Abstract
AbstractUnder many scenarios where resources may be scarce or a good Quality of Service is a requirement, appropriately sizing components and devices is one of the main challenges. New scenarios, such as IoT, mobile cloud computing, mobile edge computing or fog computing, have emerged recently. The ability to design, model and simulate those infrastructures is critical to dimension them correctly. Queuing theory models provide a good approach to understanding how a given architecture would behave for a given set of parameters, thus helping to detect possible bottlenecks and performance issues in advance. This work presents a fog-computing modelling framework based on queuing theory. The proposed framework was used to simulate a given scenario allowing the possibility of adjusting the system by means of user-defined parameters. The results show that the proposed model is a good tool for designing optimal fog architectures regarding QoS requirements. It can also be used to fine-tune the designs to detect possible bottlenecks or improve the performance parameters of the overall environment.
Highlights
As the Internet of Things (IoT) is rapidly becoming relevant, more and more smart devices can be potentially used to enhance computing power and interactivity in a wide range of scenarios
For this example, the resource needs are minimised while the Quality of Service (QoS) requirements are still guaranteed
Queuing theory models can help perform a first approach to those simulations, helping to dimension their components properly
Summary
As the Internet of Things (IoT) is rapidly becoming relevant, more and more smart devices can be potentially used to enhance computing power and interactivity in a wide range of scenarios. IoT devices are responsible for 11.5 Zettabytes of all the data generated and this is growing exponentially [4]. These devices have severe computing and storage limitations and they are not able to handle the workload of processing the data they generate. The recent adoption of Fog and Edge paradigms dramatically improves the whole system’s performance by reducing the amount of data that needs to be transmitted to and processed by the Cloud. The system architecture combines IoT sensors, fog devices and cloud infrastructures. All of these need to be considered to obtain the best availability and performance [5]
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