Quantitative static analysis of distributed systems

We introduce a quantitative approach to the analysis of distributed systems which relies on a linear operator based network semantics. A typical problem in a distributed setting is how information propagates through a network, and a typical qualitative analysis is concerned with establishing whether some information will eventually be transmitted from one node to another node in the network. The quantitative approach we present allows us to obtain additional information such as an estimation of the probability that some data is transmitted within a given interval of time. We formalise situations like this using a probabilistic version of a process calculus which is the core of KLAIM, a language for distributed and mobile computing based on interactions through distributed tuple spaces. The analysis we present exploits techniques based on Probabilistic Abstract Interpretation and is characterised by compositional aspects which greatly simplify the inspection of the nodes interaction and the detection of the information propagation through a computer network.

[1]  Emilio Tuosto,et al.  The Klaim Project: Theory and Practice , 2003, Global Computing.

[2]  D. Whittaker,et al.  A Course in Functional Analysis , 1991, The Mathematical Gazette.

[3]  Peter Buchholz,et al.  Kronecker Based Matrix Representations for Large Markov Models , 2004, Validation of Stochastic Systems.

[4]  Chris Hankin,et al.  Continuous-Time Probabilistic KLAIM , 2005, SecCo.

[5]  Richard V. Kadison,et al.  Fundamentals of the Theory of Operator Algebras. Volume IV , 1998 .

[6]  Simson Wassermann,et al.  K‐THEORY AND C*‐ALGEBRAS: A FRIENDLY APPROACH , 1995 .

[7]  Patrick Cousot,et al.  Abstract interpretation: a unified lattice model for static analysis of programs by construction or approximation of fixpoints , 1977, POPL.

[8]  Frederick J. Beutler,et al.  The operator theory of the pseudo-inverse I. Bounded operators , 1965 .

[9]  Catuscia PalamidessiDept Probabilistic Asynchronous -calculus ? , 2000 .

[10]  Patrick Cousot,et al.  Abstract Interpretation and Application to Logic Programs , 1992, J. Log. Program..

[11]  Corrado Priami,et al.  Global Computing. Programming Environments, Languages, Security, and Analysis of Systems , 2003, Lecture Notes in Computer Science.

[12]  Christopher Lance,et al.  FUNDAMENTALS OF THE THEORY OF OPERATOR ALGEBRAS Volume I Elementary Theory, Volume II Advanced Theory , 1988 .

[13]  Catuscia Palamidessi,et al.  Probabilistic Asynchronous pi-Calculus , 2000, FoSSaCS.

[14]  W. D. Ray,et al.  Stochastic Models: An Algorithmic Approach , 1995 .

[15]  Stephen Gilmore,et al.  Performance Evaluation for Global Computation , 2003, Global Computing.

[16]  A. Böttcher,et al.  Introduction to Large Truncated Toeplitz Matrices , 1998 .

[17]  S. R. Caradus,et al.  Operator theory of the pseudo-inverse , 1974 .

[18]  Adi Ben-Israel,et al.  Generalized inverses: theory and applications , 1974 .

[19]  Chris Hankin,et al.  Quantitative Relations and Approximate Process Equivalences , 2003, CONCUR.

[20]  Chris Hankin,et al.  Approximate non-interference , 2002, Proceedings 15th IEEE Computer Security Foundations Workshop. CSFW-15.

[21]  Falko Bause,et al.  Stochastic Petri Nets: An Introduction to the Theory , 2012, PERV.

[22]  Rocco De Nicola,et al.  KLAIM: A Kernel Language for Agents Interaction and Mobility , 1998, IEEE Trans. Software Eng..

[23]  H. G. Dales,et al.  BANACH ALGEBRAS AND THE GENERAL THEORY OF ""-ALGEBRAS Volume I Algebras and Banach Algebras (Encyclopedia of Mathematics and its Applications 49) By THEODORE W. PALMER: 794 pp., £60.00, ISBN 0 521 36637 2 (Cambridge University Press, 1994). , 1996 .

[24]  D. Vere-Jones Markov Chains , 1972, Nature.

[25]  P. Fillmore,et al.  A User's Guide to Operator Algebras , 1996 .

[26]  Tommaso Toffoli,et al.  Cellular automata machines - a new environment for modeling , 1987, MIT Press series in scientific computation.

[27]  Flemming Nielson,et al.  Principles of Program Analysis , 1999, Springer Berlin Heidelberg.

[28]  Albert-László Barabási,et al.  Error and attack tolerance of complex networks , 2000, Nature.

[29]  Herbert Wiklicky,et al.  Measuring the Precision of Abstract Interpretations , 2000, LOPSTR.

[30]  Susanna Donatelli,et al.  Superposed Stochastic Automata: A Class of Stochastic Petri Nets with Parallel Solution and Distributed State Space , 1993, Perform. Evaluation.

[31]  Alan Bain Stochastic Calculus , 2007 .

[32]  Herbert Wiklicky,et al.  Concurrent constraint programming: towards probabilistic abstract interpretation , 2000, PPDP '00.