Highly Efficient Multi Channel Packet Forwarding with Round Robin Intermittent Periodic Transmit for Multihop Wireless Backhaul Networks

Maruta, Kazuki; Furukawa, Hiroshi

doi:10.3390/s17112609

Cited by 5 publications

(4 citation statements)

References 43 publications

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“…For instance, in Fig 3 , we have chosen two video flows of almost equal characteristics, thus fair rate allocation is to give each, half of the channel rate. A kind of fair rate allocation is a Round Robin algorithm [33,34]. The most popular version of RR is the well-known Deficit Round Robin (DRR) algorithm, used in the NS2 simulator [35].…”

Section: Quality Variationmentioning

confidence: 99%

“…On subjective test, using SSCQE, 20 graduate students, on the screen of their laptops watch a series of video sequences and through mouse create a continuous trace of video quality. They were instructed to trace the quality such that within five quality intervals, the trace indicates: excellent (80-100), good (60-79), fair (40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50)(51)(52)(53)(54)(55)(56)(57)(58)(59), poor (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39) and bad (0-19). Please note that, currently most researchers instead of running subjective tests, they use the Netflix video quality meter (VMAF) to get quick results [41].…”

Section: Quality Variationmentioning

confidence: 99%

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PRAM: Penalized Resource Allocation Method for Video Services

Nikoonezhad

Ghanbari

2023

IEEE Trans. Multimedia

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The human visual system response to picture quality degradation due to packet loss is very different from the responses of objective quality measures. While video quality due to packet loss may be impaired by at most for one Group of Pictures (GOP), its subjective quality degradation may last for several GOPs. This has a great impact on resource allocation strategies, which normally make decisions on instantaneous conditions of multiplexing buffer. This is because, when the perceptual impact of degraded video quality is much longer than its objective degradation period, any assigned resources to the degraded flow is wasted. This paper, through both simulations and analysis shows that, during resource allocation, if the quality of a video stream is significantly degraded, it is better to penalize this degraded flow from getting its full bandwidth share and instead assign the remaining share to other flows preventing them from undergoing quality degradation.

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Section: Quality Variationmentioning

confidence: 99%

Section: Quality Variationmentioning

confidence: 99%

PRAM: Penalized Resource Allocation Method for Video Services

Nikoonezhad

Ghanbari

2023

IEEE Trans. Multimedia

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“…The routing protocol used by service providers (SPs) is modified based on inter-SP communication in order to establish a predetermined sleep interval inside the network [26]. The use of this approach results in a 29% enhancement in total performance in comparison to fixed-point scheduling, as stated in reference [27]. The radiation emitted by the source point (SP) is directed towards another SP within a network, resulting in the formation of beamforming [28].…”

Section: Related Workmentioning

confidence: 99%

Data Perturbation for Pervasive Edge Computing Environments Using Iterative Randomised Parallel Variable Perturbation in Wireless Sensor Network

Shukur,

et al. 2023

Preprint

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The reduction in the size of Packet Forwarding Nodes (PFNs) is a direct consequence of technological advancements in wireless sensor networks (WSN). Each node has an extra characteristic that results in diminished energy levels. The dispersed PFNs are arranged in a squared cross-sectional area, where each node functions as a Sensing Point (SP) capable of performing diverse applications such as temperature, ambient humidity, sound, and pressure measurements. The packet is partitioned into many fragments, with each fragment being classified as either having an exact or variable length. Each individual packet is sent over numerous Physical Forwarding Nodes (PFNs) on route to the data centre, using the PFNs as the underlying mechanism for transmission. The choice of route forwarding nodes (PFNs) is determined by their respective trust levels. Within the network, designated Packet Forwarding Nodes (PFNs) are strategically positioned to facilitate the delivery of packets to the data centre, ensuring the integrity of the data is preserved throughout the process. The process of selecting certain PFNs involves the calculation of meeting probability, remaining energy, data weight, and security value. The comparative analysis involves evaluating the Iterative Randomised Parallel Variable Perturbation (IRPVP) method against conventional approaches based on various parameters, including delay, link count, resource energy, healthy PFNs, non-healthy PFNs, health ratio computation, remaining energy, control to data ratio, and balancing factor. The results of the simulation demonstrate that the efficacy of the proposed Iterative Randomised Parallel Variable Perturbation (IRPVP) method surpasses that of other traditional algorithms.

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“…Transmission power is set to 23 dBm with 40 MHz bandwidth and antenna gain is assumed to be 13 dBi gain to enable long distance communication. The simulation is event-driven [28,29]. It proceeds per 1 µs step, and detailed procedures are implemented: exponential backoff, data packet transmission with acknowledge (ACK) response, carrier sense, collision detection and retransmission.…”

Section: Transceiver Definitionsmentioning

confidence: 99%

Analysis of Nonlinear Bypass Route Computation for Wired and Wireless Network Cooperation Recovery System

Nakayama¹,

Maruta

2018

BDCC

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It is a significant issue for network carriers to immediately restore telecommunication services when a disaster occurs. A wired and wireless network cooperation (NeCo) system was proposed to address this problem. The goal of the NeCo system is quick and high-throughput recovery of telecommunication services in the disaster area using single-hop wireless links backhauled by wired networks. It establishes wireless bypass routes between widely deployed leaf nodes to relay packets to and from dead nodes whose normal wired communication channels are disrupted. In the previous study, the optimal routes for wireless links were calculated to maximize the expected physical layer throughput by solving a binary integer programming problem. However, the routing method did not consider throughput reduction caused by sharing of wireless resources among dead nodes. Therefore, this paper proposes a nonlinear bypass route computation method considering the wireless resource sharing among dead nodes for the NeCo system. Monte Carlo base approach is applied since the nonlinear programming problem is difficult to solve. The performance of the proposed routing method is evaluated with computer simulations and it was confirmed that bandwidth division loss can be avoided with the proposed method.

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Highly Efficient Multi Channel Packet Forwarding with Round Robin Intermittent Periodic Transmit for Multihop Wireless Backhaul Networks

Cited by 5 publications

References 43 publications

PRAM: Penalized Resource Allocation Method for Video Services

PRAM: Penalized Resource Allocation Method for Video Services

Data Perturbation for Pervasive Edge Computing Environments Using Iterative Randomised Parallel Variable Perturbation in Wireless Sensor Network

Analysis of Nonlinear Bypass Route Computation for Wired and Wireless Network Cooperation Recovery System

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