Enabling Cross-technology Communication from LoRa to ZigBee in the 2.4 GHz Band

IEEE 802.15.4-based wireless sensor-actuator networks have been widely adopted by process industries in recent years because of their significant role in improving industrial efficiency and reducing operating costs. Today, industrial wireless sensor-actuator networks are becoming tremendously larger and more complex than before. However, a large, complex mesh network is hard to manage and inelastic to change once the network is deployed. In addition, flooding-based time synchronization and information dissemination introduce significant communication overhead to the network. More importantly, the deliveries of urgent and critical information such as emergency alarms suffer long delays, because those messages must go through the hop-by-hop transport. A promising solution to overcome those limitations is to enable the direct messaging from a long-range radio to an IEEE 802.15.4 radio. Then messages can be delivered to all field devices in a single-hop fashion. This article presents our study on enabling the cross-technology communication from LoRa to ZigBee using the energy emission of the LoRa radio as the carrier to deliver information. Experimental results show that our cross-technology communication approach provides reliable communication from LoRa to ZigBee with the throughput of up to 576.80 bps and the bit error rate of up to 5.23% in the 2.4 GHz band.

Energy sink-holes avoidance method based on fuzzy system in wireless sensor networks

The existence of a mobile sink for gathering data significantly extends wireless sensor networks (WSNs) lifetime. In recent years, a variety of efficient rendezvous points-based sink mobility approaches has been proposed for avoiding the energy sink-holes problem nearby the sink, diminishing buffer overflow of sensors, and reducing the data latency. Nevertheless, lots of research has been carried out to sort out the energy holes problem using controllable-based sink mobility methods. However, further developments can be demonstrated and achieved on such type of mobility management system. In this paper, a well-rounded strategy involving an energy-efficient routing protocol along with a controllable-based sink mobility method is proposed to extirpate the energy sink-holes problem. This paper fused the fuzzy A-star as a routing protocol for mitigating the energy consumption during data forwarding along with a novel sink mobility method which adopted a grid partitioning system and fuzzy system that takes account of the average residual energy, sensors density, average traffic load, and sources angles to detect the optimal next location of the mobile sink. By utilizing diverse performance metrics, the empirical analysis of our proposed work showed an outstanding result as compared with fuzzy A-star protocol in the case of a static sink.

A Secure Energy Aware Game Theory (SEGaT) Mechanism for Coordination in WSANs

A novel secure energy aware game theory (SEGaT) method has proposed to have better coordination in wireless sensor actor networks. An actor has a cluster of sensor nodes which is required to perform different action based on the need that emerge in the network individually or sometime with coordination from other actors. The method has different stages for the fulfilment of these actions. Based on energy aware actor selection (EAAS), selection of number of actors and their approach is the initial step followed by the selection of best team of sensors with each actor to carry out the action and lastly the selection of reliable node within that team to finally nail the action into place in the network for its smooth working and minimum compromise in the energy The simulations are done in MATLAB and result of the energy and the packet delivery ratio are compared with game theory (GaT) and real time energy constraint (RTEC) method. The proposed protocol performs better in terms of energy consumption, packet delivery ratio as compared to its competitive protocols.

Adaptive Monitor Placement for Near Real-time Node Failure Localisation in Wireless Sensor Networks

As sensor-based networks become more prevalent, scaling to unmanageable numbers or deployed in difficult to reach areas, real-time failure localisation is becoming essential for continued operation. Network tomography, a system and application-independent approach, has been successful in localising complex failures (i.e., observable by end-to-end global analysis) in traditional networks. Applying network tomography to wireless sensor networks (WSNs), however, is challenging. First, WSN topology changes due to environmental interactions (e.g., interference). Additionally, the selection of devices for running network monitoring processes (monitors) is an NP-hard problem. Monitors observe end-to-end in-network properties to identify failures, with their placement impacting the number of identifiable failures. Since monitoring consumes more in-node resources, it is essential to minimise their number while maintaining network tomography’s effectiveness. Unfortunately, state-of-the-art solutions solve this optimisation problem using time-consuming greedy heuristics. In this article, we propose two solutions for efficiently applying Network Tomography in WSNs: a graph compression scheme, enabling faster monitor placement by reducing the number of edges in the network, and an adaptive monitor placement algorithm for recovering the monitor placement given topology changes. The experiments show that our solution is at least 1,000× faster than the state-of-the-art approaches and efficiently copes with topology variations in large-scale WSNs.