Atsuko Takefusa's Homepage

Platforms of hosting services are expected to provide a virtual private computing infrastructure with a guaranteed level of performance according to each reservation request sent from a client. To expand the performance of the computing infrastructure for reservation requests, the platforms are required to reserve, coordinate, and control globally distributed computing and network resources across multiple domains. This paper proposes Grid Network Service - Web Services Interface version 2 (GNS-WSI2). GNS-WSI2 is a resource-reservation messaging protocol that establishes a client-server relationship. A server allocates available network resources over its own domain according to each reservation request from a client. GNS-WSI2 has the capability to reserve network resources rapidly and reliably over multiple network domains. This paper also presents demonstration results of the feasibility of GNS-WSI2 in terms of the scalable reservation of network resources over multiple network domains in a transpacific testbed. In the demonstration, two computing infrastructures over multiple network domains are dynamically provided for scientific computing and remotevisualization applications, respectively. On the provided infrastructures, these applications are executed. The feasibility is successfully shown through the demonstration.

At iGrid2005, we conducted a live demonstration where our Grid scheduling system co-allocated computing and network resources with advance reservation through Web services interfaces using the Grid Resource Scheduler (GRS), the Network Resource Management System (NRM), which is capable of GMPLS network resource management, and a GMPLS-based network test-bed, for the first time. The goal of the G-lambda project is to define a standard Web services interface (GNS-WSI) between GRS and NRM that is acceptable for both application service providers and commercial network operators, and which can be used as a tool for realizing new and emerging commercial services.

Striking progress of network technology is enabling high-performance global computing, in which computational and data resources in a wide area network (WAN) are transparently employed to solve large-scale problems. Several high-performance global computing systems, such as Ninf, NetSolve, RCS, Legion and Globus have already been proposed. Each of these systems proposes to effectively achieve high-performance with some efficient scheduling scheme, whereby a scheduler selects a set of appropriate computing resources that solve the client's computational problem. This paper proposes a performance evaluation model for effective scheduling in global computing systems. The proposed model represents a global computing system by a queueing network, in which servers and networks are represented by queueing systems. Verification of the proposed model and evaluation of scheduling schemes on the model showed that the model could simulate behavior of an actual global computing system and scheduling on the system effectively.

Co-allocation of performance-guaranteed computing and network re- sources 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 al- gorithm with extensive simulation, in terms of both functionality and practicality. The results show: The algorithm enables efficient co-allocation 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.

Grid and Network provisioning technology has enabled the construction of high-quality virtual computing infrastructures spanning several administrative organizations. However, it is still difficult for users to monitor the usage of distributed and various resources managed by multiple domains. We propose an authorization-based hierarchical distributed resource monitoring system called DMS that gathers information based on resource reservation, and filters information with the policies specified by the administrators using XACML, which is a standard authorization model and a policy description language. DMS co-works with the GridARS co-allocation framework to retrieve resource reservation information and adopts web services technologies and an extension of a standard data representation set. To confirm feasibility of the DMS system, we describe monitoring strategies for reserved computing and network resources in Collectors and we have developed a WSRF-based DMS prototype, which enables authorization by XACML. The experiments using the prototype system show: (1) Even when DMS employs a large number of policies, the overhead of the XACML authorization decision process is negligible, since that of WSRF/GSI is more dominant in the total processing time, and (2) the benefits of parallel information aggregation from multiple domains make the retrieval latency acceptable.

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 co-allocate distributed resources managed by various local schedulers stably.

This paper describes innovative architectures and techniques for reserving and coordinating highly distributed resources, a capability required for many large scale applications. In the fall of 2006, Japan's G-lambda research team and the United States' EnLIGHTened Computing research team used these innovations to achieve the world's first inter-domain coordination of resource managers for in-advance reservation of network bandwidth and compute resources between and among both the US and Japan. The compute and network resource managers had different interfaces and were independently developed. Automated interoperability among the resources in both countries was enabled through various Grid middleware components. In this paper, we describe the middleware components, testbeds, results, and lessons learned.

Advance Reservation is one possible way to enable resource co-allocation on the Grid. This method requires all the resources to have advance reservation capability as well as coordination protocol support. We employed 2-phased commit protocol as a coordination protocol, which is common in the distributed transaction area, and implemented an Advance Reservation Manager called {\bf PluS}. PluS works with existing local queuing managers, such as TORQUE or Grid Engine, and provides users advance reservation capability. To provide the capability, there are two implementation methods; 1) completely replaces the scheduling module of the queuing manger, 2) represents reservation as a queue and controls the queues using external interface. We designed and implemented a reservation manager with both way, and evaluated them. We found that the former has smaller overhead and allows arbitrary scheduling policy, while the latter is much easier to implement withacceptable response time.

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.

Data Grid is a Grid environment 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 accomodated 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.

The Computational Grid is a promising platform for the deployment of various high-performance computing applications. A number of projects have addressed the idea of software as a service on the network. These systems usually implement client-server architectures with many servers running on distributed Grid resources and have commonly been referred to as Network-enabled servers (NES). An important question is that of scheduling in this multi-client multi-server scenario. Note that in this context most requests are computationally intensive as they are generated by high-performance computing applications. The Bricks simulation framework has been developed and extensively used to evaluate scheduling strategies for NES systems. In this paper we first present recent developments and extensions to the Bricks simulation models. We discuss a deadline scheduling strategy that is appropriate for the multi-client multi-server case, and augment it with ``Load Correction'' and ``Fallback'' mechanisms which could improve the performance of the algorithm. We then give Bricks simulation results. The results show that future NES systems should use deadline-scheduling with multiple fallbacks and it is possible to allow users to make a trade-off between failure-rate and cost by adjusting the level of conservatism of deadline-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 would allow analysis and comparison of various scheduling schemes on 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 componentalized such that not only its constituents could be replaced to simulate various different system algorithms, but also allows incorporation of existing global computing components via its foreign interface. To test the validity of the latter characteristics, we incorporated the NWS system, which monitors and forecasts global computing systems behavior. Experiments were conducted by running NWS under a real environment versus the 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.

Rapid increase in speed and availability of network of supercomputers is making high-performance global computing possible, including our Ninf system. However, critical issues regarding system performance characteristics in global computing have been little investigated, especially under multi-client, multi-site WAN settings. In order to investigate the feasibility of Ninf and similar systems, we conducted benchmarks under various LAN and WAN environments, and observed the following results: 1) Given sufficient communication bandwidth, Ninf performance quickly overtakes client local performance, 2) current supercomputers are sufficient platforms for supporting Ninf and similar systems in terms of performance and OS fault resiliency, 3) for a vector-parallel machine (Cray J90), employing optimized data-parallel library is a better choice compared to conventional task-parallel execution employed for non-numerical data servers, 4) computationally intensive tasks such as EP can readily be supported under the current Ninf infrastructure, and 5) for communication-intensive applications such as Linpack, server CPU utilization dominates LAN performance, while communication bandwidth dominates WAN performance, and furthermore, aggregate bandwidth could be sustained for multiple clients located at different Internet sites; as a result, distribution of multiple tasks to computing servers on different networks would be essential for achieving higher client-observed performance. Our results are not necessarily restricted to the Ninf system, but rather, would be applicable to other similar global computing systems.

Recent developments of global computing systems such as Ninf, NetSolve, and Globus have opened up the opportunites for providing high-performance computing services over wide-area networks. However, most research focused on the individual architectural aspects of the system, or application deployment examples, instead of critical issues regarding system performance characteristics in global computing. Further, no step-by-step analysis or impartial comparison of various scheduling schemes has been conducted, though the performance and feasibility of a global computing system, which employs a large number of computational resources, highly depends on its scheduling scheme. Evaluation is made difficult by large-scale benchmarks and the need for reproducible results. Our comparative study performs deployment of example applications of network-based libraries using Ninf, NetSolve, and CORBA systems. There, we discover that dedicated systems for global computing such as Ninf and NetSolve have in some cases performance advantages over more generic distributed computing capabilities provided by CORBA. Also, we proposed the Bricks performance evaluation system, which would allow analysis and comparison of various scheduling schemes on 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 componentalized such that not only its constituents could be replaced to simulate various different system algorithms, but also allows incorporation of existing global computing components via its foreign interface. To test the validity of the latter characteristics, we incorporated the NWS system, which monitors and forecasts global computing systems behavior.

Rapid increase in speed and availability of global-network is opening up the possibilities of globally-distributed supercomputing, including our Ninf system. However, performance characteristics of these systems have been little investigated, especially under multi-clients, multi-sites situations. In order to establish methodology to schedule multiple job requests to multiple computational servers effectively and guarantee performance per each client, we conducted benchmarks under various WAN environments. There, we observed that communication bandwidth dominated performance for communication-intensive applications such as Linpack, and aggregate bandwidth could be sustained for multi-clients located at different internet sites. Based on these observations, we propose the need for a simulation model based on queuing theory. And we also performed preliminary benchmarks using our scheduling server, called the Ninf Metaserver. We also report on our collaborative efforts in bridging Ninf with NetSolve, a similar system being developed at Univ. of Tennessee/ORNL.