Improved round robin queue management algorithm for elastic and inelastic traffic flows

Nandhini, S.

doi:10.1504/ijmndi.2015.072858

Cited by 3 publications

(2 citation statements)

References 5 publications

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“…[6] investigated an SSRQM (Single Server Retrial Queueing Model) with subject to failures and repair. For queueing Internet protocol networks, [7] analyzed fuzzy-based congestion detection algorithms. They are scheduled in two separate queueing processes depending on how congested the flows are.…”

Section: Introductionmentioning

confidence: 99%

Vulnerable Server under Bernoulli Vacation and Non-Persistent Customer

Bharathi

Nandhini

2023

Preprint

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In this study, computing on the cloud is important to current technologies. CC (Cloud Computing) significantly emphasizes task scheduling as one of its most critical components, we examine an M/G/1 queueing system with two service categories and a Bernoulli vacation subject to the active breakdown. On occurrence of a breakdown , the repair on the service channel starts instantly. Furthermore, the nature of the customer is considered as reneging and balking. Significant performance measures for this queueing model are examined in steady-state using the supplementary variable technique and have also discussed a few special cases of this model. This technique handles each task using a Non-Markovian process before its real allocation to cloud resources. This step comes before the actual assignment of tasks. Numerical illustrations of the effects of various parameters on system performance have also been presented.

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Section: Introductionmentioning

confidence: 99%

Vulnerable Server under Bernoulli Vacation and Non-Persistent Customer

Bharathi

Nandhini

2023

Preprint

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“…Since the characteristics of the aircraft state network, the density is an important index which cannot be neglected. On the basis of network robustness researches and aircraft state network reality, we propose four indexes: efficiency, robustness, connection density and largest component [42], [43] to calculate network overall performance. Evaluating node importance by comparing the change of network overall performance before and after deleting nodes.…”

Section: Introductionmentioning

confidence: 99%

Identification of Key Nodes in Aircraft State Network Based on Complex Network Theory

Wang

Wen

2019

IEEE Access

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With the development of aviation, the air traffic density in the terminal area is high and the traffic situation is relatively complex, which brings challenges to the flight deployment. In order to fully understand the air flight situation and provide decision-making basis for controllers, this paper proposes a key conflict aircraft identification method based on complex network theory and node deletion method. First, an aircraft state network is constructed with an aircraft as nodes and airborne collision avoidance system (ACAS) communication relations as edges. Network efficiency, network robustness, connection density, and largest component were used as the indexes of network performance. The weight of each index is determined by using AHP-entropy weight method. A multi-attribute decision-making method was introduced to quantify network performance. Then we used a node deletion method to determine key conflict aircrafts. The simulation and experiment are respectively carried out on the artificial network and the aircraft state network of a certain day in the terminal area of Kunming Changshui Airport. The results show that the method proposed in this paper can identify the key conflict points in the aircraft state network. The deployment of selected nodes can not only effectively reduce the complexity of the flight state network, but also provide a reference for air traffic control services and reduce the control difficulty of the controller. INDEX TERMS Aircraft state network, complex network, node deletion, air traffic control (ATC).

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Node importance evaluation in aviation network based on “No Return” node deletion method

Wen

2018

Physica A: Statistical Mechanics and its Applications

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Improved round robin queue management algorithm for elastic and inelastic traffic flows

Cited by 3 publications

References 5 publications

Vulnerable Server under Bernoulli Vacation and Non-Persistent Customer

Vulnerable Server under Bernoulli Vacation and Non-Persistent Customer

Identification of Key Nodes in Aircraft State Network Based on Complex Network Theory

Node importance evaluation in aviation network based on “No Return” node deletion method

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