An adaptive optimized handover decision model for heterogeneous networks.

A heterogeneous network (HetNet), combining different technologies, is considered a promising solution adopted by several upcoming generations of mobile networks to keep up with the rapid development of mobile users' requirements while improving network performance. In this scenario, a vertical handover (VHO) algorithm is responsible for ensuring the continuity of the ongoing user connection while moving within the coverage of the HetNet. Although various VHO algorithms were proposed, achieving efficient performance from both network and user perspectives remains challenging. This paper proposes an adaptive optimized vertical handover algorithm based on a multi-attribute decision-making (MADM) algorithm integrated with particle swarm optimization and gravitational search algorithm (PSOGSA) as a framework to implement the handover process. The algorithm includes three main ideas. Firstly, a network selection framework is proposed considering the most important criteria, including signal strength and other networks' attributes, along with users' characteristics regarding their mobility and service preferences. Secondly, two new parameters are introduced as control handover parameters named load factor (LF) and score priority (SP) to reduce unnecessary handovers and the overall HetNet power consumption while achieving balanced load distribution. Lastly, the desired aims are formulated as an objective function, then the PSOGSA algorithm is used to reach the optimal values of both LF and SP, which will be considered when executing the handover algorithm. The presented algorithm is simulated in a heterogeneous wireless network where the fifth-generation (5G) wireless technology coexists with other radio access networks to improve the evaluation field of the proposed algorithm. Also, the proposed algorithm's performance is evaluated in the case of using various MADM algorithms. The simulation results show that the proposed adaptive optimized approach attains efficient performance by decreasing unnecessary handovers by more than 40% and achieving much better load distribution by around 20% to 40%, outperforming traditional handover approaches.

Enhancement of the performance of wireless sensor networks using the multihop multiantenna power beacon path selection method in intelligent structures.

Sensor nodes are the building blocks of wireless sensor networks (WSNs), which may gather, analyze, and transmit various types of information to a certain destination. Data collection and transmission to the destination are the main responsibilities of sensor nodes at specified time intervals. However, one of the biggest issues with WSNs is the creation of energy-efficient wireless network algorithms. In this paper, a multi-hop multi-antenna power beacon path selection (MMPS) protocol is proposed. The proposed approach consists of a source, a destination, relays, power beacons generating radio frequency (RF) signals for energy harvesting, and eavesdroppers. We used physical layer security associated with energy harvesting to protect data from eavesdroppers without requiring higher layer data encryption and enhance the energy consumption of wireless networks. The signal's broadcast strength must be high enough to allow for energy harvesting while being low enough to prevent eavesdropping. The process continues until the data reaches the destination. Comparing the performance of MMPS with those of conventional methods, MMPS enhanced the wireless network outage probability (OP) up to 99.7%, life time, energy consumption, protection from eavesdroppers, and more resistant to hardware impairments which increased the immunity up to 95%.