Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: A Queueing Networks Approach

Abstract

The Next Generation 5G Networks can greatly benefit from the synergy between virtualization paradigms, such as the Network Function Virtualization (NFV), and service provisioning platforms such as the IP Multimedia Subsystem (IMS). The NFV concept is evolving towards a lightweight solution based on containers that, by contrast to classic virtual machines, do not carry a whole operating system and result in more efficient and scalable deployments. On the other hand, IMS has become an integral part of the 5G core network, for instance, to provide advanced services like Voice over LTE (VoLTE). In this paper we combine these virtualization and service provisioning concepts, deriving a containerized IMS infrastructure, dubbed cIMS, providing its assessment through statistical characterization and experimental measurements. Specifically, we: i) model cIMS through the queueing networks methodology to characterize the utilization of virtual resources under constrained conditions; ii) draw an extended version of the Pollaczek-Khinchin formula, which is useful to deal with bulk arrivals; iii) afford an optimization problem focused at maximizing the whole cIMS performance in the presence of capacity constraints, thus providing new means for the service provider to manage service level agreements (SLAs); iv) evaluate a range of cIMS scenarios, considering different queuing disciplines including also multiple job classes. An experimental testbed based on the open source platform Clearwater has been deployed to derive some realistic values of key parameters (e.g. arrival and service times).

Hybrid optimization algorithm for security aware cluster head selection process to aid hierarchical routing in wireless sensor network

“…If the proper CH is elected during the selection process, [44] then it is said to be the secure process. The security constraint model probability is specified by Equation (9).…”

“…Additionally, the WSN lifetime purely depends on energy, and the nodes are prone to damage when they are distributed [7,8]. Hence, the number of nodes deal with probably consists of thousands of nodes [9]. WSN owing to its features such as resource-restricted and infrastructure-less deployment nature it introduces several issues that might change the system performance [10][11][12][13].…”

“…Additionally, the WSN lifetime purely depends on energy, and the nodes are prone to damage when they are distributed [7, 8]. Hence, the number of nodes deal with probably consists of thousands of nodes [9].…”

Effective Performance Metrics for Multimedia Mission-critical Communication Systems

“…2 5 and mission-critical system users will introduce overload, especially at the IMS side. Statistical analysis of the IMS queues helps in measuring the system performance [10].…”

Simulation of Railway Marshalling Yards Based on Four-Phase Queuing Systems

“…In particular, these can be queuing systems (QS) that are well suited for describing objects where the same type of actions are regularly repeated. Queuing systems are most often used to simulate the operation of information [7,8] and telecommunication systems [9][10][11]. The features of such systems are the random nature of the data receipt and non-deterministic processing, regardless of their semantic meaning.…”