• IEIE Transactions on Smart Processing and Computing
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• v.5 no.4
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• pp.235-242
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• 2016

The emerging High-Efficiency Video Coding (HEVC) standard attempts to improve coding efficiency by a factor of two over H.264/Advanced Video Coding (AVC) at the expense of an increase in computational complexity. Mode decision with motion estimation (ME) is still one of the most time-consuming computations in HEVC, as it is with H.264/AVC. Thus, fast mode decisions are not only an important issue to be researched, but also an urgent one. Several schemes for fast mode decisions have been presented in reference software and in other studies. However, the conventional hierarchical mode decision can be useless when block-level parallelism is exploited. This paper proposes operation-level exploration that offers more chances for early termination. An early termination condition is checked between integer and fractional MEs and between the parts of one partition type. The fast decision points of the proposed algorithm do not overlap those in previous works. Thus, the proposed algorithms are easily used with other fast algorithms, and consequently, independent speed-up is possible.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3286-3300
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• 2016

High Efficiency Video Coding (HEVC) Standard, as the latest coding standard, introduces satisfying compression structures with respect to its predecessor Advanced Video Coding (H.264/AVC). The new coding standard can offer improved encoding performance compared with H.264/AVC. However, it also leads to enormous computational complexity that makes it considerably difficult to be implemented in real time application. In this paper, based on machine learning, a fast partitioning method is proposed, which can search for the best splitting structures for Intra-Prediction. In view of the video texture characteristics, we choose the entropy of Gray-Scale Difference Statistics (GDS) and the minimum of Sum of Absolute Transformed Difference (SATD) as two important features, which can make a balance between the computation complexity and classification performance. According to the selected features, adaptive decision trees can be built for the Coding Units (CU) with different size by offline training. Furthermore, by this way, the partition of CUs can be resolved as a binary classification problem. Experimental results have shown that the proposed algorithm can save over 34% encoding time on average, with a negligible Bjontegaard Delta (BD)-rate increase.

• Journal of Communications and Networks
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• v.7 no.4
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• pp.509-524
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• 2005

Due to the strict requirements of emerging applications, per-flow admission control is gaining increasing importance. One way to implement per-flow admission control is using an on­path resource reservation protocol, where the admission decision is made hop-by-hop after a new flow request arrives at the network boundary. The next-steps in signaling (NSIS) working group of the Internet engineering task force (IETF) is standardising such an on-path signaling protocol. One of the reservation methods considered by NSIS is reduced-state mode, which, suiting the differentiated service (DiffServ) concept, only allows per-class states in interior nodes of a domain. Although there are clear benefits of not dealing with per-flow states in interior nodes-like scalability and low complexity-, without per-flow states the handling of re-routed flows, e.g., after a failure, is a demanding and highly non-trivial task. To be applied in carrier-grade networks, the protocol needs to be resilient in this situation. In this article, we will explain the consequences of a route failover to resource reservation protocols: Severe congestion and incorrect admission decisions due to outdated reservation states. We will set requirements that handling solutions need to fulfill, and we propose extensions to reduced-state protocols accordingly. We show with a set of simulated scenarios that with the given solutions reduced-state protocols can handle re-routed flows practically as fast and robust as stateful protocols.