_:n6921723ffdd64b259fcfb202929b506axb69
<http://schema.org/description>
"The increasing momentum of service-oriented architecture has led to the\nemergence of divergent delivered services, where service selection is meritedly\nrequired to obtain the target service fulfilling the requirements from both\nusers and service providers. Despite many existing works have extensively\nhandled the issue of service selection, it remains an open question in the case\nwhere requests from multiple users are performed simultaneously by a certain\nset of shared candidate services. Meanwhile, there exist some constraints\nenforced on the context of service selection, e.g. service placement location\nand contracts between users and service providers. In this paper, we focus on\nthe QoS-aware service selection with constraints from a fairness aspect, with\nthe objective of achieving max-min fairness across multiple service requests\nsharing candidate service sets. To be more specific, we study the problem of\nfairly selecting services from shared candidate sets while service providers\nare self-motivated to offer better services with higher QoS values. We\nformulate this problem as a lexicographical maximization problem, which is far\nfrom trivial to deal with practically due to its inherently multi-objective and\ndiscrete nature. A fairness-aware algorithm for concurrent service selection\n(FASS) is proposed, whose basic idea is to iteratively solve the\nsingle-objective subproblems by transforming them into linear programming\nproblems. Experimental results based on real-world datasets also validate the\neffectiveness and practicality of our proposed approach."
<https://deepai.org/profile/lizhen-cui>