Weighted Salp Swarm and Salp Swarm Algorithms in FiWi access network: A new paradigm for ONU placement

Fiber Wireless (FiWi) access network is a promising next generation broadband access network as it provides high bandwidth, better stability and anywhere-anytime connection at lower cost to the users. It integrates the wireless access network and optical access network at front-end and back-end respectively. Optimizing the ONUs position plays an important role in FiWi network as it affects the network performance and network cost. The present work focuses on ONU placement problem and proposes an efficient algorithms for optimizing the ONU?s position. A nature inspired Salp Swarm Algorithm (SSA) and Weighted Salp Swarm Algorithm (WSSA) are applied for optimal placement of ONUs based on different configurations of wireless routers and ONUs. To the best of our knowledge, these algorithms have never been used in the field of FiWi network. These novel algorithms optimize ONU?s position to minimize cost function of the network. Cost function is the average distance between an ONU and its primary wireless routers. An extensive simulation is performed to analyze the effectiveness of the proposed work. The results of proposed algorithms are compared with the well known existing Whale optimization algorithm (WOA). Results show that the proposed WSSA and SSA outperform the WOA. WSSA provides better result than SSA and WOA in terms of lower cost function value, more number of routers connected in 1-hop, increased average ONU connectivity (AONUC), faster convergence rate and lesser execution time. SSA provides better result than the WOA algorithm. It is shown in the result that the uniform placement of ONUs gives the best result than the random placement of ONUs for all the algorithms.

Automated summary

Fiber Wireless (FiWi) access network integrates wireless and optical access networks to provide high bandwidth and stability at lower cost. Optimizing ONU placement is crucial for network performance and cost reduction. Proposed Salp Swarm Algorithm (SSA) and Weighted Salp Swarm Algorithm (WSSA) outperform existing Whale optimization algorithm (WOA) in terms of cost, connectivity, convergence rate, and execution time.