Massimo Valla

A comprehensive context modeling framework for pervasive computing systems

Context management in pervasive computing environments must reflect the specific characteristics of these environments, e.g. distribution, mobility, resource-constrained devices, or heterogeneity of context sources. Although a number of context models have been presented in the literature, none of them supports all of these requirements to a sufficient extent at the same time. In this paper, we present a comprehensive and integrated approach for context modeling in pervasive computing environments. It combines the advantages of existing approaches and addresses the need for supporting effective software development. The proposed context model follows an ontology-based approach and has three layers of abstraction, i.e. conceptual layer, exchange layer, and functional layer. This layered approach facilitates a model-driven development of context-aware applications. Throughout the paper we compare our solution with the related work in order to clearly demonstrate why we needed to develop a new context management framework and where we have adopted existing ideas.

A Context Query Language for Pervasive Computing Environments

This paper identifies requirements for querying and accessing context information in mobile and pervasive computing environments. Furthermore it studies existing query languages showing that they satisfy only a subset of these requirements or cover some of them only to a limited extent. A new context query language is presented to overcome these shortcomings, improving the state of the art in several respects: heterogeneous representations of context information, definition of complex filtering mechanisms, elaborate aggregation functions and ontology integration, all in one language.

Proximity classification for mobile devices using wi-fi environment similarity

This paper describes an algorithm to compute lists of people and devices that are physically nearby to a mobile user based on the analysis of signals from existing wireless networks. The system evaluates proximity by classifying the degree of similarity of the Wi-Fi scan data through a statistical Gaussian Mixture Model. It recognizes when the devices are in the same area, and, in this case, it distinguishes three proximity levels: High (e.g. same room), Medium (e.g. same floor) and Low (e.g. same building). The algorithm can be deployed on a remote server that receives Wi-Fi scanning data (including MAC addresses and signal strength) from mobile devices. The server estimates proximity by extracting a set of features from each received pair of Wi-Fi data, feeding them to the GMM model and selecting the category with greatest probability. The method presented in the paper does not require calibration and leverages on existing Wi-Fi signals, while obtaining a percentage of correct discrimination among three levels near to 90%.

Context inference of users' social relationships and distributed policy management

Inference of high-level context is becoming crucial in development of context-aware applications. An example is social context inference - i.e., deriving social relations based upon the users daily communication with other people. The efficiency of this mechanism mainly depends on the method(s) used to draw inferences based on existing evidence and sample information, such as a training data. Our approach uses rule-based data mining, Bayesian network inference, and user feedback to compute the probabilities of another user being in the specific social relationship with a user whose daily communication is logged by a mobile phone. In addition, a privacy mechanism is required to ensure the users personal integrity and privacy when sharing this users sensitive context data. Therefore, the derived social relations are used to define a users policies for context access control, which grant the restricted context information scope depending on the users current context. Finally, we propose a distributed architecture capable of managing this context information based upon these context access policies.

The Context API in the OMA Next Generation Service Interface

Application Platforms and related APIs are becoming the foundations for emerging eco-systems of online applications/services. End-users are more and more choosing devices and services based on the available offers in the respective eco-system. Attracting and retaining application developers and end-users to a networked platform is nowadays more and more depending on the features available to developers in the form of APIs and (e.g. cloud-based) execution environments rather than on the actual portfolio of services. The Open Mobile Alliance (OMA) Next Generation Service Interfaces (NGSI) is one cornerstone of evolving a network operator towards an application platform provider with open APIs. Within NGSI, the Context API enables access to a plethora of rich information about users, places, events, and things - all made available by or brokered through the network operator. This paper explains the OMA NGSI Context API and its rationale, describes the operations, and discusses typical use cases and benefits it can bring to operators and application developers.

Context-aware networking and communications: Part 1 [Guest Editorial]

Context refers to information characterizing the situation of an entity or a group of entities, and it provides information about the present status of the entities. The term context may be understood differently in different scenarios and for different involved users. The involved entities can be either concrete entities or virtual entities. Involved concrete entities could be either a single entity, such as a person, a machine device, an object, or a location, or a group of entities. An involved virtual entity could be a software function, a software application, a service, an activity, and so on. Conventionally, much of the functionality of communications and networking is context-irrelevant. With the rapid development of modern communications and networking technologies in recent years, especially the increasing functionalities and complexities of the Internet, context-aware communications and networking (CACN) systems and applications have been developed in some limited areas and aspects. In the foreseeable future, context-aware functionalities would be much more extensively applied in information and communication technologies. CACN could be performed at all layers of communications and networking, from the physical and networking layers to transport and application layers. Context awareness may be considered as a response mechanism to the context information obtained from the involved concrete or virtual entities. Context information may have many different meanings, such as activities, geospatial information, network states, battery levels, situations of social networks, energy consumptions, environmental parameters, and signal-to-noise ratios. Context awareness allows for customization or creation of applications to match the preferences of the involved entities.

A Requirements-Driven Approach Towards Decentralized Social Networks

A new generation of distributed social networks is promising to give back users full control over their personal information as shared in private and business life. However, there are many aspects to this control, such as information ownership, access to third parties and limited persistence. This paper compares various existing solutions against an analytically elaborated list of user requirements. Based on this comparison, we also present a comprehensive and integrated approach to overcome the major issues outlined for the existing solutions, including first experiences of applying the reference implementation.

Context Grouping Mechanism for Context Distribution in Ubiquitous Environments

Context distribution is a key aspect for successful applications within mobile and ubiquitous computing environments. In such environments, context information is acquired by several and multiple context sensors distributed over the environment. Applications collect and react to these data, according to predefined adaptation mechanisms. The success of these mechanisms depends on the availability of context information, which is disseminated over the network. However, in practice, only a fraction of the observable context information is required by the adaptation mechanisms. Moreover, for privacy reasons, it is important to delimitate a scope for context dissemination. In this work we address these issues by proposing a context grouping mechanism which allows the definition of groups based on the context characteristics. Each group is defined by these characteristics and delimitate a given context information set that can be distributed among group members. This approach of context grouping acts as a two-fold mechanism. On the one hand, it controls and organizes context distribution over a peer-to-peer network. On the other hand, it proposes a primary and low-level privacy mechanism for context distribution, which is an important aspect influencing context distribution.

High level context query processing: An experience report

Pervasive applications want to describe in simple ways which context information they need about users, and be notified when low level context matches specified constraints defined by semantic expressions. In this paper we report our experience while implementing our Context Query Language and using it in a real context framework to support mobile context-aware applications in two European-funded projects. Our experience has shown that both the language design and its implementation are suitable to support complex asynchronous high-level context notification requirements from applications.

Towards a smart retail environment

Over the last decades, the advancements in digital technologies pervasiveness increasingly transformed regular physical spaces in smart ambients, where humans and objects are seamlessly hyper-connected. Large screens are commonly part of these smart environments, although most of these displays are single and not personalized installations that provide general contents and features, regardless the actual users interacting with them. This work presents challenges and opportunities of our interactive system that, applied to a smart retail environment, takes advantage of technologies that are already familiar to shoppers (smartphones, smart watches, touch screens, etc.), offering new interaction methods to virtually present to users personalized products information.