Joint Computing and Network Resource Scheduling in a Lambda Grid Network

Data-intensive Grid applications require huge data transfers between grid computing nodes. These computing nodes, where computing jobs are executed, are usually geographically separated. A grid network that employs optical wavelength division multiplexing (WDM) technology and optical switches to interconnect computing resources with dynamically provisioned multi-gigabit rate bandwidth lightpath is called a Lambda Grid network. A computing task may be executed on any one of several computing nodes which possesses the necessary resources. In order to reflect the reality in job scheduling, allocation of network resources for data transfer should be taken into consideration. However, few scheduling methods consider the communication contention on Lambda Grids. In this paper, we investigate the joint scheduling problem while considering both optical network and computing resources in a Lambda Grid network. The objective of our work is to maximize the total number of jobs that can be scheduled in a Lambda Grid network. An adaptive routing algorithm is proposed and implemented for accomplishing the communication tasks for every job submitted in the network. Four heuristics (FIFO, ESTF, LJF, RS) are implemented for job scheduling of the computational tasks. Simulation results prove the feasibility and efficiency of the proposed solution.

Joint Computing and Network Resource Scheduling in a Lambda Grid Network

Data-intensive Grid applications require huge data transfers between grid computing nodes. These computing nodes, where computing jobs are executed, are usually geographically separated. A grid network that employs optical wavelength division multiplexing (WDM) technology and optical switches to interconnect computing resources with dynamically provisioned multi-gigabit rate bandwidth lightpath is called a Lambda Grid network. A computing task may be executed on any one of several computing nodes which possesses the necessary resources. In order to reflect the reality in job scheduling, allocation of network resources for data transfer should be taken into consideration. However, few scheduling methods consider the communication contention on Lambda Grids. In this paper, we investigate the joint scheduling problem while considering both optical network and computing resources in a Lambda Grid network. The objective of our work is to maximize the total number of jobs that can be scheduled in a Lambda Grid network. An adaptive routing algorithm is proposed and implemented for accomplishing the communication tasks for every job submitted in the network. Four heuristics (FIFO, ESTF, LJF, RS) are implemented for job scheduling of the computational tasks. Simulation results prove the feasibility and efficiency of the proposed solution.

What Business Reference Librarians Need to Know about Intellectual Property: Presentations sponsored by the Patent and Trademark Depository Library Association (PTDLA) at the American Library Association Annual Conference, New Orleans, June 25, 2006

Presentations sponsored by the Patent and Trademark Depository Library Association (PTDLA) at the American Library Association Annual Conference, New Orleans, June 25, 2006 Speaker #1: Nan Myers Associate Professor; Government Documents, Patents and Trademarks Librarian Wichita State University, Wichita, KS Title: Intellectual Property Roundup: Copyright, Trademarks, Trade Secrets, and Patents Abstract: This presentation provides a capsule overview of the distinctive coverage of the four types of intellectual property – What they are, why they are important, how to get them, what they cost, how long they last. Emphasis will be on what questions patrons ask most, along with the answers! Includes coverage of the mission of Patent & Trademark Depository Libraries (PTDLs) and other sources of business information outside of libraries, such as Small Business Development Centers. Speaker #2: Jan Comfort Government Information Reference Librarian Clemson University, Clemson, SC Title: Patents as a Source of Competitive Intelligence Information Abstract: Large corporations often have R&D departments, or large numbers of staff whose jobs are to monitor the activities of their competitors. This presentation will review strategies that small business owners can employ to do their own competitive intelligence analysis. The focus will be on features of the patent database that is available free of charge on the USPTO website, as well as commercial databases available at many public and academic libraries across the country. Speaker #3: Virginia Baldwin Professor; Engineering Librarian University of Nebraska-Lincoln, Lincoln, NE Title: Mining Online Patent Data for Business Information Abstract: The United States Patent and Trademark Office (USPTO) website and websites of international databases contains information about granted patents and patent applications and the technologies they represent. Statistical information about patents, their technologies, geographical information, and patenting entities are compiled and available as reports on the USPTO website. Other valuable information from these websites can be obtained using data mining techniques. This presentation will provide the keys to opening these resources and obtaining valuable data. Speaker #4: Donna Hopkins Engineering Librarian Renssalaer Polytechnic Institute, Troy, NY Title: Searching the USPTO Trademark Database for Wordmarks and Logos Abstract: This presentation provides an overview of wordmark searching in www.uspto.gov, followed by a review of the techniques of searching for non-word US trademarks using codes from the Design Search Code Manual. These codes are used in an electronic search, either on the uspto website or on CASSIS DVDs. The search is sometimes supplemented by consulting the Official Gazette. A specific example of using a section of the codes for searching is included. Similar searches on the Madrid Express database of WIPO, using the Vienna Classification, will also be briefly described.