International Journal of Sensors Wireless Communications and Control - Current Issue

The Internet of Things (IoT) devices consist of a microcontroller unit for data processing, a low-power wireless radio module for data transmission, and various sensors for data collection. The sensor nodes and processing devices used in the Internet of Things are resource-constrained, with power consumption and security being the two most critical parameters.

This paper addresses the challenges of power consumption and security in IoT scenarios. It presents a low-power and secure heterogeneous multicore sensing architecture designed for low-power IoT and wireless sensor networks. The architecture comprises a sensing and control subsystem, an information processing unit, and a wireless communication module.

The architecture uses a microcontroller unit based on ARM Cortex M4, a low-power sub-1 GHz RF-compliant communication radio, and a few sensors. The proposed architecture has been implemented and tested using the Contiki Operating System.

The implemented sensor node architecture demonstrated performance efficiency, lower energy consumption, and higher security.

By leveraging efficient power management, data transmission strategies, and cryptographic security, the architecture contributes to developing energy-efficient and secure IoT devices.

Spectrum scarcity, spectrum efficiency, power constraints, and jamming attacks are core challenges that face wireless networks. While cognitive radio networks (CRNs) enable the sharing of licensed bands when they are unoccupied, the spectrum should be used efficiently by the secondary user (SU) to ensure a high data rate transmission. In addition, the mobility of the SUs makes power consumption a matter of concern in wireless networks. Because of the open environment, the jamming attack can easily deteriorate the performance and disrupt the connections.

We aim to enhance the performance of CRN and establish more reliable connections for the SU in the presence of smart jammer by ensuring efficient spectrum utilization and extending the network lifetime.

To achieve our objectives, we propose an anti-jamming approach that adopts frequency hopping. Our approach assumes that SUs observe spectrum availability and channel gain. Then, SU learns the jammer behaviour and goes for the appropriate policy in terms of the number of data and control channels that optimize jointly spectrum efficiency and power consumption. Within, the interaction between the SU and the jammer is modelled as a zero-sum stochastic game, and we employ reinforcement learning (RL) to address this game.

SUs learn the optimal policy that maximizes the spectrum efficiency and minimizes the power consumption in the presence of a smart jammer. Simulation results show that the low channel gain leads the SU to select a high number of data channels. However, when the channel gain is high, the SU increases the number of control channels to guarantee a more reliable connection. Taking into account the spectrum efficiency, SUs save their energy by decreasing the number of used channels. The proposed strategy achieves better performance in comparison with myopic learning and the random strategy.

Under a jamming attack, considering the gain of utilized channels, SUs select the appropriate number of control and data channels to ensure a reliable, efficient, and long-term connection.

In wireless sensor networks (WSNs), hierarchical clustered routing protocols play a crucial role in minimizing energy consumption. The Low Energy Adaptive Clustering Hierarchy (LEACH) architecture is commonly employed for application-specific protocols in WSNs. However, the LEACH protocol may lead to increased energy consumption within the network if the rotational distribution of cluster heads (CHs) is not considered.

A novel average energy, residual energy-based modified LEACH (aerem-LEACH) routing protocol for improving the WSN’s energy efficiency is proposed. This approach simultaneously considers the average energy of the networks and the residual node energy for routing, thereby reducing overall power consumption.

The suggested approach in aerem-LEACH accounts for optimal CHs numbers, and nodes in close proximity to the sink are forbidden from participating in cluster formation in order to achieve sufficient performance in the form of reduced sensor node energy consumption. Furthermore, a new threshold is employed in the proposed approach for selecting CHs for the network, and the aerem-LEACH uses free space, multiple hopping, and a hybrid communicating model for an energy-efficient network.

The simulation result demonstrates that there is a substantial reduction in the consumption of energy in WSNs with the proposed aerem-LEACH routing protocol compared with existing routing protocols, namely Stable Energy Efficient Network (SEEN), Energy Efficient LEACH (EE LEACH), Optical LEACH (O-LEACH), LEACH-Mobile (LEACH-M), LEACH-Centralized (LEACH-C), and LEACH for small-scale as well as large-scale sensor field.