Atsuko Takefusa

Overview of a performance evaluation system for global computing scheduling algorithms

While there have been several proposals of high-performance global computing systems, scheduling schemes for the systems have not been well investigated. The reason is difficulties of evaluation by large-scale benchmarks with reproducible results. Our Bricks performance evaluation system allows the analysis and comparison of various scheduling schemes in a typical high-performance global computing setting. Bricks can simulate various behaviors of global computing systems, especially the behavior of networks and resource scheduling algorithms. Moreover, Bricks is partitioned into components such that not only can its constituents be replaced to simulate various different system algorithms, but it also allows the incorporation of existing global computing components via its foreign interface. To test the validity of the latter characteristics, we incorporated the NWS (Network Weather Service) system, which monitors and forecasts global computing systems behavior. Experiments were conducted by running NWS under a real environment versus a Bricks-simulated environment, given the observed parameters of the real environment. We observed that Bricks behaved in the same manner as the real environment, and NWS also behaved similarly, making quite comparative forecasts under both environments.

G-lambda: coordination of a grid scheduler and lambda path service over GMPLS

A vertical coordination between computing resource scheduler and network resource scheduler for Grid-based applications is described. The network resource management system virtualizes and schedules network resources to inter-work with Grid resource scheduler through Web-services interface.

Performance analysis of scheduling and replication algorithms on Grid Datafarm architecture for high-energy physics applications

Data Grid is a Grid for ubiquitous access and analysis of large-scale data. Because Data Grid is in the early stages of development, the performance of its petabyte-scale models in a realistic data processing setting has not been well investigated. By enhancing our Bricks Grid simulator to accommodated Data Grid scenarios, we investigate and compare the performance of different Data Grid models. These are categorized mainly as either central or tier models; they employ various scheduling and replication strategies under realistic assumptions of job processing for CERN LHC experiments on the Grid Datafarm system. Our results show that the central model is efficient but that the tier model, with its greater resources and its speculative class of background replication policies, are quite effective and achieve higher performance, while each tier is smaller than the central model.

An advance reservation-based co-allocation algorithm for distributed computers and network bandwidth on QoS-guaranteed grids

Co-allocation of performance-guaranteed computing and network resources provided by several administrative domains is one of the key issues for constructing a QoS-guaranteed Grid. We propose an advance reservation-based co-allocation algorithm for both computing and network resources on a QoS-guaranteed Grid, modeled as an integer programming (IP) problem. The goal of our algorithm is to create reservation plans satisfying user resource requirements as an on-line service. Also the algorithm takes co-allocation options for user and resource administrator issues into consideration. We evaluate the proposed algorithm with extensive simulation, in terms of both functionality and practicality. The results show: The algorithm enables efficient coallocation of both computing and network resources provided by multiple domains, and can reflect reservation options for resource administrators issues as a first step. The calculation times needed for selecting resources using an IP solver are acceptable for an on-line service.

GridARS: an advance reservation-based grid co-allocation framework for distributed computing and network resources

For high performance parallel computing on actual Grids, one of the important issues is to co-allocate the distributed resources that are managed by various local schedulers with advance reservation. To address the issue, we proposed and developed the GridARS resource co-allocation framework, and a general advance reservation protocol that uses WSRF/GSI and a two-phased commit (2PC) protocol to enable a generic and secure advance reservation process based on distributed transactions, and provides the interface module for various existing resource schedulers. To confirm the effectiveness of GridARS, we describe the performance of a simultaneous reservation process and a case study of GridARS grid co-allocation over transpacific computing and network resources. Our experiments showed that: 1) the GridARS simultaneous 2PC reservation process is scalable and practical and 2) GridARS can coallocate distributed resources managed by various local schedulers stably.

Multi-client LAN/WAN Performance Analysis of Ninf: a High-Performance Global Computing System

Rapid increase in speed and availability of network of supercomputers is making high performance global computing possible, in which computational and data resources in the network are collectively employed to solve large-scale problems. There have been several recent proposals of global computing including our Ninf system. However, critical issues regarding system performance characteristics in global computing have been little investigated, especially under multi-clients, multi-sites WAN settings. In order to investigate the feasibility of Ninf and similar systems, we conducted benchmarks with different communication/computation characteristics on a variety of combinations of clients and servers in their performance, architecture, etc. under LAN, single-site WAN, multi-site WAN situations.

Design and Implementation of a Local Scheduling System with Advance Reservation for Co-allocation on the Grid

While advance reservation is an essential capability for co-allocating several resources on Grid environments, it is not obvious how it can co-exist with priority-based First Come First Served scheduling, that is widely used as local scheduling policy today. To investigate this problem, we 1) developed a scheduling API in Java for TORQUE, a variant of OpenPBS, that enables users to implement their own schedulers and replace the original scheduling module with them, 2) implemented a prototype scheduler module that has advance reservation capability with the API. We also provide an external interface for the reservation capability based on WSRF to enable co-allocation of resources over the Grid. Using this interface with the job submission module from Globus toolkit 4, users can make reservation for resources and submit jobs over the Grid.

GridARS: A Grid Advanced Resource Management System Framework for Intercloud

Intercloud is a promising technology for data intensive applications. However, an important issue for Intercloud applications is orchestration of various virtualized and performance-assured resources, not only computers, but also network and storage, provided from multiple domains. We have been developing an advance reservation-based resource management framework, called Grid ARS, which can integrate heterogeneous resources and construct a performance-assured virtual infrastructure over Intercloud environment. Grid ARS provides four services that address resource management, resource allocation planning, provisioning and monitoring of the constructed virtual infrastructure. Grid ARS has been developed using common Web services technologies and standards. In this paper, we present overview of Grid ARS and its service components and describe Grid ARS demonstration challenges, demonstration at GLIF2010 and SC10 and OGF NSI interoperation in 2011.

Managing and controlling GMPLS network resources for grid applications

Inter-working between GMPLS network and grid computing application through Web-services interface is demonstrated for the first time. Lambda LSP-based network resource virtualization and scheduling techniques successfully achieves nation-wide grid computing environment with advance reservation operation.

Joint storage-network resource management for super high-definition video delivery service

This paper proposes a joint storage-network resource management for a super high-definition video delivery service. The method for allocating storage and optical path resources is discussed. The feasibility of the proposed system is shown.