On specifying and monitoring epistemic properties of distributed systems
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On Specifying and Monitoring Epistemic Properties of Distributed Systems. Koushik Sen Abhay Vardhan Gul Agha Grigore Rosu. University of Illinois at Urbana-Champaign, USA. Software Reliability. Software Validation Rigorous and Complete Methods Model Checking Theorem Proving

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On specifying and monitoring epistemic properties of distributed systems

On Specifying and Monitoring Epistemic Properties of Distributed Systems

Koushik Sen

Abhay Vardhan

Gul Agha

Grigore Rosu

University of Illinois at Urbana-Champaign, USA


Software reliability
Software Reliability Distributed Systems

  • Software Validation

    • Rigorous and Complete Methods

      • Model Checking

      • Theorem Proving

    • Infeasible for large-scale open distributed systems (Actors)

      • Non-determinism and Asynchrony

    • Testing

      • Widely used

      • Ad-Hoc

      • Good Test Coverage Required

    • Runtime Monitoring

      • Adds rigor to Testing


Centralized monitoring approach
Centralized Monitoring Approach Distributed Systems

  • Monitoring – Use Formal Methods in Testing

    • Synthesize light-weight Monitors from Specification

      • Automata, Rewriting-based Monitors

    • Instrument code to insert monitors

    • Execute instrumented code

  • Distributed System Monitoring

    • Global state is distributed

    • For every state update send state to a central monitor

    • Central monitor assembles them to form consistent execution traces

      • Sequence of global states

    • Monitor execution traces


An example
An Example Distributed Systems

  • Mobile node a requests certain value from node b

  • b computes the value and sends it to a

  • Property: no node receives a value from another node to which it had not sent a request


Centralized monitoring example
Centralized Monitoring Example Distributed Systems

“If a receives a value from b then b calculated the value after receiving request from a”

valRcv → (valComputed  valReq)

valReq

valReq

valComputed  valReq

valRcv → (valComputed  valReq)

(valComputed  valReq)

b

valComputed

a

valReq

valRcv


Decentralized monitoring approach
Decentralized Monitoring Approach Distributed Systems

“If a receives a value from b then b calculated the value after receiving request from a”

valRcv → @b((valComputed  @a(valReq)))

valComputed  @a(valReq)

@a(valReq)

(valComputed  @a(valReq))

b

valComputed

a

valReq

valRcv

valReq

valRcv → @b((valComputed  @a(valReq)))


Past time distributed temporal logic pt dtl
Past time Distributed Temporal Logic (pt-DTL) Distributed Systems

  • Based on epistemic logic

    • [Aumann76][Meenakshi et al. 00]

  • Properties with respect to a process, say p


Leader election example
Leader Election Example Distributed Systems

“If a leader is elected then if the current process is a leader then, at its knowledge, none of the other processes (b and c) is a leader”

elected → (state=leader →

(@b(state ≠ leader) Æ @c(state ≠ leader)))


Leader election stronger property
Leader Election (Stronger Property) Distributed Systems

  • Every process must know the name of the process that has been elected leader

    elected → (let k=leaderName in

    (@b(leaderName = k) Æ @c(leaderName = k)))


Leader election open system
Leader Election (Open System) Distributed Systems

  • There are arbitrary number of processes whose names are not known before-hand

    elected → (let k=leaderName in

    @8 {j | j  i}(leaderName = k))


Extended distributed temporal logic xdtl
Extended Distributed Temporal Logic (xDTL) Distributed Systems

  • Suitable for Open Distributed Systems (Actors)

    • Ids of all processes are not known before-hand

  • Quantification over processes

    • All processes satisfying a predicate

      • @8 {j | pred(j)}

    • Some process satisfying a predicate

      • @9 {j | pred(j)}

  • Value-binding (Increases Expressive Power)

    • let k = x in F

    • To refer to values in remote states


Xdtl syntax
xDTL syntax Distributed Systems

  • Fi ::= true | false | P(Ei) | : Fi | FiÆ Fi propositional

    | ¯ Fi | ¡ Fi | Fi | Fi S Fi temporal

    | @8 JFj | @9 JFj epistemic

    | let k = Ei in Fibinding

  • Ei ::= c | vi2 Vi | f(Ei) | k functional

    | @jEj epistemic


Interpretation of @ 8 j e j at process i
Interpretation of @ Distributed Systems 8 JEj at process i

p3

m4

m1

m2

p2

@ {1}(x=9)

m3

p1

x=7

x=9


Monitoring algorithm
Monitoring Algorithm Distributed Systems

  • Requirements

    • Should be fast so that online monitoring is possible

    • Little memory overhead

    • Additional messages sent should be minimal; ideally zero

  • Monitoring using KnowledgeVector

    • Maintain knowledge of global state at each process

    • Update knowledge with incoming messages

    • Attach knowledge with outgoing messages

    • At each process monitor local knowledge


Conclusion
Conclusion Distributed Systems

  • Decentralized Technique to effectively verify open distributed systems at runtime

  • No extra message over-head for monitoring

  • xDTL can express interesting and useful safety properties of distributed systems

  • How to instrument code running on all processes so that monitoring can be done?


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