The development of Internet of Things and smart building technologies will accelerate many real-world entities (e.g., equipment, people flow, comfort levels) to be managed as digital data. This enables a Software-Defined Building in which advanced and complex applications realize a broad range of value propositions for smart buildings. To enable a scalable platform that can easily add and integrate a wide range of data and applications, the main issue addressed is the difficulty in unifying existing building equipment data models used in BACnet or others, or any related information in the building. Based on the Web of Things architecture, we propose a data model that accommodates both the information within buildings and the broad range of information expected to increase in the future. To enable the proposed data model to be efficiently managed by a building OS, we also propose a hierarchical mechanism that incorporates modules to convert the group of devices connected by different protocols into a unified data model. We develop a prototype building OS platform using Eclipse Ditto to evaluate the proposed model and mechanism. We confirm that the platform can correctly manage device information and that its performance is sufficient.

In this paper, we propose a tree construction method to collect and composite distributed videos on the live broad-casting system called “same world broadcasting system”. The same world broadcasting system generates and delivers a video in which video objects captured at the different places are displayed as if they were located in the same world. Our tree construction method employs an “occlusion graph” that represents the overlap relations of the video objects to give a heuristic solution to find a tree of network structure to collect and composite videos which provides a high-quality video in heterogeneous environments. We implemented the tree construction algorithm and conducted computer simulations considering different scenarios. Our simulation results show that our proposal can find a good collection tree within a practical amount of time.

As an important foundation of the smart city, MaaS (Mobility as a Service) provides a seamless passenger experience using multiple modes of transport from the beginning until the end of a journey, and its developments have attracted keen interest from the industry in recent years [1] [2] . Furthermore, as the last mile of the MaaS, electric bicycle is an important and environmental-friendly transportation [3] [4] .

A wide-area distributed application is affected by network failure due to natural disasters because the servers on which the application operates are distributed geographically in a wide area. Failure Injection Testing (FIT) is a method for verifying fault tolerance of widely distributed applications. In this paper, by limiting network failures only to the connection line, whole FIT scenarios are generated, and exhaustive evaluation of fault tolerance is performed. The authors propose a method to evaluate the resilience quantitatively by specifications of the distributed application and their service level agreements (SLAs) that consist of the distributed network. The authors compare the resilience of several distributed applications in several topologies and show returns of investigation (ROI) in each application and topology.

Many systems and services for VR spaces use avatars to represent the appearances of each user. In those systems and services, the users communicate with each other via their avatars. Currently, various techniques and researches have been studied for avatar appearance. However, the existing techniques and studies mainly regard avatars as the self-expression of each user and do not mention the influences on communication from others. In communication content, avatars are one of self-expression of each user and one of the communication tools. Therefore, this paper describes an investigation of how avatar appearances affect communication from others. The result from the research showed that the degree of deformation of avatars affects communication from others in various situations such as informal and formal situations.

Recently, live video broadcasting is frequently used due to the COVID-19 pandemic. More realistic and comfortable experiments can be realized if multiple real-time videos from different places are displayed on a single screen. This paper calls such live broadcasting "same world broadcasting" as if all objects exist in the same space. In this paper, we propose a distributed system for the same world broadcasting. We evaluate the proposed system using the experimental implementation in a LAN environment and an open testbed environment. The experiment results show that the proposed system can reduce the processing time to collect and compose many real-time videos.

Due to the increase in the speed of wireless communication in recent years, video-on-demand (VoD) systems has got great attention. In conventional VoD systems, when the number of clients receiving video data increases, the problems of longer playback interruptions or longer buffering times occur. Accordingly, several research focus on the VoD systems that adopt broadcast-type distribution (B-VoD). In B-VoD systems, video files are divided into several parts and distribution servers broadcast them in the sequences of predetermined broadcast schedules to reduce interruption time. However, conventional broadcasting methods do not consider the issues that occur in actual B-VoD systems, such as initial buffering delay and the increases of data sizes caused by video file division. Interruption time can be further reduced by considering them. Hence, in this research, we propose a data segment scheduling method for B-VoD systems. We measure the performance of our proposed method on an actual B-VoD system utilizing radio broadcasting (VHF-band) to achieve a broadcast-type distribution. The results of the experiments confirmed that, under the condition of an uninterrupted playback, the waiting time until the start of a playback can be reduced by up to 85% under our proposed method by dividing the requested video data into 6 parts and broadcasting the parts in parallel.

A wide-area distributed application is affected by network failure due to natural disasters because the servers on which the application operates are distributed geographically in a wide area. Failure Injection Testing (FIT) is a method for verifying fault tolerance of widely distributed applications. In this paper, by limiting network failures only to the connection line, whole FIT scenarios are generated, and exhaustive evaluation of fault tolerance is performed. The authors propose a method to omit the evaluations from the aspect of topological constraint conditions. And they evaluate the visualization method of performance data obtained from this evaluation and the reduction of the fault tolerance evaluation cost by the proposed method.

This paper proposes "WoT-based Logical Sensor Architecture (WLSA)," a novel virtual sensor architecture on the basis of Web of Thing (WoT) that enables IoT applications to treat the sensor data and processing results in a uniform way in edge computing environments. WLSA reduces the computing and network resources required for the IoT applications by reusing the processing results in multiple data flows. This paper also proposes a data flow transforming (DFT) algorithm, in which a subset of the data flow is automatically replaced with a process that reuses the result of running processes so that the application developers do not need to conscious of sharing the processing result. We have implemented a prototype system and an object detection application based on WLSA using Node-RED data flow processing framework in an edge computing environment and evaluated its effectiveness. The evaluation results showed that WLSA reduced the execution time with less usage of computing resources. The prototype could accommodate 20 applications with less than 100 ms response time under 4% CPU usage.

We propose a multi-plane isomorphic network that increases network throughput and reduces network latency by effectively configuring multi-plane networks. In the proposed network, each plane adopts the same graph topology but different switch-to-switch connections. We evaluate the dual-plane isomorphic hypercube network by graph analysis and cycle level simulation. Results of the graph analysis show that the dual-plane isomorphic 8-hypercube reduces the average shortest path length by 22% and improves throughput by 28% compared with the dual-plane hypercube. Similar improvements are confirmed from the results of the cycle level simulation. We also examine the dual-plane isomorphic folded-hypercube network. Finally, we discuss the effect of longer cable length caused by the isomorphic network on the network cost and latency.

In recent years, an evolutionary change occurred in the digital world when various social networking sites became popular. This led to a big increase of users who share their activities in digital form. A huge amount of digital information has become available, providing researchers with a unique insight into the behavior and activities of entire population. The use of Geo-tagged social media data became an emerging trend to represent user actions and behaviour at specific geographical locations. However, the inaccuracies of Geo-tagged data from social media often limits the utility of this data source in micro scale analysis (at the street or place of interest level (POI)). Our study supports how social media data could be matched accurately with specific physical locations. More specifically, our investigation includes Geo-tweet data and image data from flickr to map accurately physical location using machine leaning and deep learning techniques. In this paper, a preliminary discussion of this work is provided, using Geo-tagged data from Twitter and Open StreetMap in cities such as San Francisco and London as well as for image mapping using Flickr data in cities such as San Francisco and Kyoto.

A wide-area distributed application is affected by network failure due to natural disasters because the servers on which the application operates are distributed geographically in a wide-area. Failure Injection Testing (FIT) is a method for verifying fault tolerance of widely distributed applications. In this paper, by limiting network failures to connection line, whole FIT scenarios are generated and exhaustive evaluation of fault tolerance is performed. Authors evaluate the visualization method of performance data obtained from this evaluation and the reduction of the evaluation cost by the proposed method.

In IoT (Internet of Things) systems, various devices such as cameras and sensors generate a huge stream data and are cyclically send them to processing computers via computer networks. The transaction rates for processing such stream data is one of the main performances for some IoT applications. Some schemes control transaction intervals to improve transaction rates. Most of them adopt a simple approach in that processing computers request the changes of transaction intervals to data sources every a fixed number of transactions. This approach unfortunately causes the drawback of unfair (inconstant) transaction intervals. Most of IoT applications prefer constant transaction intervals, e.g., a constant frame rate for video applications, since their constantness enable stable processing. In this paper, we propose a method to dynamically determine transaction intervals based on transaction rates. In our proposed method, the processing computer for an IoT application changes the transaction interval when the average value for some previous transactions largely changes. We measured the transaction rate of our proposed method in our developed simulator and confirmed that our proposed method can give a higher fairness of the transaction rates compared with existing methods by using appropriate parameters.

Today, scientific research heavily depends on the digital world. Almost the entire process of scientific research including data acquisition, data analysis, and visualization is now being conducted in the digital world. Also, today' scientific research essentially requires the global collaboration by scientists and IT researchers, each of who works on a different organization. In this paper the authors describe the future vision of eScience as well as challenges and expectations to eScience community.

IoT (Internet of Things) security is a critical issue while IoT is a big trend where a huge number of devices would be connected to the Internet. To protect physical devices from intruders, we proposed the IoT Agent Platform mechanism to separate IoT functions from physical devices and to run isolated IoT functions on cloud environment. The Dripcast framework which provides transparent method call on cloud objects enables us to handle virtual clones for physical devices easily and intuitively. In this paper, we propose to extend the IoT Agent Platform to support m-cloud mechanism which reduces the risk of revealing privacy information contained in sensor values. This enables to secure data held by virtual clones, that is agent objects on cloud environment.

Recent rapid scale out of high performance computing systems has rapidly and continuously increased the scale and complexity of the interconnects. As a result, current static and over-provisioned interconnects are becoming cost-ineffective. Against this background, we have been working on the integration of network programmability into the interconnect control, based on the idea that dynamically controlling the packet flow in the interconnect according to the communication pattern of applications can increase the utilization of interconnects and improve application performance. Interconnect simulators come in handy especially when investigating the performance characteristics of interconnects with different topologies and parameters. However, little effort has been put towards the simulation of packet flow in dynamically controlled interconnects, while simulators for static interconnects have been extensively researched and developed. To facilitate analysis on the performance characteristics of dynamic interconnects, we have developed PFAnalyzer. PFAnalyzer is a toolset composed of PFSim, an interconnect simulator specialized for dynamic interconnects, and PFProf, a profiler. PFSim allows interconnect researchers and designers to investigate congestion in the interconnect for an arbitrary cluster configuration and a set of communication patterns collected by PFProf. PFAnalyzer is used to demonstrate how dynamically controlling the interconnects can reduce congestion and potentially improve the performance of applications.

Recently, IoT (Internet of Things) security is a critical issue while IoT is a big trend where a huge number of devices would be connected to the Internet. We focus on protecting physical devices from illegal access by intruders and give basic analysis for fundamental gaps between physical devices and embedded IoT softwares. We clarify that the critical difficulty in IoT security is implementing both of device functions and IoT functions on a same physical device. We also propose the IoT Agent Platform mechanism to separate IoT functions from physical devies and to run isolated IoT functions on cloud environment. The mechanism is based on the Dripcast which is a transparent programming framework for IoT devices where we don't care about communication, server-side programming nor database, at all. The Dripcast provides a very simple and easy development model which is a key for device vendors to develop physical devices to use IoT functions.

In this paper, we propose a lightweight multi-receiver encryption scheme for the device to device communications on Internet of Things (IoT) applications. In order for the individual user to control the disclosure range of his/her own data directly and to prevent sensitive personal data disclosure to the trusted third party, the proposed scheme uses device-generated public keys. For mutual authentication, third party generates Schnorr-like lightweight identity-based partial private keys for users. The proposed scheme provides source authentication, message integrity, replay-attack prevention and implicit user authentication. In addition to more security properties, computation expensive pairing operations are eliminated to achieve less time usage for both sender and receiver, which is favourable property for IoT applications. In this paper, we showed a proof of security of our scheme, computational cost comparison and experimental performance evaluations. We implemented our proposed scheme on real embedded Android devices and confirmed that it achieves less time cost for both encryption and decryption comparing with the existing most efficient certificate-based multi-receiver encryption scheme and certificateless multi-receiver encryption scheme.

In this paper, we propose a novel efficient sensor data stream recovery scheme called "synchronized recovery stream merging (SRSM)," for reliable event-driven IoT applications, assuming multicast delivery of data streams. SRSM synchronizes and merges multiple data streams for recovery by waiting for other data streams keeping the delivery data order, as long as the required restriction for delivery latency is satisfied. SRSM reduces the number of streams required to generate and send on the data stream sender dramatically than applying an existing stream merging scheme for recovery, thus enables to save the network bandwidth of the sender. Through extensive simulations, we evaluated the performance of SRSM and confirmed that about 48% - 60% network bandwidth was saved on the sender in the frequent failure situation compared to the existing schemes, keeping the average satisfy rate of requested delivery latency.

Summary The Pacific Rim Application and Grid Middleware Assembly (PRAGMA) is an international community of researchers that actively collaborate to address problems and challenges of common interest in eScience. The PRAGMA Experimental Network Testbed (PRAGMA‐ENT) was established with the goal of constructing an international software‐defined network (SDN) testbed to offer the necessary networking support to the PRAGMA cyberinfrastructure. PRAGMA‐ENT is isolated, and PRAGMA researchers have complete freedom to access network resources to develop, experiment, and evaluate new ideas without the concerns of interfering with production networks. In the first phase, PRAGMA‐ENT focused on establishing an international L2 backbone. With support from the Florida Lambda Rail, Internet2, PacificWave, Japan Gigabit Network, and TaiWan Advanced Research and Education Network, PRAGMA‐ENT backbone connects openflow‐enabled switches at University of Florida, University of California, San Diego, Nara Institute of Science and Technology (Japan), Osaka University (Japan), National Institute of Advanced Industrial Science and Technology (Japan), and National Applied Research Laboratories (Taiwan). The second phase of PRAGMA‐ENT consisted of an evaluation of technologies for the control plane that enables multiple experiments (ie, OpenFlow controllers) to coexist. Preliminary experiments with FlowVisor revealed some limitations leading to the development of a new approach, called AutoVFlow. This paper describes our experience in the establishment of PRAGMA‐ENT backbone (with international L2 links), its current status, and plans for the control plane. Discussion of preliminary application ideas, including optimization of routing control; multipath routing control; extending the backbone using overlay network; and remote visualization are also discussed.

Summary The feasibility of using embedded systems in real‐life applications is becoming more widespread. These applications have grown from do‐it‐yourself projects of computer enthusiasts or robotics projects to larger scale efforts and deployments. This paper describes a scenario that deployed a prototype application that allows the public to interact with features of a model and view videos from a first‐person perspective on the train. Through testing the embedded systems and their usage in a public setting, it was demonstrated that interactive features could be implemented in model train exhibits, which are featured in traditional museum environments that lack technical infrastructure. Specifically, the Arduino and Raspberry Pi provide the necessary linkages between the Internet and hardware, allowing for a greater interactive experience for museum visitors. These results provide an important use‐case scenario and lessons learned that cultural heritage institutions can use when implementing embedded systems on a larger scale, for the purpose of increasing visitors' experience through greater interaction and engagement.

On a cluster system running behind the Cloud computing, multiple processes are generated from most applications and then executed on multiple computing nodes. Their processes communicate with each other during their execution. The communication performance among multiple processes plays an important role in the total execution performance of an application. The SDN-enhanced JMS, which we have developed in the previous work, offers the framework that allows administrators to prescribe resource provisioning way using the information on both computing and network resources on a cluster system. However, an advanced and effective method for providing an appropriate set of computing and network resources to jobs is still an issue to be tackled. In this paper, we aim to design and implement an adaptive network resource allocation method with which network resources can be reallocated to jobs in execution, in response to the change of process placement occurred at job dispatch and termination events. Our evaluation shows that the proposed method can reallocate network resources of jobs in execution, and suppress the degradation of network throughput of jobs.

Recently, researchers' and scientists' interest and concern to Internet of Things (IoT) have been remarkably increasing. A diversity of IoT devices such as mobile phones, sensors and even scientific measurement facilities have been connected to the Internet and then generating an enormous amount of data. From the demands on computational resources enough to analyze such data, the utilization of the cloud has been a major trend in these days. Taking aggregation and distribution of data from and to IoT devices on the cloud into consideration, however, access control to such data gives rise to an important problem. Each of IoT devices may have a security policy and each user may have a different attribute. For achieving safe access control to data, a fully-controlled infrastructure where access to network resources is controlled as well as computational resources is required. From such a consideration, this paper proposes an access-controlled networking mechanism that dynamically organizes a flexible and secure network linking IoT devices, computational resources and users on the cloud, based on user's attribute and IoT device security policies. The architecture of FlowSieve, which we have designed and implemented in this preliminary stage of the research, is presented as well as our envisaged fully access-controlled cloud for secure data access.

A dynamic circuit network (DCN) is a production advance bandwidth reservation service. The majority of DCN operators currently provide a single class of service (CoS), e.g., either a guarantee of bandwidth or no guarantee of quality of service. Although single CoS provisioning is viable and expedient, multiple classes of service (multi-CoS) provisioning offers greatly superior practice, including quality-based charging for a commercial service and efficient resource management. This paper proposes a multi-CoS architecture with bandwidth and delay guarantees in a DCN, more specifically, the deployment of On-Demand Secure Circuits and Advance Reservation System (OSCARS) over multiprotocol label switching (MPLS) networks. The main contribution of this paper is a guaranteed bandwidth-and-delay class where the system can compute the path which can satisfy the given bandwidth and delay constraints. Our system was tested on practical routers.

In the era of cloud computing, data centers that accommodate a series of user-requested jobs with a diversity of resource usage pattern need to have the capability of efficiently distributing resources to each user job, based on individual resource usage patterns. In particular, for high-performance computing as a cloud service which allows many users to benefit from a large-scale computing system, a new framework for resource management that treats not only the CPU resources, but also the network resources in the data center is essential. In this paper, an SDN-enhanced JMS that efficiently handles both network and CPU resources and as a result accelerates the execution time of user jobs is introduced as a building block technology for such a HPC cloud. Our evaluation shows that the SDN-enhanced JMS efficiently leverages the fat-tree interconnect of cluster systems running behind the cloud to suppress the collision of communications generated by different jobs.

In recent years, much attention has been paid to wide area distributed storages to backup data remotely and ensure that business processes can continue in terms of disaster recovery. In the 'distcloud' project, authors have been involved in the research of wide area distributed storage by clustering many computer resources located in geographically distributed areas, where the number of sites is more than 2 (N>2). The storage supports a shared single POSIX file system so that LDLM (Long Distance Live Migration) of VMs (Virtual Machines) works well between multiple sites. We introduce the concept and basic architecture of the wide area distributed storage and its technical improvement for LDLM. We describe the result of our experiment, that is, 1) Nation Wide Live Migration (about 500Km) in Japan, and 2) Transpacific Live Migration (over 24,000Km). We show the technical benefit of the current implementation and discuss suitable applications and remaining issues for further research topics.

Recently, the concept of Software-Defined Network (SDN), which allows us to administer and configure a network in a centralized and software-programming manner, has gathered network engineers' and researchers' attention rapidly. In particular, the expectation and concern to OpenFlow as an implementation of the SDN is remarkable. As a result, research activities, which include prototyping, implementation, demonstration and experiments, conducted over OpenFlow networks have been a worldwide tendency. In such research activities, however, the difficulty in understanding network topology, traffic amount and an actual path of a network flow on the OpenFlow network, and the intricacies in debugging software designed for OpenFlow are serious problems in the development process of OpenFlow controller. This research aims to realize a visualization software that facilitates researchers to perform OpenFlow controller development and demonstration experiments performed on an actual OpenFlow network. In this paper, the authors summarize the achievement of their research work in progress as well as the future direction.

Optical circuit switching (OCS) technology is mostly used in all-optical network. Most OCS networks use WDM on fibers and one wavelength is assigned to one connection. However, OCS technology needs to pre-configure a lightpath before transmitting data, and the pre-configuring overhead takes more than round trip time between the source node and destination node. This pre-configuring overhead also exists when we set up optical CDM paths on a wavelength of a WDM network. Therefore, when the data size is small, the influence of the pre-configuring overhead becomes large relatively. In this paper, we propose a hybrid optical network architecture and a control method to reduce this influence. Our hybrid architecture includes a broadcast network in addition to an OCS network, an all traffic is transferred on the selected network according to the traffic characteristics. We evaluate the basic performance of the OCS network and the broadcast network and show that the broadcast network can transfer data more efficiently than the OCS network when the data size is small.

The approach of deploying hybrid wide-area Open-Flow networks is essentially important for gradual deployment of the OpenFlow technology into existing wide-area networks because it is impractical to replace such wide-area networks with OpenFlow-enabled ones at once. On the other hand, the design, deployment, and operation of such hybrid OpenFlow networks are often conducted intuitively without in-depth technical considerations. In this paper, we discuss systematically the technical and architectural aspects of hybrid OpenFlow networks based on the experiences obtained so far in the development of our wide-area hybrid OpenFlow networks on JGN2plus/JGN-X, which is nation-wide network testbed in Japan. We also describe the design and operation of RISE (Research Infrastructure for large-Scale network Experiments) on JGN-X, whose objective is to support a variety of OpenFlow network experiments.

Universities are constantly searching for ways that prepare students as effective global professionals. At the same time, cyber infrastructure leverages computing, information, and communication technology to perform research, often in an international context. In this paper we discuss a novel model, called the Cyber infrastructure Internship Program (CIP), which serves both of these goals. Specifically, students apply or develop cyber infrastructure to solve challenging research problems, but they do this via summer internships abroad. CIP has been implemented at three different Universities: The University of California San Diego in the US, Osaka University in Japan and and Monash University in Australia. We discuss details of the schemes and provide some initial evaluations of their success.

In this work, we implemented a messaging system called MONAC, by which users can disseminate Twitter messages via smartphone-based DTN. MONAC is implemented on an overlay network middleware called PIAX. We extended PIAX to enable DTN with dynamic selection of available underlay network and seamless authentication for SNS account of cloud. By these mechanisms, messages can be disseminated via DTN on heterogeneous underlay networks without falsification and user ID frauds.

In the Skip Graph, which is a structured overlay network that supports range retrievals, a key is supposed to consist of a single value. Therefore, the Skip Graph cannot perform range-to-range retrievals. In the present research, we extend the Skip Graph, enabling it to retain a range as a key, and propose the Range-Key Skip Graph, which can perform range-to-range retrievals. We also implement the proposed scheme and evaluate it on the PlanetLab.

Recently, WiFi positioning system (WPS) plays important role in ubiquitous applications. The main problem of WPS is how to collect WiFi access point (AP) locations because the most of the APs are usually installed on grass-root basis and their locations are not published. We use Locky.jp provided by Nagoya University Research Group as a WPS for our ubiquitous applications. However the precision of the AP location data in Locky.jp is not enough for our applications. To improve the precision of the AP location database, we are going to apply statistical and heuristic methods. In this paper, we described the overview of our heuristic approach and define the quality of AP observation logs and location data. We also evaluated the quality definition by simple simulations.

This paper introduces a new sensor network testbed, X-sensor, that integrates multiple sensor networks deployed at different sites. X-sensor provides three functionalities: (a) a sensor network search which enables users to find a sensor networks appropriate for experiment and data acquisition, (b) a sensor data archive which provides users with various sensor data acquired by sensor nodes, and (c) an experimental testbed which enables remote users to evaluate their network and data management protocols.

Recently, environment monitoring system attracts attention because global and/or local disasters such as global warming problem, air pollution, heavy rain and flood etc. occur everywhere. In addition, some people and companies have a weather sensor and broad band internet service become widespread as weather sensor and internet service cost lower. Many of these existing sensor network are operated by Server-Client model. However, it is difficult to manage a number of distributed sensors, and this model is weak for fault tolerance. We adopt P2P model in order to correct the necessary information effectively. On the other hand, the number of weather sensors cannot be satisfied enough to cover an arbitrary point on the earth though the users of such a weather sensor network are keen to know the information around them. In this paper, we present the method of spatial interpolation of the weather sensor data on P2P network based on location information.

We have been studying a service coordination technology that enables users to use the various types of service elements that are available in a ubiquitous computing and networking environment. We have adopted a user context handling mechanism to choose suitable service components. In this paper, we proposed an adaptive information delivery method for personalized recommendation and information provisioning. This method can provide information services based on user location, preferences, or moving history to everyone, everywhere, using a mobile phone. This system is an information circulation system based on social capital, which refers to connections between social networks. Users can obtain information about events, sightseeing information, gourmet information, disaster prevention information from SNS by marking the location information. We also applied a location-dependent recommendation method based on user's movement history. We conducted a field trial to evaluate feasibility of the system. According to the results of our questionnaire, the information-provision style is acceptable to the users. In addition, according to the analysis of the user movement and user preferences, there was a correlation between user's visited place and interested genres.

This paper introduces a sensor network testbed, X-sensor, that integrates multiple sensor networks deployed at different sites. X-sensor provides three functionalities: (a) a sensor network search which enables users to find a sensor networks appropriate for experiment and data acquisition, (b) a sensor data archive which provides users with various sensor data acquired by sensor nodes, and (c) an experimental testbed which enables remote users to evaluate their proposed methodologies.

In 2005, Osaka University, in Japan, started an international educational program called, Pacific Rim International University (PRIUS), on top of the Pacific Rim Application and Grid Middleware Assembly (PRAGMA) research framework. The PRIUS framework is based on and similar to that of the PRIME program at the University of California San Diego. Through the PRIUS program, Osaka University has explored a new structure of higher education for graduate students by combining lectures given by PRAGMA researchers and scientists as well as internship abroad opportunities to PRAGMA member institutions and universities. In this paper, we describe the goals and framework of the PRIUS program and discuss issues for the improvement of PRIUS. We also present two examples of interns' achievements as well as other educational effects brought through collaboration with PRAGMA.

Parkinson's disease is a brain disease whose medical treatment and remedy have not been established yet, although a cause of this disease is considered to be the insufficient formation and action of dopamine, which plays a role of great importance in brain activity. For this reason, there is an increasing demand on the clinical database pertaining to Parkinson's disease which multiple hospitals and research institutions can share to accumulate knowledge and know-how on the disease. In this paper, we present a clinical database for Parkinson's disease research and diagnosis which we have preliminary built, especially focusing on the access control and data filtering mechanisms built in hope that medical Grid services are seamlessly integrated to the database in future.

We proposed a distributed service oriented system with web-based interface for medical information to.. promote the practical prediction of clinical prognosis. The proposed system provided hospitals secure access for medical information and processing simulations to examine effects of surgical treatments. Through a web interface, users could operate the system in order to execute the simulations, access data from/to distributed storage, and display the medical information. These functions were combined by Web Services technique, and ontology mapping based on ICD10 was applied to combine various types of medical information. A client-side volume display using GPU was developed to visualize the result volumetric data interactively, and the system adjusted data precision dynamically to maintain the rendering speed. Being based on standardized mechanism, our framework can be applied to similar complex problems with different types of and quantities of information, such as microscopy or geography.

We demonstrate an oral scientific simulation and its visualization based on E-science. This oral scientific application will become an essential key component for medical and dental clinic in the near future because Bio-Medical simulations will provide a clinical index considering a prognostic of a disease. In this case, it was shown that the physical theory of sound production of speech sound, sibilant. However, it is difficult to acquire the computational and storage resources in the hospitals. Our E-science infrastructure enables scientists and clinicians to achieve the advanced information produced by simulations. As the result of this phase implementation for Bio-Medical simulation on E-science infrastructure, we could extract the scientific findings about the oral science. Moreover, this infrastructure can be used more generally because of the divided architecture between applications and E-science infrastructure.

The hybrid applications are needed in dental research because the result of their operation could be predicted by both modeling of an oral truct and more than two kind of physical simulations. However, it takes long time to perform the hybrid applications, cost a lot of money and needs some experience to deal with them. This paper proposes a new execution procedure of two applications which can reduce the implementation time by considering parallel efficiency of those applications. It can determine which attitude should be taken, sequential or separate execution of two different applications related with each other. Following the execution procedure, the dental hybrid application was performed. As a result of that, desirable pairs of the number of CPUs allocated to each simulation could be found. This means that the adequate procedure should be considered before execution of the hybrid applications, in order to play a compute power producer for dental clinics and hospitals.

The Cybermedia Center, Osaka University (CMC) is a research institution that offers resource with knowledge and technology of all advanced research in the area of large-scale computation, information and communication, multimedia content and education. Currently, CMC involves in Japanese national grid projects such as JGN II (Japan Gigabit Network) and BioGrid. Not limited to Japan, CMC also takes an active part in international activities such as PRAGMA. In these projects and international collaboration, CMC has developed the Grid system that allows scientists to perform their analysis by remotely controlling the world-largest ultra-high voltage electron microscope located in Osaka University. On the other, CMC has been taking a leading role at BioGrid sharing experience and knowledge on the system development for biology. In this paper, we will describe BioGrid project overview and introduce progress of Telescience group which collaborates with Telescience project lead by National Center for Microscopy and Imaging Research (NCMIR).

A new material particle dynamical domain decomposition method MPD/sup 3/ has been developed. The method is suitable for a large scale parallel molecular dynamic simulation on a heterogeneous computing net. Performance of the MPD/sup 3/ algorithm is tested in various computing environments, such as PC clusters, super computer clusters, and grid. It is shown that the MPD/sup 3/ algorithm is highly-adaptive for both computer clusters and grid computing environments, even if other programs are running on the same computer environment.

Current collaborative filtering can't represent various aspects of users' interests. We propose a recommendation method in which a user can find new interests that are partially similar to the user's taste. Partial similarity is an aspect of the user's preference which is projected by the community in which the user belongs. We developed a television program recommendation system which performs such recommendation with serendipity, conducted an actual experiment and evaluated its results.

This article presents a Web content adaptation and delivery mechanism based on application-level quality of service (QoS) policies. To realize effective Web content delivery for users, two kinds of application-level QoS policies, transmission time and transmission order of inline objects, are introduced. Next, we define a language to specify these policies. We show that transmission order control can be implemented using HTTP/1.1 pipelined requests in which a client recognizes the transmission order description in a Web page and simulates parallel transmission of inline objects by HTTP/1.1 range requests. Experimental results show that our proposed mechanism realizes effective content delivery to a diverse group of Internet users. Finally, we introduce two methods to specify application-level QoS policies, one by content authors, and the other by end users.

For the effective and early diagnosis of brain diseases, we have developed an evaluation system for brain function using an Independent Component Analysis (ICA) method. This evaluation system benefits greatly from the newly emerged Grid. To embody a Grid environment, a Globus grid toolkit has been utilized as a building block. In this research we have distributed the computational workload for the ICA on a Globus based Grid environment composed of two Alpha cluster systems and a personal computer. In addition, in order to allow scientists and application developers to easily build the Grid-enabled system, we also have adopted a Grid-enabled-Message Passing Interface, called MPICH-G. An introduction of MPICH-G to the medical analysis system on a Grid environment makes it possible for a naïve user to realize rapid analysis without special knowledge of the Grid. Magnetoencephalography (MEG), a highly sophisticated medical technology, is used for the measurement of brain function. The proposed method has the ability to integrate various geographically distributed resources and to analyze functional brain data from MEG

In this article, we propose a personalized sports digest composition system with scenario templates and show its architecture. While conventional methods only select and show important events in a simple series, our system is capable to add a direction to them with considering a story of a whole game. We apply our prototype system to the summer Japan championship tournament of high school baseball. We provided the personalized digest service of the summer championship tournament of high school baseball in 2000 to the limited audience of the Internet and received the positive feedbacks of our system from about 100 users.

A method of evaluating brain function using the metacomputer concept of the Globus system combined with a message-passing interface is described. The proposed method has the ability to exploit various geographically distributed resources and parallel computing linked to a high-technology medical instrumentation system, magnetoencephalography, to analyze the functional state of the brain. It is envisaged that the method will lead to the realization of an efficient telemedicine system for health care.