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作者机构:Sungkyunkwan Univ Sch Elect & Elect Engn Suwon 16419 South Korea Sungkyunkwan Univ Dept Interact Sci Suwon 16419 South Korea
出 版 物:《SENSORS》 (Sensors)
年 卷 期:2018年第18卷第6期
页 面:1824-1824页
核心收录:
学科分类:0710[理学-生物学] 071010[理学-生物化学与分子生物学] 0808[工学-电气工程] 07[理学] 0804[工学-仪器科学与技术] 0703[理学-化学]
基 金:Institute for Information & Communications Technology Promotion (IITP) - Korea government (MSIT), Research and Development of 5G Mobile Communications Technologies using CCN based Multi-dimensional Scalability [2013-0-00409] National Research Foundation of Korea (NRF) - MSIT, Global Research Laboratory Program [2013K1A1A2A02078326]
主 题:wireless multimedia sensor networks network coding multimedia uploading low-latency communication Internet of Things
摘 要:Recently, the wireless sensor network paradigm is shifting toward research aimed at enabling the robust delivery of multimedia content. A challenge is to deliver multimedia content with predefined levels of Quality of Service (QoS) under resource constraints such as bandwidth, energy, and delay. In this paper, we propose a distributed systematic network coding (DSNC) scheme for reliable multimedia content uploading over wireless multimedia sensor networks, in which a large number of multimedia sensor nodes upload their own content to a sink through a cluster head node. The design objective is to increase the reliability and bandwidth-efficient utilization in uploading with low decoding complexity. The proposed scheme consists of two phases: in the first phase, each sensor node distributedly encodes the content into systematic network coding packets and transmits them to the cluster head;then in the second phase, the cluster head encodes all successfully decoded incoming packets from multiple sensor nodes into innovative systematic network coding packets and transmits them to the sink. A bandwidth-efficient and channel-aware error control algorithm is proposed to enhance the bandwidth-efficient utilization by dynamically determining the optimal number of innovative coded packets. For performance analysis and evaluation, we firstly derive the closed-form equations of decoding probability to validate the effectiveness of the proposed uploading scheme. Furthermore, we perform various simulations along with a discussion in terms of three performance metrics: decoding probability, redundancy, and image quality measurement. The analytical and experimental results demonstrate that the performance of our proposed DSNC outperforms the existing uploading schemes.