Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

Massive dataflows are generated from IoT devices for sensing and controlling real-world environments. At the same time, reducing network traffic and delay utilizing hierarchical network characteristics including edge resources becomes important for maintaining long-running IoT application costs. A dataflow platform considering hierarchical networks is an ongoing research area, and it enables application developers to develop a dataflow application which usually consists of loosely coupled reusable software components for easy and flexible developments. However, the existing dataflow platform does not mention component management including software deployment and placement selection over the hierarchical network. In this paper, we proposed a component management method using a major open source product and a component deployment layer selection method considering network and resource conditions. During the definition of the component placement problem, we also extracted parameters required to estimate component deployment costs. Furthermore, we implemented a simple dataflow application based on two use cases and confirmed the validity of the proposed method.

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

Reducing energy consumption in data centers is one of the important issues in IT industry. Since Power Usage Effectiveness (PUE) focuses on a fraction of the power consumed by IT equipment such as servers and networking devices, the power consumption of environmental control systems such as Computer Room Air Conditioning (CRAC) is "overhead" in the sense of PUE. In order to improve PUE, dense monitoring of data center environment is required for preventing excessive cooling. One of the promising approaches for dense environment monitoring is utilizing wireless sensor network (WSN). An issue in applying WSN to data centers is message encryption and authentication. Compared to the wired network, wireless network communication might be monitored from the outside of the data center and it becomes a critical issue for data center security. In this paper, we aim to establish secure WSN for data center use cases and several preliminary experiments for applying message encryption and authentication will be discussed.

A software-based monitoring system is required for choosing monitor points flexibly in cloud network forensics. Especially, in the mission-critical network, since system halt cannot be allowed, the infected system must remove malware analyzing existing attack patterns and estimating potential attack scenarios. It requires full capture for reconstructing the attack behavior. In this research, we realize a software-based full capture monitoring system. First, Linux and libpcap packet capture procedure are investigated, and it is clarified that the packet losses occur depending on ingress throughput, the read stop time, the number of blocks and the block size of the ring buffer. We proposed a tuning method using those parameters for loss-less capturing and confirmed the proposed method can establish loss-less property.

In bus companies, it is important for the operation manager to grasp operation states of the vehicle from the viewpoint of safety management and improving the operation efficiency. Currently, for allowing the operation manager to grasp operation states of the vehicle, the driver records operation states by manually operating a recorder called `Digital-tachograph'. However, operating a digital tachograph is a heavy burden to the driver. In this research, in order to solve this problem and to realize efficient operation, we propose a method for automatic classification of operation states using sensor data obtained from the buses. We implemented a classifier using Random Forest with the sensor data. The correct answer rate was 0.9 or more in each condition unless it was irregular operation.

Sometimes the overlay networks for large-scale distributed middleware are constructed without considering the underlying network structure. For improving the performance, many kinds of middleware which actively control underlying network are proposed. In this case, both overlay and underlay network behavior should be tested. On the other hand, they provide different functions since they target different systems, e.g. pub/sub system, distributed file system and so on. While the integration of their functions is required for a new advanced application, it may cause conflicts among active controls. DNetSpec provides a toolset for testing such middleware in emulated networks. The toolset consists of four tools, and it provides the functions which can be mainly used for measuring the amount of traffic and delay associated with application layer messages. In this paper, we evaluated the toolset whether it can capture packets without CPU saturation and packet losses, and we confirmed that it can provide accurate and complete network testing in some environments. The results are promising and show that DNetSpec may possibly contribute to progressing the development of advanced distributed middleware.

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

Navigation in unfamiliar cities often requires frequent map checking, which is troublesome for wayfinders. We propose a novel approach for improving real-world navigation by generating short, memorable and intuitive routes. To do so we detect useful landmarks for effective route navigation. This is done by exploiting not only geographic data but also crowd footprints in Social Network Services (SNS) and Location Based Social Networks (LBSN). Specifically, we detect point, area, and line landmarks by using three indicators to measure landmark's utility: visit popularity, direct visibility, and indirect visibility. We then construct an effective route graph based on the extracted landmarks, which facilitates optimal path search. In the experiments, we show that landmark-based routes out-perform the ones created by baseline from the perspectives of the lap time and the number of references necessary to check self-positions for adjusting route directions.

Pub/Sub communication model becomes a basis of various applications, e.g. IoT/M2M, SNS. These application domains require new properties of the Pub/Sub infrastructure, for example, supporting a large number of devices with widely distributed manner, handling emergency messaging with priority control and so on. In order to meet the demands, we proposed Software Defined Network Aware Pub/Sub (SAPS) which utilize the both Application Layer Multicast (ALM) and SDN, especially Open Flow based multicast (OFM). A simulation was done for evaluating the hybrid architecture in traffic and transmission delay reduction, and then the issues to be solved in the current design were discussed.

Topic-based pub/sub (TBPS) messaging plays an important role in building event-driven Internet of Things (IoT) applications. In IoT applications, scalability and locality-awareness are important properties that help to achieve low-latency message delivery and efficient usage of network resources. However, none of the existing distributed TBPS methods can simultaneously achieve a sufficient level of both properties. This paper proposes a new TBPS overlay method called 'Skip Graph-based TBPS with Locality-Awareness' (STLA), which extends existing Skip Graph-based TBPS messaging by adding locality- awareness. STLA determines the order of the keys on a Skip Graph overlay network according to the network hierarchy structure using 'locality-aware topic keys' (LATK). Using 'split-forward broadcasting' (SFB) with LATK, the locality-awareness can be dramatically improved. Simulation results show that our method can achieve locality-awareness and reduce the average latency of message delivery for 100,000 subscribers by 76% compared with existing methods. In addition, we have conducted experiments on real distributed data centers using an STLA prototype system, and have confirmed the practicality and feasibility of the proposed method.

Microblogging platforms such as Twitter have been recently frequently used for detecting real-time events. The spatial component, as reflected by user location, usually plays a key role in such systems. However, an often neglected source of spatial information are location mentions expressed in tweet contents. In this paper we demonstrate a novel visualization system for analyzing how Twitter users collectively talk about space and for uncovering correlations between geographical locations of Twitter users and the locations they tweet about. Our exploratory analysis is based on the development of a model of spatial information extraction and representation that allows building effective visual analytics framework for large scale datasets. We show visualization results based on half a year long dataset of Japanese tweets and a four months long collection of tweets from USA. The proposed system allows observing many space related aspects of tweet messages including the average scope of spatial attention of social media users and variances in spatial interest over time. The analytical framework we provide and the findings we outline can be valuable for scientists from diverse research areas and for any users interested in geographical and social aspects of shared online data.

Microblogging platforms such as Twitter have recently received much attention as great sources for live web sensing, real-time event detection and opinion analysis. Previous works usually assumed that tweets mainly describe "what's happening now". However, a large portion of tweets contains time expressions that refer to time frames within the past or the future. Such messages often reflect expectations or memories of social media users. In this work we investigate how microblogging users collectively refer to time. In particular, we analyze half a year long portion of Japanese and four months long collection of US tweets and we quantify collective temporal attention of users as well as other related temporal characteristics. This kind of knowledge is helpful in the context of growing interest for detection and prediction of important events within social media. The exploratory analysis we perform is possible thanks to the development of visual analytics framework for robust overview and easy detection of various regularities in the past and future-oriented thinking of Twitter users. We believe that the visualizations we provide and the findings we outline can be also valuable for sociologists and computer scientists to test and refine their models about time in natural language.

This paper presents TWinChat, a Twitter and Web user interactive chat system to support simultaneous communication between microbloggers and Web users in real-time through both the contents of microblogs and Web pages. TWinChat provides a question answering interface attached to Web pages, which allows Web users to chat with Twitter users in real-time while presenting tweets that are associated with Web pages, i.e., simultaneous cross-media communication. In order to map heterogeneous media, the system extracts relationship between tweets and Web pages by generating queries based on location names. Thus, our system can effectively present messages from Web users to help Twitter users immediately obtain useful information or knowledge, and it also can effectively present tweets from the Twitter users to help the Web users easily grasp the current situation in real-time.

GakuNin is a federation for constructing an academic authn & authz infrastructure by using single sign-on (SSO) technology in Japan and it consists of academic eresource providers and consumers, e.g. Universities, Electric Journal Publishers and so on. The expansion of SSO target systems causes several issues in its infrastructure. In this paper, we focus on the issues, (1) rapidly increasing the importance of the user credential at the identity provider, (2) its phishing risk at service providers and (3) the difficulty of choosing own identity provider from the large number of federated providers. We propose a framework to solve the problems using web browser add-on. We have implemented a prototype of the framework. We also discuss the issues in the current implementation.

We present a novel system that combines the advantages of social communication and Web search by simultaneously discovering important pages and users. First, the system provides a communication interface attached to pages, which allows users to talk with each other in real time while browsing the same page, i.e., page-centric communication. Then, the system can efficiently provide two ranking lists of pages and users by analyzing a hybrid structure of hyperlinks (page-page relationship) and social links (page-user relationship and user-user relationship). Thus, users can efficiently search for important pages as well as important users related to their queries through the ranking function, and immediately obtain useful information or knowledge from not only pages themselves but also from other users.

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.

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.