Reinforcement Learning Based QoS Guarantee Traffic Scheduling Algorithm for Wireless Networks

2020 ◽  
pp. 1522-1532
Author(s):  
Qingchuan Liu ◽  
Ao Xiong ◽  
Yimin Li ◽  
Siya Xu ◽  
Zhiyuan An ◽  
...  
Keyword(s):  
Wireless Networks ◽  
Reinforcement Learning ◽  
Scheduling Algorithm ◽  
Traffic Scheduling ◽  
Qos Guarantee

scholarly journals Congestion Control and Traffic Scheduling for Collaborative Crowdsourcing in SDN Enabled Mobile Wireless Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Dawei Shen ◽  
Wei Yan ◽  
Yuhuai Peng ◽  
Yanhua Fu ◽  
Qingxu Deng
Keyword(s):  
Wireless Networks ◽  
Load Balancing ◽  
Congestion Control ◽  
Communication Networks ◽  
Mobile Networks ◽  
Scheduling Algorithm ◽  
Mobile Wireless Networks ◽  
Traffic Scheduling ◽  
Mobile Wireless ◽  
Artificial Fish Swarm Algorithm

Currently, a number of crowdsourcing-based mobile applications have been implemented in mobile networks and Internet of Things (IoT), targeted at real-time services and recommendation. The frequent information exchanges and data transmissions in collaborative crowdsourcing are heavily injected into the current communication networks, which poses great challenges for Mobile Wireless Networks (MWN). This paper focuses on the traffic scheduling and load balancing problem in software-defined MWN and designs a hybrid routing forwarding scheme as well as a congestion control algorithm to achieve the feasible solution. The traffic scheduling algorithm first sorts the tasks in an ascending order depending on the amount of tasks and then solves it using a greedy scheme. In the proposed congestion control scheme, the traffic assignment is first transformed into a multiknapsack problem, and then the Artificial Fish Swarm Algorithm (AFSA) is utilized to solve this problem. Numerical results on practical network topology reveal that, compared with the traditional schemes, the proposed congestion control and traffic scheduling schemes can achieve load balancing, reduce the probability of network congestion, and improve the network throughput.

scholarly journals Shortest Link Scheduling in Wireless Networks Under The Rayleigh Fading Model

2021 ◽  
Author(s):  
Baogui Huang ◽  
Jiguo Yu ◽  
Chunmei Ma ◽  
Fengyin Li ◽  
Guangshun Li
Keyword(s):  
Wireless Networks ◽  
Rayleigh Fading ◽  
Scheduling Algorithm ◽  
Random Variable ◽  
Rayleigh Distribution ◽  
Interference Model ◽  
Link Scheduling ◽  
Signal Power ◽  
Schedule Delay ◽  
Radio Signals

Abstract Many shortest link scheduling algorithms adopt non-fading SINR interference model, which assumes that the received signal power will always remain determinate as long as the transmission power of the corresponding sender is fixed. In fact, because environment always influences the propagation of radio signals, the received signal power is by no means a certain value. Rayleigh fading is a statistical model for radio signals propagation. It assumes that the strength of a signal on a receiver is a random variable, varying with the Rayleigh distribution. This paper proposes a shortest link scheduling algorithm under the Rayleigh fading model (SLSRF). The SLSRF partitions the wireless network area into hexagons and colors the hexagons with 3 different colors such that two neighboring hexagons have different colors. The senders of the links scheduled simultaneously are arranged in hexagons with the same color. The correctness of the SLSRF is proved through theoretical analysis, and the efficiency is illustrated by elaborate simulations. Our simulation results demonstrate that the schedule delay of SLSRF is less than that of some results under the non-fading SINR interference model. Furthermore, we extend the SLSRF to a distributed version, which is suitable for large wireless networks.

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