Reduction in Average Distance Cost by Optimizing Position of ONUs in FiWi Access Network using Grey Wolf Optimization Algorithm

Chouhan, Nitin; Bhatt, Uma Rathore; Upadhyay, Raksha

doi:10.1007/978-981-33-6977-1_8

Cited by 6 publications

(4 citation statements)

References 20 publications

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“…This includes the enhancement of network performance by physical layer transmissions, high throughput, and delay management. 4,[15][16][17][18] Previous methods focused only on routing and throughput efficiency which increased the cost and energy consumption in various applications. Therefore, models that involve minimizing energy consumption in communication via FiWi are necessary and have been presented.…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, delay-differentiated routing algorithm, capacity and delay aware routing (CaDAR), and risk-and-delay aware routing (RADAR) algorithm DDRA) and delay-aware routing algorithms were available. 5,14,15 Most of these previous studies formulated routing in FiWi access networks as an optimization problem and obtained results mainly employing simulation. Even though routing in a network plays a significant role in the enhancement of the communication system other aspects like information source placement, transmitter, receiver, and communication channel also should be improved.…”

Section: Introductionmentioning

confidence: 99%

“…Design of routing algorithms for the wireless front‐end only or for both the wireless and optical domains of FiWi access networks has received a great deal of attention, resulting in a large number of wireless, integrated optical‐wireless, multipath, and energy‐aware routing algorithms. Similarly, delay‐differentiated routing algorithm, capacity and delay aware routing (CaDAR), and risk‐and‐delay aware routing (RADAR) algorithm DDRA) and delay‐aware routing algorithms were available 5,14,15 . Most of these previous studies formulated routing in FiWi access networks as an optimization problem and obtained results mainly employing simulation.…”

Section: Introductionmentioning

confidence: 99%

“…Even though routing in a network plays a significant role in the enhancement of the communication system other aspects like information source placement, transmitter, receiver, and communication channel also should be improved. This includes the enhancement of network performance by physical layer transmissions, high throughput, and delay management 4,15‐18 . Previous methods focused only on routing and throughput efficiency which increased the cost and energy consumption in various applications.…”

Section: Introductionmentioning

confidence: 99%

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CSAT‐FRMET: An energy‐efficient hybrid FiWi network‐based 5G model

Kali Raman,

Saini

2023

Trans Emerging Tel Tech

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Hybrid fiber wireless (FiWi) access networks seek to combine the vast amount of bandwidth that is available for optical networks and wireless network mobility; hence, it favors larger bandwidth request but cause the highly nonlinear lagrangian dual problem that decrease energy‐efficient network resilience. Hence, a novel Ceplato‐SAT3 model has been proposed in which the SAT3 algorithm locates the optical network unit (ONU) in an optimal position with high‐speed cost‐efficient placement and weight factor introduced into the position update to improve the exploitation and exploration capability of the algorithm. To prioritize the large bandwidth request during resource allocation, gradient priority justifier requests (GPJR) has been utilized and a novel messaging technique termed flow‐random‐message‐exchanger‐topology (FRMET) provides the index for these prioritized requests depending on QoS parameters such as notification control, reflective QoS attribute (RQA), flow bit rates and maximum packet loss rate thereby decreasing the overhead and eliminate nonlinear langrage dualand perform O2U scheduling to reduce network resilience however synchronization between different ONU clocks may cause upstream data fatal crash at the optical line terminal (OLT). Hence, curl‐trio‐opt control mechanism has been proposed in which the minimization problem is transformed into a joint optimization problem of energy consumption, traffic demand, network requests, and service flow requests by the Lyapunov technique thereby minimizing the upstream data fatal lash. The proposed model has been implemented in Python and the output obtained showed better performance in terms of ONU arrangement, throughput, energy consumption, computation, latency, and error.

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