Danny Hughes

Goal-Based Modeling of Dynamically Adaptive System Requirements

Self-adaptation is emerging as an increasingly important capability for many applications, particularly those deployed in dynamically changing environments, such as ecosystem monitoring and disaster management. One key challenge posed by dynamically adaptive systems (DASs) is the need to handle changes to the requirements and corresponding behavior of a DAS in response to varying environmental conditions. Berry et al. previously identified four levels of RE that should be performed for a DAS. In this paper, we propose the levels of RE for modeling that reify the original levels to describe RE modeling work done by DAS developers. Specifically, we identify four types of developers: the system developer, the adaptation scenario developer, the adaptation infrastructure developer, and the DAS research community. Each level corresponds to the work of a different type of developer to construct goal model(s) specifying their requirements. We then leverage the levels of RE for modeling to propose two complementary processes for performing RE for a DAS. We describe our experiences with applying this approach to GridStix, an adaptive flood warning system, deployed to monitor the River Ribble in Yorkshire, England.

LooCI: a loosely-coupled component infrastructure for networked embedded systems

Considerable research has been performed in applying run-time reconfigurable component models to the domain of wireless sensor networks. The ability to dynamically deploy and reconfigure software components has clear advantages in sensor network deployments, which are typically large in scale and expected to operate for long periods in the face of node mobility, dynamic environmental conditions and changing application requirements. To date, research on component and binding models for sensor networks has primarily focused on the development of specialized component models that are optimized for use in resource-constrained environments. However, current approaches impose significant overhead upon developers and tend to use inflexible binding models based on remote procedure calls. To address these concerns, we introduce a novel component and binding model for networked embedded systems (LooCI). LooCI components are designed to impose minimal additional overhead on developers. Furthermore, LooCI components use a novel event-based binding model that allows developers to model rich component interactions, while providing support for easy interception, re-wiring and re-use. A prototype implementation of our component and binding model has been realised for the SunSPOT platform. Our preliminary evaluation shows that LooCI has an acceptable memory footprint and imposes minimal overhead on developers.

Genie: supporting the model driven development of reflective, component-based adaptive systems

Engineering adaptive software is an increasingly complex task. Here, we demonstrate Genie, a tool that supports the modelling, generation, and operation of highly reconfigurable, component-based systems. We showcase how Genie is used in two case-studies: i) the development and operation of an adaptive flood warning system, and ii) a service discovery application. In this context, adaptation is enabled by the Gridkit reflective middleware platform.

Extending sensor networks into the Cloud using Amazon Web Services

Sensor networks provide a method of collecting environmental data for use in a variety of distributed applications. However, to date, limited support has been provided for the development of integrated environmental monitoring and modeling applications. Specifically, environmental dynamism makes it difficult to provide computational resources that are sufficient to deal with changing environmental conditions. This paper argues that the Cloud Computing model is a good fit with the dynamic computational requirements of environmental monitoring and modeling. We demonstrate that Amazon EC2 can meet the dynamic computational needs of environmental applications. We also demonstrate that EC2 can be integrated with existing sensor network technologies to offer an end-to-end environmental monitoring and modeling solution.

Dynamic reconfiguration in sensor middleware

Middleware solutions for sensor networks have so far mainly focused on communication abstractions, ad-hoc message routing protocols, and power conservation techniques. We argue that customisation and dynamic reconfiguration of sensor network middleware are additional important dimensions to consider. This paper describes a sensor middleware that can be customised to suit different sensor application types, and provides a reflective approach for co-ordinated network-wide dynamic reconfiguration of sensor behaviour. To evaluate our approach we illustrate customisation and dynamic reconfiguration of the Gridkit sensor middleware in a flood-monitoring scenario.

LooCI: The Loosely-coupled Component Infrastructure

Creating and managing applications for Wireless Sensor Networks (WSNs) is complicated by large scale, resource constraints and network dynamics. Reconfigurable component models minimize these complexities throughout the application lifecycle. However, contemporary component based middleware for WSNs is limited by its poor support for distribution. This paper introduces the Loosely-coupled Component Infrastructure (LooCI), a middleware for building distributed component-based WSN applications. LooCI advances the state-of-the-art by cleanly separating distributed concerns from component implementation, supporting application-level interoperability between heterogeneous WSN platforms and providing compatibility testing of bindings at runtime. Together, these features promote the safe and efficient composition and reconfiguration of distributed WSN applications. We evaluate the performance of LooCI on three classes of sensor nodes and demonstrate that these features can be provided with minimal overhead in terms of computation, memory and message passing.

Supporting Law Enforcement in Digital Communities through Natural Language Analysis

Recent years have seen an explosion in the number and scale of digital communities (e.g. peer-to-peer file sharing systems, chat applications and social networking sites). Unfortunately, digital communities are host to significant criminal activity including copyright infringement, identity theft and child sexual abuse. Combating this growing level of crime is problematic due to the ever increasing scale of todays digital communities. This paper presents an approach to provide automated support for the detection of child sexual abuse related activities in digital communities. Specifically, we analyze the characteristics of child sexual abuse media distribution in P2P file sharing networks and carry out an exploratory study to show that corpus-based natural language analysis may be used to automate the detection of this activity. We then give an overview of how this approach can be extended to police chat and social networking communities.

Composition challenges and approaches for cyber physical systems

A wide variety of programming abstractions have been developed for cyber-physical systems. These approaches provide support for the composition of cyber-physical systems from generic units of application functionality. This paper surveys the current state-of-the-art in composition mechanisms for cyber physical systems and reviews each approach in terms of its support for composition analysis, re-use and adaptation. We then review approaches for modeling and verifying cyber-physical application compositions and conclude by proposing promising research directions that will address these shortcomings.

Visualizing the Analysis of Dynamically Adaptive Systems Using i* and DSLs

Self-adaptation is emerging as a crucial enabling capability for many applications, particularly those deployed in dynamically changing environments. One key challenge posed by dynamically adaptive systems (DASs) is the need to handle changes to the requirements and corresponding behavior of a DAS in response to varying environmental conditions. In this paper we propose a visual model-driven approach that uses the i* modeling language to represent goal models for the DAS requirements. Our approach applies a rigorous separation of concerns between the requirements for the DAS to operate in stable conditions and those that enable it to adapt at run-time to enable it to cope with changes in its environment. We further show how requirements derived from the i* modeling can be used by a domain-specific language to achieve requirements model-driven development. We describe our experiences with applying this approach to GridStix, an adaptive flood warning system, deployed on the River Ribble in North Yorkshire, England.

A framework for P2P application development

Although Peer-to-Peer (P2P) computing has become increasingly popular over recent years, there still exist only a very small number of application domains that have exploited it on a large scale. This can be attributed to a number of reasons including the rapid evolution of P2P technologies, coupled with their often-complex nature. This paper describes an implemented abstraction framework that seeks to aid developers in building P2P applications. A selection of example P2P applications that have been developed using this framework are also presented.