萬代 雅希

Now is the age of neuromorphic computing that creates brain circuits. The analog and digital circuit theory changes because the values of the basic conductance elements can be made variable by learning. The computer structure changes to in-memory computing technology in cooperation with a von Neumann architecture. In this paper, we propose a gyrator neuron (GN) that enables analog computer operations by nodal equation. The GN is constructed based on memristor elements. The GN executes learning by back propagation processing and association by forward propagation processing.

In this paper, we propose a tile quality selection method in tile-based video streaming. The proposed method suppresses the spatial quality variation within viewport caused by the change of the viewport region due to the movement of the user’s head. In the proposed method, client checks whether the difference of quality level between viewport and around viewport is large. When assigning quality, if the difference of quality level between the viewport and around viewport is large, the difference is reduced. As a result of simulation, when the segment length is long, quality variation can be suppressed without significantly reducing the perceived bitrate. Especially, the quality variation within viewport can be greatly suppressed.

In Adaptive Bit Rate (ABR) utilized in MPEG-DASH (MPEG Dynamic Adaptive Streaming over HTTP), there have been proposed three representative algorithms, rate-based, buffer-based and hybrid-based ones. In the information centric networks, which have been widely studied as a network architecture for efficient content distribution including video streaming, routers are generally equipped with cache storage. When some segments of a required content is occasionally downloaded from cache storage in a router, content download from a router might be faster than segment retrieval from the original content server. This inaccurate throughput estimation might lead to inappropriate bitrate selection of ABR algorithm running on the user's application and significant degradation of QoE (Quality of Experience) performance. In this paper, from the viewpoint of QoE, we evaluate the influence of in-network caches on three types of ABR algorithm in video streaming.

In this paper, we propose a quality-level control method based on quality of experience (QoE) characteristics for HTTP adaptive streaming (HAS). The proposed method works as an adaptive bitrate controller on the HAS client. The proposed method consists of two operations: buffer-Aware control and QoE-Aware control. We implement the proposed method on an actual dynamic adaptive streaming over HTTP (DASH) program and evaluate the QoE performance of the proposed method via both objective and subjective evaluations. The results show that the proposed method effectively improves both objective and subjective QoE performances by preventing stalling events and quality-level switchings that have a negative influence on subjective QoE performance.

Resource Pooling concept has been proposed as fair sharing of total network resources among all users sharing a network so that a whole network is treated as a single pooled resource. MPTCP (Multipath TCP) has been proposed as one of the most promising congestion controls which realize the Resource Pooling in the situation that each user can utilize multiple paths. In CCN (Content-Centric Networking), several multipath/multisource congestion control methods have been proposed. A fundamental difference between CCN congestion control and MPTCP where single source is assumed, is multisource and the Resource Pooling in multipath/multisource situation is quite a new research issue. In this paper, we discuss congestion control for CCN from the viewpoint of the Resource Pooling and show that our previously proposed congestion control satisfies the Resource Pooling concept. Our simulation results also show that our proposed congestion control achieves macroscopic fairness among users, which means the Resource Pooling concept is satisfied.

In the paper, we propose a new congestion control method based on hop-by-hop rate control in named data networking (NDN). The proposed method suppresses the excessive reduction of the Interest sending rate due to continuous negative acknowledgement (NACK) packets caused by the propagation delay. The proposed method limits the rate reduction to once per congestion. The point of the proposed method is to keep the Interest sending rate for NACK packets unchanged after the rate reduction for congestion until the rate reduction becomes effective. Performance evaluation is conducted through computer simulations in order to demonstrate that the proposed method improves the throughput performance as compared to the conventional method.