User Activity Recognition through Software Sensors

Context-aware systems are an instance of the ubiquitous or pervasive computing vision. They sense the users’ physical and virtual surrounding to identify the best system support for that user and adapt the system behaviour accordingly. The overall architecture of a context aware system can be broken into a number of logical aspects: gathering context data, storing the data, deriving knowledge through reasoning and mining and retrieving that knowledge to finally adapting system behaviours. Context is anything characterizing the environment of the user – their location, the ambient temperature, the people they are with, their current activity and some even consider the user’s mood. Traditionally context information has been gathered through the use of hardware sensors, such as GPS sensors or smart badges for locations and there has been work to track user’s eye movements at their desk to see which application they are using. However, determining the activity of a user has shown to be elusive to being sensed with hardware sensors. As users use web services more frequently they are exchanging messages with the services through the SOAP protocol. SOAP messages contain data, which is valuable if gathered and interpreted right – especially as this data can be shedding information on the activity of a user that goes beyond “sitting at the computer and typing”. We propose a complimentary sensor technology through the use of software sensors. The software sensors are essentially based on monitoring SOAP messages and inserting data for further reasoning and querying into a semantic context model. In this paper we consider details of extracting the data from SOAP messages in a non-obstructive way and show a solution to map the data from a SOAP message to our OWL ontology model automatically. On the latter, we specifically explain the methodology to map from SOAP messages to an existing structure of knowledge

Fast Data Processing for Large-Scale SOA and Event-Based Systems

The deluge of intelligent objects that are providing continuous access to data and services on one hand and the demand of developers and consumers to handle these data on the other hand require us to think about new communication paradigms and middleware. In hyper-scale systems, such as in the Internet of Things, large scale sensor networks or even mobile networks, one emerging requirement is to process, procure, and provide information with almost zero latency. This work is introducing new concepts for a middleware to enable fast communication by limiting information flow with filtering concepts using policy obligations and combining data processing techniques adopted from complex event processing

Towards an Off-the-cloud IoT data processing Architecture via a Smart Car Parking Example

Nowadays, it is obvious that technology has revolutionised our lives by supporting us to do complicated jobs. The Internet of Things (IoT) is one of the emerging technologies. One of the most significant current research topics in the IoT is smart city. The smart city includes several applications such assmart home, smart industry and smart mobility. The smart car parking system is an aspect of smart mobility and an important application in smart city projects, because of the rapidly increasing number of cars in urban areas. However, most of the current proposals in smart car parking systems manage the data on the cloud side which is a problem since the system needs to send the raw data from sensor to cloud and receive instructions back: this is expensive in terms of energy and data transmission cost. To tackle this issue we present a proposal to save energy and to reduce the amount of data that is transmitted over the network to cloud by processing closer to source in this paper. The architecture is demonstrated through a case study

Matching Customer Requests to Service Offerings in Real-Time

Classic request-response Service-oriented architecture (SOA) has reached a level of maturity where SOA inspired extensions are enabling new and creative domains like the Internet of Things, real-time business or real-time Web. These new domains impose new requirements on SOA, such as a huge data volume, meditation between various data structures and a large number of sources that need to be procured, processed and provided with almost zero latency. Service selection is one of the areas where decisions have to be made based consumer requests and service offerings. Processing this data requires typical SOA behavior combined with more elaborate approaches to process large amounts of data with near-zero latency. The approach presented in this paper combines pub-sub approaches for processing service offerings and mediations with classical request-response SOA approaches for consumer requests facilitated by Complex Event Processing (CEP). This paper presents a novel approach for subscribing to dynamic service properties and receiving up-to-date information in real-time. Therefore, we are able to select services with zero latency since there is no need to pull for property values anymore. The paper shows how to map requests to streaming data, how to process and answer complex requests with low latency and how to enable real-time service selection

Towards Feature Interactions in Business Processes

The feature interaction problem is generally associated with conflicting features causing undesirable effects. However, in this paper we report on a situation where the combination of features (as policies) and service-targeted business processes yields non-negative effects. We consider business processes as base systems and policies as a feature mechanism for defining user-centric requirements and system variability. The combination of business processes and a diverse range of policies leads to refinement of activities and possible reconfiguration of processes. We discuss the ways in which policies can interact with a business process and how these interactions are different from other approaches such as the classical view of POTS or telecommunications features. We also discuss the conflicts that can arise and potential resolutions

HIAWSC: An Immune Algorithm Based Heuristic Web Service Composition Framework

The introduction of of web services has led to web service composition being a focus of many researchers. Composing web services using workflows is seen as the most realistic method from an industrial viewpoint. Amongst other method, the use of natural computing methods has been proposed previously to automate web service composition. The need for a fast response when computing the most suitable sequence of services is addressed in this paper. In particular, we propose a novel heuristic immune algorithm with an efficient encoding and mutation method. The algorithm involves two steps: an immune selection operation, which is maintaining antibody population diversity and the clonal selection. The use of a vaccine during the evolution provides heuristic information that accelerates the convergence. Our experimental results illustrate that the proposed heuristic immune algorithm is very effective in improving the convergence speed. We also provide a schema analysis for this method

Towards an Off-the-cloud IoT data processing Architecture via a Smart Car Parking Example

Nowadays, it is obvious that technology has revolutionised our lives by supporting us to do complicated jobs. The Internet of Things (IoT) is one of the emerging technologies. One of the most significant current research topics in the IoT is smart city. The smart city includes several applications such assmart home, smart industry and smart mobility. The smart car parking system is an aspect of smart mobility and an important application in smart city projects, because of the rapidly increasing number of cars in urban areas. However, most of the current proposals in smart car parking systems manage the data on the cloud side which is a problem since the system needs to send the raw data from sensor to cloud and receive instructions back: this is expensive in terms of energy and data transmission cost. To tackle this issue we present a proposal to save energy and to reduce the amount of data that is transmitted over the network to cloud by processing closer to source in this paper. The architecture is demonstrated through a case study

Policy Support for Business-oriented Web Service Management

Policies have been adopted for many reasons within Web services and service-oriented architecture in general. However, while they are a favoured method of management, this only occurs at the service level and in the software domain. Policies already exist in a narrow variety more focussed on service properties such as authorisation. As a significant number of Web services become available, more emphasis needs to be placed on management of services in the business domain. In this paper, we propose a policy framework that can be used to express business requirements for Web services, at a business level that is more abstract than the high-level composition and orchestration technologies

Extending a Policy Language in a Structured way using Model Driven Techniques

Policy languages have been used for a variety of applications in software systems - usually each application has received its own language. An example of a policy language that has been designed with domain specialization in mind is APPEL, however so far no structured way for domain specialization has been designed. In this paper we use model driven design techniques, in particular parameterization, to present a framework for providing said structured way for adopting/extending APPEL to a specific domain. We exemplify the approach with a case study

VOML: A Framework for Modelling Virtual Organizations and Virtual Breeding Environment

This paper presents the VOML (Virtual Organization Modelling Language) framework. VOML is a formal approach for specifying VOs (Virtual Organizations) and their VBEs (Virtual Breeding Environments).The VOML framework allows domain users to model a system in terms of their domain terminology and from that domain specific model IT community can derive a complete operational model closer to underlying execution environment. The framework is a collection of three sub-languages, each covering different aspects which are considered paramount at a particular level of VO representation. We present VOML and its underlying methodological approach in detail and demonstrate how to model VOs. Our focus will be on the methodological approach that VOML supports and on the language primitives that VOML offers for modelling VOs