Streaming Proxy Research Articles

PPCensor: Architecture for real-time pornography detection in video streaming

Convolutional neural network (CNN) models are typically composed of several gigabytes of data, requiring dedicated hardware and significant processing capabilities for proper handling. In addition, video-detection tasks are typically performed offline, and each video frame is analyzed individually, meaning that the video’s categorization (class assignment) as normal or pornographic is only complete after all the video frames have been evaluated. This paper proposes the Private Parts Censor (PPCensor), a CNN-based architecture for transparent and near real-time detection and obfuscation of pornographic video frame regions. Our contribution is two-fold. First, the proposed architecture is the first that addresses the detection of pornographic content as an object detection problem. The objective is to apply user-friendly content filtering such that an inevitable false positive will obfuscate only regions (objects) within the video frames instead of blocking the entire video. Second, the PPCensor architecture is deployed on dedicated hardware, and real-time detection is deployed using a video-oriented streaming proxy. If a pornographic video frame is identified in the video, the system can hide pornographic content (private parts) in real time without user interaction or additional processing on the user’s device. Based on more than 50,000 objects labeled manually, the evaluation results show that the PPCensor is capable of detecting private parts in near real time for video streaming. Compared to cutting-edge CNN architectures for image classification, PPCensor achieved similar results, but operated in real time. In addition, when deployed on a desktop computer, PPCensor handled up to 35 simultaneous connections without the need for additional processing on the end-user device.

Coordination Algorithm Design of the Distributed Storage Proxy Servers for Streaming Media

For streaming media proxy server systems which are geographically far apart, distributed streaming media proxy server clusters can be a good solution to reduce upward bandwidth consumption, shorten access distance, and improve service capacity; the key is to solve the coordination problem among the proxy servers. The decision problem of the user request dispatch actually belongs to NP-complete. This article proposes an online coordination algorithm for the distributed storage streaming media proxy servers, and discusses the relative deviation of the approximate solution from the optimal solution, to serve as a reference to the specific applications of clustered streaming media proxy servers.

Coordination Algorithm Design of the Load Sharing Proxy Servers for Streaming Media

With the rapid development of streaming media applications, clustered streaming media proxy servers have become the mainstream of high-end streaming media proxy. To increase the IO throughput capacity of streaming media proxy servers, the most effective method is middle-ware technology in which several servers are bridged together to form a proxy cache server cluster, and the key is the coordination of individual proxy servers. The decision problem of the user request dispatch actually belongs to NP-complete. This article proposes an online coordination algorithm for the load sharing streaming media proxy servers, and discusses the relative deviation of the online algorithm from the optimal solution, to serve as a reference to the specific applications of clustered streaming media proxy servers.

New fair QoS-based charging solution for mobile multimedia streams

In this paper, we present a new streaming proxy based charging architecture for QoS differentiated charging in 3G. We give a short overview of charging concepts in next generation mobile networks and we describe the most important network attributes on which the quality depends. Our goal is to point out the importance of bursty packet loss which determines the quality of the multimedia streaming in contrast with the average loss rate. We propose several methods for QoS differentiated charging which are in compliance with the recommendations of 3GPP. We describe three models which can predict the QoS of a stream. The algorithms are evaluated on a real GPRS streaming flow.

Throughput optimization for video streaming proxy servers based on video staging

A video streaming proxy server needs to handle hundreds of simultaneous connections between media servers and clients. Inside, every video arrived at the server and delivered from it follows a specific arrival and delivery schedule. While arrival schedules compete for incoming network bandwidth, delivery schedules compete for outgoing network bandwidth. As a result, a proxy server has to provide sufficient buffer and disk cache for storage, together with memory space, disk space and disk bandwidth. In order to optimize the throughput, a proxy server has to govern the usage of these resources. In this paper, we first analyze the property of a traditional smoothing algorithm and a video staging algorithm. Then we develop, based on the smoothing algorithm, a video staging algorithm for video streaming proxy servers. This algorithm allows us to devise an arrival schedule based on the delivery schedule. Under this arrival and delivery schedule pair, we can achieve a better resource utilization rate gracefully between different parameter sets. It is also interesting to note that the usage of the resources such as network bandwidth, disk bandwidth and memory space becomes interchangeable. It provides the basis for inter-resource scheduling to further improve the throughput of a video streaming proxy server system.

Design and implementation of contractual based real-time scheduler for multimedia streaming proxy server

In nowadays World Wide Web topology, it is not difficult to find the presence of proxy servers. They reduce network traffic through the cut down of repetitive information. However, traditional proxy server does not support multimedia streaming. One of the reasons is that general scheduling strategy adopted by most of the traditional proxy servers does not provide real-time support to multimedia services. Based on the concept of contractual scheduling, we have developed a proxy server that supports real-time multimedia applications. Moreover, we developed the group scheduling mechanism to enable processing power transfer between tasks that can hardly be achieved by traditional schedulers. They result in a substantially improved performance particularly when both time-constrained and non-time-constrained processes coexist within the proxy server. In this paper, the design and implementation of this proxy server and the proposed scheduler are detailed.

Dynamic cache reconfiguration strategies for cluster-based streaming proxy

The high bandwidth and the relatively long-lived characteristics of digital video are key limiting factors in the wide-spread usage of streaming content over the Internet. The problem is further complicated by the fact that video popularity changes over time. In this paper, we study caching issues for a cluster-based streaming proxy in the face of changing video popularity. We show that the cache placement problem for a given video popularity is NP-complete, and propose a series of techniques to address the problem. We first introduce the dynamic first fit (DFF) algorithm that give the results close to the optimal cache placement (OCP). We then propose minimum weight perfect matching (MWPM) and swapping-based techniques that can dynamically reconfigure the cache placement to adapt to changing video popularity with minimum copying overhead. Our simulation results show that MWPM reconfiguration can reduce the copying overhead by a factor of more than two, and that swapping-based reconfiguration can further reduce the copying overhead compared to MWPM, and allow for the tradeoffs between the reconfiguration copying overhead and the proxy bandwidth utilization.

Optimized streaming media proxy and its applications

Multimedia streaming is one of the most popular services on the current Internet. However, the major problem hinders streaming media applications is the network bandwidth. In this paper, we put forward a optimized streaming proxy system and think of utilizing it in peer-to-peer (P2P) applications. The main contribution of our proxy system is RTP segments splicing, prefix caching size determination and prefetching techniques, which are detailed discussed in this paper. By validating our implementation, the experimental results show that the streaming proxy can effectively contribute to reduce the server and backbone network load, thus achieve improved media quality and scalability. In addition, P2P network is a fascinate way for Internet resource sharing, many of researchers are devoting to research on P2P-based client communications. In our project, we make use of our proxy prototype into the streaming sharing over P2P network, each peer node just like a lightweight proxy between the server and the target peers. The real-time video sharing (RVS) system efficiently utilizes network bandwidth between peer clients through combining with our proxy as expected.

MUVIS: Multi-source video streaming service over WLANs

Video streaming over wireless networks is challenging due to node mobility and high channel error rate. In this paper, we propose a multi-source video streaming (MUVIS) system to support high quality video streaming service over IEEE 802.11-based wireless networks. We begin by collocating a streaming proxy with the wireless access point to help leverage both the media server and peers in the WLAN. By tracking the peer mobility patterns and performing content discovery among peers, we construct a multi-source sender group and stream video using a rate-distortion optimized scheme. We formulate such a multi-source streaming scenario as a combinatorial packet scheduling problem and introduce the concept of asynchronous clocks to decouple the problem into three steps. First, we decide the membership of the multi-source sender group based on the mobility pattern tracking, available video content in each peer and the bandwidth each peer allocates to the multi-source streaming service. Then, we select one sender from the sender group in each optimization instance using asynchronous clocks. Finally, we apply the point-to-point rate-distortion optimization framework between the selected sender-receiver pair. In addition, we implement two different caching strategies, simple caching simple fetching (SCSF) and distortion minimized smart caching (DMSC), in the proxy to investigate the effect of caching on the streaming performance. To design more realistic simulation models, we use the empirical results from corporate wireless networks to generate node mobility. Simulation results show that our proposed multi-source streaming scheme has better performance than the traditional server-only streaming scheme and that proxy-based caching can potentially improve video streaming performance.