Po-Chi Shih

Integrating grid with intrusion detection

In recent years, distributed denial-of-service (DDoS) and denial-of-service (DoS) are the most dreadful network threats. Single-node IDS often suffers from losing its detection effectiveness and capability when processing enormous network traffic. To solve the drawbacks, we propose grid-based IDS, called grid intrusion detection system (GIDS), which uses grid computing resources to detect intrusion packets. For balancing detection load, score subtraction approach (SSA) and score addition approach (SAA) are deployed. Furthermore, to effectively detect intrusions, a two-phase packet detection process is proposed. The first phase detects logical and momentary attacks. Chronic attacks are detected in the second phase. Experiments are also performed and the results show that GIDS is truly an outstanding system in detecting attacks.

A high-performance computational resource broker for grid computing environments

Internet computing and grid technologies promise to change the way we tackle complex problems. They will enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. As grid computing is becoming a reality, there is a need for managing and monitoring the available resources worldwide, as well as the need for conveying these resources to the everyday user. This paper describes a resource broker with its main function as to match the available resources to the users needs. The use of the resource broker provides a uniform interface to access any of the available and appropriate resources using users credentials. The resource broker runs on top of the Globus toolkit. Therefore, it provides security and current information about the available resources and serves as a link to the diverse systems available in the grid.

Design and Implementation of TIGER Grid: an Integrated Metropolitan-Scale Grid Environment

Internet computing and Grid technologies promise to change the way we tackle complex problems. Harnessing these new technologies effectively, it will transform scientific disciplines ranging from highenergy physics to life sciences. This paper describes a metropolitan-scale Grid computing platform named TIGER Project (standing for Taichung Integrating Grid Environment and Resource), which basically interconnects universities and high schools’ cluster computing resources and sharing available resources among them, for investigations in system technologies and high performance applications. This novel project shows the viability of implementation of such project in a metropolitan city.

An efficient network information model using NWS for grid computing environments

Grid computing technologies enable large-scale aggregation and sharing of resources via wide-area networks focused on sharing computational, data, and other resources to form general-purpose services for users. In this paper, we address network information gathering and focus on providing approximate measurement models for network-related information using Network Weather Service (NWS) for future scheduling and benchmarking. We propose a network measurement model for gathering network-related information including bandwidth, latency, forecasting, error rates, etc., without generating excessive system overhead. We consider inaccuracies in real-world network values in generating approximation values for future use.

A resource broker with an efficient network information model on grid environments

Abstract This paper describes a resource broker whose main function is to match available resources to user needs. The resource broker provides a uniform interface for accessing available and appropriate resources via user credentials. We also focus on providing approximate measurement models for network-related information using NWS for future scheduling and benchmarking. We first propose a network measurement model for gathering network-related information (including bandwidth, latency, forecasting, error rates, etc.) without generating excessive system overhead. Second, we constructed a grid platform using Globus Toolkit that integrates the resources of five schools in Taichung integrated grid environment resources (TIGER). The resource broker runs on top of TIGER. Therefore, it provides security and current information about available resources and serves as a link to the diverse systems available in the Grid.

A Resource Broker for Computing Nodes Selection in Grid Computing Environments

As Grid Computing is becoming a reality, there is a need for manag- ing and monitoring the available resources worldwide, as well as the need for conveying these resources to the everyday user. This paper describes a resource broker with its main function as to match the available resources to the users needs. The use of the resource broker provides a uniform interface to access any of the available and appropriate resources using users credentials. The resource broker runs on top of the Globus Toolkit. Therefore, it provides security and current information about the available resources and serves as a link to the di- verse systems available in the Grid.

Towards feasible and effective load sharing in a heterogeneous computational grid

A grid has to provide strong incentive for participating sites to join and stay in it. Participating sites are concerned with the performance improvement brought by the gird for the jobs of their own local user communities. Feasible and effective load sharing is key to fulfilling such a concern. This paper explores the load-sharing policies concerning feasibility and heterogeneity on computational grids. Several job scheduling and processor allocation policies are proposed and evaluated through a series of simulations using workloads derived from publicly available trace data. The simulation results indicate that the proposed job scheduling and processor allocation policies are feasible and effective in achieving performance improvement on a heterogeneous computational grid.

Adaptive Processor Allocation for Moldable Jobs in Computational Grid

In a computational grid environment, a common practice is try to allocate an entire parallel job onto a single participating site. Sometimes a parallel job, upon its submission, cannot fit in any single site due to the occupation of some resources by running jobs. How the job scheduler handles such situations is an important issue which has the potential to further improve the utilization of grid resources as well as the performance of parallel jobs. This paper develops adaptive processor allocation policies based on the moldable property of parallel jobs to deal with such situations in a heterogeneous computational grid environment. The proposed policies are evaluated through a series of simulations using real workload traces. The results indicate that the proposed adaptive processor allocation policies can further improve the system performance of a heterogeneous computational grid significantly.

Middleware of Taiwan UniGrid

Taiwan UniGrid (Taiwan <u>Uni</u>versity <u>Grid</u>) is a Grid computing platform, which is founded by a community of educational and research organizations interested in Grid computing technologies in Taiwan. In this paper, we present the design and development of a middleware for Taiwan UniGrid. Taiwan UniGrid middleware consists of three primary modules: 1) UniGrid Portal, 2) Computing Service, and 3) Data Service. We explain the major design issues that we suffered from the development of these three modules and propose the corresponding approaches to them. The detailed system architecture, software components and features are elaborated. Finally, an example of a workflow consisting of MPI parallel jobs demonstrates that users can utilize Grid resources with ease via our middleware platform.

Design and implementation of a workflow-based resource broker with information system on computational grids

The grid is a promising infrastructure that can allow scientists and engineers to access resources among geographically distributed environments. Grid computing is a new technology which focuses on aggregating resources (e.g., processor cycles, disk storage, and contents) from a large-scale computing platform. Making grid computing a reality requires a resource broker to manage and monitor available resources. This paper presents a workflow-based resource broker whose main functions are matching available resources with user requests and considering network information statuses during matchmaking in computational grids. The resource broker provides a graphic user interface for accessing available and the appropriate resources via user credentials. This broker uses the Ganglia and NWS tools to monitor resource status and network-related information, respectively. Then we propose a history-based execution time estimation model to predict the execution time of parallel applications, according to previous execution results. The experimental results show that our model can accurately predict the execution time of embarrassingly parallel applications. We also report on using the Globus Toolkit to construct a grid platform called the TIGER project that integrates resources distributed across five universities in Taichung city, Taiwan, where the resource broker was developed.