Adaptation execution cost definition for a multimedia adaptation decision engine using a neural network

Multimedia content adaptation decision is necessary whenever a multimedia transmission system has multiple adaptations available to adjust the content representation requirements to the present available system resources. The implementation of an adaptation decision module, based on a Markov Decision Process, requires to weight the adaptations, to establish the adaptation plan to deliver the best possible Quality of Experience (QoE) to the user. We present a method, using a feedforward neural network, to determine these costs using two approaches: user and service provider perspectives.Multimedia content adaptation decision is necessary whenever a multimedia transmission system has multiple adaptations available to adjust the content representation requirements to the present available system resources. The implementation of an adaptation decision module, based on a Markov Decision Process, requires to weight the adaptations, to establish the adaptation plan to deliver the best possible Quality of Experience (QoE) to the user. We present a method, using a feedforward neural network, to determine these costs using two approaches: user and service provider perspectives.

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Adaptation execution cost definition for a multimedia adaptation decision engine using a neural network

Semantic Scholar · Computer Science · 2019

Abstract

Multimedia content adaptation decision is necessary whenever a multimedia transmission system has multiple adaptations available to adjust the content representation requirements to the present available system resources. The implementation of an adaptation decision module, based on a Markov Decision Process, requires to weight the adaptations, to establish the adaptation plan to deliver the best possible Quality of Experience (QoE) to the user. We present a method, using a feedforward neural network, to determine these costs using two approaches: user and service provider perspectives.Multimedia content adaptation decision is necessary whenever a multimedia transmission system has multiple adaptations available to adjust the content representation requirements to the present available system resources. The implementation of an adaptation decision module, based on a Markov Decision Process, requires to weight the adaptations, to establish the adaptation plan to deliver the best possible Quality of Experience (QoE) to the user. We present a method, using a feedforward neural network, to determine these costs using two approaches: user and service provider perspectives.

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