Paper Info
Title
Enhanced scheme for adaptive multimedia delivery over wireless video sensor networks
Abstract
Lately Video Sensor Networks (VSN) are increasingly being used in the context of smart cities, smart homes, for environment monitoring, surveillance, etc. In such system, the trade-off between Quality of Service (QoS) and energy consumption is always a big issue. As the wireless transmission part plays the dominant role in power consumption, many researches propose energy saving schemes based on the adjustment of duty cycle by adaptively switching between wake-up/sleep state of nodes. However, the main drawback of this method is that it affects streaming quality in terms of throughput and delay. Therefore, one of the most important challenges when designing an energy-aware VSN is to keep the balance between energy consumption and video delivery quality. This paper proposes an Enhanced scheme for Adaptive Multimedia Delivery (eAMD) that dynamically adjusts the wake-up/sleep duration of video sensor nodes based on the node remaining battery levels and network performance. A Markov Decision Process (MDP)-based framework is used to formulate the problem and an innovative algorithm based on Q-Learning is proposed to find the optimal policy for video sensor nodes. Using both a systematic and algorithmic approach, our proposed system architecture and algorithms hold the potential to improve the trade-off between video streaming quality and energy efficiency in comparison with other state-of-the-art adaptive video based algorithms.
Year
DOI
Venue
2017
10.1109/BMSB.2017.7986222
2017 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)
Keywords
Field
DocType
enhanced scheme-for-adaptive multimedia delivery,wireless video sensor networks,smart cities,smart homes,environment monitoring,quality-of-service,QoS,energy consumption,wireless transmission part,power consumption,energy saving schemes,duty cycle adjustment,throughput,delay,wake-up node state,sleep node state,energy-aware VSN,video delivery quality,eAMD,wake-up duration adjustment,sleep duration adjustment,video sensor nodes,battery levels,network performance,Markov decision process-based framework,MDP-based framework,Q-Learning,system architecture,video streaming quality
Computer science,Efficient energy use,Computer network,Markov decision process,Quality of service,Real-time computing,Throughput,Systems architecture,Energy consumption,Wireless sensor network,Network performance
Conference
ISSN
ISBN
Citations 
2155-5044
978-1-5090-4938-7
0
PageRank 
References 
Authors
0.34
22
3
Name
Order
Citations
PageRank
Bao Trinh Nguyen100.34
Liam Murphy281174.94
Gabriel-Miro Muntean31880143.82