Dynamically Iterative MapReduce

[[abstract]]MapReduce is a distributed and parallel computing model for data-intensive tasks with features of optimized scheduling, flexibility, high availability, and high manageability. MapReduce can work on various platforms; however, MapReduce is not suitable for iterative programs because the performance may be lowered by frequent disk I/O operations. In order to improve system performance and resource utilization, we propose a novel MapReduce framework named Dynamically Iterative MapReduce (DIMR) to reduce numbers of disk I/O operations and the consumption of network bandwidth by means of using dynamic task allocation and memory management mechanism. We show that DIMR is promising with detail discussions in this paper.[[notice]]補正完畢[[incitationindex]]SCI[[incitationindex]]EI[[booktype]]紙本[[booktype]]電子

Vector Graph Implementations in E-Book Viewer Software and Cloud Platform

[[abstract]]Recently, many E-book readers have been developed to help people reading comic or novel on handheld devices. However, there are some challenges of developing ebook application such as image distortion, storage space, and vary of e-book format. Hence, we propose a system solution to solve these problems. We integrate vector graphic library into Android system and we also develop an e-book Android apps that combines cloud platform to extend e-book format supporting and user’s storage space. Our solution achieves near-linear speedup on cloud platforms.[[conferencetype]]國際[[conferencedate]]20120716~20120719[[booktype]]紙本[[iscallforpapers]]Y[[conferencelocation]]Las Vegas, US

Energy Efficient Geographic Routing Algorithms in Wireless Sensor Network

[[abstract]]Over the past decade, energy efficiency has consistently been a critical research topic in the field of wireless sensor networks. In wireless networks, signal interference often leads to power waste in a sensor node. Several SINR-based routing algorithms designed for energy efficiency or interference avoidance had been proposed. However, they are either too complex to be useful in practices or may slow in routing computation speed. In this paper, two energy efficient geographic routing algorithms (EEGRA) for wireless sensor network are proposed to address the power consumption issue while considering the routing computation speed. The first algorithm take the value of interference into the routing cost function, and uses it in the routing decision. The second algorithm transforms the problem into a constrained optimization problem, and solves it by searching the optimal discretized interference level. We adopt four geographic routing algorithms: GOAFR+, Face Routing, GPSR, and RandHT, in EEGRA algorithms and compare them with three other routing methods in terms of power consumption and computation cost for the grid and irregular sensor topologies. The experimental result shows that the EEGRA algorithms reduce energy consumption by 30–50% comparing to geographic routing methods. In addition, the time complexity of EEGRA algorithms is similar to the geographic greedy routing methods, which is much faster than the optimal SINR-based algorithm.[[notice]]補正完畢[[incitationindex]]EI[[booktype]]紙本[[booktype]]電子

CacheRAID: An Efficient Adaptive Write Cache Policy to Conserve RAID Disk Array Energy

[[abstract]]Cloud storage is a hot topic at the moment with Google's Google Storage, Microsoft's Sky Drive, iCloud, Drop box, Mozy and dozens of others. Because of these applications, conserving energy of storage systems is becoming a growing concern in current storage technology. The factors of disk power consumption include disk idle time, poor random writing performance and random read in distributed file systems. Hence, we present an adaptive write cache mechanism - Cache RAID. Redundant Arrays of Inexpensive Disk (RAID) is widely used in modern distributed storage systems. Our Cache RAID aims to improve the random access problems that implicitly exist in RAID techniques to create more idle time of hard drives, and conserve RAID disk array energy. The experimental results show that Cache RAID storage system can conserved 50%~70% of the power consumption compared to the conventional software RAID system.[[sponsorship]]IEEE Technical Committee on Scalable Computing[[conferencetype]]國際[[conferencedate]]20121105~20121108[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Chicago, Illinois, US

Parallel non-linear dimension reduction algorithm on GPU

[[abstract]]Advances in non-linear dimensionality reduction provide a way to understand and visualise the underlying structure of complex datasets. The performance of large-scale non-linear dimensionality reduction is of key importance in data mining, machine learning, and data analysis. In this paper, we concentrate on improving the performance of non-linear dimensionality reduction using large-scale datasets on the GPU. In particular, we focus on solving problems including k-nearest neighbour (KNN) search and sparse spectral decomposition for large-scale data, and propose an efficient framework for local linear embedding (LLE). We implement a k-d tree-based KNN algorithm and Krylov subspace method on the GPU to accelerate non-linear dimensionality reduction for large-scale data. Our results enable GPU-based k-d tree LLE processes of up to about 30-60? faster compared to the brute force KNN (Hernandez et al., 2007) LLE model on the CPU. Overall, our methods save O(n²-6n-2k-3) memory space.[[cooperationtype]]國外[[booktype]]紙

The Monitoring System Based on Nagios for Data Grid Environment

[[abstract]]The amount of digital data in today’s society is already enormous and it will continue to grow exponentially. Therefore, it is necessary to devise new ways to preserve and manage the data effectively and efficiently. SRB (Storage Resource Broker), and its extension iRODS (the Integrated Rule-Oriented Data System), are data grid technologies for managing colossal amounts of data. In a distributed environment, monitoring systems oversee the operation of computing systems. The monitoring service is crucial because it must ensure a high-quality computing environment and provide reliable services. In this paper, we introduce a monitoring system called SIAM, which is based on Nagios. SIAM supports full monitoring services for SRB/iRODS-based systems, including fault-tolerance and notification functions. This study focuses on extending existing components and notification functions to satisfy clients’ needs and improve our system’s failover scheme. The results of experiments show that the proposed system is feasible for cloud storage services, and it is adaptable robust, and responsive in the face of system failures. Overall, SIAM enhances the reliability of SRB/iRODS based systems significantly.[[conferencetype]]國際[[conferencedate]]20110717~20110721[[booktype]]紙本[[iscallforpapers]]Y[[conferencelocation]]Las Vegas, US

An Efficient Routing Algorithm to Optimize the Lifetime of Sensor Network Using Wireless Charging Vehicle

[[sponsorship]]IEEE Computer Society[[conferencetype]]國際[[conferencedate]]20141027~20141030[[booktype]]紙本[[iscallforpapers]]Y[[conferencelocation]]Philadelphia, US