Thomas A. Gray

Use case maps for the capture and validation of distributed systems requirements

Functional scenarios describing system views, uses, or services are a common way of capturing requirements of distributed systems. However, integrating individual scenarios in different ways may result in different kinds of unexpected or undesirable interactions. We present an innovative approach based on the combined use of two notations. The first one is a recent visual notation for causal scenarios called use case maps (UCMs), which is used to capture and integrate the requirements. Integrating UCMs together helps avoiding many interactions before any prototype is generated. The second notation is the formal specification language LOTOS. UCM scenarios are translated into high-level LOTOS specifications, which can be used to validate the requirements formally through numerous techniques, including functional testing based on UCMs. LOTOS possesses powerful testing concepts and tools that we use for the detection of remaining undesirable interactions. To illustrate these concepts, we use a simple connection example and results from the capture and the validation of several telephony features from the First Feature Interaction Contest.

Coordinating with obligations

Organizations constrain the behavior of agents by imposing multiple, often contradictory, obligations and interdictions amongst them. To work in harmony, agents must find ways to satisfy these constraints, or to break less important ones when necessary. In this paper, we present a solution to this problem based on a representation of obligations and interdictions in an organizational framework, together with nn inference method that also decides which obligations to break in contradictory situations. These are integrated in an operational, practically useful agent development language that covers the spectrum from defining organizations, roles, agents, obligations, goals, conversations to inferring and exccuting coordinated agent behaviors in multi-agent applications, One strength of the approach is the way it supports negotiation by exchanging deontic constraints amongst agents, We illustrate this and the entire system with a negotiated solution to the feature interaction problem in the telecommunications industry and a work process coordination example for a manufacturing supply chain.

Policy support for call control

The need for policies to control calls is justified by the changing face of communications. It is argued that call control requires distinctive capabilities in a policy system. A specialised policy language called APPEL (ACCENT Project Policy Environment/Language) has therefore been developed for this purpose. However, the policy language is cleanly separated into a core plus specialisations for various application domains. The paper describes both the foundation and the call control ontologies. Sample policy examples are provided to illustrate use for call control. The paper also presents the policy system architecture in which the policy language is interpreted. The components of the policy system are described, particularly the policy server and the policy wizard.

Policy-enabled mechanisms for feature interactions: reality, expectations, challenges

This paper is based on the discussion during a panel that took place at the 7th Workshop on Feature Interactions in Telecommunications and Software Systems in Ottawa, Canada, June 2003. It presents a holistic picture on two paradigms, namely feature and policy, and their intertwining. The guest panelists brought examples from complementary areas and presented their experiences on using the concept of policy for defining features and for treating the feature interaction problem. The intrinsic interactions commonly called policy conflicts within policy-based systems were also discussed. The panelists considered methodological issues, such as the use of deontic logic and the representation of features through policies, as well as industrial applications, such as service provisioning and policy-based management applications for service bundling. They also brought out different views that reflect some disparity between the communities involved in this research.

Applying use case maps to multi-agent systems: a feature interaction example

Multi-agent systems are emerging as a potential solution to the problem of constructing flexible network-based software. A characteristic of such systems is that whole-system behaviour patterns emerge from the combination of many details in many agents, in sometimes intricate ways. Understanding the big picture by composing the details is often difficult and designing the details to achieve some desired whole-system behaviour pattern can easily become a cut-and-try exercise. To help solve these problems, the authors offer use case maps (UCMs) to provide a first-class representation of whole-system behaviour patterns, at a level above details. To illustrate the approach, they apply it to a classical distributed system problem of a kind that agent systems must be capable of solving, namely feature interaction in telephony.

Interactive conflict detection and resolution for personalized features

In future telecommunications systems, behaviour will be defined by inexperienced users for many different purposes, often by specifying requirements in the form of policies. The call processing language (CPL) was developed by the IETF in order to make it possible to define telephony policies in an Internet telephony environment. However, user-defined policies can hide inconsistencies or feature interactions. In this paper, a method and a tool are proposed to flag inconsistencies in a set of policies and to assist the user in correcting them. These policies can be defined by the user in a user-friendly language or derived automatically from a CPL script. The approach builds on a pre-existing logic programming tool that is able to identify inconsistencies in feature definitions. Our new tool is capable of explaining in user-oriented terminology the inconsistencies flagged, to suggest possible solutions, and to implement the chosen solution. It is sensitive to the types of features and interactions that will be created by naive users. This tool is also capable of assembling a set of individual policies specified in a user-friendly manner into a single CPL script in an appropriate priority order for execution by telecommunication systems.

An Agent Model for the Resolution of Feature Conflicts in Telephony

Most telecommunication service providers resolve the feature interaction problem by providing specific instructions in their management software to handle scenarios where feature interaction may occur. This approach suffers from the complexity of the resulting code and the difficulty of adding new features to the system. Moreover, the system predefines the result of the resolution of the conflicting features and the end user has no means of choosing a different behavior, depending on the preferences of the user. In this paper we propose an agent-based architecture to detect and resolve feature interactions. Our system benefits from the flexibility and the semantic richness of policies and fuzzy logic to allow the end user to alter the behavior of the system, thus obtaining a more personalized service.

Approaching Secure Communications in a Message-Oriented Mobile Computing Environment

The Personal Mobility Management System (PMMS), an agent-based message-oriented mobile computing application developed at Multimedia and Mobile Agent Research Laboratory, aims to provide personalized services and resources access to its nomadic users within a virtual network across different organizations. This paper analyses and discusses the security weaknesses exposed in the system architecture, then proposes several security frameworks to overcoming these security concerns. The paper tries to address and provide a general architectural solution to ensure secure communications for a typical message-oriented mobile computing system.

Coordination based on obligation

The authors explore the view that coordinated behavior is driven by the social constraints (e.g. obligations and interdictions) that agents in organizations are subject to. In this framework, agents adopt those goals that are requested by their obligations, knowing that not fulfilling obligations induces a price to pay or a loss of utility. Based on this idea they build an integrated agent coordination system where they represent the organization, the roles played by agents, the obligations imposed among roles, the goals and the plans that agents may adopt. To consistently update an agents obligations and interdictions they present an incremental propagation method that also helps with detecting and deciding between conflicting obligations. One strength of this method is that it supports a generic coordination method based on ex-changing and locally propagating obligations and interdictions. Once a goal adopted, a special brand of plans, conversation plans, are available to the agents for effectively carrying out coordinated action. They illustrate the framework with examples from service provisioning in telecommunication networks and supply chain integration.

Policies for Feature Interaction Resolution

Telephone systems are marked by the provision of many hundreds of features. Conflict between these features is inherent as the actions of one feature can be in direct opposition to the aims of another feature. Most telecommunication service providers resolve the feature interaction problem by providing specific instructions in their management software. This approach suffers from the complexity of the resulting code and the difficulty of adding new features to the system. In this paper, we propose an agent-based architecture in which the actions of each agent are controlled by a set of policies. We also introduced the concept of fuzzy-policies, which are policies whose suitability for handling an event is calculated dynamically, based on the value of some fuzzy-variables. Conflicts are resolved using an arbitrator agent, which recalculates the suitability of the proposed actions of each agent and deduces the best action that satisfies the end user. The end user has the ability to add new policies, or modify the values of the fuzzy-parameters of the user-agent to alter the behavior of the system, thus obtaining a more personalized service.