Gabriella Castelli

Self-aware Pervasive Service Ecosystems

Here we present the overall objectives and approach of the SAPERE (“Self-aware Pervasive Service Ecosystems”) project, focussed on the development of a highly-innovative nature-inspired framework, suited for the decentralized deployment, execution, and management, of self-aware and adaptive pervasive services in future network scenarios.

Developing pervasive multi-agent systems with nature-inspired coordination

Pervasive computing systems can be modelled effectively as populations of interacting autonomous components. The key challenge to realizing such models is in getting separately-specified and -developed sub-systems to discover and interoperate with each other in an open and extensible way, supported by appropriate middleware services. In this paper, we argue that nature-inspired coordination models offer a promising way of addressing this challenge. We first frame the various dimensions along which nature-inspired coordination models can be defined, and survey the most relevant proposals in the area. We describe the nature-inspired coordination model developed within the SAPERE project as a synthesis of existing approaches, and show how it can effectively support the multifold requirements of modern and emerging pervasive services. We conclude by identifying what we think are the open research challenges in this area, and identify some research directions that we believe are promising.

Supporting location-aware services for mobile users with the whereabouts diary

Modern handheld devices provided with localization capabilities could be used to automatically create a diary of users whereabouts, and use it as a complement of the user profile in many applications. In this paper we present the Whereabouts diary, an application/service to log the places visited by the user and to label them, in an automatic way, with descriptive semantic information. In particular, Web-retrieved data and the temporal patterns in which places are visited can be used to define such meaningful semantic labels. In this paper, we describe the general idea at the basis of our service and discuss our implementation and the associated experimental results. In addition, we illustrate an application that can fruitfully exploit the whereabouts diary as a supporting service, and discuss areas for future work.

Engineering Pervasive Service Ecosystems: The SAPERE Approach

Emerging pervasive computing services will typically involve a large number of devices and service components cooperating together in an open and dynamic environment. This calls for suitable models and infrastructures promoting spontaneous, situated, and self-adaptive interactions between components. SAPERE (Self-Aware Pervasive Service Ecosystems) is a general coordination framework aimed at facilitating the decentralized and situated execution of self-organizing and self-adaptive pervasive computing services. SAPERE adopts a nature-inspired approach, in which pervasive services are modeled and deployed as autonomous individuals in an ecosystem of other services and devices, all of which interact in accord to a limited set of coordination laws, or eco-laws. In this article, we present the overall rationale underlying SAPERE and its reference architecture. We introduce the eco-laws--based coordination model and show how it can be used to express and easily enforce general-purpose self-organizing coordination patterns. The middleware infrastructure supporting the SAPERE model is presented and evaluated, and the overall advantages of SAPERE are discussed in the context of exemplary use cases.

Engineering contextual knowledge for autonomic pervasive services

In this paper, we identify the key software engineering challenges introduced by the need of accessing and exploiting huge amount of heterogeneous contextual information. Following, we survey the relevant proposals in the area of context-aware pervasive computing, data mining and granular computing discussing their potentials and limitations with regard to their adoption in the development of context-aware pervasive services. On these bases, we propose the W4 model for contextual data and show how it can represent a simple yet effective model to enable flexible general-purpose management of contextual knowledge by pervasive services. A summarizing discussion and the identification of current limitations and open research directions conclude the paper.

Pervasive Middleware Goes Social: The SAPERE Approach

Pervasive computing middleware, to support the spatially and socially situated activities of users, has to effectively support both self-organizing spatial activities and social models of interactions. In this paper, we present the solution that we are going to integrate in the SAPERE middleware to tackle this problem. The basic idea is to exploit the graph of a social network (e.g., Face book), in conjunction with relations deriving from spatial proximity, to drive and rule the actual topology of interactions among devices, users, and services. The approach can facilitates the autonomous and adaptive activities of pervasive services while accounting for both social and spatial issues, can support effective service discovery and orchestration, and can enable tackling critical privacy issues.

The whereabouts diary

The user profile is one of the main context-information in a wide range of pervasive computing applications. Modern handheld devices provided with localization capabilities could automatically create a diary of users whereabouts and use that information as a surrogate (or a complement) of the user profile. The places we go, in fact, reveal also something about us, for example, two persons can be matched as compatible given the fact they visit the same places. Web-retrieved information, and the temporal patterns with which different places are visited, can be used to automatically define meaningful semantic labels to the visited places. In our work we used geocoding and whitepages Web-services to extract information about a place, and Bayesian networks to classify places on the basis of the time in which they have been visited. In this paper we describe the general idea at the basis of the whereabouts diary, discuss our implementation, and present experimental results. Finally, several applications that can exploit the diary are illustrated.

Extracting high-level information from location data: the W4 diary example

Services for mobile and pervasive computing should extensively exploit contextual information both to adapt to user needs and to enable autonomic behavior. To fulfill this idea it is important to provide two key tools: a model supporting context-data representation and manipulation, and a set of algorithms relying on the model to perform application tasks. Following these lines, we first describe the W4 context model showing how it can represent a simple yet effective framework to enable flexible and general-purpose management of contextual information. In particular, we show the model suitability in describing user-centric situations, e.g., describing situations in terms of where a user is located and what he is doing. Then, we illustrate a set of algorithms to semantically enrich W4 represented data and to extract relevant information from it. In particular, starting from W4 data, such algorithms are able to identify the places that matter to the user and to describe them semantically. Overall, we show how the context-model and the algorithms allow to create an high-level, semantic and context-aware diary-based service. This service meaningfully collects and classifies the user whereabouts and the places that the user visited.

A Coordination Approach to Adaptive Pervasive Service Ecosystems

Technology evolution is providing new pervasive service scenarios characterised by a huge number of distributed and dynamic devices. Accordingly, a new generation of services and infrastructures are emerging which support situatedness, adaptivity and diversity. In this paper we model the overall world of services, data and devices, as a distributed computational ecosystem. As such, each entity will be modelled as an autonomous, spatially-situated individual of the ecosystem, whose existence and state is reified by an LSA (Live Semantic Annotation). Ecosystem behaviour is controlled by coordination rules called eco-laws, which are chemical-like reactions evolving the population of LSAs. We describe an architecture supporting this vision along with a model of eco-laws, and show their usefulness in a scenario of adaptive pervasive displays.

The changing role of pervasive middleware: From discovery and orchestration to recommendation and planning

Future pervasive computing scenarios will be characterized by an increasing diversity and dynamics of services and of contextual data sources, and by an increasing exploitation of crowdsourcing for social sensing and human computation. Accordingly, the role of middleware should no longer be limited to facilitating interactions and compositions via discovery and orchestration, but should approach that of a recommendation engine capable of dynamically and adaptively planning patterns of service interaction and composition on a best-effort basis. Along these lines, this position paper elaborates on the limitations of traditional middleware infrastructures in meeting the new requirements of the emerging pervasive computing scenarios. Then, it introduces two case study scenarios to motivate and clarify the concepts expressed. Finally, it identifies some key research challenges for future pervasive middleware infrastructures.