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Policies in Accountable Contracts: An Overview of Self-Enforcing Rational Contracts

This presentation, delivered by Brian Shand on April 16, 2002, explores the intricate landscape of accountable contracts, emphasizing contract negotiation, performance, and practical applications. The research focuses on self-enforcing automatic rational contracts between computers, outlining a contract framework that incorporates resource accounting and a trust model. Key topics include multi-level contracts for introspection, risk estimation with minimal resource expenditure, and the integration of reputation into contracts. Additionally, it addresses the implications of trust and distrust within distributed systems, providing insights into flexible prioritization and event management in public compute servers.

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Policies in Accountable Contracts: An Overview of Self-Enforcing Rational Contracts

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  1. Opera Group Presentation:Policies in Accountable Contracts Brian Shand 16 April 2002

  2. Contract Negotiation • Signing • Performance Overview • PhD Research: Self-Enforcing Automatic Rational Contracts between Computers • Contract Framework, Resource Accounting, Trust Model • Application Scenarios • Public compute servers (GRID computation) • Flexible prioritisation in large distributed systems • Web services

  3. Key Terms { { { { {

  4. Contract Framework • Contracts specify promises between participants • Multi-level contracts allow introspection 1. Participant identities 2. Estimated resource consumption 3. Accounting function (payment policy) 4. Actions to perform • Allows risk estimates, with limited resource outlay • All accounting messages signed and timestamped • Message passing substrate assumed

  5. Resource Accounting • Homogeneous model • of scarce resources: bandwidth, CPU cycles, trust, currency • Constrained language for accounting functions • A subset of the Python language • Predictable execution times • Example code: def processResourceAtom(self, atom, imports): if atom.type != resources.cpuTime: return [] # Charge for CPU only rate = imports[0] if self.totalCPU < 10: result = rate+0.01 else: result = rate+0.002 self.totalCPU += atom.quantity return [ResourceAtom(resources.money, '£', result*atom.quantity) ]

  6. Uncertainty (0,0,1) Trust Distrust (1,0,0) (0,1,0) Trust Model • Subjective Trust Model (Jøsang, A Logic for Uncertain Probabilities, 2001) • Local assessments of trustworthiness • Second-order model incorporates uncertainty • Moderates contractual promises • Constantly updated • Transfer of Trust: Trust delegation certificates • Web of trust, c.f. PGP recommendations • Subsume reputation agencies • Distributed trust management

  7. Accountable Contracts • Separation of task acceptance and performance • introspectible contracts • explicit risk assessments • Multi-scale representation • Accounting of all resources • economic services • Distributed trust model deters cheats • Overhead in a PBIL application: • about 20% of bandwidth, 2% of CPU

  8. Further Work • Explicit integration of reputation into contracts • Prototype applications • Compute Servers • Complex negotiation, pricing by servers • Clients that plan • Active City • Event prioritisation in publish-subscribe • Theoretical basis for trust model • SECURE collaboration • Model risks of stolen signatures • Distrust in own actions

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