F.M. Brazier

Managing Violations in Service Level Agreements

A Service Level Agreement (SLA) represents an agreement between a service user and a provider in the context of a particular service provision. SLAs contain Quality of Service properties that must be maintained by a provider. These are generally defined as a set of Service Level Objectives (SLOs). These properties need to be measurable and must be monitored during the provision of the service that has been agreed in the SLA. The SLA must also contain a set of penalty clauses specifying what happens when service providers fail to deliver the preagreed quality. Although significant work exists on how SLOs may be specified and monitored, not much work has focused on actually identifying how SLOs may be impacted by the choice of specific penalty clauses. The participation of a trusted mediator may be necessary to resolve conflicts between involved parties. The main focus of the paper is on identifying particular penalty clauses that can be associated with an SLA.

Security in Large-Scale Open Distributed Multi-Agent Systems

Designing large-scale distributed multi-agent systems that operate in open environments, such as the Internet, creates new challenges, especially with respect to security issues. Agents are autonomous, pro-active, communicative, goal-directed, often capable of learning, and sometimes mobile [8]. Mobile agents traverse the network to access services and resources they need to achieve the goals they pursue. The potential of mobile agent technology in sectors such as E-Commerce [17, 18], E-Health [29] and E-Governance [10, 52] is well recognized. In these sectors, security issues such as authentication, authorization, privacy, and copyright are of utmost importance. Data access control is mandatory: by moving agents to the location at which data is stored, data access and processing can be done locally and controlled. Many security requirements need to be addressed for large-scale distributed multiagent systems in open environments. The focus of this chapter lies on security requirements specific for agent systems rather than security requirements for distributed computers systems in general. Section 2 identifies the most relevant security requirements for agent systems. This set of requirements is a minimum that needs to be fulfilled for secure agent systems in open environments. Sections 3 through 7 discuss the security requirements and possible solutions in detail. The solutions are illustrated within the context of the AgentScape [20] agent platform. This platform has been chosen as it has been specially designed to be used in a large-scale, distributed, open environment. However, similar implementations of these solutions are possible in other agent platforms. The chapter closes with an overview of a number of well-known agent platforms, such as AgentScape [20], Ajanta [23], SeMoA [41], and JADE [5] with its security extensions JADE-S [34] and S-Agent [16]. The discussion focuses on what techniques these agent systems have used to solve some of the discussed security requirements.

A Purpose Driven Method for Language Comparison

Current efforts to compare knowledge engineering (KE) modelling languages have been limited to either rather shallow comparisons on a broad-set of languages, or to detailed comparisons with limited applicability to a narrow set of languages. In this paper we propose a novel way of organising language comparisons. This method is based on an alternating decomposition of the goals that a language tries to achieve and the linguistic methods it employs to achieve these goals. This new method for comparing languages allows a general comparison at high levels of abstraction, while not preventing more precise comparisons whenever possible. One result of our comparison method is an insight in the different assumptions that underly the languages to be compared. Two further consequences follow from the proposed comparison method, namely (i) a measure for the degree of similarity between languages, and (ii) a method for translating between languages. After describing our method, we apply it to a pair of KE modelling languages, and show how it yields insights in the assumptions underlying the languages and how it can be used to produce a translation procedure between the languages.