Distributed Environment Control Using Wireless Sensor/Actuator Networks for Lighting Applications

We propose a decentralized algorithm to calculate the control signals for lights in wireless sensor/actuator networks. This algorithm uses an appropriate step size in the iterative process used for quickly computing the control signals. We demonstrate the accuracy and efficiency of this approach compared with the penalty method by using Mote-based mesh sensor networks. The estimation error of the new approach is one-eighth as large as that of the penalty method with one-fifth of its computation time. In addition, we describe our sensor/actuator node for distributed lighting control based on the decentralized algorithm and demonstrate its practical efficacy

Simple Random Sampling-Based Probe Station Selection for Fault Detection in Wireless Sensor Networks

Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by only assigning the fault detection task to the manager node the whole network is out of balance, and this quickly overloads the already heavily burdened manager node, which in turn ultimately shortens the lifetime of the whole network. Secondly, probing with a fixed frequency often generates too much useless network traffic, which results in a waste of the limited network energy. Thirdly, the traditional algorithm for choosing a probing node is too complicated to be used in energy-critical wireless sensor networks. In this paper, we study the distribution characters of the fault nodes in wireless sensor networks, validate the Pareto principle that a small number of clusters contain most of the faults. We then present a Simple Random Sampling-based algorithm to dynamic choose sensor nodes as probe stations. A dynamic adjusting rule for probing frequency is also proposed to reduce the number of useless probing packets. The simulation experiments demonstrate that the algorithm and adjusting rule we present can effectively prolong the lifetime of a wireless sensor network without decreasing the fault detected rate

Design and Evaluation of IoT-Enabled Instrumentation for a Soil-Bentonite Slurry Trench Cutoff Wall

In this work, we describe our approach and experiences bringing an instrumented soil-bentonite slurry trench cutoff wall into a modern IoT data collection and visualization pipeline. Soil-bentonite slurry trench cutoff walls have long been used to control ground water flow and contaminant transport. A Raspberry Pi computer on site periodically downloads the sensor data over a serial interface from an industrial datalogger and transmits the data wirelessly to a gateway computer located 1.3 km away using a reliable transmission protocol. The resulting time-series data is stored in a MongoDB database and data is visualized in real-time by a custom web application. The system has been in operation for over two years achieving 99.42% reliability and no data loss from the collection, transport, or storage of data. This project demonstrates the successful bridging of legacy scientific instrumentation with modern IoT technologies and approaches to gain timely web-based data visualization facilitating rapid data analysis without negatively impacting data integrity or reliability. The instrumentation system has proven extremely useful in understanding the changes in the stress state over time and could be deployed elsewhere as a means of on-demand slurry trench cutoff wall structural health monitoring for real-time stress detection linked to hydraulic conductivity or adapted for other infrastructure monitoring applications

Using the RPL Protocol for Supporting Passive Monitoring in the Internet of Things

International audienceMost devices deployed in the Internet of Things (IoT) are expected to suffer from resource constraints. Using specialized tools on such devices for monitoring IoT networks would take away precious resources that could otherwise be dedicated towards their primary task. In many IoT applications such as Advanced Metering Infrastructure (AMI) networks, higher order devices are expected to form the backbone infrastructure, to which the constrained nodes would connect. It would, as such, make sense to exploit the capabilities of these higher order devices to perform network monitoring tasks. We propose in this paper a distributed monitoring architecture that takes benefits from specificities of the IoT routing protocol RPL to passively monitor events and network flows without having impact upon the resource constrained nodes. We describe the underlying mechanisms of this architecture, quantify its performances through a set of experiments using the Cooja environment. We also evaluate its benefits and limits through a use case scenario dedicated to anomaly detection

Mitigation of Topological Inconsistency Attacks in RPL based Low Power Lossy Networks

International audienceRPL is a routing protocol for low-power and lossy networks. A malicious node can manipulate header options used by RPL to create topological inconsistencies, thereby causing denial of service attacks, reducing channel availability, increased control message overhead, and higher energy consumption at the targeted node and its neighborhood. RPL overcomes these topological inconsistencies via a fixed threshold, upon reaching which all subsequent packets with erroneous header options are ignored. However, this threshold value is arbitrarily chosen and the performance can be improved by taking into account network characteristics. To address this we present a mitigation strategy that allows nodes to dynamically adapt against a topological inconsistency attack based on the current network conditions. Results from our experiments show that our approach outperforms the fixed threshold and mitigates these attacks without significant overhead

The Minimum Scheduling Time for Convergecast in Wireless Sensor Networks

We study the scheduling problem for data collection from sensor nodes to the sink node in wireless sensor networks, also referred to as the convergecast problem. The convergecast problem in general network topology has been proven to be NP-hard. In this paper, we propose our heuristic algorithm (finding the minimum scheduling time for convergecast (FMSTC)) for general network topology and evaluate the performance by simulation. The results of the simulation showed that the number of time slots to reach the sink node decreased with an increase in the power. We compared the performance of the proposed algorithm to the optimal time slots in a linear network topology. The proposed algorithm for convergecast in a general network topology has 2.27 times more time slots than that of a linear network topology. To the best of our knowledge, the proposed method is the first attempt to apply the optimal algorithm in a linear network topology to a general network topology

BARI+: A Biometric Based Distributed Key Management Approach for Wireless Body Area Networks

Wireless body area networks (WBAN) consist of resource constrained sensing devices just like other wireless sensor networks (WSN). However, they differ from WSN in topology, scale and security requirements. Due to these differences, key management schemes designed for WSN are inefficient and unnecessarily complex when applied to WBAN. Considering the key management issue, WBAN are also different from WPAN because WBAN can use random biometric measurements as keys. We highlight the differences between WSN and WBAN and propose an efficient key management scheme, which makes use of biometrics and is specifically designed for WBAN domain

A Component-based Approach for Service Distribution in Sensor Networks

ABSTRACT The increasing number of distributed applications over Wireless Sensor Networks (WSNs) in ubiquitous environments raises the need for high-level mechanisms to distribute sensor services and integrate them in modern IT systems. Existing work in this area mostly focuses on low-level networking issues, and fails to provide high-level and off-the-shelf programming abstractions for this purpose. In this paper, we therefore consider WSN programming models and service distribution as two interrelated factors and we present a new component-based abstraction for integrating WSNs within existing IT systems. Our approach emphasizes on reifying distribution strategies at the software architecture level, thus allowing remote invocation of component services, and facilitating interoperability of sensor services with the Internet through Web service-enabled components. The latter is efficiently provided by incorporating the REST architectural style-emphasizing on abstraction of high-level services as resources-to our component-based framework. The preliminary evaluation results show that the proposed framework has an acceptable memory overhead on a TelosB sensor platform