Delay analysis of multiclass queues with correlated train arrivals and a hybrid priority/FIFO scheduling discipline

Walraevens, Joris; Bruneel, Herwig; Fiems, Dieter; Wittevrongel, Sabine

doi:10.1016/j.apm.2017.01.044

Cited by 14 publications

(12 citation statements)

References 26 publications

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“…The performance of the Npqt ++ is evaluated in terms of the following parameters throughput, average delay, and power consumption. Then, using the Contiki OS and Cooja simulator, we compare the Npqt ++ with two other congestion control algorithms in our related works 11,16 to test the performance of our approach: (1) a hybrid priority/FIFO scheduling discipline (priorityFIFO)—this scheme considers a discrete‐time single sever queueing model with two‐layered arrival process and a hybrid priority/FIFO scheduling where the traffic types are grouped into different priority classes, 16 and (2) the polling‐TCPW‐in this algorithm, the status report policy in the RLC protocol stack of the radio link control layer of the NB‐IoT is enhanced to control data transmission and to realize automatic repeat‐request retransmission 11 . The key parameters and protocols used in the simulation are presented in Table 1.…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…(1) a hybrid priority/FIFO scheduling discipline (priorityFIFO)-this scheme considers a discrete-time single sever queueing model with two-layered arrival process and a hybrid priority/FIFO scheduling where the traffic types are grouped into different priority classes, 16 and (2) the polling-TCPW-in this algorithm, the status report policy in the RLC protocol stack of the radio link control layer of the NB-IoT is enhanced to control data transmission and to realize automatic repeat-request retransmission. 11 The key parameters and protocols used in the simulation are presented in Table 1.…”

Section: Resultsmentioning

confidence: 99%

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Using priority queuing for congestion control in IoT‐based technologies for IoT applications

Oyewobi

Djouani

Kurien

2020

Int J Communication

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The Internet of Things (IoT) connect millions of devices in diverse areas such as smart cities, e-health, transportation and defense to meet a wide range of human needs. To provide these services, a large amount of data needs to be transmitted to the IoT network servers. However, the IoT networks suffer from limited resources such as buffer size, node processing capabilities, and server capacities adversely affecting throughputs, latency, and energy consumption.Additionally, the ensuing heavy network traffic due to large amount of data transmitted results in congestion which degrades IoT network performance.Therefore, innovative congestion control techniques, e.g., queue management approach needs to be developed to overcome congestion problems in IoT networks. In this paper, a novel priority queuing technique (Npqt++) is developed to control congestion in IoT networks. The Npqt++ implements a preemptive/nonpreemptive discipline with a discretion rule to classify network traffic based on their real-time requirement into priority groups. If the discretion rule for low priority packets is satisfied, high priority packets are pushed to the front of the queue; otherwise, they wait in the queue. Our approach significantly outperforms existing techniques in terms of throughput, delay, and energy consumption.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Using priority queuing for congestion control in IoT‐based technologies for IoT applications

Oyewobi

Djouani

Kurien

2020

Int J Communication

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“…(iv) Uniform vehicle type is assumed. Mixed traffic could be incorporated to the models by arrival rates in Poisson arrivals (Walraevens et al (2017)). Impact of different vehicle types would impact intersection capacity and location information.…”

Section: Limitations Of the Studymentioning

confidence: 99%

Queue Length Estimation at Traffic Signals: Connected Vehicles with Range Measurement Sensors

Comert¹,

Cetin²

2020

Preprint

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Today vehicles are becoming a rich source of data as they are equipped with localization or tracking and with wireless communications technologies. With the increasing interest in automated-or selfdriving technologies, vehicles are also being equipped with range measuring sensors (e.g., LIDAR, stereo cameras, and ultrasonic) to detect other vehicles and objects in the surrounding environment. It is possible to envision that such vehicles could share their data with the transportation infrastructure elements (e.g., a traffic signal controller) to enable different mobility and safety applications. Data from these connected vehicles could then be used to estimate the system state in real-time. This paper develops queue length estimators from connected vehicles equipped with range measurement sensors. Simple plugand-play models are developed for queue length estimations without needing ground truth queue lengths by extending the previous formulations. The proposed method is simple to implement and can be adopted to cyclic queues at traffic signals with known phase lengths. The derived models are evaluated with data from microscopic traffic simulations. From numerical experiments, the QLE model with range sensors improves the errors as much as 25% in variance-to-mean ratio and 5% in coefficient of variation at low ≤ 20% market penetration rates.

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“…Arrival and departure of the train has actually been done in accordance with his schedule, but one day can happen a train is required to come or depart first. This is done by delaying the train schedule to be inserted [8].…”

Section: Related Workmentioning

confidence: 99%

Hybrid Method of First Come First Served and Priority Queue for Queue System in Hospital

Salim¹,

Suseno²,

Nurhayati³

2018

IJCA

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People must have been queuing up at service places like banks, hospitals, etc. For now most of the queues are still conventional. The queue is done manually, the customer takes the queue number and waits until it's his turn. In computer systems people are familiar with queuing theory, such as FIFO, LIFO, PQ, etc. Sometimes, it combines several queue theories to execute the program. This study, queuing system will adopt from queue theory which is used by computer system. Hybrid system from FCFS and PQ will serve customers according to their needs. This study was conducted at the service place of one of the government hospital in Surakarta city. The sample queue data will be analyzed and compared when using the conventional queue and after using this queue system. This queuing system utilizes cloud technology to be accessible anywhere and display results in real time. The average waiting time in the hospital service using a conventional queue system is 2-5 hours, while using this system is 10-30 minutes.

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Delay analysis of multiclass queues with correlated train arrivals and a hybrid priority/FIFO scheduling discipline

Cited by 14 publications

References 26 publications

Using priority queuing for congestion control in IoT‐based technologies for IoT applications

Using priority queuing for congestion control in IoT‐based technologies for IoT applications

Queue Length Estimation at Traffic Signals: Connected Vehicles with Range Measurement Sensors

Hybrid Method of First Come First Served and Priority Queue for Queue System in Hospital

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