Cloud-based High Definition (HD) video streaming is becoming more and more popular day by day. On one hand, it is important for both end users and large storage servers to store their huge amount of data on different servers at different locations from security and mobile availability point of views, especially for end users having small amount of storage in their mobile devices. On the other hand, it is becoming a big challenge for network service providers to provide constant and reliable connectivity to the network users. There have been many studies over cloud-based video streaming for Quality of Experience (QoE) for services like Youtube. Packet losses and bit errors are very common in transmission networks, producing annoying effects such as frame freezing and blocky artifacts, which affects the user feedback over cloud-based media services. To cover up packet losses and bit errors, Error Concealment (EC) techniques are usually applied at decoder/receiver side to estimate the lost information. This paper proposes a time efficient and quality oriented EC method. The proposed method considers H.265/HEVC based Intra-encoded videos for the estimation of whole Intra-frame loss. The unsliced mode of H.265 is targeted for the proposed approach. The main emphasis in the proposed approach is the recovery of Motion Vectors (MVs) of a lost frame in real-time. The search to find the optimum MV is performed in parallel in nearby four sub-blocks in the reference frame. To boost-up the search process for the lost MVs, a bigger block size and searching in parallel are both considered. The simulation results clearly show that our proposed method outperforms the traditional Block Matching Algorithm (BMA) by approximately 2.5 dB and Frame Copy (FC) by up to 12 dB at a Packet Loss Rates of 1%, 3% and 5% with different Quantization Parameters (QPs). The computational time of the proposed approach outperforms the BMA by approximately 1,788 seconds. The proposed technique can readily be applied for real-time cloudbased HD video streaming.

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The encoding of HD videos faces two challenges: requirements for a strong processing power and a large storage space. One time-efficient solution addressing these challenges is to use a cloud platform and to use a scalable video coding technique to generate multiple video streams with varying bitrates. Packet-loss is very common during the transmission of these video streams over the Internet and becomes another challenge. One solution to address this challenge is to retransmit lost video packets, but this will create end-to-end delay. Therefore, it would be good if the problem of packet-loss can be dealt with at the user's side. In this paper, we present a novel system that encodes and stores the videos using the Amazon cloud computing platform, and recover lost video frames on user side using a new Error Concealment (EC) technique. To efficiently utilize the computation power of a user's mobile device, the EC is performed based on a multiple-thread and parallel process. The simulation results clearly show that, on average, our proposed EC technique outperforms the traditional Block Matching Algorithm (BMA) and the Frame Copy (FC) techniques.