Mahmoud Darwich

Mahmoud Darwich

Video streams tremendously occupied the highest portion of online traffic. Multiple versions of a video are created to fit the user's device specifications. In cloud storage, Keeping all versions of frequently accessed video streams in the repository for the long term imposes a significant cost paid by video streaming providers. Generally, the popularity of a video changes each period of time, which means the number of views received by a video could be dropped, thus, the video must be deleted from the repository. Therefore, in this paper, we develop a method that predicts the popularity of each video stream in the repository in the next period. On the other hand, we propose an algorithm that utilizes the predicted popularity of a video to compute the storage cost, and then it decides whether the video will be kept or deleted from the cloud repository. The experiment results show a cost reduction of the cloud services by 15% compared to keeping all video streams.

Mahmoud Darwich, Yasser Ismail, Talal Darwich et al.

Frequently accessed video streams are pre-transcoded into several formats to satisfy the characteristics of all display devices. Storing several video stream formats imposes a high cost on video stream providers using the old classical way. Alternatively, cloud providers offer a high flexibility of using their services and at a low cost relatively. Therefore, video stream companies adopted cloud technology to store their video streams. Generally, having all video streams stored in one type of cloud storage, the cost rises gradually. More importantly, the variation of the access pattern to frequently accessed video streams impacts negatively the storage cost and increases it significantly. To optimize storage usage and lower its cost, we propose a method that manages the cloud hierarchy storage. Particularly, we develop an algorithm that operates on parts of different videos that are frequently accessed and stores them in their suitable storage type cloud. Experiments came up with promising results on reducing the cost of using cloud storage by 18.75 %.

Mahmoud Darwich, Ege Beyazit, Mohsen Amini Salehiy et al.

Video transcoding is the process of converting a video to the format supported by the viewer's device. Video transcoding requires huge storage and computational resources, thus, many video stream providers choose to carry it out on the cloud. Video streaming providers generally need to prepare several formats of the same video (termed pre-transcoding) and stream the appropriate format to the viewer. However, pre-transcoding requires enormous storage space and imposes a significant cost to the stream provider. More importantly, pre-transcoding proven to be inefficient due to the long-tail access pattern to video streams in a repository. To reduce the incurred cost, in this research, we propose a method to partially pre-transcode video streams and re-transcode the rest of it in an on-demand manner. We will develop a method to strike a trade-off between pre-transcoding and on-demand transcoding of video streams to reduce the overall cost. Experimental results show the efficiency of our approach, particularly, when a high percentage of videos are accessed frequently. In such repositories, the proposed approach reduces the incurred cost by up to 70\%.

Xiangbo Li, Mahmoud Darwich, Magdy Bayoumi et al.

Video streaming, in various forms of video on demand (VOD), live, and 360 degree streaming, has grown dramatically during the past few years. In comparison to traditional cable broadcasters whose contents can only be watched on TVs, video streaming is ubiquitous and viewers can flexibly watch the video contents on various devices, ranging from smart-phones to laptops and large TV screens. Such ubiquity and flexibility are enabled by interweaving multiple technologies, such as video compression, cloud computing, content delivery networks, and several other technologies. As video streaming gains more popularity and dominates the Internet traffic, it is essential to understand the way it operates and the interplay of different technologies involved in it. Accordingly, the first goal of this paper is to unveil sophisticated processes to deliver a raw captured video to viewers' devices. In particular, we elaborate on the video encoding, transcoding, packaging, encryption, and delivery processes. We survey recent efforts in academia and industry to enhance these processes. As video streaming industry is increasingly becoming reliant on cloud computing, the second goal of this survey is to explore and survey the ways cloud services are utilized to enable video streaming services. The third goal of the study is to position the undertaken research works in cloud-based video streaming and identify challenges that need to be obviated in future to advance cloud-based video streaming industry to a more flexible and user-centric service.

Mahmoud Darwich, Yasser Ismail, Talal Darwich et al.

Video stream is converted to several formats to support the user's device, this conversion process is called video transcoding, which imposes high storage and powerful resources. With emerging of cloud technology, video stream companies adopted to process video on the cloud. Generally, many formats of the same video are made (pre-transcoded) and streamed to the adequate user's device. However, pre-transcoding demands huge storage space and incurs a high-cost to the video stream companies. More importantly, the pre-transcoding of video streams could be hierarchy carried out through different storage types in the cloud. To minimize the storage cost, in this paper, we propose a method to store video streams in the hierarchical storage of the cloud. Particularly, we develop a method to decide which video stream should be pre-transcoded in its suitable cloud storage to minimize the overall cost. Experimental simulation and results show the effectiveness of our approach, specifically, when the percentage of frequently accessed videos is high in repositories, the proposed approach minimizes the overall cost by up to 40 percent.