Hirotake Abe

Anomaly Detection Using Layered Networks Based on Eigen Co-occurrence Matrix

Anomaly detection is a promising approach to detecting intruders masquerading as valid users (called masqueraders). It creates a user profile and labels any behavior that deviates from the profile as anomalous. In anomaly detection, a challenging task is modeling a user’s dynamic behavior based on sequential data collected from computer systems. In this paper, we propose a novel method, called Eigen co-occurrence matrix (ECM), that models sequences such as UNIX commands and extracts their principal features. We applied the ECM method to a masquerade detection experiment with data from Schonlau et al. We report the results and compare them with results obtained from several conventional methods.

An approach to mobile software robots for the WWW

This paper describes a framework for developing mobile software robots by using the PLANET mobile object system, which is characterized by a language-neutral layered architecture, the native code execution of mobile objects, and asynchronous object passing. We propose an approach to implementing mobile Web search robots that takes full advantage of these characteristics, and we base our discussion of its effectiveness on experiments conducted in the Internet environment. The results show that the PLANET approach to mobile Web search robots significantly reduces the amount of data transferred via the Internet and that it enables the robots to work more efficiently than the robots in the conventional stationary scheme whenever nontrivial amounts of HTML files are processed.

Architecture of a High-Speed MPI_Bcast Leveraging Software-Defined Network

Collective communication is of great importance in MPI because the execution time of an MPI program is affected by the communication performance it can gain. Particularly these days, when a cluster system composed of multiple computing nodes has become dominant as a large-scale computing system, the execution time of collective communication affects the total execution time of the MPI program. However, in many implementations of MPI, collective communication is developed to make use of unicast-based communication in a repeated and combined way, which may result in inefficient communication. In this paper, we explore the use of a Software-Defined Network, which was originally expected to help network administrators operate networks through central control in a software-programming manner, to accelerate MPI_Bcast, a basic collective communication used in MPI. The evaluation in this paper indicates that our prototyped SDN_MPI_Bcast is superior to MPI_Bcast in OpenMPI in communication performance. Also, the evaluation implies that SDN_MPI_Bcast is feasible.

Efficacy Analysis of a SDN-enhanced Resource Management System through NAS Parallel Benchmarks

In the field of social science, a variety of high-performance computing simulations such as the Monte Carlo simulation and the Multi-agent simulation must be efficiently performed to deal with social scientific big data. To facilitate social scientists in performing their own analysis against such big data, the information infrastructure for social science must be equipped with a core technology that efficiently and effectively leverages limited resources available on the information infrastructure. From such a perspective, a new type of job management technology, which treats not only computational resources such as the Central Processing Unit (CPU) and memory, but also network resources unlike traditional job management, is investigated in this paper. A cluster system with a fat-tree topology interconnect is conventional cluster architecture these days. For this investigation, the National Aeronautics Space Administration Advanced Supercomputing, USA (NAS) Parallel Benchmarks, which contain computation patterns often observed in social scientific simulations, are used to assess the efficacy of the resource allocation by our proposed job management technology on a cluster system with a fat-tree topology interconnect.

A network performance-aware routing for multisite virtual clusters

Despite the development of virtualization technologies in computing resources, how best to build virtual networks is still an open issue. Virtual network is an important technology that can hide physical network topologies and policies and provide a dedicated virtual computing environment for each user. However, it is difficult to figure out the actual mapping between a physical network and a virtual network from a logical point of view; the difficulty will cause performance degradation in the virtual network and inefficient network routing. We have therefore proposed a network performance-aware routing mechanism using SDN technologies. By using SDN technology, we can control the network in a centralized manner. Our proposed system automatically aggregates the information on network performance, and then defines an appropriate routing policy by solving optimal path problems based on the observed network performance. We have improved the performance of the inter-domain network for a multisite virtual cluster with the proposed system. We have also started to deploy the proposed system into an actual environment consisting of different multiple organizations.

A Scalable Approach to Avoid Incast Problem from Application Layer

With the development of distributed computing technology and cloud computing technology, the amount of data is rising dramatically, as well as the number of datacenters, where we keep these data for long periods. In these datacenters, TCP protocol is still widely used in most of the network traffic. On the other hand, TCP protocol can also result in severe goodput collapse in a high bandwidth and low latency datacenter environment. One of the problems is called incast problem. In order to efficiently utilize the bandwidth of distributed systems such as datacenter environments, some traffic control mechanisms should be very necessary. In this paper, we discussed about an application layer control mechanism to improve the performance of certain traffic pattern which may cause incast problem. The main idea is to make the data flows be staggered and transferred in serialized manner. We conducted both simulation-based and real-machine-based experiments. In the real-machine-based experiments, we conducted both small scale test and large scale test. We find out that the proposed approach, staggered flows, is able to avoid incast problem and to make the performance better in most cases. Also, this paper shows the potential of scalability that this approach can keep the performance well with the increment of node quantity.

A Prototype of Network Failure Avoidance Functionality for SAGE Using OpenFlow

A tiled display wall (TDW), which is a single large display device composed of multiple sets of computers and displays, has recently gained the attention of scientists. In particular, SAGE, which is a middleware for building TDW, allows scientists to browse a multiple series of visualized results of computer simulation and analysis through the use of network streaming. Each visualized result can be generated on a different remote computer. For this reason SAGE has been increasingly hailed as a promising visualization technology that will solve the geographical distribution problem of computational and data resources. SAGE depends heavily on a network streaming technique in its architecture, but does not have any recovery mechanism against cases of network problems. This research, therefore, aims at realizing a network failure avoidance functionality for SAGE, focusing on OpenFlow against SAGE vulnerability to network failure. Specifically, the functionality is designed and developed as a composition of the following three functions: network failure detection, network topology understanding, and a packet forwarding control function. The key concept behind our design is that the network control function from OpenFlow should be built into SAGE. The evaluation in the paper confirms that the proposed and prototyped network failure avoidance functionality can detect failures on network routes and then reroute network streaming for visualization on TDW.

SAGE-based Tiled Display Wall enhanced with dynamic routing functionality triggered by user interaction

To empower scientists who are engaged in nation-wide or global-scale collaborative projects for scientific discovery, a large amount of scientific data needs to be visualized and then shared among the scientists. Tiled Display Wall?(TDW) has been widely accepted and used for visualization of large-scale scientific data. Scalable Adaptive Graphics Environment?(SAGE) has received attention from scientists as a middleware that organizes multiple display monitors into a network-aware large display monitor. Using a SAGE TDW, scientists can display multiple visualized contents on a single display monitor, each of which can be located at geographically distant site managed by other organizations. However, SAGE does not have a mechanism for managing multiple visualized data streams heading to a single TDW. In a conventional network, data flows for a same destination tend to share a same link, resulting in drop of packets and therefore poor visual quality. Moreover, because of the flexible nature of SAGE, rate of each visual data flow may change dynamically as a result of user interaction on a TDW, such as moving and resizing an application window. For the reason above, we propose and develop a dynamic route allocation method that switches packet flows onto network links where better performance is expected, in response to user interaction such as window movement and resizing. Technically, we have leveraged OpenFlow, an implementation of Software Defined Networking?(SDN), to integrate network programmability into SAGE. In this paper, we show how SAGE enhanced with the proposed method succeeded in avoiding network congestion and improving the quality of visualization on the TDW over the wide area OpenFlow network on the Internet. SAGE is a TDW middleware that can receive multiple streams from multi site.Dynamic changes of network traffic caused by user-interaction in SAGE.We modified SAGE with dynamic routing functionality triggered by user interaction.Dynamic routing functionality is implemented using OpenFlow.It aims to avoid network congestion for keeping high quality visualization.

Performance Characteristics of an SDN-Enhanced Job Management System for Cluster Systems with Fat-Tree Interconnect

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.

An Architectural Design of a Job Management System Leveraging Software Defined Network

Whether to be able to efficiently utilize the interconnect in a cluster system is a key factor in deciding the computational performance especially for a class of jobs that require intensive communications between processes. However, most of Job Management Systems (JMSs), which are deployed on cluster systems for load-balancing, do not have any mechanism that takes the pattern and requirements of communication occurred in a job into consideration, regardless of potential large impact on its performance. In this research, we explore a novel JMS that can assign computing resources to jobs submitted to the JMS from a standpoint of efficient use of both network and processor resource. More technically, in this paper, a JMS that integrates the network programming functionality of OpenFlow as Software Defined Network is proposed and discussed towards better and more efficient allocation of computing and network resources.