Using mobile sinks in wireless sensor networks to improve building emergency response.

We propose an opportunistic routing scheme for wireless sensor networks operating in volatile environments. In particular, we consider a sensor field for sensing and reporting on buildings during fires, where sensors are progressively being destroyed by the fire. We envisage firefighters equipped with small computers which can act as mobile sink nodes, offering transient shorter routes for relaying data, and offering connectivity to disconnected areas of the network. We examine different ways in which these uncontrolled mobile sinks could enhance performance, and develop protocols for advertising the presence of the mobile sinks, gathering data for forwarding, and prioritising disconnected regions. We evaluate the performance in simulation, and on randomly damaged networks, we show that we can increase the data delivery by up to 50%

Autonomous discovery and repair of damage in Wireless Sensor Networks

Wireless Sensor Networks in volatile environments may suffer damage, and connectivity must be restored. The repairing agent must discover surviving nodes and damage to the physical and radio environment as it moves around the sensor field to execute the repair. We compare two approaches, one which re-generates a full plan whenever it discovers new knowledge, and a second which attempts to minimise the required number of new radio nodes. We apply each approach with two different heuristics, one which attempts to minimise the cost of new radio nodes, and one which aims to minimise the travel distance. We conduct extensive simulation-based experiments, varying key parameters, including the level of damage suffered, and comparing directly with the published state-of-the-art. We quantify the relative performance of the different algorithms in achieving their objectives, and also measure the execution times to assess the impact on being able to make autonomous decisions in reasonable time

Restoring wireless sensor network connectivity in damaged environments

A wireless sensor network can become partitioned due to node failure, requiring the deployment of additional relay nodes in order to restore network connectivity. This introduces an optimisation problem involving a tradeoff between the number of additional nodes that are required and the costs of moving through the sensor field for the purpose of node placement. This tradeoff is application-dependent, influenced for example by the relative urgency of network restoration. We propose four heuristic algorithms which integrate network design with path planning, recognising the impact of obstacles on mobility and communication. We conduct an empirical evaluation of the four algorithms on random connectivity and mobility maps, showing their relative performance in terms of node and path costs, and assessing their execution speeds. Finally, we examine how the relative importance of the two objectives influences the choice of algorithm

Integration of node deployment and path planning in restoring network connectivity

A wireless sensor network can become partitioned due to node failure, requiring the deployment of additional relay nodes in order to restore network connectivity. This introduces an optimisation problem involving a tradeoff between the number of additional nodes that are required and the costs of moving through the sensor field for the purpose of node placement. This tradeoff is application-dependent, influenced for example by the relative urgency of network restoration. We propose two heuristic algorithms which integrate network design with path planning, recognising the impact of obstacles on mobility and communication. We conduct an empirical evaluation of the two algorithms on random connectivity and mobility graphs, showing their relative performance in terms of node and path costs, and assessing their execution speeds. Finally, we examine how the relative importance of the two objectives influences the choice of algorithm

Demo: Deploying a drone to restore connectivity in a WSN

This paper describes our demonstration of a network repair problem where a drone places a new sensor node to replace a failed node in order to heal the connectivity for a Wireless Sensor Network (WSN). It serves to show the potential of our published solutions for automated network repair when the repairing agent is a drone

Repairing Wireless Sensor Network connectivity with mobility and hop-count constraints

Wireless Sensor Networks can become partitioned due to node failure or damage, and must be repaired by deploying new sensors, relays or sink nodes to restore some quality of service. We formulate the task as a multi-objective problem over two graphs. The solution specifies additional nodes to reconnect a connectivity graph subject to network path-length constraints, and a path through a mobility graph to visit those locations. The objectives are to minimise both the cost of the additional nodes and the length of the mobility path. We propose two heuristic algorithms which prioritise the different objectives. We evaluate the two algorithms on randomly generated graphs, and compare their solutions to the optimal solutions for the individual objectives. Finally, we assess the total restoration time for different classes of agent, i.e. small robots and larger vehicles, which allows us to trade-off longer computation times for shorter mobility paths

Multi-objective hierarchical algorithms for restoring Wireless Sensor Network connectivity in known environments

A Wireless Sensor Network can become partitioned due to node failure, requiring the deployment of additional relay nodes in order to restore network connectivity. This introduces an optimisation problem involving a tradeoff between the number of additional nodes that are required and the costs of moving through the sensor field for the purpose of node placement. This tradeoff is application-dependent, influenced for example by the relative urgency of network restoration. We propose a family of algorithms based on hierarchical objectives including complete algorithms and heuristics which integrate network design with path planning, recognising the impact of obstacles on mobility and communication. We conduct an empirical evaluation of the algorithms on random connectivity and mobility graphs, showing their relative performance in terms of node and path costs, and assessing their execution speeds. Finally, we examine how the relative importance of the two objectives influences the choice of algorithm. In summary, the algorithms which prioritise the node cost tend to find graphs with fewer nodes, while the algorithm which prioritise the cost of moving find slightly larger solutions but with cheaper mobility costs. The heuristic algorithms are close to the optimal algorithms in node cost, and higher in mobility costs. For fast moving agents, the node algorithms are preferred for total restoration time, and for slow agents, the path algorithms are preferred

MICROENCAPSULATION OF MERCAPTAN USING POLYCAPROLACTONE AS SHELL MATERIAL TOWARD SELF-HEALING COATING APPLICATIONS

Polymer materials incorporating microencapsulated self-healing agents have a wide range of application from paint coating, anti-corrosion coatings to automotive and construction materials. In this research, microcapsules containing reactive mercaptan compound for use in self healing polymers were successfully fabricated via the oil-in-water emulsion method. We employed for the first time the UV-initiated thiol-ene reaction between an alkene-functionalized polycaprolactone and a tetrathiol compound to form the microcapsule shell. To synthesize microcapsules, the tetrathiol was used in large excess, thus maintaining inside the microcapsules as the core material. The obtained microcapsules were analyzed by Fourier Transform infrared microscopy, optical microscopy, scanning electron microscopy (SEM) and laser diffraction particle size analysis. The core was extracted by Soxhlet extraction and analyzed by 1H NMR and FTIR spectroscopy

Demonstration of robotic repair for wireless networks

This paper describes our demonstration of a network repair problem where a robot bridges a gap between two disconnected wireless nodes by searching for a good position and moving there to forward data between the two nodes. It serves to show the potential for our published solutions for automated network repair. A simple Adhoc network consists of two Intel Galileo Gen 2 nodes exchanging messages and an NXT Mindstorm robot with another Galileo on board healing the network connection between the two Galileos in the case the two get disconnected. The demo showcases a solution that employs mobile agents to serve as relays to bridge the connectivity gaps in the wireless network