Mathew L. Wymore

A Robust Time Synchronization Scheme for Industrial Internet of Things

Energy-efficient and robust-time synchronization is crucial for industrial Internet of things (IIoT). Some energy-efficient time synchronization schemes that achieve high accuracy have been proposed recently. However, some unsynchronized nodes namely isolated nodes exist in the schemes. To deal with the problem, this paper presents R-Sync, a robust time synchronization scheme for IIoT. We use a pulling timer to pull isolated nodes into synchronized networks whose initial value is set according to level of spanning tree. Then, another timer is set up to select backbone node and its initial value is related to the distance to parent node. Moreover, we do experiments based on simulation tool NS-2 and testbed based on wireless hardware nodes. The experimental results show that our approach makes all the nodes get synchronized and gets the better performance in terms of accuracy and energy consumption, compared with three existing time synchronization algorithms TPSN, GPA, STETS.

Optimized barrier location for barrier coverage in mobile sensor networks

Barrier coverage is an important application of sensor networks. This paper studies how to build a strong barrier with mobile sensors in which the maximum moving distance of sensors is minimized. Our work differs from others in the way the y-coordinate of the barrier is determined. We optimize the y-coordinate of the barrier instead of fixing it a priori. An efficient algorithm is proposed, in which the search space of the y-coordinate of the barrier is first discretized and then searched over iteratively. In the theoretical worst case, O(N4) iterations may be needed to find the optimal barrier location, where N is the number of sensors, but in practice, our algorithm requires less than O(N2) iterations, as confirmed in simulation.

EDAD: Energy-centric data collection with anycast in duty-cycled wireless sensor networks

Recent efforts in applying anycast techniques to duty-cycled wireless sensor networks have shown promising results in terms of reduced delay and energy consumption. This paper further increases the energy savings by introducing EDAD, an energy-centric cross-layer data collection protocol designed for anycast communications in asynchronously duty-cycled wireless sensor networks. EDAD uses a new anycast routing metric, EEP, that minimizes the expected energy consumed along the path of a packet and automatically adapts to network settings. Simulation results show that EDAD consumes less energy than similar existing protocols, while maintaining a comparable delay and high delivery rate.

Cost-efficient barrier coverage with a hybrid sensor network under practical constraints

Barrier coverage is a natural application of sensor networks in which sensors are deployed to detect intruders or protect crucial resources. In this paper, we consider a hybrid sensor network with a two-phase deployment, in which less-expensive static sensors are first randomly deployed in an area, and then more-expensive mobile sensors are deployed to fill coverage gaps. We use a probabilistic model to take into account the practical constraints of detection probability and false positives. We propose an iterative scheme that finds a sensor deployment strategy that minimizes the total sensor cost. Our scheme makes use of a graph transformation and includes speed-up strategies. We present simulation results that verify the correctness of the proposed scheme and demonstrate the effectiveness of the speed-up strategies.

BladeMAC: Radio duty-cycling in a dynamic, cyclical channel

As wind energy continues to expand to new frontiers in terms of the location, number, and size of wind turbines, the industry has begun to seek smarter operations and management solutions. Wireless sensing nodes could provide a low-cost platform to support a variety of applications designed to reduce the levelized cost of energy and increase the safety of wind turbines. However, a wireless sensor node deployed on a wind turbine blade would have an extremely limited energy supply. To combat this limitation, we present BladeMAC, a new MAC-layer protocol designed for sensor nodes deployed on rotating wind turbine blades. BladeMAC overcomes a unique cyclical channel problem to allow a sensor node attached to a rotating blade to opportunistically and efficiently offload its data to a sink node attached to the turbine tower. We have implemented and evaluated BladeMAC using Contiki OS and the Cooja simulation tool. We present results showing that BladeMAC effectively deals with the cyclical channel problem at a wide range of data arrival intervals, and that BladeMAC is insensitive to rotation speed and rotation speed fluctuations.

An iterative method for strong barrier coverage under practical constraints

Barrier coverage is a fundamental application for wireless sensor networks. In this paper, we consider a practical probabilistic sensing model and propose an iterative scheme, called BaCo, to provide strong barrier coverage under this model, with the objective of minimizing the number of active sensors. Moreover, we build the barrier under practical constraints of minimum detection probability and maximum false alarm probability. We use simulations to show that BaCo converges quickly and achieves better results than previous work while also bounding the system false alarm probability.

DiVA: Distributed Voronoi-based acoustic source localization with wireless sensor networks

This paper presents DiVA, a novel hybrid range-free and range-based acoustic source localization scheme that uses an ad-hoc network of microphone sensor nodes to produce an accurate estimate of the sources location in the presence of various real-world challenges. DiVA uses range-free pairwise comparisons of sound detection timestamps between local Voronoi neighbors to identify the node closest to the acoustic source, which then estimates the sources location using a constrained range-based method. Through simulation and experimental evaluations, DiVA is shown to be accurate and highly robust, making it practical for real-world applications.