Optimizing co-existing multicast routing trees in IP network via discrete artificial fish school algorithm

Liu, Qing; Ren, Hang; Tang, Rongjun; Yao, Junliang

doi:10.1016/j.knosys.2019.105276

Cited by 7 publications

(6 citation statements)

References 25 publications

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“…Energy efficient multicasting in wireless networks is a multi-faceted problem that can be addressed in several ways, to name a few, including optimization of transmission power [ 3 ], optimization of routing paths [ 4 ], and spectrum and bandwidth optimization for multicast sessions [ 5 ]. CR is considered a promising candidate technology to be used in this field.…”

Section: Related Workmentioning

confidence: 99%

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Energy Efficient Multicast Communication in Cognitive Radio Wireless Mesh Network

Baig

Hasan

Valsalan

et al. 2022

Sensors

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Multicasting is a basic networking primitive used in a wide variety of applications that is also true for cognitive radio-based networks. Although cognitive radio technology is considered to be the most promising technology to deal with spectrum scarcity, it relates to completely different aspects of networking and presents new challenges. For cognitive radio-based multicast sessions, it is important to use the spectrum efficiently by reducing the number of channels used as well as engaging fewer nodes in data relaying. This will benefit the network in three ways. First, it will decrease the number of transmissions. Second, it will help to reduce energy usage. Third, it will spare more channels and relay nodes for simultaneous multicast sessions. To achieve these advantages, efficient channel selection and relay nodes are required based on hop-to-hop communication. In this paper an algorithm has been developed that attempts to minimize energy consumption by selecting the minimum possible number of relay nodes and channels for a multicast session, taking into account the sporadic availability of the spectrum. The proposed method performs effectively compared to the flooding method in terms of energy consumption for the provided examples in multicasting.

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Section: Related Workmentioning

confidence: 99%

“…CR is considered a promising candidate technology to be used in this field. However, these results in [ 3 , 4 , 5 ] are not applicable to the CRN because of its unique features in terms of spectrum availability. Thus, it is essential to develop new protocols and algorithms for multicasting in CRNs.…”

Section: Related Workmentioning

confidence: 99%

Energy Efficient Multicast Communication in Cognitive Radio Wireless Mesh Network

Baig

Hasan

Valsalan

et al. 2022

Sensors

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“…The experiment showed that the algorithm has better congestion handling ability under high-traffic conditions than for other conditions. With the continuous improvements in the routing strategies of ground-based wireless networks, intelligent optimization algorithms such as the bee colony algorithm, ant colony algorithm and particle swarm algorithm have been extended to topological optimization and routing decision making for satellite networks in recent years [8][9][10]. Reference [30] verified the application value of the ant colony algorithm in single-layer NGEO.…”

Section: Related Workmentioning

confidence: 99%

“…A detected wolf randomly searches for the largest benefit function values within a certain number of steps. The concentration formula is shown in (8).…”

Section: ) Detected-wolf Satellite and Its Behaviormentioning

confidence: 99%

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A Routing Model Based on Multiple-User Requirements and the Optimal Solution

Liu

Zhang

2020

IEEE Access

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To promote the development of high-bandwidth IP networks of nongeostationary Earth orbit (NGEO) satellites, this paper designs a new benefit measurement model. Moreover, we propose the class-A QoS benefit criterion (QABC), which is established based on a mathematical model involving the remaining queue length and QoS. The benefit model includes three maximum and minimum conflict subgoals and is designed to avoid the problem that the ant colony algorithm easily falls to local optima. This new model is solved with the wolf colony algorithm, which provides both next-hop selection and bottleneck bandwidth reservation mechanisms. Additionally, many burst flows can occur in satellite networks, and they lead to a slow convergence speed and unnecessary overhead. In this paper, the Kalman filter algorithm is used to address these issues. Considering the long-term correlation of satellite traffic, it is feasible to smooth the queue length with a Kalman filter. Finally, the Kalman filter wolf colony algorithm (KFWCA) can solve the conflict problem in the new benefit measurement model. The algorithm is applied in the network simulator NS2.35, and the results verify the effectiveness of load balancing and QoS maximization in a satellite network. The results indicate that the KFWCA yields better performance than other algorithms based on traffic allocation, the average delay, the packet loss rate and other factors, especially under high-traffic conditions. INDEX TERMS benefit measurement model; KFWCA; QoS support; load balancing I. INTRODUCTION

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A Novel Heuristic Optimization Algorithm for Solving the Delay-Constrained Least-Cost Problem

Boudjelida

Lemouari

2021

Machine Learning for Networking

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Optimizing co-existing multicast routing trees in IP network via discrete artificial fish school algorithm

Cited by 7 publications

References 25 publications

Energy Efficient Multicast Communication in Cognitive Radio Wireless Mesh Network

Energy Efficient Multicast Communication in Cognitive Radio Wireless Mesh Network

A Routing Model Based on Multiple-User Requirements and the Optimal Solution

A Novel Heuristic Optimization Algorithm for Solving the Delay-Constrained Least-Cost Problem

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