Pervasive computing systems can be modeled 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.

No abstract

Chemical-based coordination models have proven useful to engineer self-organising and self-adaptive systems. Formal assessment of emergent global behaviours in self-organising systems is still an issue, most of the time emergent properties are being analysed through extensive simulations. This paper aims at integrating logic programs into a chemical-based coordination model in order to engineer self-organising systems as well as assess their emergent properties. Our model is generic and accommodates various logics. By tuning the internal logic language we can tackle and solve coordination problems in a rigorous way, without renouncing to important engineering properties such as compactness, modularity and reusability of code. This paper discusses our logic-based coordination model and shows how to engineer and verify a simple pattern detection example and a gradient-chemotaxis example.

Abstract-The assessment of emergent global behaviors of self-organizing applications is an important task to accomplish before employing such systems in real scenarios, yet their intrinsic complexity make this activity still challenging. In this paper we present a logic language used to verify graph-based global properties of self-organizing systems at run-time. The logic language extends a chemical-based coordination model based on logic inference recently proposed. The logic formulae defined by using the language operators depict the intended global spatial properties arising from local interactions among components. Logic formulae are evaluated in a distributed manner by using an inference procedure which checks them against the current global state of the system, verifying whether the intended emergent global behavior actually appears in the system. As examples of spatial properties we consider color patterns: at first we show how to verify specified patterns of identified colors in sets of nodes directly connected, then we present other formulae verifying the appearance of global patterns of colors without specifying the colors themselves. We conclude the examples with the computation of mathematical functions, like the verification of the existence of a maximum value in a specific node of the system.

Mobile devices make it possible to create, store, access, share or publish personal content on the Internet, anywhere and at anytime. This leads to situations of potential intentional or unintentional misuse of content as well as privacy issues. Recent techniques involving the use of contextual information focus on access of documents stored in clouds, or authentication for secured Web sites. These techniques or more traditional solutions, such as steganography or Digital Rights Management, do not empower the user itself, or data controller in professional settings, with a fine-grained control of the access to or manipulations actions on documents stored on mobile devices, e.g., copying, sharing, etc. In this paper, we propose SmartContent, a novel approach for content protection and privacy. Documents are active and context-aware documents that sense and analyse their current context, e.g., location, noise, neighbouring devices, social network, expiration time, etc. Based on user provided policies, they grant, deny or limit access and manipulation actions, or destroy themselves if necessary. We present the generic model of SmartContent, a concrete architecture and an implementation of a proof-of-concept specifically designed for mobile devices. We deployed it on tablets and showed that a picture dynamically reveals or conceals itself based on sensed context or on changing policies. The implementation leverages the SAPERE middleware specifically developed for context-aware systems.