@article{HossfeldHeegaardVarelaetal.2024, author = {Hoßfeld, Tobias and Heegaard, Poul E. and Varela, Mart{\´i}n and Jarschel, Michael}, title = {User-centric Markov reward model for state-dependent Erlang loss systems}, volume = {2024}, pages = {102425}, journal = {Performance Evaluation}, number = {165}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0166-5316}, doi = {https://doi.org/10.1016/j.peva.2024.102425}, year = {2024}, abstract = {Markov reward models are commonly used in the analysis of systems by integrating a reward rate to each system state. Typically, rewards are defined based on system states and reflect the system's perspective. From a user's point of view, it is important to consider the changing system conditions and dynamics while the user consumes a service. The key contributions of this paper are proper definitions for (i) system-centric reward and (ii) user-centric reward of the Erlang loss model M/M/n-0 and M/M(x)/n with state-dependent service rates, as well as (iii) the analysis of the relationships between those metrics. Our key result allows a simple computation of the user-centric rewards. The differences between the system-centric and the user-centric rewards are demonstrated for a real-world cloud gaming use case. To the best of our knowledge, this is the first analysis showing the relationship between user-centric rewards and system-centric rewards. This work gives relevant and important insights in how to integrate the user's perspective in the analysis of Markov reward models and is a blueprint for the analysis of other services beyond cloud gaming while also considering user engagement.}, language = {en} }