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Mitigating Provider Uncertainty in Service Provision Contracts
"... Uncertainty is an inherent property of open, distributed and multi-party systems. The viability of the mutually beneficial relationships which motivate these systems relies on rational decision-making by each constituent party under uncertainty. Service provision in Grid systems is one such relation ..."
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Uncertainty is an inherent property of open, distributed and multi-party systems. The viability of the mutually beneficial relationships which motivate these systems relies on rational decision-making by each constituent party under uncertainty. Service provision in Grid systems is one such relationship. Uncertainty is experienced by the service provider in his ability to deliver a service with selected quality level guarantees due to inherent non-determinism, such as load fluctuations and hardware failures. Statistical estimators utilized to model this non-determinism introduce additional uncertainty through sampling error. Inability of the provider to accurately model and analyze uncertainty in the quality level guarantees can result in the formation of sub-optimal service provision contracts. Emblematic consequences include loss of revenue, under-utilization of resources and erosion of trust and reputation. We propose a utility model for contract-based service provision to provide a systematic approach to optimal service provision contract formation under uncertainty. Monitoring policies to enable the derivation of statistical estimators for quality level are introduced, with analysis of their resultant accuracy and cost. 1
Optimizing revenue: Service provisioning systems with qos contracts
, 2007
"... Abstract: We consider the problem of how best to structure and control a distributed computer system containing many processors, subject to Quality of Service contracts. Services of different types are offered, with different charges for running jobs and penalties for failing to meet the QoS require ..."
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Abstract: We consider the problem of how best to structure and control a distributed computer system containing many processors, subject to Quality of Service contracts. Services of different types are offered, with different charges for running jobs and penalties for failing to meet the QoS requirements. The aim is to choose the number of servers allocated to each service type, and the admission criteria for jobs of that type, so as to maximize the total average revenue per unit time. The performance of a fast allocation heuristic is evaluated. 1
DFCA: A Flexible Refundable Auction for Limited Capacity Suppliers
"... Abstract. This paper proposes anovel auction-basedmechanismsnamed Decreasing Cancellation Fee Auction (DCFA) for task allocation in the environment where a service provider has finite capacities and consumers could withdraw their bids. We consider a new type of auction called the refundable auction, ..."
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Abstract. This paper proposes anovel auction-basedmechanismsnamed Decreasing Cancellation Fee Auction (DCFA) for task allocation in the environment where a service provider has finite capacities and consumers could withdraw their bids. We consider a new type of auction called the refundable auction, i. e. refund means that a consumer’s showing up is un-certain and he can get back partial of his payment if his cancellation or no-show occurs. This mechanism can boost seller revenue, satisfy incen-tive compatibility, individual rationality and still hold a high efficiency.
unknown title
, 2010
"... Efficient, non obstructive scheduling on computing grids using virtual execution environments ..."
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Efficient, non obstructive scheduling on computing grids using virtual execution environments
Added entries UNIVERSITY OF NEWCASTLE UPON TYNE
, 1023
"... We consider the problem of how best to structure and control a distributed computer system containing many processors, subject to Quality of Service contracts. Services of different types are offered, with different charges for running jobs and penalties for failing to meet the QoS requirements. The ..."
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We consider the problem of how best to structure and control a distributed computer system containing many processors, subject to Quality of Service contracts. Services of different types are offered, with different charges for running jobs and penalties for failing to meet the QoS requirements. The aim is to choose the number of servers allocated to each service type, and the admission criteria for jobs of that type, so as to maximize the total average revenue per unit time. For a given set of parameters, it is shown how to compute the optimal server allocation and the associated admission policy. The performance of a fast allocation heuristic is also evaluated. © 2007 University of Newcastle upon Tyne. Printed and published by the University of Newcastle upon Tyne,
Towards Modeling Trust Based Decisions: A Game Theoretic Approach
"... Abstract. Current trust models enable decision support at an implicit level by means of thresholds or constraint satisfiability. Decision support is mostly included only for a single binary action, and does not explicitly consider the purpose of a transaction. In this paper, we present a game theore ..."
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Abstract. Current trust models enable decision support at an implicit level by means of thresholds or constraint satisfiability. Decision support is mostly included only for a single binary action, and does not explicitly consider the purpose of a transaction. In this paper, we present a game theoretic model that is specifically tuned for decision support on a whole host of actions, based on specified thresholds of risk. As opposed to traditional representations on the real number line between 0 and +1, Trust in our model is represented as an index into a set of actions ordered according to the agent’s preference. A base scenario of zero trust is defined by the equilibrium point of a game described in normal form with a certain payoff structure. We then present the blind trust model, where an entity attempts to initiate a trust relationship with another entity for a one-time transaction, without any prior knowledge or recommendations. We extend this to the incentive trust model where entities can offer incentives to be trusted in a multi-period transaction. For a specified risk threshold, both models are analyzed by using the base scenario of zero trust as a reference. Lastly, we present some issues involved in the translation of our models to practical scenarios, and suggest a rich set of extensions of the generalized game theoretic approach to model decision support for existing trust frameworks.
1 Abstract
, 2006
"... trust, pricing This document discusses extensions to the pricing structures presented in [2] for the provision of IT services that ensure trust without requiring repeated interactions between service providers and users. We extend [2] by providing theorems demonstrating the existence of incentivecom ..."
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trust, pricing This document discusses extensions to the pricing structures presented in [2] for the provision of IT services that ensure trust without requiring repeated interactions between service providers and users. We extend [2] by providing theorems demonstrating the existence of incentivecompatible mechanisms for a broad class of expected costs to the user, and also introduce a notion of fairness with which to constrain the space of acceptable mechanisms.
Towards Modeling Trust Based Decisions: A Game Theoretic Approach
"... Abstract. Current trust models enable decision support at an implicit level by means of thresholds or constraint satisfiability. Decision support is mostly included only for a single binary action, and does not explicitly consider the purpose of a transaction. In this paper, we present a game theore ..."
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Abstract. Current trust models enable decision support at an implicit level by means of thresholds or constraint satisfiability. Decision support is mostly included only for a single binary action, and does not explicitly consider the purpose of a transaction. In this paper, we present a game theoretic model that is specifically tuned for decision support on a whole host of actions, based on specified thresholds of risk. As opposed to traditional representations on the real number line between 0 and +1, Trust in our model is represented as an index into a set of actions ordered according to the agent’s preference. A base scenario of zero trust is defined by the equilibrium point of a game described in normal form with a certain payoff structure. We then present the blind trust model, where an entity attempts to initiate a trust relationship with another entity for a one-time transaction, without any prior knowledge or recommendations. We extend this to the incentive trust model where entities can offer incentives to be trusted in a multi-period transaction. For a specified risk threshold, both models are analyzed by using the base scenario of zero trust as a reference. Lastly, we present some issues involved in the translation of our models to practical scenarios, and suggest a rich set of extensions of the generalized game theoretic approach to model decision support for existing trust frameworks.
