# Performability Evaluation and Sensitivity Analysis of a Video Streaming on Demand Architecture
## 6 Related Works  
Performability modeling and analysis is a crucial aspect of the design and operation of video streaming services. It involves the evaluation of the performance and reliability of the system under different operating conditions, such as varying traffic patterns, network conditions, and hardware configurations. There are several techniques that have been proposed in the literature for the performability modeling and analysis of video streaming services. In this literature review, we will discuss some of the most popular and effective techniques. * _Queueing Theory:_ Queueing theory is a mathematical approach that is widely used for the performance analysis of systems that involve the flow of customers or packets through a series of servers or channels. It is particularly useful for analyzing systems with finite capacity, such as video streaming services, where the rate of incoming traffic may exceed the capacity of the system at certain times. Queueing theory can be used to model the waiting times of packets or customers in the system, as well as the utilization of the servers or channels. * _Markov models_: Markov models are a class of mathematical models that are based on the assumption of memoryless transitions between states. They are widely used for the analysis of systems that exhibit temporal dependencies, such as video streaming services, where the state of the system at any given time depends on the state of the system in the previous time step. Markov models can be used to model the reliability and availability of video streaming services, as well as the time it takes for a request to be served. * _Petri nets_: Petri nets are a graphical modeling language that is widely used for the analysis of systems with concurrent and asynchronous events, such as video streaming services. They can be used to model the flow of packets or requests through the system, as well as the dependencies between different events. Petri nets can be used to analyze the performance of video streaming services under different operating conditions, such as varying traffic patterns and network conditions. * _Simulation_: Simulation is a technique that involves the creation of a mathematical model of a system and the use of computer algorithms to evaluate the performance of the system under different operating conditions. It is a powerful tool for the analysis of video streaming services, as it allows researchers to explore the behavior of the system under a wide range of scenarios. Simulation can be used to analyze the reliability and availability of video streaming services, as well as the impact of different hardware configurations and network conditions on the performance of the system. In summary, performability modeling and analysis is a crucial aspect of the design and operation of video streaming services. There are several techniques that have been proposed in the literature for this purpose, including queueing theory, Markov models, Petri nets, and simulation. These techniques allow researchers to evaluate the performance and reliability of video streaming services under different operating conditions, and to identify potential bottlenecks and areas for improvement. Performability evaluation is the process of assessing the performance and reliability of video streaming services. It is an important factor in ensuring a high-quality user experience and ensuring that streaming services are dependable and meet the needs of users. Previous studies have found that the performance of video streaming services is often influenced by network congestion, content delivery network (CDN) performance, and device capabilities [26; 27]. Network congestion can occur when too many users are accessing the same network resources at the same time, leading to delays and buffering. CDN performance can also impact the performance of the video stream, as the CDN is responsible for delivering the content to the user's device.