A Hybrid Prediction and Assessment Quality of Experience Approach for Videostreaming Applications over Wireless Mesh Networks

DIG: Um Servição de Custos e Estatísticas para o Processamento Distribuído de Consultas

André F. RikerElisangela S. AguiarDiogo C. B. CardosoPatrícia A. de OliveiraEduardo CerqueiraAntônio J. G. Abelém

Nicolaas RubergGabriela RubergMarta Mattoso

As Wireless Mesh Networks (WMNs) have been increasinglydeployed, the need of new quality measurement schemes became essentialsince operators want to control and optimize their network resources, whilekeeping users of multimedia applications with a good quality level. However,currently WMN in-service assessment schemes fails in capturing subjectiveaspects of real-time multimedia content related to the user perception.Therefore, this paper proposes a new on-the-fly quality estimator approach,called Hybrid Quality of Experience (HyQoE) Prediction, for real-timevideostreaming applications. Moreover, performance evaluation resultspresent the benefits and accuracy of HyQoE in predicting the user perceptioncompared to well-know subjective and objective methods in a WMN scenario. Cost parameters and database statistics are the basis of query optimization techniques. However, in distributed and heterogeneous database systems, acquiring and treating information to help the optimization process are often tasks of a global query processor, tailoring these functionalities to a specific system architecture. Moreover, this acquisition process involves a large number of parameters and requires customized methods to retrieve data from specific sources. DIG (Distributed Information Gatherer) is a cost and statistics provider that, through an independent and flexible service, aims to support global query optimization processing in distributed and heterogeneous database systems over autonomous data sources. We developed a DIG prototype and evaluated it with specific wrappers for a query middleware on semi-structured data sources and also for a ORDBMS.

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