Multi-agent Systems for Personalized QoE-Management

Abstract : User satisfaction is becoming a key factor to secure the success of any online service. Quality of Experience is a subjective measure of the service quality as perceived by the user. QoE has been introduced to bridge the gap between the purely technical characteristics of QoS and user satisfaction. Recent research on QoE has shown that QoE is highly personal and influenced by multiple interrelated factors including the user expectations, preferences and cultural background. However, most existing QoE management solutions overlook the personal aspect of QoE and ignore inter-user differences despite the promise of adopting a user-centric approach. In this paper, we propose multi-agent technology as means to achieve personalized QoE-management. In particular, we propose a multi-agent architecture called EMan where each end-user is embodied by an autonomous agent that represents her personal preferences and expectations and seeks to maximize her QoE. To evaluate our approach, we use Repast, a multi-agent simulation platform. The preliminary results proves that such a decentralized multi-agent QoE-management outperforms an equivalent centralized approach both in terms of end-user satisfaction and service acceptability.
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Amro Najjar, Christophe Gravier, Xavier Serpaggi, Olivier Boissier. Multi-agent Systems for Personalized QoE-Management. 28th International Teletraffic Congress (ITC 28), Sep 2016, Würzburg, Germany. ⟨10.1109/ITC-28.2016.308⟩. ⟨emse-01687106⟩

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