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Performance analysis of the internet‐protocol multimedia‐subsystem's control layer using a detailed queueing Petri‐net model
Author(s) -
Roshani Mozafar,
Khorsandi Siavash
Publication year - 2018
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.3885
Subject(s) - computer science , quality of service , scalability , computer network , bottleneck , the internet , protocol stack , queueing theory , petri net , application layer , distributed computing , embedded system , operating system , software deployment , wireless sensor network
Summary In the current trend in telecommunications industry towards all‐internet‐protocol (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.