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Nature-inspired Coordination
                           for Complex Distributed Systems

                                             Andrea Omicini
                                        andrea.omicini@unibo.it

                         Dipartimento di Informatica: Scienza e Ingegneria (DISI)
                            Alma Mater Studiorum—Universit` di Bologna
                                                                  a


                                                   IDC 2012
                                       Intelligent Distributed Computing
                                    Calabria, Italy – 26th of September 2012




Omicini (DISI, Universit` di Bologna)
                        a                    Nature-inspired Coordination      IDC 2012, 26/9/2012   1 / 47
Outline




1    Why?


2    Examples
       Early
       Modern
       Issues


3    Tuples


4    Trends




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   2 / 47
Why?


Outline


1    Why?

2    Examples
       Early
       Modern
       Issues

3    Tuples

4    Trends



Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   3 / 47
Why?


Why Nature-inspired Models?

Complex natural systems
   such as physical, chemical, biochemical, biological, social systems
   natural system exhibit features
                such as distribution, opennes, situation, fault tolerance, robustness,
                adaptiveness, . . .
        which we would like to understand, capture, then bring to
        computational systems

Nature-Inspired Computing (NIC)
        For instance, NIC [Liu and Tsui, 2006] summarises decades of
        research activities
        putting emphasis on autonomy of components, and on
        self-organisation of systems

Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   4 / 47
Why?


Why Coordination Models?


Interaction
     most of the complexity of complex computational systems comes
     from interaction [Omicini et al., 2006]
        along with an essential part of their expressive power [Wegner, 1997]

Coordination
    since coordination is essentially the science of managing the space of
    interaction [Wegner, 1997]
        coordination models and languages [Ciancarini, 1996] provide
        abstractions and technologies for the engineering of complex
        computational systems [Ciancarini et al., 2000]



Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   5 / 47
Why?


Why Nature-inspired Coordination?

Coordination issues in natural systems
    coordination issues did not first emerge in computational systems
        [Grass´, 1959] noted that in termite societies “The coordination of
              e
        tasks and the regulation of constructions are not directly dependent
        from the workers, but from constructions themselves.”

Coordination as the key issue
    many well-known examples of natural systems – and, more generally,
    of complex systems – seemingly rely on simple yet powerful
    coordination mechanisms for their key features—such as
    self-organisation
        it makes sense to focus on nature-inspired coordination models as the
        core of complex nature-inspired computational systems

Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   6 / 47
Examples


Outline


1    Why?

2    Examples
       Early
       Modern
       Issues

3    Tuples

4    Trends



Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   7 / 47
Examples     Early


Stigmergy I



Stigmergy in insect societies
    nature-inspired models of coordination are grounded in studies on the
    behaviour of social insects, like ants or termites
        [Grass´, 1959] introduced the notion of stigmergy as the fundamental
              e
        coordination mechanism in termite societies
        in ant colonies, pheromones act as environment markers for specific
        social activities, and drive both the individual and the social
        behaviour of ants




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   8 / 47
Examples     Early


Stigmergy II




Stigmergy in computational systems
    nowadays, stigmergy generally refers to a set of nature-inspired
    coordination mechanisms mediated by the environment
        digital pheromones [Parunak et al., 2002] and other signs made and
        sensed in a shared environment [Parunak, 2006] can be exploited for
        the engineering of adaptive and self-organising computational systems




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   9 / 47
Examples     Early


Chemical Coordination

Chemical reactions as (natural) coordination laws
        inspiration comes from the idea that complex physical phenomena are
        driven by the (relatively) simple chemical reactions
        coordinating the behaviours of a huge amount of components, as well
        as the global system evolution

Chemical reactions as (computational) coordination laws
        Gamma [Banˆtre and Le M´tayer, 1990] is a chemistry-inspired
                     a            e
        coordination model—as for the CHAM (chemical abstract machine)
        model [Berry, 1992]
        coordination in Gamma is conceived as the evolution of a space
        governed by chemical-like rules, globally working as a rewriting system
        [Ban˘tre et al., 2001]
            a

Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   10 / 47
Examples     Modern


Field-based Coordination



Computational fields as coordination laws
   field-based coordination models like TOTA
   [Mamei and Zambonelli, 2004] are inspired by the way masses and
   particles move and self-organise according to
   gravitational/electromagnetic fields [Mamei and Zambonelli, 2006]
        there, computational force fields, generated either by the active
        components or by the pervasive coordination infrastructure, propagate
        across the environment, and drive the actions and motion of the
        component themselves




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   11 / 47
Examples     Modern


(Bio)chemical Coordination


Chemical reactions as coordination laws
    chemical tuple spaces [Viroli et al., 2010] exploit the chemical
    metaphor at its full extent—beyond Gamma
        data, devices, and software agents are represented in terms of
        chemical reactants, and system behaviour is expressed by means of
        chemical-like laws
        which are actually time-dependent and stochastic
        embedded within the coordination medium
        biochemical tuple spaces [Viroli and Casadei, 2009] add
        compartments, diffusion, and stochastic behaviour of coordination
        primitives



Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   12 / 47
Examples     Issues


Basic Issues of Nature-inspired Coordination I



Environment
     environment is essential in nature-inspired coordination
                it works as a mediator for component interaction — through which the
                components of a distributed system can communicate and coordinate
                indirectly
                it is active — featuring autonomous dynamics, and affecting
                component coordination
                it has a structure — requiring a notion of locality, and allowing
                components of any sort to move through a topology




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   13 / 47
Examples     Issues


Basic Issues of Nature-inspired Coordination II



Stochastic behaviour
    complex systems typically require probabilistic models
                don’t know / don’t care non-deterministic mechanisms are not
                expressive enough to capture all the properties of complex systems such
                as biochemical and social systems
                probabilistic mechanisms are required to fully capture the dynamics of
                coordination in nature-inspired systems
                coordination models should feature (possibly simple yet) expressive
                mechanisms to provide coordinated systems with stochastic behaviours




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   14 / 47
Tuples


Outline


1    Why?

2    Examples
       Early
       Modern
       Issues

3    Tuples

4    Trends



Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   15 / 47
Tuples


The Ancestor



Linda [Gelernter, 1985]
        Linda is the ancestor of all tuple-based coordination models
        [Rossi et al., 2001]
        in Linda, coordinables synchronise, cooperate, compete
                based on tuples
                available in the tuple spaces, working as the coordination media
                by associatively accessing, consuming and producing tuples
        the same holds for any tuple-based coordination model




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   16 / 47
Tuples


Linda is not a Nature-inspired Model




So, why Linda?

                                        Why tuple-based models???




Omicini (DISI, Universit` di Bologna)
                        a                   Nature-inspired Coordination   IDC 2012, 26/9/2012   17 / 47
Tuples


Why Tuple-based Models? I



Expressiveness
    Linda is a sort of core coordination model
        making it easy to face and solve many typical problems of complex
        distributed systems
        complex coordination problems are solved with few, simple primitives
        whatever the model used to measure expressiveness of coordination,
        tuple-based languages are highly-expressive [Busi et al., 1998]




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   18 / 47
Tuples


Why Tuple-based Models? II


Environment-based coordination
     generative communication [Gelernter, 1985] requires permanent
     coordination abstractions
        so, tuple spaces are provided as coordination services by the
        coordination infrastructure [Viroli and Omicini, 2006]
        they can be interpreted as coordination artefacts shaping
        computational environment [Omicini et al., 2004]
        as such, they can be exploited to support environment-based
        coordination [Ricci et al., 2005]




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   19 / 47
Tuples


Why Tuple-based Models? III


Extensibility
    whatever its expressiveness, Linda was conceived as a coordination
    model for closed, parallel systems
        so, in fact, some relevant problems of today open, concurrent systems
        cannot be easily solved with Linda either in practice or in theory
        as a result, tuple-based models have been extended with new simple
        yet powerful mechanisms
        generating a plethora of tuple-based coordination models
        [Rossi et al., 2001]




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   20 / 47
Tuples


Why Tuple-based Models? IV


Nature-inspired extensions
    Linda may not be nature-inspired, but many of its extensions are
    many of the coordination models depicted before
                stigmergy [Parunak, 2006]
                field-based [Mamei and Zambonelli, 2004]
                chemical [Viroli et al., 2010] and biochemical [Viroli and Casadei, 2009]
        along with many others, such as
                cognitive stigmergy [Ricci et al., 2007]
                pervasive ecosystems [Viroli et al., 2012]
        are actually nature-inspired tuple-based coordination models




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   21 / 47
Tuples


Toward Self-organising Coordination I

Just some is not enough
     capturing just some of the principles and mechanisms of natural
     systems does not ensure to capture their essence
        for instance, chemical coordination models such as Gamma and
        CHAM exploit the raw schema of computation as chemical reaction,
        but are not expressive enough to fully reproduce any non-trivial
        chemical system
        in fact, e.g., even the simplest model for real chemical reactions
        requires a notion of reaction rate
        neither Gamma nor CHAM provide for such a notion, they are not
        expressive enough to fully match the behaviour of real chemical
        systems


Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   22 / 47
Tuples


Toward Self-organising Coordination II


Self-organising coordination [Viroli et al., 2009]
        most of the traditional coordination models feature abstractions
        enacting coordination laws that are typically reactive, (mostly)
        deterministic, and global as well
        in complex systems featuring self-* properties, instead, coordination
        patterns typically appear at the global level by emergence, from
        probabilistic, time-dependent coordination laws based on local criteria
        in particular, many coordination models either implicitly or explicitly
        recognise that full expressiveness requires addressing the issues of
        time dependency and stochasticity




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   23 / 47
Tuples


Examples I

StoKlaim
   StoKlaim [De Nicola et al., 2006] – a stochastic extension of the
   Linda-derived Klaim model for mobile coordination
   [De Nicola et al., 1998] – adds distribution rates to coordination
   primitives—thus making it possible the modelling of non-deterministic
   real-life phenomena such as failure rates and inter-arrival times

SwarmLinda
    SwarmLinda [Tolksdorf and Menezes, 2004] enhances Linda
    implementation with swarm intelligence to achieve features such as
    scalability, adaptiveness, and fault-tolerance—by modelling tuple
    templates as ants, featuring probabilistic behaviour when looking for
    matching tuples in a distributed setting

Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   24 / 47
Tuples


Examples II



Time-aware ReSpecT
        ReSpecT [Omicini and Denti, 2001] generally addresses time
        dependency by capturing time events and supporting the definition
        and enforcement of timed coordination policies
        [Omicini et al., 2005]—so, ReSpecT-programmed tuple centres can
        work as time-dependent abstractions for the coordination of
        distributed processes [Omicini et al., 2007]




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   25 / 47
Tuples


Enough?



No.
        in the overall, the above-mentioned models fail to capture all the
        essential features of nature-inspired coordination
        this is why many novel research lines stretch existing tuple-based
        models to achieve the expressive power required to model and build
        distributed systems with a complexity comparable to natural systems
        [Omicini and Viroli, 2011]




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   26 / 47
Trends


Outline


1    Why?

2    Examples
       Early
       Modern
       Issues

3    Tuples

4    Trends



Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   27 / 47
Trends


Full Dynamics



Expressing the full dynamics of complex natural systems
    for instance, Gamma mimics chemical reactions, but does not capture
    essential issues in chemical processes such as reaction rates and
    concentration [Banˆtre and Le M´tayer, 1990, Ban˘tre et al., 2001]
                         a            e                  a
        instead, (bio)chemical tuple spaces fully exploit the chemical
        metaphor by providing time-dependent and stochastic chemical laws
        [Viroli et al., 2010, Viroli and Casadei, 2009]
        more generally, the goal is to allow coordinated systems to express the
        full dynamics of complex natural systems




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   28 / 47
Trends


Blending Metaphors



Mixing abstractions & mechanisms from different conceptual sources
    for instance, the SAPERE coordination model for pervasive service
    ecosystems [Zambonelli et al., 2011, Viroli et al., 2012] exploits
                the chemical metaphor for driving the evolution of coordination
                abstractions
                biochemical abstractions for topology and diffusion
                the notion of ecosystem in order to model the overall system structure
                and dynamics
        this mostly resembles natural systems, when they are observed in their
        whole complexity, crossing their many layers




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   29 / 47
Trends


Knowledge-oriented Coordination

Integrating nature-inspired with knowledge-oriented coordination
     intelligent distributed systems in knowledge intensive environments,
     as well as complex socio-technical systems, require automatic
     understanding of data and information
        knowledge-oriented coordination [Nardini et al., ] exploits
        coordination abstractions capable of semantic interpretation
        for instance
                both chemical tuple spaces and SAPERE abstractions relay on the
                semantic interpretation of coordination items—in the same way as
                semantic tuple centres [Nardini et al., 2011]
                MoK (Molecules of Knowledge) is a a nature-inspired coordination
                model focussing on knowledge management
                [Mariani and Omicini, 2012], exploiting the full power of the
                biochemical metaphor to achieve knowledge self-organisation within
                knowledge-intensive environments

Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   30 / 47
Trends


Core Mechanisms


Understanding the basic elements of expressiveness
    Linda is a glaring example of a minimal set of coordination
    mechanisms providing a wide range of coordination behaviours
        the goal is understanding the minimal set of coordination primitives
        required to design complex stochastic behaviours
        for instance, uniform coordination primitives – that is, Linda-like
        coordination primitives returning tuples matching a template with a
        uniform distribution [Gardelli et al., 2007] – seemingly capture the
        full-fledged dynamics of real chemical systems within the coordination
        abstractions




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   31 / 47
Trends


Predicting Complex Behaviours

Engineering unpredictable systems around predictable abstractions
    coordination models and technologies are typically in charge of
    harnessing the complexity of articulated computational systems
    [Ciancarini et al., 2000]
        coordination abstractions are often at the core of complex systems
        while this does not make complex system generally predictable, it
        makes it possible in principle to make them partially predictable,
        based on the predictably of the core coordinative behaviour
        suitably-formalised coordination abstractions, along with a
        suitably-defined engineering methodology, could in principle ensure the
        predictability of given system properties within generally-unpredictable
        coordinated systems—such as nature-inspired systems


Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   32 / 47
Conclusion


Conclusion I



History and evolution
     starting from early chemical and stigmergic approaches,
     nature-inspired models of coordination evolved to become the core of
     complex distributed systems—such as pervasive, knowledge-intensive,
     intelligent, and self-* systems
        in this talk we shorty surveyed their history, devise their main issues,
        and point out the most promising trends
        focussing in particular on tuple-based coordination models




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   33 / 47
Conclusion


Conclusion II



In the overall. . .
     nature-inspired models of coordination already have a long history
     behind them
        and apparently a huge potential for development still to be explored
        to provide core abstractions and technologies for the engineering of
        complex computational systems




Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   34 / 47
Conclusion


Thanks to. . .




        . . . everybody here for listening, despite yesterday night
        . . . Giancarlo Fortino for inviting me
        . . . the SAPERE Project for the support                       1




    1
      This work has been supported by the EU-FP7-FET Proactive project SAPERE
Self-aware Pervasive Service Ecosystems, under contract no. 256873.
Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination       IDC 2012, 26/9/2012   35 / 47
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Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination    IDC 2012, 26/9/2012   36 / 47
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                        a               Nature-inspired Coordination    IDC 2012, 26/9/2012   37 / 47
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Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination       IDC 2012, 26/9/2012   38 / 47
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Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination     IDC 2012, 26/9/2012   39 / 47
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                        a               Nature-inspired Coordination     IDC 2012, 26/9/2012   40 / 47
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Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination    IDC 2012, 26/9/2012   41 / 47
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       Tuple-based technologies for coordination.
       In Omicini, A., Zambonelli, F., Klusch, M., and Tolksdorf, R., editors, Coordination of
       Internet Agents: Models, Technologies, and Applications, chapter 4, pages 83–109.
       Springer.
       Tolksdorf, R. and Menezes, R. (2004).
       Using Swarm Intelligence in Linda Systems.
       In Omicini, A., Petta, P., and Pitt, J., editors, Engineering Societies in the Agents World
       IV, volume 3071 of LNCS, pages 49–65. Springer.
       4th International Workshops (ESAW 2003), London, UK, 29-31 October 2003. Revised
       Selected and Invited Papers.



Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination      IDC 2012, 26/9/2012    42 / 47
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Bibliography VIII

       Viroli, M. and Casadei, M. (2009).
       Biochemical tuple spaces for self-organising coordination.
       In Field, J. and Vasconcelos, V. T., editors, Coordination Languages and Models, volume
       5521 of LNCS, pages 143–162. Springer, Lisbon, Portugal.
       11th International Conference (COORDINATION 2009), Lisbon, Portugal, June 2009.
       Proceedings.
       Viroli, M., Casadei, M., Nardini, E., and Omicini, A. (2010).
       Towards a chemical-inspired infrastructure for self-* pervasive applications.
       In Weyns, D., Malek, S., de Lemos, R., and Andersson, J., editors, Self-Organizing
       Architectures, volume 6090 of LNCS, chapter 8, pages 152–176. Springer.
       1st International Workshop on Self-Organizing Architectures (SOAR 2009), Cambridge,
       UK, 14-17 September 2009, Revised Selected and Invited Papers.
       Viroli, M., Casadei, M., and Omicini, A. (2009).
       A framework for modelling and implementing self-organising coordination.
       In Shin, S. Y., Ossowski, S., Menezes, R., and Viroli, M., editors, 24th Annual ACM
       Symposium on Applied Computing (SAC 2009), volume III, pages 1353–1360, Honolulu,
       Hawai’i, USA. ACM.



Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination   IDC 2012, 26/9/2012   43 / 47
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Bibliography IX

       Viroli, M. and Omicini, A. (2006).
       Coordination as a service.
       Fundamenta Informaticae, 73(4):507–534.
       Special Issue: Best papers of FOCLASA 2002.
       Viroli, M., Pianini, D., Montagna, S., and Stevenson, G. (2012).
       Pervasive ecosystems: a coordination model based on semantic chemistry.
       In Ossowski, S., Lecca, P., Hung, C.-C., and Hong, J., editors, 27th Annual ACM
       Symposium on Applied Computing (SAC 2012), Riva del Garda, TN, Italy. ACM.
       Wegner, P. (1997).
       Why interaction is more powerful than algorithms.
       Communications of the ACM, 40(5):80–91.
       Zambonelli, F., Castelli, G., Ferrari, L., Mamei, M., Rosi, A., Di Marzo, G., Risoldi, M.,
       Tchao, A.-E., Dobson, S., Stevenson, G., Ye, Y., Nardini, E., Omicini, A., Montagna, S.,
       Viroli, M., Ferscha, A., Maschek, S., and Wally, B. (2011).
       Self-aware pervasive service ecosystems.
       Procedia Computer Science, 7:197–199.
       Proceedings of the 2nd European Future Technologies Conference and Exhibition 2011
       (FET 11).


Omicini (DISI, Universit` di Bologna)
                        a               Nature-inspired Coordination      IDC 2012, 26/9/2012   44 / 47
Extras


URLs I




Slides
     On APICe
                             http://apice.unibo.it/xwiki/bin/view/Talks/
                                              InvitedIdc2012
        On SlideShare
                                http://www.slideshare.net/andreaomicini/
               natureinspired-coordination-for-complex-distributed-systems




Omicini (DISI, Universit` di Bologna)
                        a                Nature-inspired Coordination   IDC 2012, 26/9/2012   45 / 47
Extras


URLs II



Article
     On APICe
                       http://apice.unibo.it/xwiki/bin/view/Publications/
                                         NatureinspcoordIdc2012



        On SpringerLink
                                   http://www.springerlink.com/content/
                                              43tmmn1j4t5616q8




Omicini (DISI, Universit` di Bologna)
                        a                 Nature-inspired Coordination   IDC 2012, 26/9/2012   46 / 47
Nature-inspired Coordination
                           for Complex Distributed Systems

                                             Andrea Omicini
                                        andrea.omicini@unibo.it

                         Dipartimento di Informatica: Scienza e Ingegneria (DISI)
                            Alma Mater Studiorum—Universit` di Bologna
                                                                  a


                                                   IDC 2012
                                       Intelligent Distributed Computing
                                    Calabria, Italy – 26th of September 2012




Omicini (DISI, Universit` di Bologna)
                        a                    Nature-inspired Coordination      IDC 2012, 26/9/2012   47 / 47

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Nature-inspired Coordination for Complex Distributed Systems

  • 1. Nature-inspired Coordination for Complex Distributed Systems Andrea Omicini andrea.omicini@unibo.it Dipartimento di Informatica: Scienza e Ingegneria (DISI) Alma Mater Studiorum—Universit` di Bologna a IDC 2012 Intelligent Distributed Computing Calabria, Italy – 26th of September 2012 Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 1 / 47
  • 2. Outline 1 Why? 2 Examples Early Modern Issues 3 Tuples 4 Trends Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 2 / 47
  • 3. Why? Outline 1 Why? 2 Examples Early Modern Issues 3 Tuples 4 Trends Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 3 / 47
  • 4. Why? Why Nature-inspired Models? Complex natural systems such as physical, chemical, biochemical, biological, social systems natural system exhibit features such as distribution, opennes, situation, fault tolerance, robustness, adaptiveness, . . . which we would like to understand, capture, then bring to computational systems Nature-Inspired Computing (NIC) For instance, NIC [Liu and Tsui, 2006] summarises decades of research activities putting emphasis on autonomy of components, and on self-organisation of systems Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 4 / 47
  • 5. Why? Why Coordination Models? Interaction most of the complexity of complex computational systems comes from interaction [Omicini et al., 2006] along with an essential part of their expressive power [Wegner, 1997] Coordination since coordination is essentially the science of managing the space of interaction [Wegner, 1997] coordination models and languages [Ciancarini, 1996] provide abstractions and technologies for the engineering of complex computational systems [Ciancarini et al., 2000] Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 5 / 47
  • 6. Why? Why Nature-inspired Coordination? Coordination issues in natural systems coordination issues did not first emerge in computational systems [Grass´, 1959] noted that in termite societies “The coordination of e tasks and the regulation of constructions are not directly dependent from the workers, but from constructions themselves.” Coordination as the key issue many well-known examples of natural systems – and, more generally, of complex systems – seemingly rely on simple yet powerful coordination mechanisms for their key features—such as self-organisation it makes sense to focus on nature-inspired coordination models as the core of complex nature-inspired computational systems Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 6 / 47
  • 7. Examples Outline 1 Why? 2 Examples Early Modern Issues 3 Tuples 4 Trends Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 7 / 47
  • 8. Examples Early Stigmergy I Stigmergy in insect societies nature-inspired models of coordination are grounded in studies on the behaviour of social insects, like ants or termites [Grass´, 1959] introduced the notion of stigmergy as the fundamental e coordination mechanism in termite societies in ant colonies, pheromones act as environment markers for specific social activities, and drive both the individual and the social behaviour of ants Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 8 / 47
  • 9. Examples Early Stigmergy II Stigmergy in computational systems nowadays, stigmergy generally refers to a set of nature-inspired coordination mechanisms mediated by the environment digital pheromones [Parunak et al., 2002] and other signs made and sensed in a shared environment [Parunak, 2006] can be exploited for the engineering of adaptive and self-organising computational systems Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 9 / 47
  • 10. Examples Early Chemical Coordination Chemical reactions as (natural) coordination laws inspiration comes from the idea that complex physical phenomena are driven by the (relatively) simple chemical reactions coordinating the behaviours of a huge amount of components, as well as the global system evolution Chemical reactions as (computational) coordination laws Gamma [Banˆtre and Le M´tayer, 1990] is a chemistry-inspired a e coordination model—as for the CHAM (chemical abstract machine) model [Berry, 1992] coordination in Gamma is conceived as the evolution of a space governed by chemical-like rules, globally working as a rewriting system [Ban˘tre et al., 2001] a Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 10 / 47
  • 11. Examples Modern Field-based Coordination Computational fields as coordination laws field-based coordination models like TOTA [Mamei and Zambonelli, 2004] are inspired by the way masses and particles move and self-organise according to gravitational/electromagnetic fields [Mamei and Zambonelli, 2006] there, computational force fields, generated either by the active components or by the pervasive coordination infrastructure, propagate across the environment, and drive the actions and motion of the component themselves Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 11 / 47
  • 12. Examples Modern (Bio)chemical Coordination Chemical reactions as coordination laws chemical tuple spaces [Viroli et al., 2010] exploit the chemical metaphor at its full extent—beyond Gamma data, devices, and software agents are represented in terms of chemical reactants, and system behaviour is expressed by means of chemical-like laws which are actually time-dependent and stochastic embedded within the coordination medium biochemical tuple spaces [Viroli and Casadei, 2009] add compartments, diffusion, and stochastic behaviour of coordination primitives Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 12 / 47
  • 13. Examples Issues Basic Issues of Nature-inspired Coordination I Environment environment is essential in nature-inspired coordination it works as a mediator for component interaction — through which the components of a distributed system can communicate and coordinate indirectly it is active — featuring autonomous dynamics, and affecting component coordination it has a structure — requiring a notion of locality, and allowing components of any sort to move through a topology Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 13 / 47
  • 14. Examples Issues Basic Issues of Nature-inspired Coordination II Stochastic behaviour complex systems typically require probabilistic models don’t know / don’t care non-deterministic mechanisms are not expressive enough to capture all the properties of complex systems such as biochemical and social systems probabilistic mechanisms are required to fully capture the dynamics of coordination in nature-inspired systems coordination models should feature (possibly simple yet) expressive mechanisms to provide coordinated systems with stochastic behaviours Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 14 / 47
  • 15. Tuples Outline 1 Why? 2 Examples Early Modern Issues 3 Tuples 4 Trends Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 15 / 47
  • 16. Tuples The Ancestor Linda [Gelernter, 1985] Linda is the ancestor of all tuple-based coordination models [Rossi et al., 2001] in Linda, coordinables synchronise, cooperate, compete based on tuples available in the tuple spaces, working as the coordination media by associatively accessing, consuming and producing tuples the same holds for any tuple-based coordination model Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 16 / 47
  • 17. Tuples Linda is not a Nature-inspired Model So, why Linda? Why tuple-based models??? Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 17 / 47
  • 18. Tuples Why Tuple-based Models? I Expressiveness Linda is a sort of core coordination model making it easy to face and solve many typical problems of complex distributed systems complex coordination problems are solved with few, simple primitives whatever the model used to measure expressiveness of coordination, tuple-based languages are highly-expressive [Busi et al., 1998] Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 18 / 47
  • 19. Tuples Why Tuple-based Models? II Environment-based coordination generative communication [Gelernter, 1985] requires permanent coordination abstractions so, tuple spaces are provided as coordination services by the coordination infrastructure [Viroli and Omicini, 2006] they can be interpreted as coordination artefacts shaping computational environment [Omicini et al., 2004] as such, they can be exploited to support environment-based coordination [Ricci et al., 2005] Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 19 / 47
  • 20. Tuples Why Tuple-based Models? III Extensibility whatever its expressiveness, Linda was conceived as a coordination model for closed, parallel systems so, in fact, some relevant problems of today open, concurrent systems cannot be easily solved with Linda either in practice or in theory as a result, tuple-based models have been extended with new simple yet powerful mechanisms generating a plethora of tuple-based coordination models [Rossi et al., 2001] Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 20 / 47
  • 21. Tuples Why Tuple-based Models? IV Nature-inspired extensions Linda may not be nature-inspired, but many of its extensions are many of the coordination models depicted before stigmergy [Parunak, 2006] field-based [Mamei and Zambonelli, 2004] chemical [Viroli et al., 2010] and biochemical [Viroli and Casadei, 2009] along with many others, such as cognitive stigmergy [Ricci et al., 2007] pervasive ecosystems [Viroli et al., 2012] are actually nature-inspired tuple-based coordination models Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 21 / 47
  • 22. Tuples Toward Self-organising Coordination I Just some is not enough capturing just some of the principles and mechanisms of natural systems does not ensure to capture their essence for instance, chemical coordination models such as Gamma and CHAM exploit the raw schema of computation as chemical reaction, but are not expressive enough to fully reproduce any non-trivial chemical system in fact, e.g., even the simplest model for real chemical reactions requires a notion of reaction rate neither Gamma nor CHAM provide for such a notion, they are not expressive enough to fully match the behaviour of real chemical systems Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 22 / 47
  • 23. Tuples Toward Self-organising Coordination II Self-organising coordination [Viroli et al., 2009] most of the traditional coordination models feature abstractions enacting coordination laws that are typically reactive, (mostly) deterministic, and global as well in complex systems featuring self-* properties, instead, coordination patterns typically appear at the global level by emergence, from probabilistic, time-dependent coordination laws based on local criteria in particular, many coordination models either implicitly or explicitly recognise that full expressiveness requires addressing the issues of time dependency and stochasticity Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 23 / 47
  • 24. Tuples Examples I StoKlaim StoKlaim [De Nicola et al., 2006] – a stochastic extension of the Linda-derived Klaim model for mobile coordination [De Nicola et al., 1998] – adds distribution rates to coordination primitives—thus making it possible the modelling of non-deterministic real-life phenomena such as failure rates and inter-arrival times SwarmLinda SwarmLinda [Tolksdorf and Menezes, 2004] enhances Linda implementation with swarm intelligence to achieve features such as scalability, adaptiveness, and fault-tolerance—by modelling tuple templates as ants, featuring probabilistic behaviour when looking for matching tuples in a distributed setting Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 24 / 47
  • 25. Tuples Examples II Time-aware ReSpecT ReSpecT [Omicini and Denti, 2001] generally addresses time dependency by capturing time events and supporting the definition and enforcement of timed coordination policies [Omicini et al., 2005]—so, ReSpecT-programmed tuple centres can work as time-dependent abstractions for the coordination of distributed processes [Omicini et al., 2007] Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 25 / 47
  • 26. Tuples Enough? No. in the overall, the above-mentioned models fail to capture all the essential features of nature-inspired coordination this is why many novel research lines stretch existing tuple-based models to achieve the expressive power required to model and build distributed systems with a complexity comparable to natural systems [Omicini and Viroli, 2011] Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 26 / 47
  • 27. Trends Outline 1 Why? 2 Examples Early Modern Issues 3 Tuples 4 Trends Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 27 / 47
  • 28. Trends Full Dynamics Expressing the full dynamics of complex natural systems for instance, Gamma mimics chemical reactions, but does not capture essential issues in chemical processes such as reaction rates and concentration [Banˆtre and Le M´tayer, 1990, Ban˘tre et al., 2001] a e a instead, (bio)chemical tuple spaces fully exploit the chemical metaphor by providing time-dependent and stochastic chemical laws [Viroli et al., 2010, Viroli and Casadei, 2009] more generally, the goal is to allow coordinated systems to express the full dynamics of complex natural systems Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 28 / 47
  • 29. Trends Blending Metaphors Mixing abstractions & mechanisms from different conceptual sources for instance, the SAPERE coordination model for pervasive service ecosystems [Zambonelli et al., 2011, Viroli et al., 2012] exploits the chemical metaphor for driving the evolution of coordination abstractions biochemical abstractions for topology and diffusion the notion of ecosystem in order to model the overall system structure and dynamics this mostly resembles natural systems, when they are observed in their whole complexity, crossing their many layers Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 29 / 47
  • 30. Trends Knowledge-oriented Coordination Integrating nature-inspired with knowledge-oriented coordination intelligent distributed systems in knowledge intensive environments, as well as complex socio-technical systems, require automatic understanding of data and information knowledge-oriented coordination [Nardini et al., ] exploits coordination abstractions capable of semantic interpretation for instance both chemical tuple spaces and SAPERE abstractions relay on the semantic interpretation of coordination items—in the same way as semantic tuple centres [Nardini et al., 2011] MoK (Molecules of Knowledge) is a a nature-inspired coordination model focussing on knowledge management [Mariani and Omicini, 2012], exploiting the full power of the biochemical metaphor to achieve knowledge self-organisation within knowledge-intensive environments Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 30 / 47
  • 31. Trends Core Mechanisms Understanding the basic elements of expressiveness Linda is a glaring example of a minimal set of coordination mechanisms providing a wide range of coordination behaviours the goal is understanding the minimal set of coordination primitives required to design complex stochastic behaviours for instance, uniform coordination primitives – that is, Linda-like coordination primitives returning tuples matching a template with a uniform distribution [Gardelli et al., 2007] – seemingly capture the full-fledged dynamics of real chemical systems within the coordination abstractions Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 31 / 47
  • 32. Trends Predicting Complex Behaviours Engineering unpredictable systems around predictable abstractions coordination models and technologies are typically in charge of harnessing the complexity of articulated computational systems [Ciancarini et al., 2000] coordination abstractions are often at the core of complex systems while this does not make complex system generally predictable, it makes it possible in principle to make them partially predictable, based on the predictably of the core coordinative behaviour suitably-formalised coordination abstractions, along with a suitably-defined engineering methodology, could in principle ensure the predictability of given system properties within generally-unpredictable coordinated systems—such as nature-inspired systems Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 32 / 47
  • 33. Conclusion Conclusion I History and evolution starting from early chemical and stigmergic approaches, nature-inspired models of coordination evolved to become the core of complex distributed systems—such as pervasive, knowledge-intensive, intelligent, and self-* systems in this talk we shorty surveyed their history, devise their main issues, and point out the most promising trends focussing in particular on tuple-based coordination models Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 33 / 47
  • 34. Conclusion Conclusion II In the overall. . . nature-inspired models of coordination already have a long history behind them and apparently a huge potential for development still to be explored to provide core abstractions and technologies for the engineering of complex computational systems Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 34 / 47
  • 35. Conclusion Thanks to. . . . . . everybody here for listening, despite yesterday night . . . Giancarlo Fortino for inviting me . . . the SAPERE Project for the support 1 1 This work has been supported by the EU-FP7-FET Proactive project SAPERE Self-aware Pervasive Service Ecosystems, under contract no. 256873. Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 35 / 47
  • 36. Bibliography Bibliography I Ban˘tre, J.-P., Fradet, P., and Le M´tayer, D. (2001). a e Gamma and the chemical reaction model: Fifteen years after. In Calude, C. S., P˘un, G., Rozenberg, G., and Salomaa, A., editors, Multiset Processing. a Mathematical, Computer Science, and Molecular Computing Points of View, volume 2235 of LNCS, pages 17–44. Springer. Banˆtre, J.-P. and Le M´tayer, D. (1990). a e The GAMMA model and its discipline of programming. Science of Computer Programming, 15(1):55–77. Berry, G. (1992). The chemical abstract machine. Theoretical Computer Science, 96(1):217–248. Busi, N., Gorrieri, R., and Zavattaro, G. (1998). A process algebraic view of Linda coordination primitives. Theoretical Computer Science, 192(2):167–199. Ciancarini, P. (1996). Coordination models and languages as software integrators. ACM Computing Surveys, 28(2):300–302. Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 36 / 47
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  • 39. Bibliography Bibliography IV Mamei, M. and Zambonelli, F. (2006). Field-Based Coordination for Pervasive Multiagent Systems. Models, Technologies, and Applications. Springer Series in Agent Technology. Springer. Mariani, S. and Omicini, A. (2012). Molecules of knowledge: Self-organisation in knowledge-intensive environments. In Intelligent Distributed Computing VI, pages 17–22. Springer, Calabria, Italy. 6th International Symposium on Intelligent Distributed Computing (IDC 2012). Nardini, E., Omicini, A., and Viroli, M. Semantic tuple centres. Science of Computer Programming. Special Issue on Self-Organizing Coordination. To appear. Nardini, E., Omicini, A., Viroli, M., and Schumacher, M. I. (2011). Coordinating e-health systems with TuCSoN semantic tuple centres. Applied Computing Review, 11(2):43–52. Omicini, A. and Denti, E. (2001). From tuple spaces to tuple centres. Science of Computer Programming, 41(3):277–294. Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 39 / 47
  • 40. Bibliography Bibliography V Omicini, A., Ricci, A., and Viroli, M. (2005). Time-aware coordination in ReSpecT. In Jacquet, J.-M. and Picco, G. P., editors, Coordination Models and Languages, volume 3454 of LNCS, pages 268–282. Springer-Verlag. 7th International Conference (COORDINATION 2005), Namur, Belgium, 20–23 April 2005. Proceedings. Omicini, A., Ricci, A., and Viroli, M. (2006). The multidisciplinary patterns of interaction from sciences to Computer Science. In Goldin, D. Q., Smolka, S. A., and Wegner, P., editors, Interactive Computation: The New Paradigm, pages 395–414. Springer. Omicini, A., Ricci, A., and Viroli, M. (2007). Timed environment for Web agents. Web Intelligence and Agent Systems, 5(2):161–175. Omicini, A., Ricci, A., Viroli, M., Castelfranchi, C., and Tummolini, L. (2004). Coordination artifacts: Environment-based coordination for intelligent agents. In Jennings, N. R., Sierra, C., Sonenberg, L., and Tambe, M., editors, 3rd international Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2004), volume 1, pages 286–293, New York, USA. ACM. Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 40 / 47
  • 41. Bibliography Bibliography VI Omicini, A. and Viroli, M. (2011). Coordination models and languages: From parallel computing to self-organisation. The Knowledge Engineering Review, 26(1):53–59. Parunak, H. V. D. (2006). A survey of environments and mechanisms for human-human stigmergy. In Weyns, D., Parunak, H. V. D., and Michel, F., editors, Environments for Multi-Agent Systems II, volume 3830 of LNCS, pages 163–186. Springer. Parunak, H. V. D., Brueckner, S., and Sauter, J. (2002). Digital pheromone mechanisms for coordination of unmanned vehicles. In Castelfranchi, C. and Johnson, W. L., editors, 1st International Joint Conference on Autonomous Agents and Multiagent systems, volume 1, pages 449–450, New York, NY, USA. ACM. Ricci, A., Omicini, A., Viroli, M., Gardelli, L., and Oliva, E. (2007). Cognitive stigmergy: Towards a framework based on agents and artifacts. In Weyns, D., Parunak, H. V. D., and Michel, F., editors, Environments for MultiAgent Systems III, volume 4389 of LNCS, pages 124–140. Springer. 3rd International Workshop (E4MAS 2006), Hakodate, Japan, 8 May 2006. Selected Revised and Invited Papers. Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 41 / 47
  • 42. Bibliography Bibliography VII Ricci, A., Viroli, M., and Omicini, A. (2005). Environment-based coordination through coordination artifacts. In Weyns, D., Parunak, H. V. D., and Michel, F., editors, Environments for Multi-Agent Systems, volume 3374 of LNAI, pages 190–214. Springer. 1st International Workshop (E4MAS 2004), New York, NY, USA, 19 July 2004. Revised Selected Papers. Rossi, D., Cabri, G., and Denti, E. (2001). Tuple-based technologies for coordination. In Omicini, A., Zambonelli, F., Klusch, M., and Tolksdorf, R., editors, Coordination of Internet Agents: Models, Technologies, and Applications, chapter 4, pages 83–109. Springer. Tolksdorf, R. and Menezes, R. (2004). Using Swarm Intelligence in Linda Systems. In Omicini, A., Petta, P., and Pitt, J., editors, Engineering Societies in the Agents World IV, volume 3071 of LNCS, pages 49–65. Springer. 4th International Workshops (ESAW 2003), London, UK, 29-31 October 2003. Revised Selected and Invited Papers. Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 42 / 47
  • 43. Bibliography Bibliography VIII Viroli, M. and Casadei, M. (2009). Biochemical tuple spaces for self-organising coordination. In Field, J. and Vasconcelos, V. T., editors, Coordination Languages and Models, volume 5521 of LNCS, pages 143–162. Springer, Lisbon, Portugal. 11th International Conference (COORDINATION 2009), Lisbon, Portugal, June 2009. Proceedings. Viroli, M., Casadei, M., Nardini, E., and Omicini, A. (2010). Towards a chemical-inspired infrastructure for self-* pervasive applications. In Weyns, D., Malek, S., de Lemos, R., and Andersson, J., editors, Self-Organizing Architectures, volume 6090 of LNCS, chapter 8, pages 152–176. Springer. 1st International Workshop on Self-Organizing Architectures (SOAR 2009), Cambridge, UK, 14-17 September 2009, Revised Selected and Invited Papers. Viroli, M., Casadei, M., and Omicini, A. (2009). A framework for modelling and implementing self-organising coordination. In Shin, S. Y., Ossowski, S., Menezes, R., and Viroli, M., editors, 24th Annual ACM Symposium on Applied Computing (SAC 2009), volume III, pages 1353–1360, Honolulu, Hawai’i, USA. ACM. Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 43 / 47
  • 44. Bibliography Bibliography IX Viroli, M. and Omicini, A. (2006). Coordination as a service. Fundamenta Informaticae, 73(4):507–534. Special Issue: Best papers of FOCLASA 2002. Viroli, M., Pianini, D., Montagna, S., and Stevenson, G. (2012). Pervasive ecosystems: a coordination model based on semantic chemistry. In Ossowski, S., Lecca, P., Hung, C.-C., and Hong, J., editors, 27th Annual ACM Symposium on Applied Computing (SAC 2012), Riva del Garda, TN, Italy. ACM. Wegner, P. (1997). Why interaction is more powerful than algorithms. Communications of the ACM, 40(5):80–91. Zambonelli, F., Castelli, G., Ferrari, L., Mamei, M., Rosi, A., Di Marzo, G., Risoldi, M., Tchao, A.-E., Dobson, S., Stevenson, G., Ye, Y., Nardini, E., Omicini, A., Montagna, S., Viroli, M., Ferscha, A., Maschek, S., and Wally, B. (2011). Self-aware pervasive service ecosystems. Procedia Computer Science, 7:197–199. Proceedings of the 2nd European Future Technologies Conference and Exhibition 2011 (FET 11). Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 44 / 47
  • 45. Extras URLs I Slides On APICe http://apice.unibo.it/xwiki/bin/view/Talks/ InvitedIdc2012 On SlideShare http://www.slideshare.net/andreaomicini/ natureinspired-coordination-for-complex-distributed-systems Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 45 / 47
  • 46. Extras URLs II Article On APICe http://apice.unibo.it/xwiki/bin/view/Publications/ NatureinspcoordIdc2012 On SpringerLink http://www.springerlink.com/content/ 43tmmn1j4t5616q8 Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 46 / 47
  • 47. Nature-inspired Coordination for Complex Distributed Systems Andrea Omicini andrea.omicini@unibo.it Dipartimento di Informatica: Scienza e Ingegneria (DISI) Alma Mater Studiorum—Universit` di Bologna a IDC 2012 Intelligent Distributed Computing Calabria, Italy – 26th of September 2012 Omicini (DISI, Universit` di Bologna) a Nature-inspired Coordination IDC 2012, 26/9/2012 47 / 47