1) The SAPERE project aims to develop a theoretical and practical framework for pervasive service ecosystems that are highly adaptive and self-managing. 2) It takes a bio-chemical inspiration to model interactions between components as reactions in a spatial substrate governed by "eco-laws". 3) The goals are to define novel self-organization algorithms and knowledge management techniques to enable systems to be situation-aware and anticipate future situations.

1. SAPERE: Self‐aware Pervasive
Service Ecosystems
Franco Zambonelli
Università di Modena e Reggio Emilia
STREP – 3 years
www.sapere‐project.eu
www sapere‐project eu
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2. The Consortium
The Consortium
• Università di Modena e Reggio Emilia
– Franco Zambonelli & Marco Mamei
Franco Zambonelli & Marco Mamei
• Birkbeck College University of London
– Giovanna Di Marzo Serugendo
Giovanna Di Marzo
• Alma Mater Studiorum – Università di Bologna
– Mirko Viroli & Andrea Omicini
• St. Andrews University
– Simon Dobson
• Johannes Kepler Universitaet Linz
p
– Alois Ferscha
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3. The Scenario
The Scenario
• Pervasive computing
– Sensor rich and always connected smart phones
– Sensor networks and information tags
– Localization and activity recognition
– Internet of things and the real‐time Web
Internet of things and the real time Web
• Innovative pervasive services arising
– Situation‐aware adaptation
Situation aware adaptation
– Interactive reality
– Pervasive collective intelligence and pervasive participation
• Open co‐production scenario, very dynamic, diverse
needs and diverse services, continuously evolving
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4. The Overall Objective
The Overall Objective
• Develop and demonstrate a highly‐innovative
theoretical and practical framework for pervasive
service ecosystems
service ecosystems
– Adaptivity and self‐management as inherent properties of
the ecosystem
y
– Systemic self‐awareness as an observable property of the
overall system
– Long lasting (eternal) adaptivity
Long‐lasting (eternal) adaptivity
– Bio‐chemical inspiration
• Foundational re‐thinking of
Foundational re thinking of
– Service architectures and associated middleware
– Self‐* algorithms and contextual knowledge management
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5. The Architectural Approach
The Architectural Approach
• Open production model
• Smooth data/services
distinction
– LSA  live semantic
annotations
• Interactions
Interactions
– Sorts of bio‐chemical reactions
among components
– In a spatial substrate
In a spatial substrate
• Eco‐laws
– Rule all interactions
– Discovery + orchestration
+ orchestration
seamlessly merged
• Built over a pervasive network
world
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6. Specific Objectives
Specific Objectives
• Both of a scientific and technological nature
• Around which the various WPs are organized
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7. Model, Structures, and Knowledge
Model Structures and Knowledge
• M d l & M th d l
Model & Methodology
– Innovative chemical‐inspired semantic model for interactions among
components and their dynamic composition/aggregation
– S
Semantic (LSA) description and semantic pattern‐ mathing
ti (LSA) d i ti d ti tt thi
– Uniform traitment of data and services
– Methodological guidelines associated
• Structures & Space
– Model distributed self‐* algorithms via the chemical LSA framework
– Innovative flexible means for aggregation and composition
gg g p
– Define decentralized means to control the behaviour of the ecosystem
• Knowledge & Time
– Distributed knowledge management algorithms via the LSA framework
Distributed knowledge management algorithms via the LSA framework
– Define new means to perform distributed recognition of current situations
– As well as to enable recognition of future situations
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8. Key Challenges
y g
for model, structure and knowledge
• C
Can our chemically‐inspired computation model and the
h i ll i i d t ti d l d th
eco‐laws?
– Be flexible and general‐purpose enough?
g p p g
– Effectively deal with the complexity and diversity of modern
pervasive scenarios?
– Be effectively implementable?
Be effectively
• And, for structure and knowledge
– Can it accommodate all needed distributed aggregation and
self‐composition algorthims
lf iti l thi
– Can it express all needed forms of knowledge management?
• Or should we rather go for application‐specific (or location‐
Or should go for application specific (or location
specific) eco‐laws?
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9. Infrastructure and Applications
Infrastructure and Applications
• I f t t
Infrastructure
– A very lightweight infrastructure
– Ruling all interactions (from discovery to data exchange and
synchronization) by embedding the concept of eco‐laws
h i ti ) b b ddi th t f l
– To most extent, acting as a recommendation and planning engine
– Possibly inspired by tuple space coordination models
– Yet made it more “fluid” and suitable for a pervasive computing
continuum substrate  not a network but a continuum of tuple spaces
• Applications
– The “Ecosystem of Display” as a general and impactful testbed
– To put at work and demonstrate the SAPERE findings
p g
– Active and dynamic information sharing in urban scenarios
– Active participation of citizens to the working of the urban infrastructure
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10. Key Tangible Results
y g
(hopefully)
• A novel model and methodology to support the development
of complex service systems in open and dynamic pervasive
scenarios
• A uniform set of:
– Self‐* algorithms for service/data composition and aggregation (in
the form of libraries)
th f f lib i )
– Algorithms and tools for distributed management of contextual‐
knowledge, to enforce present‐ and future‐awareness in the
ecosystem
• A novel middleware for pervasive computing scenarios (Open
Source)
)
– Integrating the stated algorithms in the form of libraries
• A set of released innovative application showcased on the
Ecosystem of Displays testbed
E t f Di l t tb d
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