Matteo Casadei

Spatial Coordination of Pervasive Services through Chemical-Inspired Tuple Spaces

To support and engineer the spatial coordination of distributed pervasive services, we propose a chemical-inspired model, which extends tuple spaces with the ability of evolving tuples mimicking chemical systems, that is, in terms of reaction and diffusion rules that apply to tuples modulo semantic match. The suitability of this model is studied by considering a self-adaptive display infrastructure providing people nearby with several visualization services (advertisements, news, personal and social content). The key result of this article is that general-purpose chemical reactions inspired by population dynamics can be used in pervasive applications to enact spatial computing patterns of competition and gradient-based interaction.

Biochemical Tuple Spaces for Self-organising Coordination

Inspired by recent works in computational systems biology and existing literature proposing nature-inspired approaches for the coordination of today complex distributed systems, this paper proposes a mechanism to leverage exact computational modelling of chemical reactions for achieving self-organisation in system coordination. We conceive the notion of biochemical tuple spaces. In this model: a tuple resembles a chemical substance, a notion of activity/pertinency value for tuples is used to model chemical concentration, coordination rules are structured as chemical reactions evolving tuple concentration over time, a tuple space resembles a single-compartment solution, and finally a network of tuple spaces resembles a tissue-like biological system. The proposed model is formalised as a process algebra with stochastic semantics, and several examples are described up to an ecology-inspired scenario of system coordination, which emphasises the self-organisation features of the proposed model.

A framework for modelling and implementing self-organising coordination

Research fields like pervasive computing are showing that the interactions between components in large-scale, mobile, and open systems are highly affected by unpredictability: self-organising techniques are increasingly adopted within infrastructures aimed at managing such interactions in a robust and adaptive way. Accordingly, in this paper we discuss the framework of self-organising coordination: coordination media spread over the network are in charge of managing interactions with each other and with agents solely according to local criteria, making interesting and fruitful global properties of the resulting system appearing by emergence---probability and timing typically playing a crucial role. We show that the TuCSoN coordination infrastructure can be used as a general platform for enacting self-organising coordination; we put it to test on two cases: an inter-space application of adaptive tuple clustering, and a intra-space application of chemical-like coordination reactions.

Simulating Emergent Properties of Coordination in Maude: the Collective Sort Case

Recent coordination languages and models are moving towards the application of techniques coming from the research context of complex systems: adaptivity and self-organization are exploited in order to tackle the openness, dynamism and unpredictability of todays distributed systems. In this area, systems are to be described using stochastic models, and simulation is a valuable tool both for analysis and design. Accordingly, in this work we focused on modelling and simulating emergent properties of coordination techniques. We first develop a framework acting as a general-purpose engine for simulating stochastic transition systems, built as a library for the Maude term rewriting system. We then evaluate this tool to a coordination problem called collective sort, where autonomous agents move tuples across different tuple spaces according to local criteria, and resulting in the emergence of the complete clustering property.

Situated tuple centres in ReSpecT

Coordination languages and models can play a key role in the engineering of environment in MAS (multiagent systems). In this paper, we take the ReSpecT coordination language for programming tuple centres, and extend it so as to govern interactions between agents and environment. In particular, we show how its event model can be generalised to support the management of general environment events and make tuple centres situated. To this end, first a case study is sketched where it is shown how the extended ReSpecT can be adopted to coordinate a system for sensing and controlling environmental properties. Then the syntax and semantics of the extended version of ReSpecT is discussed.

On the collective sort problem for distributed tuple spaces

In systems coordinated with a distributed set of tuple spaces, it is crucial to assist agents in retrieving the tuples they are interested in. This can be achieved by sorting techniques that group similar tuples together in the same tuple space, so that the position of a tuple can be inferred by similarity. Accordingly, we formulate the collective sort problem for distributed tuple spaces, where a set of agents is in charge of moving tuples up to a complete sort has been reached, namely, each of the N tuple spaces aggregate tuples belonging to one of the N kinds available. After pointing out the requirements for effectively tackling this problem, we propose a self-organizing solution resembling brood sorting performed by ants. This is based on simple agents that perform partial observations and accordingly take decisions on tuple movement. Convergence is addressed by a fully adaptive method for simulated annealing, based on noise tuples inserted and removed by agents on a need basis so as to avoid sub-optimal sorting. Emergence of sorting properties and scalability are evaluated through stochastic simulations.

Designing self-organising MAS environments: the collective sort case

Self-organisation is being recognised as an effective conceptual framework to deal with the complexity inherent to modern artificial systems. In this article, we explore the applicability of self-organisation principles to the development of multi-agent system (MAS) environments. First, we discuss a methodological approach for the engineering of complex systems, which features emergent properties: this is based on formal modelling and stochastic simulation, used to analyse global system dynamics and tune system parameters at the early stages of design. Then, as a suitable target for this approach, we describe an architecture for self-organising environments featuring artifacts and environmental agents as fundamental entities. As an example, we analyse a MAS distributed environment made of tuple spaces, where environmental agents are assigned the task of moving tuples across tuples spaces in background and according to local criteria, making complete clustering an emergent property achieved through self-organisation.

Simulation in Agent-Oriented Software Engineering: The SODA case study

The key role of simulation in the engineering of complex multiagent systems (MAS) is today generally acknowledged in the MAS community. However, the adoption of simulation in state-of-the-art Agent-Oriented Software Engineering (AOSE) methodologies is still incomplete at its best. In this paper we present a simulation-based approach to MAS engineering and discuss its integration within AOSE methodologies. Integration is first discussed in general by adopting standard method engineering techniques, then detailed by means of a case study-that is, integrating simulation in SODA.

Core operational semantics of Proto

The Proto spatial computing language [6] simplifies the creation of scalable, robust, distributed programs by abstracting a network of locally communicating devices as a continuous geometric manifold. However, Protos successful application in a number of domains is becoming a challenge to its coherence across different platforms and distributions. We thus present an operational semantics for a core subset of the Proto language. This semantics covers all the key operations of the three space-time operator families unique to Proto---restriction, feedback, and neighborhood---as well as a few of the pointwise operations that it shares with most other languages. Because Proto programs are distributed, we also present an operational semantics for their asynchronous execution across a network. This formalization will provide a reference to aid implementers in preserving language coherence across platforms, domains, and distributions.

A self-organizing approach to tuple distribution in large-scale tuple-space systems

A system is said to be self-organizing if its execution yields temporal global structures out of simple and local interactions amongst its constituents (e.g agents, processes). In nature, one can find many natural systems that achieve organization at the global level without a reference to the status of the global organization; real examples include ants, bees, and bacteria. The future of tuple-space systems such as LINDA lies on (i) their ability to handle non-trivial coordination constructs common in complex applications, and (ii) their scalability to environments where hundreds and maybe thousands of nodes exist. The Achilles heel of scalability in current tuple-space systems is tuple organization. Legacy solutions based on antiquated approaches such as hashing are (unfortunately) commonplace. This paper gets inspiration from self-organization to improve the status quo of tuple organization in tuple-space systems. We present a solution that organizes tuples in large networks while requiring virtually no global knowledge about the system.