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MANET is an important configuration of network for operations that employ mechanisms to enable dynamic selfconfiguration, self-optimization and self-healing, which is a challenging task for the routing protocols, new multimedia application and the battery energy consumption of wireless and mobile devices. These protocols are challenging because battery problems are more serious in this type of network and the existing protocols are not adapted to current problems, particularly mobile multimedia streaming, that can be found in most Internet flow. This paper proposes a reliable energyefficient multilayer mechanism to address this to make improvements in the main current protocols. The proposal adds decision metrics to an energy-efficient computational intelligence technique based on Fuzzy-System with QoE, mobility and battery guarantees, choosing the best path in an efficient and accuracy way. The proposal has been evaluated in a network simulator.

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Resumo-Devido ao constante avanço das redes móveis celulares, operadoras tornaram-se novas participantes no competitivo mercado de serviços de dados. Aspectos econômicos como o preço cobrado pelo serviço fazem parte da maioria das estratégias de marketing atualmente. O foco deste artigoé estudar o problema da alocação de recursos e definir preços em um cenário onde operadoras competem por usuários. A solução centralizada para o problemaé revisada e uma solução distribuída utilizando informações locais de qualidade do canaĺ e proposta. Os resultados indicam que a solução proposta possui uma pequena degradação em relação a solução centralizada. Abstract-With the continuous development of mobile wireless networks, they have become a new player in the competitive market of data service provision. Economical aspects such as pricing strategy are part of most of today's market strategies.In this article, we focus on the problem of resource allocation and price definition in a competitive scenario with mobile wireless providers. In this context we review the centralized solution of the welfare maximization problem and propose a distributed solution that uses only local channel information. The results show that the proposed solution presents a small error when compared to the centralized solution.