Yasushi Inoguchi

Bio: Yasushi Inoguchi is an academic researcher from Japan Advanced Institute of Science and Technology. The author has contributed to research in topics: Network performance & Massively parallel. The author has an hindex of 16, co-authored 102 publications receiving 1105 citations. Previous affiliations of Yasushi Inoguchi include National Presto Industries.

Performance evaluation of a Green Scheduling Algorithm for energy savings in Cloud computing

Abstract: With energy shortages and global climate change leading our concerns these days, the power consumption of datacenters has become a key issue. Obviously, a substantial reduction in energy consumption can be made by powering down servers when they are not in use. This paper aims at designing, implementing and evaluating a Green Scheduling Algorithm integrating a neural network predictor for optimizing server power consumption in Cloud computing. We employ the predictor to predict future load demand based on historical demand. According to the prediction, the algorithm turns off unused servers and restarts them to minimize the number of running servers, thus minimizing the energy use at the points of consumption to benefit all other levels. For evaluation, we perform simulations with two load traces. The results show that the PP20 mode can save up to 46.3% of power consumption with a drop rate of 0.03% on one load trace, and a drop rate of 0.12% with a power reduction rate of 46.7% on the other.

Secure Data Aggregation in Wireless Sensor Networks: A Survey

Abstract: Data aggregation is a widely used technique in wireless sensor networks. The security issues, data confidentiality and integrity, in data aggregation become vital when the sensor network is deployed in a hostile environment. There has been many related work proposed to address these security issues. In this paper we survey these work and classify them into two cases: hop-by-hop encrypted data aggregation and end-to-end encrypted data aggregation. We also propose two general frameworks for the two cases respectively. The framework for end-to-end encrypted data aggregation has higher computation cost on the sensor nodes, but achieves stronger security, in comparison with the framework for hop-by-hop encrypted data aggregation.

CPU Load Predictions on the Computational Grid

Abstract: The ability to accurately predict future resource capabilities is of great importance for applications and scheduling algorithms which need to determine how to use time-shared resources in a dynamic grid environment. In this paper we present and evaluate a new and innovative method to predict the one-stepahead CPU load in a grid. Our prediction strategy forecasts the future CPU load based on the tendency in several past steps and in previous similar patterns, and uses a polynomial fitting method. Our experimental results demonstrate that this new prediction strategy achieves average prediction errors that are between 37% and 86% lower than those incurred by the previously best tendency-based method.

CPU Load Predictions on the Computational Grid*This research is conducted as a program for the 21st Century COE Program by Ministry of Education, Culture, Sports, Science and Technology, Japan.

Abstract: To make the best use of the resources in a shared grid environment, an application scheduler must make a prediction of available performance on each resource. In this paper, we examine the problem of predicting available CPU performance in time-shared grid system. We present and evaluate a new and innovative method to predict the one-step-ahead CPU load in a grid. Our prediction strategy forecasts the future CPU load based on the variety tendency in several past steps and in previous similar patterns, and uses a polynomial fitting method. Our experimental results on large load traces collected from four different kinds of machines demonstrate that this new prediction strategy achieves average prediction errors which are between 22% and 86% less than those incurred by four previous methods.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Introduction to the Finite Element Method

Abstract: This chapter introduces the finite element method (FEM) as a tool for solution of classical electromagnetic problems. Although we discuss the main points in the application of the finite element method to electromagnetic design, including formulation and implementation, those who seek deeper understanding of the finite element method should consult some of the works listed in the bibliography section.

Internet of Things (IoT): A Vision, Architectural Elements, and Future Directions

Abstract: Ubiquitous sensing enabled by Wireless Sensor Network (WSN) technologies cuts across many areas of modern day living. This offers the ability to measure, infer and understand environmental indicators, from delicate ecologies and natural resources to urban environments. The proliferation of these devices in a communicating-actuating network creates the Internet of Things (IoT), wherein, sensors and actuators blend seamlessly with the environment around us, and the information is shared across platforms in order to develop a common operating picture (COP). Fuelled by the recent adaptation of a variety of enabling device technologies such as RFID tags and readers, near field communication (NFC) devices and embedded sensor and actuator nodes, the IoT has stepped out of its infancy and is the the next revolutionary technology in transforming the Internet into a fully integrated Future Internet. As we move from www (static pages web) to web2 (social networking web) to web3 (ubiquitous computing web), the need for data-on-demand using sophisticated intuitive queries increases significantly. This paper presents a cloud centric vision for worldwide implementation of Internet of Things. The key enabling technologies and application domains that are likely to drive IoT research in the near future are discussed. A cloud implementation using Aneka, which is based on interaction of private and public clouds is presented. We conclude our IoT vision by expanding on the need for convergence of WSN, the Internet and distributed computing directed at technological research community.