Christopher Gibson

Towards Relevancy Aware Service Oriented Systems in WSNs

The increasing interest of researchers in service oriented architecture (SOA) for wireless sensor networks (WSNs) is opening new unexplored venues in the field of WSNs. In service oriented systems, services are configured and composed of various other services and thus perform complex tasks. In such composite services, the geospatial locations of services and their coverage is of vital importance as they signify the geospatial relevance of the service to the area of interest to the user. In this paper, we present a service-oriented system for WSNs that is capable of performing service configuration under geospatial and relevancy constraints. We present and evaluate “Cost Based Model (CBM)” and “Gain Based Model (GBM)” approaches to capture the relevancy of services hosted on WSN nodes in composite service configuration. The system is resilient to failures and can operate in manual or autonomous recovery modes. The system supports three service configuration methods namely, distributed, centralized and hybrid. Furthermore, we present a novel emulation mechanism for testing the performance of our proposed relevancy models and show that our system efficiently configures services.

Sensors as a Service Oriented Architecture: Middleware for Sensor Networks

There is a significant challenge in designing, optimizing, deploying and managing complex sensor networks over heterogeneous communications infrastructures. The ITA Sensor Fabric addresses these challenges in the areas of sensor identification and discovery, sensor access and control, and sensor data consumability, by extending the message bus model commonly found in commercial IT infrastructures out to the edge of the network. In this paper we take the message bus model further into a semantically rich, model-based design and analysis approach that considers the sensor network and its contained services as a Service Oriented Architecture. We present an application of a hierarchic schema for nested service definitions together with an initial ontology that describes the assets and services deployed in a sensor network infrastructure.

ITA Sensor Fabric

The diverse sensor types and networking technologies commonly used in fielded sensro networks provide a unique set of challenges [1] in the areas of sensor identification, interoperability, and sensor data consumability. The ITA Senor Fabric is a middleware infrastructure - developed as part of the International Technology Alliance (ITA)[2] in Network and Information Science - that addresses these challenges by providing unified access to, and management of, sensor networks. The Fabric spans the network from command and control, through forward operating bases, and out to mobile forces and fielded sensors, maximizing the availability and utility of intelligence information to users.

Inference management, trust and obfuscation principles for quality of information in emerging pervasive environments ☆

Abstract The emergence of large scale, distributed, sensor-enabled, machine-to-machine pervasive applications necessitates engaging with providers of information on demand to collect the information, of varying quality levels, to be used to infer about the state of the world and decide actions in response. In these highly fluid operational environments, involving information providers and consumers of various degrees of trust and intentions, information transformation, such as obfuscation, is used to manage the inferences that could be made to protect providers from misuses of the information they share, while still providing benefits to their information consumers. In this paper, we develop the initial principles for relating to inference management and the role that trust and obfuscation plays in it within the context of this emerging breed of applications. We start by extending the definitions of trust and obfuscation into this emerging application space. We, then, highlight their role as we move from the tightly-coupled to loosely-coupled sensory-inference systems and describe how quality, value and risk of information relate in collaborative and adversarial systems. Next, we discuss quality distortion illustrated through a human activity recognition sensory system. We then present a system architecture to support an inference firewall capability in a publish/subscribe system for sensory information and conclude with a discussion and closing remarks.

Autonomous configuration of spatially aware sensor services in service oriented WSNs

Service-oriented Architectures (SOA) for Wireless Sensor Networks (WSNs) are an active research topic. Yet, autonomous configuration of services for real life constraints (spatio-temporal, input/output interoperability, policies, security etc.) is still a challenging problem. In this demonstration we describe the results of our research into the automated and intelligent configuration and composition of services for complex tasks. We present a service-oriented system capable of performing service configuration under spatial and relevancy constraints. It can configure services in one of the three following modes: distributed, centralized and hybrid. It also supports automatic reconfiguration in the event of service failures. This system uses a generic cost representation for services that may include spatial coverage of the services in an area of interest along with other service configuration cost metrics. We demonstrate our system using state-of-the-art emulation frameworks with a real life scenario.

Model-driven SOA for sensor networks

Our previous work has explored the application of enterprise middleware techniques at the edge of the network to address the challenges of delivering complex sensor network solutions over heterogeneous communications infrastructures. In this paper, we develop this approach further into a practicable, semantically rich, model-based design and analysis approach that considers the sensor network and its contained services as a service-oriented architecture. The proposed model enables a systematic approach to service composition, analysis (using domain-specific techniques), and deployment. It also enables cross intelligence domain integration to simplify intelligence gathering, allowing users to express queries in structured natural language (Controlled English).