Fair Resource Allocation in Systems With Complete Information Sharing
Fossati, Francesca; Hoteit, Sahar; Moretti, Stefano; Secci, Stefano (2018), Fair Resource Allocation in Systems With Complete Information Sharing, IEEE/ACM Transactions on Networking, 26, 6, p. 2801-2814
TypeArticle accepté pour publication ou publié
Journal nameIEEE/ACM Transactions on Networking
IEEE - Institute of Electrical and Electronics Engineers
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Laboratoire d'Informatique de Paris 6 [LIP6]
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Centre d'études et de recherche en informatique et communications [CEDRIC]
Abstract (EN)In networking and computing, resource allocation is typically addressed using classical resource allocation protocols as the proportional rule, the max-min fair allocation, or solutions inspired by cooperative game theory. In this paper, we argue that, under awareness about the available resource and other users demands, a cooperative setting has to be considered in order to revisit and adapt the concept of fairness. Such a complete information sharing setting is expected to happen in 5G environments, where resource sharing among tenants (slices) need to be made acceptable by users and applications, which therefore need to be better informed about the system status via ad-hoc (northbound) interfaces than in legacy environments. We identify in the individual satisfaction rates the key aspect of the challenge of defining a new notion of fairness in systems with complete information sharing, consequently, a more appropriate resource allocation algorithm. We generalize the concept of user satisfaction considering the set of admissible solutions for bankruptcy games and we adapt to it the fairness indices. Accordingly, we propose a new allocation rule we call mood value: for each user, it equalizes our novel game-theoretic definition of user satisfaction with respect to a distribution of the resource. We test the mood value and a new fairness index through extensive simulations about the cellular frequency scheduling use-case, showing how they better support the fairness analysis. We complete the paper with further analysis on the behavior of the mood value in the presence of multiple competing providers and with cheating users.
Subjects / KeywordsResource allocation games; fairness
Showing items related by title and author.
Fossati, Francesca; Medhi, Deep; Moretti, Stefano; Secci, Stefano (2019) Article accepté pour publication ou publié