Dissertation•
A synergistic reputation-policy based trust model for Grid resource selection
01 Jan 2011-
TL;DR: An internal workflow simulation utilises the GREPTrust testbed in order to empirically assess the criteria by which the synergistic reputation-policy based trust model outperforms esoteric trust models regarding resource selection and provides substantive evidence that the reputation- policy paradigm is a welcome addition to the Grid computing community.
Abstract: In the context of Grid computing, reputation-based trust management
systems are playing an increasingly important role for supporting
coordinated resource sharing and ensuring provision of quality of service
However, the existing Grid reputation-based trust management systems
are considered limited as they are bounded to esoteric reputation-based
trust models encompassing predefined metrics for calculating and selecting
trusted computing resources and as a result, they prevent external
involvement in the trust and reputation evaluation processes
This thesis suggests an alternative approach for reputation modelling
founded on its core argument proclaiming that reputation is a subjective
matter as well as context dependent Consequently, it offers a synergistic
reputation-policy based trust model for Grid resource selection This
exoteric trust model introduces a novel paradigm for evaluating Grid resources,
in which Grid client applications (eg monitoring toolkits and
resource brokers) are endeavoured to carry out an active participation in
the trust and reputation evaluation processes This is achieved by augmenting
the standard reputation queries with a set of reputation-policy
assertions constituting as complete trust metrics supplied into the reputation
algorithm Consecutively, the Grid Reputation-Policy Trust management
system (GREPTrust) provides a concrete implementation for
the trust model and it’s underlying artifacts whilst the GREPTrust testbed
provides an adequate infrastructure for comparing the reputationpolicy
trust model with a production available esoteric model (GridPP)
Based on a computational finance case study, an internal workflow
simulation utilises the GREPTrust testbed in order to empirically assess
the criteria by which the synergistic reputation-policy based trust model
outperforms esoteric trust models regarding resource selection and
consequently provides substantive evidence that the reputation-policy
paradigm is a welcome addition to the Grid computing community
Citations
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01 Jan 2003
TL;DR: In this article, the authors propose a web of trust, in which each user maintains trust in a small number of other users and then composes these trust values into trust values for all other users.
Abstract: Though research on the Semantic Web has progressed at a steady pace, its promise has yet to be realized. One major difficulty is that, by its very nature, the Semantic Web is a large, uncensored system to which anyone may contribute. This raises the question of how much credence to give each source. We cannot expect each user to know the trustworthiness of each source, nor would we want to assign top-down or global credibility values due to the subjective nature of trust. We tackle this problem by employing a web of trust, in which each user maintains trusts in a small number of other users. We then compose these trusts into trust values for all other users. The result of our computation is not an agglomerate "trustworthiness" of each user. Instead, each user receives a personalized set of trusts, which may vary widely from person to person. We define properties for combination functions which merge such trusts, and define a class of functions for which merging may be done locally while maintaining these properties. We give examples of specific functions and apply them to data from Epinions and our BibServ bibliography server. Experiments confirm that the methods are robust to noise, and do not put unreasonable expectations on users. We hope that these methods will help move the Semantic Web closer to fulfilling its promise.
567 citations
252 citations
Book Chapter•
01 Jan 2009TL;DR: This paper presents the Grid reputation-policy trust management service (GREPTrust) for managing resource selection in computational grids, which encompasses a novel reputation- policy trust model, which enables service consumers to carry out an active participation in the trust and reputation evaluation processes.
Abstract: The concept of trust and reputation had a long profound impact on the way systems were measured in terms of their credibility and performance. This has consecutively lead into numerous reputation-based trust management systems being deployed for various computing environments as a decision support tool for assessing the trustworthiness of participating parties. In the context of Grid computing, reputation-based trust management systems play an important role for supporting coordinated resource sharing as they can reduce job execution failure by selecting relatively competent resources based on aggregated historical recommendations and given job requirements. In this paper, we present the Grid reputation-policy trust management service (GREPTrust) for managing resource selection in computational grids. This infrastructure level service encompasses a novel reputation-policy trust model, which enables service consumers (e.g. monitoring toolkits and resource brokers), to carry out an active participation in the trust and reputation evaluation processes. This is achieved by enabling service consumers to augment standard reputation queries with a set of reputation-policy statements rectified as trust decision strategies. Each strategy forms complete trust metrics blueprint for the reputation algorithm and therefore allows fine-grained resource selection adapted to specific job requirements.
1 citations
21 May 2007
TL;DR: In this paper, a case study illustrates benefits central to a GRiD virtualization implementation, including how to provide mission critical reliability at commodity prices, how business flexibility can be supported without costly support services, how an enterprise can share computing resources among lines of business while guaranteeing service level agreements, and new application architectures and legacy systems can simultaneously be supported on the shared infrastructure.
Abstract: Financial Services companies are increasingly faced with lower margins, competitive pressures, and new regulatory requirements. More so than ever, IT decisions are scrutinized for the business value they add, the potential ROI to the enterprise, and the Total Cost of Ownership (TCO). To be competitive in a global world, FS are creating ever more complex products for managing currency, interest rates, credit, and other exposures. This presents a real challenge. Structured products with complex payoff structures, interest rate derivatives requiring stochastic Monte Carlo, and VaR recalculations challenge the current computing model and put tension on already stretched budgets. Traditional siloed computing infrastructures result in a “cause-effectum” problem. Scalability and peak performance can be addressed only with over provisioning. This results in a dual problem: idling of expensive IT infrastructure when not in use and suboptimal utilization of IT capital. Through this case study, the paper illustrates benefits central to a GRiD virtualization implementation. Solutions to the following business and technical dilemmas are provide: How to provide mission critical reliability at commodity prices How business flexibility can be supported without costly support services How an enterprise can share computing resources among lines of business while guaranteeing service level agreements How new application architectures and legacy systems can simultaneously be supported on the shared infrastructure. How lines of business can avoid provisioning systems for peak usage and use compute resource on demand How disaster recovery and business continuity can be a working asset rather than an idle expense
1 citations
References
More filters
01 Jan 1985
TL;DR: A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented and two applications of the method to industrial processes are discussed: a water cleaning process and a converter in a steel-making process.
Abstract: A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented. The premise of an implication is the description of fuzzy subspace of inputs and its consequence is a linear input-output relation. The method of identification of a system using its input-output data is then shown. Two applications of the method to industrial processes are also discussed: a water cleaning process and a converter in a steel-making process.
18,803 citations
"A synergistic reputation-policy bas..." refers methods in this paper
...There are two broad categories of fuzzy reasoning systems: The Mamdani method [73] and the Takagi & Sugeno method [74]....
[...]
01 Aug 1999-International Journal of Human-computer Studies \/ International Journal of Man-machine Studies
TL;DR: Fuzzy logic is used to convert heuristic control rules stated by a human operator into an automatic control strategy, and the control strategy set up linguistically proved to be far better than expected in its own right.
Abstract: This paper describes an experiment on the “linguistic” synthesis of a controller for a model industrial plant (a steam engine). Fuzzy logic is used to convert heuristic control rules stated by a human operator into an automatic control strategy. The experiment was initiated to investigate the possibility of human interaction with a learning controller. However, the control strategy set up linguistically proved to be far better than expected in its own right, and the basic experiment of linguistic control synthesis in a non-learning controller is reported here.
6,392 citations
"A synergistic reputation-policy bas..." refers methods in this paper
...There are two broad categories of fuzzy reasoning systems: The Mamdani method [73] and the Takagi & Sugeno method [74]....
[...]
Book•
01 Dec 1994
TL;DR: This chapter discusses Fuzzy Systems Simulation, specifically the development of Membership Functions and the Extension Principle, and some of the methods used to derive these functions.
Abstract: About the Author. Preface to the Third Edition. 1 Introduction. The Case for Imprecision. A Historical Perspective. The Utility of Fuzzy Systems. Limitations of Fuzzy Systems. The Illusion: Ignoring Uncertainty and Accuracy. Uncertainty and Information. The Unknown. Fuzzy Sets and Membership. Chance Versus Fuzziness. Sets as Points in Hypercubes. Summary. References. Problems. 2 Classical Sets and Fuzzy Sets. Classical Sets. Operations on Classical Sets. Properties of Classical (Crisp) Sets. Mapping of Classical Sets to Functions. Fuzzy Sets. Fuzzy Set Operations. Properties of Fuzzy Sets. Alternative Fuzzy Set Operations. Summary. References. Problems. 3 Classical Relations and Fuzzy Relations. Cartesian Product. Crisp Relations. Cardinality of Crisp Relations. Operations on Crisp Relations. Properties of Crisp Relations. Composition. Fuzzy Relations. Cardinality of Fuzzy Relations. Operations on Fuzzy Relations. Properties of Fuzzy Relations. Fuzzy Cartesian Product and Composition. Tolerance and Equivalence Relations. Crisp Equivalence Relation. Crisp Tolerance Relation. Fuzzy Tolerance and Equivalence Relations. Value Assignments. Cosine Amplitude. Max Min Method. Other Similarity Methods. Other Forms of the Composition Operation. Summary. References. Problems. 4 Properties of Membership Functions, Fuzzification, and Defuzzification. Features of the Membership Function. Various Forms. Fuzzification. Defuzzification to Crisp Sets. -Cuts for Fuzzy Relations. Defuzzification to Scalars. Summary. References. Problems. 5 Logic and Fuzzy Systems. Part I Logic. Classical Logic. Proof. Fuzzy Logic. Approximate Reasoning. Other Forms of the Implication Operation. Part II Fuzzy Systems. Natural Language. Linguistic Hedges. Fuzzy (Rule-Based) Systems. Graphical Techniques of Inference. Summary. References. Problems. 6 Development of Membership Functions. Membership Value Assignments. Intuition. Inference. Rank Ordering. Neural Networks. Genetic Algorithms. Inductive Reasoning. Summary. References. Problems. 7 Automated Methods for Fuzzy Systems. Definitions. Batch Least Squares Algorithm. Recursive Least Squares Algorithm. Gradient Method. Clustering Method. Learning From Examples. Modified Learning From Examples. Summary. References. Problems. 8 Fuzzy Systems Simulation. Fuzzy Relational Equations. Nonlinear Simulation Using Fuzzy Systems. Fuzzy Associative Memories (FAMS). Summary. References. Problems. 9 Decision Making with Fuzzy Information. Fuzzy Synthetic Evaluation. Fuzzy Ordering. Nontransitive Ranking. Preference and Consensus. Multiobjective Decision Making. Fuzzy Bayesian Decision Method. Decision Making Under Fuzzy States and Fuzzy Actions. Summary. References. Problems. 10 Fuzzy Classification. Classification by Equivalence Relations. Crisp Relations. Fuzzy Relations. Cluster Analysis. Cluster Validity. c-Means Clustering. Hard c-Means (HCM). Fuzzy c-Means (FCM). Fuzzy c-Means Algorithm. Classification Metric. Hardening the Fuzzy c-Partition. Similarity Relations from Clustering. Summary. References. Problems. 11 Fuzzy Pattern Recognition. Feature Analysis. Partitions of the Feature Space. Single-Sample Identification. Multifeature Pattern Recognition. Image Processing. Summary. References. Problems. 12 Fuzzy Arithmetic and the Extension Principle. Extension Principle. Crisp Functions, Mapping, and Relations. Functions of Fuzzy Sets Extension Principle. Fuzzy Transform (Mapping). Practical Considerations. Fuzzy Arithmetic. Interval Analysis in Arithmetic. Approximate Methods of Extension. Vertex Method. DSW Algorithm. Restricted DSW Algorithm. Comparisons. Summary. References. Problems. 13 Fuzzy Control Systems. Control System Design Problem. Control (Decision) Surface. Assumptions in a Fuzzy Control System Design. Simple Fuzzy Logic Controllers. Examples of Fuzzy Control System Design. Aircraft Landing Control Problem. Fuzzy Engineering Process Control. Classical Feedback Control. Fuzzy Control. Fuzzy Statistical Process Control. Measurement Data Traditional SPC. Attribute Data Traditional SPC. Industrial Applications. Summary. References. Problems. 14 Miscellaneous Topics. Fuzzy Optimization. One-Dimensional Optimization. Fuzzy Cognitive Mapping. Concept Variables and Causal Relations. Fuzzy Cognitive Maps. Agent-Based Models. Summary. References. Problems. 15 Monotone Measures: Belief, Plausibility, Probability, and Possibility. Monotone Measures. Belief and Plausibility. Evidence Theory. Probability Measures. Possibility and Necessity Measures. Possibility Distributions as Fuzzy Sets. Possibility Distributions Derived from Empirical Intervals. Deriving Possibility Distributions from Overlapping Intervals. Redistributing Weight from Nonconsonant to Consonant Intervals. Comparison of Possibility Theory and Probability Theory. Summary. References. Problems. Index.
4,958 citations
"A synergistic reputation-policy bas..." refers background in this paper
...The basic idea is that for each behavioural parameter, a set of (possibly overlapping) fuzzy sets is defined in terms of membership functions, which specify the degree of membership of the various sets for the possible values of the parameter [62, 64]....
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20 May 2003
TL;DR: An algorithm to decrease the number of downloads of inauthentic files in a peer-to-peer file-sharing network that assigns each peer a unique global trust value, based on the peer's history of uploads is described.
Abstract: Peer-to-peer file-sharing networks are currently receiving much attention as a means of sharing and distributing information. However, as recent experience shows, the anonymous, open nature of these networks offers an almost ideal environment for the spread of self-replicating inauthentic files.We describe an algorithm to decrease the number of downloads of inauthentic files in a peer-to-peer file-sharing network that assigns each peer a unique global trust value, based on the peer's history of uploads. We present a distributed and secure method to compute global trust values, based on Power iteration. By having peers use these global trust values to choose the peers from whom they download, the network effectively identifies malicious peers and isolates them from the network.In simulations, this reputation system, called EigenTrust, has been shown to significantly decrease the number of inauthentic files on the network, even under a variety of conditions where malicious peers cooperate in an attempt to deliberately subvert the system.
3,715 citations
"A synergistic reputation-policy bas..." refers background or methods in this paper
...[28] by exploiting the beneficial properties of EigenTrust algorithm [29]....
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...This has consequently led into numerous reputation-based trust management systems being deployed for various computing environments (such as P2P and electronic markets [48]) as a decision support tool for assessing the trustworthiness of participating parties [70, 27, 29]....
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01 Mar 2007
TL;DR: Trust and reputation systems represent a significant trend in decision support for Internet mediated service provision as mentioned in this paper, where the basic idea is to let parties rate each other, for example after the completion of a transaction, and use the aggregated ratings about a given party to derive a trust or reputation score.
Abstract: Trust and reputation systems represent a significant trend in decision support for Internet mediated service provision. The basic idea is to let parties rate each other, for example after the completion of a transaction, and use the aggregated ratings about a given party to derive a trust or reputation score, which can assist other parties in deciding whether or not to transact with that party in the future. A natural side effect is that it also provides an incentive for good behaviour, and therefore tends to have a positive effect on market quality. Reputation systems can be called collaborative sanctioning systems to reflect their collaborative nature, and are related to collaborative filtering systems. Reputation systems are already being used in successful commercial online applications. There is also a rapidly growing literature around trust and reputation systems, but unfortunately this activity is not very coherent. The purpose of this article is to give an overview of existing and proposed systems that can be used to derive measures of trust and reputation for Internet transactions, to analyse the current trends and developments in this area, and to propose a research agenda for trust and reputation systems.
3,493 citations