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This document is the Accepted Manuscript version of the following article: Xianhui Che, Barry Ip, and Ling Lin, ???A survey of current YouTube video characteristics???, IEEE Multimedia, Vol. 22 (2): 55- 63, June 2015. The Version of Record is available online at DOI: https://doi.org/10.1109/MMUL.2015.34. Published by IEEE, ?? 2015 IEEE.Given the impact of YouTube on Internet services and social networks, a healthy quantity of research has been conducted over the past few years. The majority of studies on traffic capture and evaluation were carried out prior to Google's acquisition of YouTube in 2007. Since then, there have been some changes made to the user policy and service infrastructure, including limits placed on video duration, file size, and resolution. This article depicts the latest YouTube traffic profiles and delivers updated and valuable information for future researchers. To obtain a detailed understanding of YouTube video characteristics, a customized Web spider was employed to crawl over a million YouTube videos. The study demonstrates consistency with previous research for major video streams while revealing that new categories of features have emerged within the YouTube service provision. Compared with traditional video repositories, YouTube exhibits many unique characteristics that could introduce novel challenges and opportunities for optimizing the performance of short video-sharing services

Most underwater sensor networks choose acoustics as the medium for wireless transmission. However, electromagnetic waves also offer great merits for transmission in special underwater environment. A small scale wireless sensor network is deployed using electromagnetic waves with a multi-hop static topology under shallow water conditions where there is a high level of sediment and aeration in the water column. Data delivery is scheduled via daily cycles of sleeping and waking up to transmit. Due to the unique features of the network, ad-hoc on-demand Distance Vector (AODV) is chosen as the routing protocol. Modeling and simulations are conducted to evaluate network performance in terms of failure tolerance, congestion handling, and optimal grid arrangements. The results demonstrate the likely effectiveness of the designated network for this and similar scenarios.

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