A hybrid memory architecture (HMA) that consists of some distinct memory devices is expected to achieve a good balance between high performance and large capacity. Unlike conventional memory architectures, the HMA needs the metadata for data management since the data are migrated between the memory devices during the execution of an application. The memory controller caches the metadata to avoid accessing the memory devices for the metadata reference. However, as the amount of the metadata increases in proportion to the size of the HMA, the memory controller needs to handle a large amount of metadata. As a result, the memory controller cannot cache all the metadata and increases the number of metadata references. This results in an increase in the access latency to reach the target data and degrades the performance. To solve this problem, this paper proposes a metadata prefetching mechanism for HMAs. The proposed mechanism loads the metadata needed in the near future by prefetching. Moreover, to increase the effect of the metadata prefetching, the proposed mechanism predicts the metadata used in the near future based on an address difference that is the difference between two consecutive access addresses. The evaluation results show that the proposed metadata prefetching mechanism can improve the instructions per cycle by up to 44% and 9% on average.

Since the quality of video streaming services is degraded due to the encoding, network congestion, and lack of a playout buffer, the normality of services needs to be monitored by gathering the quality measured at the end clients. When measuring quality at the end clients, the computational power should be sufficiently low, the bitstream information cannot be accessed for the quality estimation due to the encryption, and reference video cannot be used at the end clients. Therefore, metadata-based models have been developed and standardized that take metadata such as the resolution, framerate, and bitrate, and stalling information as input and calculate the quality. However, calculated quality for linear TV and video on demand (VoD) services cannot be compared because metadata-based models cannot calculate the impacts of codec strategies (e.g., H.264/AVC, H.265/HEVC, and AV1) and configurations (e.g., 1-pass encoding for linear TV or 2-pass encoding for VoD) on the quality. To take into account the impact of codec strategies and configurations, coefficients of metadata-based model need to be optimized per codec strategy and configuration using subjective quality. However, extensive subjective assessment tests are difficult to frequently conduct because they are expensive and time consuming and need to be conducted by video quality experts. Therefore, to monitor the quality of several types of video streaming services (e.g., linear TV and VoD) and to compare these qualities, a derivation procedure is proposed for obtaining coefficients of metadata-based models using a full-reference model. To validate the procedure, extensive subjective assessment tests were conducted. Finally, it is shown that three metadata-based models (i.e., the P.1203.1 mode 0 model, extended P.1203.1 mode 0 model, and model proposed by Yamagishi et al.) based on the proposed procedure using the video multimethod assessment fusion (VMAF) algorithm estimate quality accurately in terms of root mean squared error.

In this paper, we address the problem of analyzing topics, included in a social video group, to improve the retrieval performance of videos. Unlike previous methods that focused on an individual visual aspect of videos, the proposed method aims to leverage the “mutual reinforcement” of heterogeneous modalities such as tags and users associated with video on the Internet. To represent multiple types of relationships between each heterogeneous modality, the proposed method constructs three subgraphs: user-tag, video-video, and video-tag graphs. We combine the three types of graphs to obtain a heterogeneous graph. Then the extraction of latent features, i.e., topics, becomes feasible by applying graph-based soft clustering to the heterogeneous graph. By estimating the membership of each grouped cluster for each video, the proposed method defines a new video similarity measure. Since the understanding of video content is enhanced by exploiting latent features obtained from different types of data that complement each other, the performance of visual reranking is improved by the proposed method. Results of experiments on a video dataset that consists of YouTube-8M videos show the effectiveness of the proposed method, which achieves a 24.3% improvement in terms of the mean normalized discounted cumulative gain in a search ranking task compared with the baseline method.

In recent years, cognition and use of manga pervade, and people who use manga for various purposes such as entertainment, study, marketing are increasing more and more. However, when people who do not specialize in it create it for these purposes, they can write plots expressing what they want to convey but the technique of the composition which arranges elements in manga such as characters or balloons corresponding to the plot create obstacles to using its merits for comprehensibility based on high flexibility of its expression. Therefore, we consider that support of this composition technique is necessary for amateurs to use manga while taking advantage of its benefits. We propose a method of generating composition proposal to support manga creation by amateurs. For the method, we also define new manga metadata model which summarize and extend metadata models by earlier studies. It represents the compostion and the plot in manga. We apply a neural machine translation mechanism for learing the relation between the composition and the plot. It considers that the plot annotation is the source of the composition annotation that is the target, and learns from the annotation dataset based on the metadata model. We conducted experiments to evaluate how the composition proposal generated by our method helps amateur manga creation, and demonstrated that it is useful.

We propose simple but efficient encapsulation architecture. In the architecture, clients can better decode Extensible Markup Language (XML) based service information for TV contents with schema digest. Our experimental results show the superiority of the proposed architecture by comparing the compression ratios and decoding times of the proposed architecture and the existing architectures.

Energy-aware distributed file systems are increasingly moving toward power-proportional designs. However, current works have not considered the cost of updating data sets that were modified in a low-power mode, where a subset of nodes were powered off. In detail, when the system moves to a high-power mode, it must internally replicate the updated data to the reactivated nodes. Effectively reflecting the updated data is vital in making a distributed file system, such as the Hadoop Distributed File System (HDFS), power proportional. In the current HDFS design, when the system changes power mode, the block replication process is ineffectively restrained by a single NameNode because of access congestion of the metadata information of blocks. This paper presents a novel architecture, a NameNode and DataNode Coupling Hadoop Distributed File System (NDCouplingHDFS), which effectively reflects the updated blocks when the system goes into high-power mode. This is achieved by coupling metadata management and data management at each node to efficiently localize the range of blocks maintained by the metadata. Experiments using actual machines show that NDCouplingHDFS is able to significantly reduce the execution time required to move updated blocks by 46% relative to the normal HDFS. Moreover, NDCouplingHDFS is capable of increasing the throughput of the system supporting MapReduce by applying an index in metadata management.

Metadata registry (MDR) is based on the international standard ISO/IEC 11179. The committee of ISO/IEC JTC 1/SC 32, which had standardized the MDR, has started to improvise the MDR, and the improvised version is named extended MDR (XMDR). However, the XMDR does not fully support the ontology concept, and no method is available for mapping ontology registrations onto registries. To overcome the limitations of the outdated XMDR, this paper proposes an extended XMDR (XMDR+) framework. The XMDR+ framework provides a method for mapping of ontology registrations between the metadata registry and ontologies. To improve the functions of the XMDR, we have proposed herein a framework that is capable of defining a model that manages the relations not only among ontological concepts but also among instances, and guarantees the management and storage of their relationships for supporting valid relations of the ontologies.

Due to the detachability of Flash storage, which is a dominant portable storage, data integrity stored in Flash storages becomes an important issue. This study considers the performance of Flash Translation Layer (FTL) schemes embedded in Flash storages in conjunction with file system behavior that pursue high data integrity. To assure extreme data integrity, file systems synchronously write all file data to storage accompanying hot write references. In this study, we concentrate on the effect of hot write references on Flash storage, and we consider the effect of absorbing the hot write references via nonvolatile write cache on the performance of the FTL schemes in Flash storage. In so doing, we quantify the performance of typical FTL schemes for a realistic digital camera workload that contains hot write references through experiments on a real system environment. Results show that for the workload with hot write references FTL performance does not conform with previously reported studies. We also conclude that the impact of the underlying FTL schemes on the performance of Flash storage is dramatically reduced by absorbing the hot write references via nonvolatile write cache.

File systems make use of the buffer cache to enhance their performance. Traditionally, part of DRAM, which is volatile memory, is used as the buffer cache. In this paper, we consider the use of of Non-Volatile RAM (NVRAM) as a write cache for metadata of the file system in embedded systems. NVRAM is a state-of-the-art memory that provides characteristics of both non-volatility and random byte addressability. By employing NVRAM as a write cache for dirty metadata, we retain the same integrity of a file system that always synchronously writes its metadata to storage, while at the same time improving file system performance to the level of a file system that always writes asynchronously. To show quantitative results, we developed an embedded board with NVRAM and modify the VFAT file system provided in Linux 2.6.11 to accommodate the NVRAM write cache. We performed a wide range of experiments on this platform for various synthetic and realistic workloads. The results show that substantial reductions in execution time are possible from an application viewpoint. Another consequence of the write cache is its benefits at the FTL layer, leading to improved wear leveling of Flash memory and increased energy savings, which are important measures in embedded systems. From the real numbers obtained through our experiments, we show that wear leveling is improved considerably and also quantify the improvements in terms of energy.

Most large-scale distributed file systems decouple a metadata operation from read and write operations for a file. In the distributed file systems, a certain server named a metadata server (MDS) is responsible for maintaining the metadata information of the file systems. In this paper, we propose a new metadata management scheme in order to provide the high metadata throughput and scalability for a cluster of MDSs. First, we derive a new metadata distribution technique. Then, we present a load balancing technique based on the distribution technique. Several experiments show that our scheme outperforms existing metadata management scheme in terms of scalability and load balancing.

Video summarization is defined as creating a video summary which includes only important scenes in the original video streams. In order to realize automatic video summarization, the significance of each scene needs to be determined. When targeted especially on broadcast sports videos, a play scene, which corresponds to a play, can be considered as a scene unit. The significance of every play scene can generally be determined based on the importance of the play in the game. Furthermore, the following two issues should be considered: 1) what is important depends on each user's preferences, and 2) the summaries should be tailored for media devices that each user has. Considering the above issues, this paper proposes a unified framework for user and device adaptation in summarizing broadcast sports videos. The proposed framework summarizes sports videos by selecting play scenes based on not only the importance of each play itself but also the users' preferences by using the metadata, which describes the semantic content of videos with keywords, and user profiles, which describe users' preference degrees for the keywords. The selected scenes are then presented in a proper way using various types of media such as video, image, or text according to device profiles which describe the device type. We experimentally verified the effectiveness of user adaptation by examining how the generated summaries are changed by different preference degrees and by comparing our results with/without using user profiles. The validity of device adaptation is also evaluated by conducting questionnaires using PCs and mobile phones as the media devices.

We propose an enhanced method for translating Topic Maps to RDF/RDF Schema, to realize the Semantic Web. A critical issue for the Semantic Web is to efficiently and precisely describe Web information resources, i.e., Web metadata. Two representative standards, Topic Maps and RDF have been used for Web metadata. RDF-based standardization and implementation of the Semantic Web have been actively performed. Since the Semantic Web must accept and understand all Web information resources that are represented with the other methods, Topic Maps-to-RDF translation has become an issue. Even though many Topic Maps to RDF translation methods have been devised, they still have several problems (e.g. semantic loss, complex expression, etc.). Our translation method provides an improved solution to these problems. This method shows lower semantic loss than the previous methods due to extract both explicit semantics and implicit semantics. Compared to the previous methods, our method reduces the encoding complexity of resulting RDF. In addition, in terms of reversibility, the proposed method regenerates all Topic Maps constructs in an original source when is reverse translated.

An application profile specifies a set of terms, drawn from one or more standard namespaces, for annotation of data, and constrains their usage and interpretations in a particular local application. An approach to representation of and reasoning with application profiles based on the OWL and OWL/XDD languages is proposed. The former is a standard Web ontology language, while the latter is a definite-clause-style rule language that employs XML expressions as its underlying data structure. Semantic constraints are defined in terms of rules, which are represented as XDD clauses. Application of the approach to defining application profiles with fine-grained semantic constraints, involving implicit properties of metadata elements, is illustrated. A prototype application profile development environment equipped with metadata validation features has been implemented based on the proposed framework.

We describe an online method for selecting and annotating highlight scenes in soccer matches being televised. The stadium crowd noise and the play-by-play announcer's voice are used as input signals. Candidate scenes for highlights are extracted from the crowd noise by dynamic thresholding and spectral envelope analysis. Using a dynamic threshold solves the problem in conventional methods of how to determine an appropriate threshold. Semantic-meaning information about the kind of play and the related team and player is extracted from the announcer's commentary by using domain-based rules. The information extracted from the two types of audio input is integrated to generate segment-metadata of highlight scenes. Application of the method to six professional soccer games has confirmed its effectiveness.

This paper discusses effective configuration methods for peer-to-peer (P2P) network topologies within a mobile ad-hoc network. With recent progress in mobile ad-hoc network technology promoting the creation of new and attractive services, we are examining and developing P2P network systems for operation within ad-hoc networks. Our focus is on identifying methods of network-topology control that provide the best balance between performance and availability. We evaluate three methods through computer simulation and field trials from the viewpoints of resource consumption and network integrity, and clarify their domains of applicability. The results are expected to contribute to the design of future P2P networks for operation in mobile ad-hoc networks.

A huge amount of information is being accumulated on the Internet as the Internet usage spreads and numbers of Web pages increase. However, it is also becoming very difficult to find required information, even when the information exists. The actual value of the Web is thus much lower than its potential value. In order to solve this problem, technologies which allow machines to handle Web content in an efficient, accurate, and flexible way by using machine-readable metadata are being developed. This paper is a survey of knowledge representation on the Web, and the utilization of metadata and ontology for data integration and information sharing, with a focus on the Semantic Web concept.

In this paper, we study an effective video-on-demand traffic control algorithm using the metadata over the network supporting bandwidth-renegotiations. The proposed algorithm includes bandwidth smoothing, bandwidth-burstiness estimation and rate adaptation algorithms. The proposed video-on-demand server has not only video database but also metadata database that includes coding information of the compressed video in video database and the traffic burst characteristics with respect to control parameters of the bandwidth smoothing algorithm. Thus, we can predict the traffic properties accurately with a low computational complexity by using the stored metadata, and then determine the efficient bandwidth renegotiating variables such as the renegotiating instants and the required bandwidth in terms of network utilization and video-on-demand service quality. In addition, we present a rate adaptation algorithm that pursues an effective trade-off between spatial and temporal qualities of the decoded video to improve the perceptual video quality when the bandwidth request is rejected.

A set of systematic experiments on intelligent email categorization has been conducted with different machine learning algorithms applied to different parts of data in order to achieve the most correct classification. The categorization is based on not only the body but also the header of an email message. The metadata (e.g. sender name, sender organization, etc.) provide additional information that can be exploited to improve the categorization capability. Results of experiments on real email data demonstrate the feasibility of our approach to find the best learning algorithm and the metadata to be used, which is a very significant contribution in email classification. It is also shown that categorization based only on the header information is comparable or superior to that based on all the information in a message for all the learning algorithms considered.

Quality of service (QoS) technology has been implemented and started to be applied to new applications on the next-generation Internet. However, as new applications have many kinds of features and requirements, some additional features should be added to current QoS control technology. For example, they require a definition of a single policy to operate QoS control in the management domain consistently and efficiently. Policy definition for transport layer in a domain and among domains is being discussed at IETF to set a standard process, however detailed policy corresponding to the application or contents information according to the application semantics has not been discussed. Therefore we developed QoS policy control mechanism using metadata which is defined as a structured data according to the application semantics. Though metadata and transport mechanism can be located into quite different positions in the concept of network layers, we made them successfully collaborated by defining meta policy. In this paper, we describe our approach to define a meta policy based on the requirements and information contents from the application as a high level layer concept to be able to classify the network behavior. Our approach enables to multiple QoS control and collaboration among domains. We also report of the activities in IETF and ITU-T.

Caching at the Web proxy server plays an important role in reducing the response time, the network traffic, and the load of Web servers. Many recent studies have proposed and examined the replacement and consistency policies for the proxy cache, which plays a central role in the performance of caching components. For better performance, they exploit various metadata of Web objects, such as the reference count, reference time, and modification time information of past behaviors, to estimate the re-reference likelihood and freshness of the objects. However, all of these known to the authors use the metadata only when the actual object is in the cache. We observed from various proxy traces that about 20-30% of clients' requests incurred only the validity checks of cached objects without transferring actual objects from the proxy server. In this case, only the metadata are necessary at the proxy server. This paper proposes a proxy cache consistency policy that uses the metadata even for absent objects. These include the time information of evicted objects from the cache and those out of the header-only replies from Web servers. Trace-driven simulations with public proxy cache traces show that our policy reduces the response time and the number of connections to Web servers significantly.