CRSN Energy-Efficient Mechanism Based on Dynamic Spectrum Access and Asynchronous Sleep-Wake Scheduling

Abstract

Cognitive Radio Sensor Network (CRSN) is considered as a viable wireless networking paradigm solution to address the issues of spectrum underutilization and uncontrollable interferences in Wireless Sensor Network (WSN) due to wireless sensor devices proliferation. However, CRSN itself is the technology is faced with several challenges such as interference in the wireless channels, operational complexities, poor Quality of Service (QoS), and high energy consumption. These challenges are mainly inherited from both the Cognitive Radio (CR) and the WSN. In particular, the high energy consumption is due to wireless nodes performing channel sensing and switching, data transmission and re-transmission due to packet loss. Therefore, an energy-efficient mechanism is required to ensure that sensor nodes are not crippled by fast energy depletion. This is addressed in this research by employing two strategies: Sensor-Medium Access Control (S-MAC) protocol and the K-Means clustering algorithm. These strategies are designed and implemented in the CRSN to improve the existing energy-aware mechanism and to minimize high energy consumption. K-Means clustering reduces the overall network complexities by partitioning the network into sub-networks while the S-MAC protocol proffers periodic and asynchronous data transmission and sleep-wake cycles to control the flow of data and reduce interferences in the network. To evaluate the performance and effectiveness of the solution, simulations were conducted on six S-MAC's duty cycles of 3%, 5%, 10%, 15%, 25%, and 50% and assessed using metrics such as throughput, average consumed energy, residual energy and delay. The simulation results show the higher attainable efficiency for 10% S-MAC's duty in all six metrics than the other simulated duty cycles considered. Based on the simulations conducted, the 10% duty has the highest attainable efficiency due to the minimized duty cycle, and this lead to selecting it for the best possible implementation of an energy-efficient mechanism in a real world CRSN.