Advances in Scalability of Queueing Models for Large-Scale Complex Systems

Dear Colleagues,

Service systems are prevalent and consistently appear in our daily lives.  For example, we encounter these systems in communication and computer systems, transportation systems, manufacturing systems, etc.  These service systems have been studied intensively under the subject queueing theory.  Queueing models are developed to understand how a service system behaves and performs under different scenarios, including existing and future environments. Delays encountered by system users is a major performance measure used to assess how effective a queueing system is. Ensuring that a system experiences minor delays is a leading target of the system providers. The ultimate goal is to be able to use the models to plan and manage a queueing system in order to minimize or limit delay experiences to system users while keeping the level of used resources for running the system to a reasonably profitable level for the service provider. Extensive research has been carried out on this subject by engineers, mathematicians, computer scientists, operations research analysts, etc., for more than 100 years. The plethora of literature on the subject is impressive, ranging from highly theoretical models to computationally focused models, including simulations and numerically based approaches; a good percentage of these models are very successful, in terms of catching the essence of the system representation and developing computationally feasible tools. Even though there are excellent conventional models with mathematical precision for analysing queueing systems, one of the major weaknesses with the existing models is their lack of scalability to large and very complex systems.  Most of the existing models can effectively analyze small-size queueing systems accurately, but are limited when considered for large systems. When dealing with large complex queueing systems, one has to resort to approximations or simulations; the two types of approximations tend to oversimplify the view of the system. Developing queueing models and analyses that are scalable to large systems, and which do not oversimplify the system representation, seems to be one of the next major frontiers that needs to be explored and focused on in order to make major advances in queueing theory. The aim of this Special Issue is to invite and encourage researchers to consider developing non-conventional and/or extend existing conventional queueing models that are scalable to large systems.

Prof. Dr. Attahiru Alfa
Dr. Haitham Abu Ghazaleh
Guest Editors

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• queueing models
• large-scale systems
• complex networks
• scalable models