Pricing Computational Resources in Grid Economies

Pricing Computational Resources in Grid Economies

Kurt Vanmechelen (University of Antwerp, Belgium), Jan Broeckhove (University of Antwerp, Belgium), Wim Depoorter (University of Antwerp, Belgium) and Khalid Abdelkader (University of Antwerp, Belgium)
DOI: 10.4018/978-1-60566-184-1.ch017
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As grid computing technology moves further up the adoption curve, the issues of dealing with conflicting user requirements formulated by different users become more prevalent. In addition, the need to negotiate static sharing agreements between the different stakeholders in a grid system is time-consuming and offers limited incentive for resource owners to step into the grid’s infrastructure in a provider role. Resource management approaches that are currently adopted in grids are not able to deal with these issues in a flexible, value-maximizing way because of their system-centric approach. This contribution presents a clear motivation for the use of economic forms of scheduling in grid computing environments to address these shortcomings. The authors also provide an introductory overview of the different forms of market mechanisms that have been adopted by researchers in the field. In addition, the authors present simulation results concerning the use of Vickrey auctions and commodity markets as market mechanisms for dynamic pricing in grid resource markets.
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Grid technology has reached a maturity level in which computational resources are being virtualized, shared and used on a global scale. Large scale deployments of the technology in production level academic environments are being driven by projects such as EGEE in Europe and TeraGrid in the United States. These projects now make hundreds of teraflops in compute capacity and petabytes of storage capacity available to researchers in more than 40 countries. One of the crucial components of grid middleware, the software which enables the operation of a grid infrastructure, is the resource management system. This subsystem is responsible for mapping a user’s request for service to resources available in the grid. Often this involves a two staged process in which a grid service, called the resource broker, first determines a set of suitable local resource managers based on the request’s quality of service requirements. In the second stage, the local resource managers are contacted to fulfill the request by engaging the local resources they control (e.g. the set of CPUs in the cluster).

Currently, the resource management and scheduling approaches found in production level grid middleware have a strong focus on the efficient scheduling of jobs from a system-oriented point of view. This means that the broker schedules jobs in a way that maximizes the overall utilization of the infrastructure or that obtains the highest possible level of overall system throughput. These approaches to scheduling do not take into account the actual value grid users associate with their computations. As a result, the broker may be performing optimally from a system-oriented point of view, but suboptimally from a user-oriented point of view. The potential for value loss as a result of these suboptimal scheduling decisions increases with the load on the grid infrastructure and the heterogeneity of the valuations among users. As shown by Chun (2005), user valuations for allocations of motes on a sensor net testbed can vary by four orders of magnitude1.

In addition, current resource management systems assume the existence of static bilateral sharing agreements between the different parties that contribute to the shared grid infrastructure. These agreements are often hard to negotiate, and result in limited flexibility and openness with respect to the integration of new parties in the global grid infrastructure. As a result, several grid ‘islands’ or ‘silos’ emerge and the full potential of the infrastructure is not realized. This is partly due to the specific funding contracts under which grid resources are procured and brought into operation. Indeed, a currently debated topic is how to build grid infrastructures that are sustainable over the long term, i.e. that are self-supporting and do not require funding from a source that imposes the vision of global sharing of resources for their operation.

We believe that the introduction of an electronic market place for trading grid usage rights provides a promising approach to deal with the issues of openness, sustainability, and value maximization. Such a market place is open to all parties that wish to participate in the system as a provider or consumer. The incentives for (well-behaved) participation in such a market stem from a common value model and accounting system that charges or rewards the different parties involved, for their requested or delivered service.

Firstly, this differs from the negotiation model that is currently in place in which users need to lobby for access rights which are subsequently enforced by long term, static policies. A market-based approach allows for greater flexibility in terms of accepting new parties in the infrastructure and in terms of determining usage rights for users, resulting in a more open and agile grid infrastructure. This is especially important for the potential grid user base that is formed by small research institutions or SMEs. Their relative cost for maintaining and procuring computing infrastructure is high due to limited economics of scale and their often strongly fluctuating requirements. As a consequence, these users are not able to engage in bartering during negotiations of sharing agreements as they do not own a significant amount of computing infrastructure. On the other hand, this user base has the greatest potential for benefiting from the added value a grid infrastructure can provide. The possibility to pay for usage rights enables them to tap into this added value.

Key Terms in this Chapter

Bayes-Nash Equilibrium: When a system is in a Bayes-Nash equilibrium, the best strategy for each participant is to be truthful, provided that all other participants are truthful as well.

Incentive Compatibility: A mechanism is incentive compatible if it is best for all participants to be truthful in their actions. This means that there is no strategic advantage to be gained by being dishonest.

Best-Response Algorithm: An algorithm that determines the strategy that produces the best possible immediate outcome for a bidder, taking other bidder’s strategies as given.

Commodity Market: A market in which products are traded that have no qualitative difference.

Futures Market: A market in which goods are sold that are to be delivered at a certain point in the future, at a specified price.

Walrasian Auctioneer: A hypothetical entity that facilitates market adjustment in disequilibrium by announcing prices and collecting information about supply and demand at those prices without any disequilibrium transactions actually taking place.

Vickrey Auction: A second-price sealed-bid auction that has been proven to be incentive compatible. Bidders are not allowed to see each other’s bids. The highest bidder wins the auction and pays a transaction price which corresponds to the bid of the second highest bidder.

Spot Market: A market in which goods are sold and delivered immediately.

Exposure Problem: The problem that occurs when bidders have to win several objects in a (set of) auction(s) but are exposed to the risk of not winning all of them as competition on some of these objects turns out to be tougher than expected.

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Editorial Advisory Board
Table of Contents
Ruth E. Shaw
Emmanuel Udoh, Frank Zhigang Wang
Emmanuel Udoh
Chapter 1
Emmanuel Udoh, Frank Zhigang Wang, Vineet R. Khare
This chapter presents a historical record of the advent of Grid with a recourse to some basic definitions commonly accepted by most researchers. It... Sample PDF
Overview of Grid Computing
Chapter 2
Eric Aubanel
The problem of load balancing parallel applications is particularly challenging on computational grids, since the characteristics of both the... Sample PDF
Resource-Aware Load Balancing of Parallel Applications
Chapter 3
Enis Afgan, Purushotham Bangalore
Grid computing has emerged as the next generation computing platform. Because of the resource heterogeneity that exists in the grid environment... Sample PDF
Assisting Efficient Job Planning and Scheduling in the Grid
Chapter 4
Kuo-Chan Huang, Po-Chi Shih, Yeh-Ching Chung
Most current grid environments are established through collaboration among a group of participating sites which volunteer to provide free computing... Sample PDF
Effective Resource Allocation and Job Scheduling Mechanisms for Load Sharing in a Computational Grid
Chapter 5
Tevfik Kosar
As the data requirements of scientific distributed applications increase, the access to remote data becomes the main performance bottleneck for... Sample PDF
Data-Aware Distributed Batch Scheduling
Chapter 6
Gianni Pucciani, Flavia Donno, Andrea Domenici, Heinz Stockinger
Data replication is a well-known technique used in distributed systems in order to improve fault tolerance and make data access faster. Several... Sample PDF
Consistency of Replicated Datasets in Grid Computing
Chapter 7
Ming Wu, Xian-He Sun
Rapid advancement of communication technology has changed the landscape of computing. New models of computing, such as business-on-demand, Web... Sample PDF
Quality of Service of Grid Computing
Chapter 8
QoS in Grid Computing  (pages 75-83)
Zhihui Du, Zhili Cheng, Xiaoying Wang, Chuang Lin
This chapter first summarizes popular terms of QoS related concepts and technologies in grid computing, including SLA, End-to-End QoS Provision and... Sample PDF
QoS in Grid Computing
Chapter 9
Kris Bubendorfer, Ben Palmer, Ian Welch
A Grid resource broker is the arbiter for access to a Grid’s computational resources and therefore its performance and functionality has a... Sample PDF
Trust and Privacy in Grid Resource Auctions
Chapter 10
Sandro Fiore, Alessandro Negro, Salvatore Vadacca, Massimo Cafaro, Giovanni Aloisio, Roberto Barbera
Grid computing is an emerging and enabling technology allowing organizations to easily share, integrate and manage resources in a distributed... Sample PDF
An Architectural Overview of the GRelC Data Access Service
Chapter 11
Man Wang, Zhihui Du, Zhili Cheng
Resource Management System (RMS), which manages the Grid resources and matches the applications’ requests to the proper resources, is one of the... Sample PDF
Adaptive Resource Management in Grid Environment
Chapter 12
Vineet R. Khare, Frank Zhigang Wang
The need for a dynamic and scalable expansion of the grid infrastructure and resources and other scalability issues in terms of execution efficiency... Sample PDF
Bio-Inspired Grid Resource Management
Chapter 13
Yuhui Deng, Frank Zhigang Wang, Na Helian
Storage Grid is a new model for deploying and managing the heterogeneous, dynamic, large-scale, and geographically distributed storage resources.... Sample PDF
Service Oriented Storage System Grid
Chapter 14
Dominic Cherry, Maozhen Li, Man Qi
This chapter presents MediaGrid, a distributed storage system for archiving broadcast media contents. MediaGrid utilizes storage resources donated... Sample PDF
A Distributed Storage System for Archiving Broadcast Media Content
Chapter 15
Maozhen Li, Man Qi, Bin Yu
The computational grid is rapidly evolving into a service-oriented computing infrastructure that facilitates resource sharing and large-scale... Sample PDF
Service Discovery with Rough Sets
Chapter 16
Irfan Habib, Ashiq Anjum, Richard McClatchey
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On the Pervasive Adoption of Grid Technologies: A Grid Operating System
Chapter 17
Kurt Vanmechelen, Jan Broeckhove, Wim Depoorter, Khalid Abdelkader
As grid computing technology moves further up the adoption curve, the issues of dealing with conflicting user requirements formulated by different... Sample PDF
Pricing Computational Resources in Grid Economies
Chapter 18
Rosario M. Piro
Large, geographically distributed and heterogeneous computing infrastructures, such as the Grid, often span multiple organizations and... Sample PDF
Resource Usage Accounting in Grid Computing
Chapter 19
Frans Arickx, Jan Broeckhove, Peter Hellinckx, David Dewolfs, Kurt Vanmechelen
Quantum structure or scattering calculations often belong to a class of computational problems involving the aggregation of a set of matrices... Sample PDF
Grid-Based Nuclear Physics Applications
Chapter 20
Gabriel Aparicio, Fernando Blanco, Ignacio Blanquer, César Bonavides, Juan Luis Chaves, Miguel Embid, Álvaro Hernández
In the last years an increasing demand for Grid Infrastructures has resulted in several international collaborations. This is the case of the EELA... Sample PDF
Developing Biomedical Applications in the Framework of EELA
Chapter 21
Gerald Schaefer, Roger Tait
Efficient approaches to computationally intensive image processing tasks are currently highly sought after. In this chapter, the authors show how a... Sample PDF
Distributed Image Processing on a Blackboard System
Chapter 22
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The BaBar experiment uses data since 1999 in examining the violation of charge and parity (CP) symmetry in the field of high energy physics. This... Sample PDF
Simulated Events Production on the Grid for the BaBar Experiment
Chapter 23
Diego Liberati
A framework is proposed that creates, uses, and communicates information, whose organizational dynamics allows performing a distributed cooperative... Sample PDF
A Framework for Semantic Grid in E-Science
Chapter 24
Roberto Barbera, Valeria Ardizzone, Leandro Ciuffo
The Grid INFN virtual Laboratory for Dissemination Activities (GILDA) is a fully working Grid test-bed devoted to training and dissemination... Sample PDF
Grid INFN Virtual Laboratory for Dissemination Activities (GILDA)
Chapter 25
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The simulation and optimization of complex systems is a very time consuming and computationally intensive task. Therefore, global surrogate modeling... Sample PDF
Grid Enabled Surrogate Modeling
Chapter 26
Patrik Skogster
Grid computing is becoming as essential part of different business analysis. In traditional business computing infrastructures data transfer occurs... Sample PDF
GIS Grids and the Business Use of GIS Data
Chapter 27
Gokop Goteng, Ashutosh Tiwari, Rajkumar Roy
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Grid Computing: Combating Global Terrorism with the World Wide Grid
Chapter 28
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Chapter 29
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Chapter 30
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