Reem Ibrahim Alkanhel¹, Doaa Sami Khafaga², Ahmed Mohamed Zaki³, Marwa M. Eid^4,5, Abdyalaziz A. Al-Mooneam⁶, Abdelhameed Ibrahim⁷, S. K. Towfek^3,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3549-3568, 2024, DOI:10.32604/cmc.2024.049582

Abstract The networks of wireless sensors provide the ground for a range of applications, including environmental monitoring and industrial operations. Ensuring the networks can overcome obstacles like power and communication reliability and sensor coverage is the crux of network optimization. Network infrastructure planning should be focused on increasing performance, and it should be affected by the detailed data about node distribution. This work recommends the creation of each sensor’s specs and radius of influence based on a particular geographical location, which will contribute to better network planning and design. By using the ARIMA model for time… More >

K. Saravanan^1,*, G. M. Tamilselvan², A. Rajendran³

Computer Systems Science and Engineering, Vol.42, No.3, pp. 1063-1077, 2022, DOI:10.32604/csse.2022.020789

Abstract As huge users are involved, there is a difficulty in spectrum allocation and scheduling in Cognitive Radio Networks (CRNs). Collision increases when there is no allocation of spectrum and these results in huge drop rate and network performance degradation. To solve these problems and allocate appropriate spectrum, a novel method is introduced termed as Quality of Service (QoS) Improvement Proper Scheduling (QIPS). The major contribution of the work is to design a new cross layer QoS Aware Scheduling based on Loss-based Proportional Fairness with Multihop (QoSAS-LBPFM). In Medium Access Control (MAC) multi-channel network environment mobile More >

Karunanithi Praveen kumar, Perumal Sivanesan^*

Computer Systems Science and Engineering, Vol.41, No.1, pp. 67-82, 2022, DOI:10.32604/csse.2022.018867

Abstract In this work, we propose a context-aware switching of routing protocol scheme for specific application requirements of IoT in real-time using a software-defined networking controller in wireless sensor networks. The work planned has two stages i) Selection of suitable routing protocol (RP) for given IoT applications using higher cognitive process and ii) Deployment of the corresponding routing protocol. We use the supervised learning-regression method for classification of the routing protocol while considering the network parameters like stability, path delay, energy utilization, and throughput. The chosen routing protocol will be set in the sensor network using… More >