Mobile sensor networks (MSNs) have emerged from the interaction between mobile robotics and wireless sensor networks. MSNs can be deployed in harsh environments, where failures in some nodes can partition MSNs into disconnected network segments or reduce the coverage area. A $k$ -connected network can tolerate at least $k$ -1 arbitrary node failures without losing its connectivity. In this study, we present a coverage-aware distributed $k$ -connectivity maintenance (restoration) algorithm that generates minimum-cost movements of active nodes after a node failure to preserve a persistent $k$ value subject to a coverage conservation criterion. The algorithm accepts a coverage conservation ratio (as a trade-off parameter between coverage and movements) and facilitates coverage with the generated movements according to this value. Extensive simulations and testbed experiments reveal that the proposed algorithm restores $k$ -connectivity more efficiently than the existing restoration algorithms. Furthermore, our algorithm can be utilized to maintain $k$ -connectivity without sacrificing the coverage, significantly.

A Wireless Sensor Network (WSN) is connected if a communication path exists among each pair of sensor nodes (motes). Maintaining reliable connectivity in WSNs is a complicated task, since any failure in the nodes can cause the data transmission paths to break. In a k-connected WSN, the connectivity survives after failure in any k-1 nodes; hence, preserving the k-connectivity ensures that the WSN can permit k-1 node failures without wasting the connectivity. Higher k values will increase the reliability of a WSN against node failures. We propose a simple and efficient algorithm (PINC) to accomplish movement-based k-connectivity restoration that divides the nodes into the critical, which are the nodes whose failure reduces k, and non-critical groups. The PINC algorithm pickups and moves the non-critical nodes when a critical node stops working. This algorithm moves a non-critical node with minimum movement cost to the position of the failed mote. The measurements obtained from the testbed of real IRIS motes and Kobuki robots, along with extensive simulations, revealed that the PINC restores the k-connectivity by generating optimum movements faster than its competitors.

The heating system and related thermostat is an important part of any home. As part of a solution for an intelligent home, the thermostat needs to behave in a way that controls the heating system to save the energy by providing automatic adjustments. In this paper, an IoT based smart thermostat is designed and implemented. The nodes in the system consist of DHT22 temperature sensors connected to Arduinos and communicating with each other through nRF24L01 modules. The sink node uses an ESP8266 to the Internet. The system can interact with authorized family members through a mobile application by sending push notifications. They also can adjust the home heating settings via this application. In this way, the system can intelligently turn the heating system on or off considering the availability of people at home. In addition, the system can adjust the rooms' temperature automatically and save the energy.