Ant colony optimization approach for satellite broadcast scheduling problem

Kιlιç, Sezgin; Özkan, Ömer

doi:10.1109/rast.2017.8002936

Cited by 8 publications

(4 citation statements)

References 28 publications

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“…Currently, ant colony algorithms are widely used in networks, such as avoiding the interflow and intraflow interference or balancing the loads in backbone networks [19], calculating the best route for vehicles in vehicle networks [20,21], designing dynamic source routing algorithm meeting high QoS requirements in ad hoc networks [22], balancing energy efficiency for WSNs and IPv6 networks [23,24], and solving the scheduling (SBS) problem of satellite broadcasting between satellites and ground stations [25]. Wang et al proposed a load balancing scheme based on the ant colony algorithm (LBRA-CP) [18].…”

Section: Related Workmentioning

confidence: 99%

An Ant Colony Optimization-Based Routing Algorithm for Load Balancing in LEO Satellite Networks

Deng

Zeng

Chang

et al. 2022

Wireless Communications and Mobile Computing

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Satellite networks can provide a wider service range and lower delay than traditional terrestrial optical fiber networks. However, due to the bursty characteristic of the Internet traffic and the distributive feature of satellite links, traffic-intensive areas often suffer from link congestion while links in other areas are underutilized, i.e., the traffic imbalance problem in LEO satellite networks. In this paper, an ant colony optimization routing algorithm with window reduction for LEO satellite networks, ACORA-WR, is proposed to achieve load balancing. ACORA-WR limits the movement of the ant colony to a specific range and comprehensively considers the path distance, transmission direction, and link load to find a path with low delay and overhead. Simulation results verify that the proposed ACORA-WR scheme demonstrates high data delivery ratio and network throughput, while ensuring low average delay and network transmission overhead.

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Section: Related Workmentioning

confidence: 99%

An Ant Colony Optimization-Based Routing Algorithm for Load Balancing in LEO Satellite Networks

Deng

Zeng

Chang

et al. 2022

Wireless Communications and Mobile Computing

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“…Zhang et al [18] introduced an overall planning technique to solve the problem of earth satellite schedule. In contrast, Kilic and Ozkan [19] proposed an ant colony optimization metaheuristic approach to solve the broadcast's scheduling problem. Lin [20] utilized HTS and dynamic programming method to effectively solve the problem of mission planning for the electromagnetism environment monitors satellite.…”

Section: Research On Ground Stations Scheduling Problemmentioning

confidence: 99%

Reinforcement learning-based ground stations scheduling algorithm for LEO satellites

Chen

Xiao

Jicheng

et al. 2022

Seventh International Conference on Electromechanical Control Technology and Transportation (ICECTT 2022)

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With the rapidly increasing number and movement of satellites, the ground stations scheduling problem for Low Earth Orbit (LEO) satellites becomes more complex due to its over-constraint nature. In this paper, we propose a novel ground stations scheduling algorithm named Reinforcement Learning-Based Ground Stations Scheduling Algorithm (RLBGSSA). Its batch tasks planning branch (RLBGSBSA) ensures ground stations efficiently track satellites and achieve timeliness. Under the state constraints, the individual task planning branch of RLBGSSA (RLBGSISA) generates the feasible planning combinations based on reinforcement learning, and gains the combination constraints to filter the planning combinations. To maintain the stability of tasks and equipment, the optimal combination among the screened results is selected via a designed value function, which can achieve minimal changes to planned tasks. Furthermore, RLBGSBSA can reset the scheduling of ground stations to void planning overflow, when the number of individual tasks newly added is too large. Finally, the rationality and effectiveness of our algorithm are verified by numerical simulation.

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“…In the context of networks, an ant is a routing packet emitted by a satellite node, interspersed with the normal traffic, with a randomly chosen destination node. Pheromones represent the quality of the traversed paths and a transition rule is used to define the probability that the ant chooses to move through the edge, as explained in [61] and [64]- [66]. The ACO algorithm proceeds as follows.…”

Section: ) Modified Random Walkmentioning

confidence: 99%

Towards Quantum Satellite Internetworking: A Software-Defined Networking Perspective

et al. 2020

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Ant colony optimization approach for satellite broadcast scheduling problem

Cited by 8 publications

References 28 publications

An Ant Colony Optimization-Based Routing Algorithm for Load Balancing in LEO Satellite Networks

An Ant Colony Optimization-Based Routing Algorithm for Load Balancing in LEO Satellite Networks

Reinforcement learning-based ground stations scheduling algorithm for LEO satellites

Towards Quantum Satellite Internetworking: A Software-Defined Networking Perspective

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