4.6 Article

Distributed Systematic Network Coding for Reliable Content Uploading in Wireless Multimedia Sensor Networks

Journal

SENSORS
Volume 18, Issue 6, Pages -

Publisher

MDPI
DOI: 10.3390/s18061824

Keywords

wireless multimedia sensor networks; network coding; multimedia uploading; low-latency communication; Internet of Things

Funding

  1. 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]
  2. National Research Foundation of Korea (NRF) - MSIT, Global Research Laboratory Program [2013K1A1A2A02078326]

Ask authors/readers for more resources

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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available