Analysis of quality-of-service metrics in IMS networks

Nikolay, Kulikov

doi:10.3103/s0146411616010077

Cited by 4 publications

(2 citation statements)

References 10 publications

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“…The work of Rajagopal and Devetsikiotis formulates an IMS network utility function and calculates optimal service rates of network queues, considering delay constraints, by analyzing real IMS environments. The work of Kulikov has employed cumulant analysis to estimate response time in IMS network and assumed the IMS nodes as M/G/k queues. It has validated its model by using the simulation.…”

Section: Discussion and Related Workmentioning

confidence: 99%

Performance analysis of the internet‐protocol multimedia‐subsystem's control layer using a detailed queueing Petri‐net model

Roshani

Khorsandi

2018

Int J Communication

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In the current trend in telecommunications industry towards all-internetprotocol (IP) infrastructures, IP multimedia subsystem (IMS) plays a critical role by providing a coherent data and control-plane solution for large-scale live multimedia applications in a flexible and cost-effective manner. On the other hand, such a large-scale service platform would inevitably fail without effective support for the quality-of-service (QoS) requirements perceived by its users. Among the most important factors that influence user QoS are system performance and scalability. In this paper, a performance model for IMS systems is developed using the queueing Petri nets (QPNs) as the modeling formalism.The model's parameters are tuned based on the measurements carried out using a well-known IMS implementation. The model is validated against the real system. During the model calibration, the Java garbage-collector process used in the home subscriber-server (HSS) implementation was found to be a main factor in the discrepancy between the model and the reality. In addition, the effects of other factors such as the network stack in the operating system are investigated. The validated model is employed to give insights into the scalability of every single instance of IMS implementation. The model is extended to study load balancing among multiple instances of HSS to remove the main bottleneck in the system. It provides a valuable platform for resource management of various components of the IMS ecosystem to support the intended level of QoS for the users.

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Section: Discussion and Related Workmentioning

confidence: 99%

Performance analysis of the internet‐protocol multimedia‐subsystem's control layer using a detailed queueing Petri‐net model

Roshani

Khorsandi

2018

Int J Communication

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“…The growing use of SIP signalling in these services has led to creation of measurement methodology for SIP server performances [9], [10]. Many research activities have been directed to evaluation of various SIP performance metrics in different environments, e.g., Mobile Ad Hoc Network (MANET) [11], Long Term Evolution (LTE) [12], [13], IP Multimedia Subsystem (IMS) [14], Software Defined Network (SDN) [15]/ Network Function Virtualization (NFV) environment [16], [17].…”

Section: Related Workmentioning

confidence: 99%

The Influence of SIP Call Control Signalling on VoIP Quality of Experience

Husić

Baraković

Kasumović³

2019

Teh. vjesn.

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The rapid growth in subscribers and usage of multimedia services enlarges the volume of Session Initiation Protocol (SIP) call control signalling creating a need to understand Quality of Experience (QoE) in this case and improve it. This paper provides an analysis of influence of SIP call control signalling on QoE for Voice over Internet Protocol (VoIP) service. The aim was to investigate whether SIP call control signalling load has the influence on the human perception of SIP signalling performances and QoE, and to identify the importance of distinct SIP-based signalling performance metrics. Moreover, the intention was to determine whether SIP call control signalling load changes its impact if previously proposed algorithm for differentiated treatment of SIP messages is activated, and quantify mutual relationships of considered user perceptions and QoE. The findings show that SIP call control signalling load has a strong and negative impact on dependent variables and that the proposed algorithm improves QoE and human perception of SIP signalling performances.

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Evaluation of the improved particle swarm optimization algorithm efficiency inward peer to peer video streaming

Golchi

Motameni

2018

Computer Networks

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Analysis of quality-of-service metrics in IMS networks

Cited by 4 publications

References 10 publications

Performance analysis of the internet‐protocol multimedia‐subsystem's control layer using a detailed queueing Petri‐net model

Performance analysis of the internet‐protocol multimedia‐subsystem's control layer using a detailed queueing Petri‐net model

The Influence of SIP Call Control Signalling on VoIP Quality of Experience

Evaluation of the improved particle swarm optimization algorithm efficiency inward peer to peer video streaming

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