Ontology-based collaborative framework for disaster recovery scenarios

This paper aims at designing of adaptive framework for supporting collaborative work of different actors in public safety and disaster recovery missions. In such scenarios, firemen and robots interact to each other to reach a common goal; firemen team is equipped with smart devices and robots team is supplied with communication technologies, and should carry on specific tasks. Here, reliable connection is mandatory to ensure the interaction between actors. But wireless access network and communication resources are vulnerable in the event of a sudden unexpected change in the environment. Also, the continuous change in the mission requirements such as inclusion/exclusion of new actor, changing the actor's priority and the limitations of smart devices need to be monitored. To perform dynamically in such case, the presented framework is based on a generic multi-level modeling approach that ensures adaptation handled by semantic modeling. Automated self-configuration is driven by rule-based reconfiguration policies through ontology

A goal-based approach to policy refinement

As the interest in using policy-based approaches for systems management grows, it is becoming increasingly important to develop methods for performing analysis and refinement of policy specifications. Although this is an area that researchers have devoted some attention to, none of the proposed solutions address the issue of deriving implementable policies from high-level goals. A key part of the solution to this problem is having the ability to identify the operations, available on the underlying system, which can achieve a given goal. This paper presents an approach by which a formal representation of a system, based on the Event Calculus, can be used in conjunction with abductive reasoning techniques to derive the sequence of operations that will allow a given system to achieve a desired goal. Additionally it outlines how this technique might be used for providing tool support and partial automation for policy refinement. Building on previous work on using formal techniques for policy analysis, the approach presented here applies a transformation of both policy and system behaviour specifications into a formal notation that is based on Event Calculus. Finally, it shows how the overall process could be used in conjunction with UML modelling and illustrates this by means of an example. 1

Policy conflict analysis for diffserv quality of service management

Policy-based management provides the ability to (re-)configure differentiated services networks so that desired Quality of Service (QoS) goals are achieved. This requires implementing network provisioning decisions, performing admission control, and adapting bandwidth allocation to emerging traffic demands. A policy-based approach facilitates flexibility and adaptability as policies can be dynamically changed without modifying the underlying implementation. However, inconsistencies may arise in the policy specification. In this paper we provide a comprehensive set of QoS policies for managing Differentiated Services (DiffServ) networks, and classify the possible conflicts that can arise between them. We demonstrate the use of Event Calculus and formal reasoning for the analysis of both static and dynamic conflicts in a semi-automated fashion. In addition, we present a conflict analysis tool that provides network administrators with a user-friendly environment for determining and resolving potential inconsistencies. The tool has been extensively tested with large numbers of policies over a range of conflict types

Reasoning techniques for analysis and refinement of policies for service management

The work described in this technical report falls under the general problem of developing methods that would allow us to engineer software systems that are reliable and would offer a certain acceptable level of quality in their operation. This report shows how the analysis and refinement of policies for Quality of Service can be carried out within logic by exploiting forms of abductive and argumentative reasoning. In particular, it provides two main contributions. The first is an extension of earlier work on the use of abductive reasoning for automatic policy refinement by exploiting the use of integrity constraints within abduction and its integration with constraint solving. This has allowed us to enhance this refinement process in various ways, e.g. supporting parameter values derivation to quantify abstract refinement to specific policies ready to be put in operation, and calculating utility values to determine optimal refined policies. The second contribution is a new approach for modelling and formulating Quality of Service policies, and more general policies for software requirements, as preference policies within logical frameworks of argumentation. This is shown to be a flexible and declarative approach to the analysis of such policies through high-level semantic queries of argumentation, demonstrated here for the particular case of network firewall policies where the logical framework of argumentation allows us to detect anomalies in the firewalls and facilitates the process of their resolution. To our knowledge this is the first time that the link between argumentation and the specification and analysis of requirement policies has been studied

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

Policy analysis for DiffServ quality of service management

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Model-based provisioning and management of adaptive distributed communication in mobile cooperative systems

Adaptation of communication is required to maintain the reliable connection and to ensure the minimum quality in collaborative activities. Within the framework of wireless environment, how can host entities be handled in the event of a sudden unexpected change in communication and reliable sources? This challenging issue is addressed in the context of Emergency rescue system carried out by mobile devices and robots during calamities or disaster. For this kind of scenario, this book proposes an adaptive middleware to support reconfigurable, reliable group communications. Here, the system structure has been viewed at two different states, a control center with high processing power and uninterrupted energy level is responsible for global task and entities like autonomous robots and firemen owning smart devices act locally in the mission. Adaptation at control center is handled by semantic modeling whereas at local entities, it is managed by a software module called communication agent (CA). Modeling follows the well-known SWRL instructions which establish the degree of importance of each communication link or component. Providing generic and scalable solutions for automated self-configuration is driven by rule-based reconfiguration policies. To perform dynamically in changing environment, a trigger mechanism should force this model to take an adaptive action in order to accomplish a certain task, for example, the group chosen in the beginning of a mission need not be the same one during the whole mission. Local entity adaptive mechanisms are handled by CA that manages internal service APIs to configure, set up, and monitors communication services and manages the internal resources to satisfy telecom service requirements