Draft Regional Recommendations for the Pacific Northwest on Water Quality Trading

In March 2013, water quality agency staff from Idaho, Oregon, and Washington, U.S. EPA Region 10, Willamette Partnership, and The Freshwater Trust convened a working group for the first of a series of four interagency workshops on water quality trading in the Pacific Northwest. Facilitated by Willamette Partnership through a USDA-NRCS Conservation Innovation Grant, those who assembled over the subsequent eight months discussed and evaluated water quality trading policies, practices, and programs across the country in an effort to better understand and draw from EPA's January 13, 2003, Water Quality Trading Policy, and its 2007 Permit Writers' Toolkit, as well as existing state guidance and regulations on water quality trading. All documents presented at those conversations and meeting summaries are posted on the Willamette Partnership's website.The final product is intended to be a set of recommended practices for each state to consider as they develop water quality trading. The goals of this effort are to help ensure that water quality "trading programs" have the quality, credibility, and transparency necessary to be consistent with the "Clean Water Act" (CWA), its implementing regulations and state and local water quality laws

A Novel Workload Allocation Strategy for Batch Jobs

The distribution of computational tasks across a diverse set of geographically distributed heterogeneous resources is a critical issue in the realisation of true computational grids. Conventionally, workload allocation algorithms are divided into static and dynamic approaches. Whilst dynamic approaches frequently outperform static schemes, they usually require the collection and processing of detailed system information at frequent intervals - a task that can be both time consuming and unreliable in the real-world. This paper introduces a novel workload allocation algorithm for optimally distributing the workload produced by the arrival of batches of jobs. Results show that, for the arrival of batches of jobs, this workload allocation algorithm outperforms other commonly used algorithms in the static case. A hybrid scheduling approach (using this workload allocation algorithm), where information about the speed of computational resources is inferred from previously completed jobs, is then introduced and the efficiency of this approach demonstrated using a real world computational grid. These results are compared to the same workload allocation algorithm used in the static case and it can be seen that this hybrid approach comprehensively outperforms the static approach

Towards Autonomic Service Provisioning Systems

This paper discusses our experience in building SPIRE, an autonomic system for service provision. The architecture consists of a set of hosted Web Services subject to QoS constraints, and a certain number of servers used to run session-based traffic. Customers pay for having their jobs run, but require in turn certain quality guarantees: there are different SLAs specifying charges for running jobs and penalties for failing to meet promised performance metrics. The system is driven by an utility function, aiming at optimizing the average earned revenue per unit time. Demand and performance statistics are collected, while traffic parameters are estimated in order to make dynamic decisions concerning server allocation and admission control. Different utility functions are introduced and a number of experiments aiming at testing their performance are discussed. Results show that revenues can be dramatically improved by imposing suitable conditions for accepting incoming traffic; the proposed system performs well under different traffic settings, and it successfully adapts to changes in the operating environment.Comment: 11 pages, 9 Figures, http://www.wipo.int/pctdb/en/wo.jsp?WO=201002636