Admission control and buffer management of wireless communication systems with mobile stations and integrated voice and data services

Gemikonaklı, Eser; Ever, Enver; Mapp, Glenford; Gemikonakli, Orhan

doi:10.1007/s11235-016-0259-y

Cited by 3 publications

(8 citation statements)

References 24 publications

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“…All of the following results are not based on one run, but rather the average of 1000 runs for statistically stable results with varying seed values for the random number generator to ensure more practical performance and results. A simulation tool is developed for discrete event simulation of the queuing systems considered similar to [4], [7], [8], [17]. The simulated system environment is described by population and packet size.…”

Section: Discussion and Resultsmentioning

confidence: 99%

“…In [17] an improvement in queue management policies in presence of two different types of packets (data and voice) is considered. The process introduced is simple and effective and uses the concept of pre-emption.…”

Section: Related Workmentioning

confidence: 99%

“…The details of the proposed flow are also presented explicitly for the decisions to be made depending on different situations. In contrast to the proposed approach in [17], our algorithm tries to handle the flow of four types of packets to the buffer with different generators, those being human and machine, hence a more dynamic and active queue-management scheme is proposed to manage the four packet types.…”

Section: Related Workmentioning

confidence: 99%

“…• The probability that two or more arrivals occur at the same time t is negligibly small compared to the probability of zero or one arrival. For service time as well similar to the arrival processes, it is possible to use exponential distribution assuming that the minimum service time is very small compared to the mean value [16], [17].…”

Section: Sahci Approachmentioning

confidence: 99%

“…Otherwise the indicator is set to be three and in algorithm two both M2M and data packets in front are served. Unlike many of the existing scheduling approaches in the literature such as the ones employed in [2], [5] and the one introduced in [17], our approach provides a more dynamic priority scheme which can be used to further improve QoS by fine tuning. In other words, in studies such as [17], data packets do not receive any service in case there are voice packets waiting.…”

Section: Sahci Approachmentioning

confidence: 99%

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SAHCI: Scheduling Approach for Heterogeneous Content-Centric IoT Applications

et al. 2019

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The Internet of Things (IoT) is one of the dominating paradigms of the new era with its abilities to provide ubiquitous intelligence and pervasive interconnections to diverse physical objects. With the advancements, such as new generation 5G communication and cloud/edge computing-based paradigms, the degree of domination is expected to further increase. Therefore, improvements for quality of service have become a critical issue. Traditional packets scheduling algorithms cannot meet the requirements of the large-scale IoT systems. In this paper, a novel scheduling approach is proposed for different data classes (types) to be exchanged between heterogeneous nodes of a generic IoT infrastructure. The possible ways of organizing these classes depending on different metrics, such as time latency, reliability, and data loss, are investigated. The proposed approach has the advantage of being able to tune the priorities and network characteristics to reach a specifically desired performance state. Since each type of packets is considered separately, it is possible to prioritize them, by tuning the related parameters, which changes the priorities between packets. The numerical results presented show that the new approach performs better than the existing typical scheduling approaches. The developed approach can be used in the various IoT applications with the support of 5G communication and edge computing, such as agriculture, wearables, connected cars, smart retail, and smart cities.

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Section: Discussion and Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Sahci Approachmentioning

confidence: 99%

Section: Sahci Approachmentioning

confidence: 99%

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SAHCI: Scheduling Approach for Heterogeneous Content-Centric IoT Applications

et al. 2019

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A stochastic approximation approach to active queue management

2017

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Recently, a dynamic adaptive queue management with random dropping (AQMRD) scheme has been developed to capture the time-dependent variation of average queue size by incorporating the rate of change of average queue size as a parameter. A major issue with AQMRD is the choice of parameters. In this paper, a novel online stochastic approximation based optimization scheme is proposed to dynamically tune the parameters of AQMRD and which is also applicable for other active queue management (AQM) algorithms. Our optimization scheme significantly improves the throughput, average queue size, and loss-rate in relation to other AQM schemes.

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Call Admission Control Decision Maker Based on Optimized Fuzzy Inference System for 5G Cloud Radio Access Networks

Kalyanasundaram

Kumaratharan

2021

Wireless Pers Commun

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Admission control and buffer management of wireless communication systems with mobile stations and integrated voice and data services

Cited by 3 publications

References 24 publications

SAHCI: Scheduling Approach for Heterogeneous Content-Centric IoT Applications

SAHCI: Scheduling Approach for Heterogeneous Content-Centric IoT Applications

A stochastic approximation approach to active queue management

Call Admission Control Decision Maker Based on Optimized Fuzzy Inference System for 5G Cloud Radio Access Networks

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