized with het- erogeneous sensors. The approach was implemented in an experimental platform consisting of car-like mobile robots equipped with omnidirectional video cameras and IEEE 802.11b wireless networking. The experimental results validate the approach.

A Dedicated MAC Protocol Package for Real-Time Ocean Current Field Estimation Using Distributed Underwater Acoustic Sensor Networks

Distributed underwater acoustic sensor networks(UASNs)are envisioned in real-time ocean current velocity estimation.However,UASNs at present are still dominated by post-processing partially due to the complexity of on-line detection for travel times and lack of dedicated medium access control(MAC)protocols.In this study,we propose a dedicated MAC protocol package for real-time ocean current velocity estimation using distributed UASNs.First,we introduce the process and requirements of ocean current velocity estimation.Then,we present a series of spatial reuse time division multiple access(TDMA)protocols for each phase of real-time ocean current field estimation using distributed UASNs,followed by numerical analysis.We divide UASNs into two categories according to their computing ability:feature-complete and feature-incomplete systems.The feature-complete systems that have abundant computing ability carry out the presented MAC protocol package in three phases,whereas the feature-incomplete ones do not have enough computing ability and the presented MAC protocol package is reduced to two phases plus an additional downloading phase.Numerical analysis shows that feature-complete systems using mini-slot TDMA have the best real-time performance,in comparison with feature-incomplete systems and other feature-complete counterparts.Feature-incomplete systems are more energy-saving than feature-complete ones,owing to the absence of in-network data exchange.

A Fast Global Node Selection Algorithm for Bearings-only Target Localization

In the target tracking, the nodes aggregate their observations of the directions of arrival of the target. The network then uses an extended Kalman filter （EKF） to combine the measurements from multiple snapshots to track the target. In order to rapidly select the best subset of nodes to localize the target with the minimum mean square position error and low power consumption, this paper proposes a simple algorithm, which uses the location information of the target and the network. The lower botmd of localization error is utilized according to the distances between the target and the selected active nodes. Furthermore, the direction likelihoods of the active nodes is predicted by way of the node/target bearing distributing relationships.

Ethernet based time synchronization for Raspberry Pi network improving network model verification for distributed active turbulent flow control

Friction drag primarily determines the total drag of transport systems. A promising approach to reduce drag at high Reynolds numbers(> 104) are active transversal surface waves in combination with passive methods like a riblet surface. For the application in transportation systems with large surfaces such as airplanes, ships or trains, a large scale distributed real-time actuator and sensor network is required. This network is responsible for providing connections between a global flow control and distributed actuators and sensors. For the development of this network we established at first a small scale network model based on Simulink and True Time. To determine timescales for network events on different package sizes we set up a Raspberry Pi based testbed as a physical representation of our first model. These timescales are reduced to time differences between the deterministic network events to verify the behavior of our model. Experimental results were improved by synchronizing the testbed with sufficient precision. With this approach we assure a link between the large scale model and the later constructed microcontroller based real-time actuator and sensor network for distributed active turbulent flow control.