Fair energy efficient scheduler providing high system capacity for wireless networks

Gueguen, Cédric; Merlhe, Christopher

doi:10.1007/s42452-020-03965-8

Cited by 5 publications

(3 citation statements)

References 17 publications

(28 reference statements)

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“…The QoS was improved by the utilization of adaptive priority‐based scheduling (APS), and the forward links were selected by using PF with padding and packing (PF‐PP) approach. Gueguen and Merlhe 39 introduced a novel method known as fairness, energy efficiency, and high system capacity (FEC) scheduler. This method schedules the opportunistic scheduling by the utilization of the cross‐layer technique from the physical layer to higher layers.…”

Section: Review Of Related Workmentioning

confidence: 99%

A proportional fair scheduling strategy using multiobjective gradient‐based African buffalo optimization algorithm for effective resource allocation and interference minimization

Kesavan

Periyathambi²,

Chokkalingam

2021

Int J Communication

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Summary The increased usage of Internet of Things (IoT) applications in several areas, like healthcare, agriculture, and business, has aggravated mobile traffic issues to a large extent. The deployment of 5G technology has resulted in increased traffic globally. These coherent devices, on the other hand, use the internet to fine‐tune the quality of service in order to provide scalability, anonymity, and accessibility. Despite its numerous virtues, it is bound to encounter issues with interference management, fairness, throughput, and computational complexities. In this paper, a novel Multi‐Objective Gradient‐based African Buffalo Optimization (MOGABO) algorithm is developed to handle proportional fairness scheduling, improve interference management, increase throughput, and reduce computational complexities in cellular communication systems, particularly device‐to‐device (D2D) communication. The simulation analysis is done against other approaches such as the Hungarian technique, DDDPG technique, heuristic technique, and SC‐FDMA technique demonstrates that this method has improved system fairness over the existing approaches. Our method maximizes throughput, and for 500 UE, the throughput is 10.4 Mbps, with an average queuing delay of 24 ms. As a result, when compared to the existing method, MOGABO method offers a 1.2% increase in throughput. Thus, our method offers better coverage and throughput for D2D cellular communication with the reduction of computational complexities.

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Section: Review Of Related Workmentioning

confidence: 99%

A proportional fair scheduling strategy using multiobjective gradient‐based African buffalo optimization algorithm for effective resource allocation and interference minimization

Kesavan

Periyathambi²,

Chokkalingam

2021

Int J Communication

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“…• The energy consumption is defined as the mean energy consumed to send one bit between two nodes (in mJ/bit). In this study, we consider the consumption of a mobile while transmitting equals to a constant amount of energy per time tick of 157 mW [31].…”

Section: B Studied Kpismentioning

confidence: 99%

Buffer occupancy and link state opportunistic routing for wireless mesh networks

et al. 2021

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Providing a high level of Quality of Service (QoS) is essential for future wireless networks. This article presents a new multihop wireless routing protocol that opportunistically takes profit from variations of radio conditions in terms of path loss, shadowing and multipath fading to maximize the system capacity. However, guaranteeing high system capacity should not evade the packet delay minimization objective. Consequently, the best path should not only be considered as the path with best throughput but a combination of a good link throughput and, in addition, low router buffer occupancy load. Taking into account the available router buffer occupancy in its path selection, our proposal uses queuing theory information in order to also provide an efficient load balancing solution that adequately distributes the traffic load in the whole network. Exploiting this information, our solution dynamically adapts the selected path across time avoiding overexploited efficient links as well as low throughput link usage. This adaptation is performed considering each link state and the amount of channel information available. This improves the throughput and delay with only small marginal overhead cost. Our proposal applies to all wireless multihop networks, with increased benefit for extending cell coverage. We demonstrate through our simulation study that our solution raises the system capacity by more than 50 % in several scenarii as well as reduces packet delays compared to state-of-the-art protocols such as Ad-hoc On-demand Distance Vector (AODV), Optimized Link State Routing (OLSR) and Link State Opportunistic Routing (LSOR).

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“…Similarly, opportunistic scheduling techniques have been deployed in telecommunication networks in general and in computer networks in particular to optimize and saving energy [30], [31], [32].…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of opportunistic schedulers based on fairness and throughput in new-generation mobile networks

et al. 2023

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This paper is focused on the study of the allocation of radio resources using the scheduling and opportunistic techniques. This allows us to compare the quality of service afforded to each user when the types of traffic transmitted are highly heterogeneous and efficiently evaluate the performance of resource allocation algorithms and schedulers. Many scheduling algorithms are used for resource allocation and scheduling: Round Robin, MaxSNR and PF. The main objective of this research work is to analyze and develop the main performances relating to schedulers deployed by telecommunication operators. It should be noted that scheduling is a primodridial phase preceding the phase of allocation and allocation of radio resources in a mobile radio telecommunications system. We will focus in this paper on the major advantages and the contribution of opportunistic

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Fair energy efficient scheduler providing high system capacity for wireless networks

Cited by 5 publications

References 17 publications

A proportional fair scheduling strategy using multiobjective gradient‐based African buffalo optimization algorithm for effective resource allocation and interference minimization

A proportional fair scheduling strategy using multiobjective gradient‐based African buffalo optimization algorithm for effective resource allocation and interference minimization

Buffer occupancy and link state opportunistic routing for wireless mesh networks

Performance evaluation of opportunistic schedulers based on fairness and throughput in new-generation mobile networks

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