'Crash failures' presentation slideshows

SECOND PART Algorithms for UNRELIABLE Distributed Systems: The consensus problem

SECOND PART Algorithms for UNRELIABLE Distributed Systems: The consensus problem. Failures in Distributed Systems. Link failure : A link fails and remains inactive forever; the network may get disconnected

1.17k views • 105 slides

SECOND PART Algorithms for UNRELIABLE Distributed Systems: The consensus problem

SECOND PART Algorithms for UNRELIABLE Distributed Systems: The consensus problem. Failures in Distributed Systems. Link failure : A link fails and remains inactive forever; the network may get disconnected

1.05k views • 105 slides

Distributed Resilient Consensus Nitin Vaidya University of Illinois at Urbana-Champaign

Distributed Resilient Consensus Nitin Vaidya University of Illinois at Urbana-Champaign. capacity. User Applications. Multi-channel protocol. channels. Capacity bounds. Insights on protocol design. Fixed. D. IP Stack. OS improvements Software architecture. Net-X testbed. F. B.

1.05k views • 90 slides

941 views • 74 slides

829 views • 69 slides

Faults and fault-tolerance

One of the selling points of a distributed system is that the system will continue to perform (at some level) even if some components / processes / links fail. Faults and fault-tolerance. Cause and effect. Study examples of what causes what .

731 views • 57 slides

Faults and fault-tolerance

One of the selling points of a distributed system is that the system will continue to perform (at some level) even if some components / processes / links fail. Faults and fault-tolerance. Cause and effect. Study examples of what causes what .

590 views • 57 slides

Reliable Distributed Systems

635 views • 55 slides

P2P P2P 2005

614 views • 43 slides

CS5412: Lecture 8 Using Time in I o T Applications

CS5412: Lecture 8 Using Time in I o T Applications. Ken Birman Spring, 2019. Context: Quick reminder. Real-time clocks have limitations on precision, accuracy and skew. Lamport defines the happens-before relation ( ?), implements logical clocks (and vector clocks), defines consistent cuts.

547 views • 43 slides

Faults and fault-tolerance

One of the selling points of a distributed system is that the system will continue to perform (at some level) even if some components / processes / links fail. Faults and fault-tolerance. Cause and effect. Study examples of what causes what .

672 views • 43 slides

Distributed Systems Principles and Paradigms

Distributed Systems Principles and Paradigms. Chapter 07 Fault Tolerance. 01 Introduction 02 Communication 03 Processes 04 Naming 05 Synchronization 06 Consistency and Replication. 07 Fault Tolerance 08 Security 09 Distributed Object-Based Systems 10 Distributed File Systems

476 views • 43 slides

PERSPECTIVES ON THE CAP THEOREM

PERSPECTIVES ON THE CAP THEOREM. Seth Gilbert, National U of Singapore Nancy A. Lynch, MIT. Paper highlights. The CAP theorem as a negative result Cannot have Consistency + Availability + Partition Tolerance Tradeoffs between safety and liveness in unreliable systems

491 views • 28 slides

Reliable Multicast for Time-Critical Systems

Reliable Multicast for Time-Critical Systems. Mahesh Balakrishnan Ken Birman Cornell University. Mission-Critical Datacenters. COTS Datacenters Online e-tailers, search engines, corporate applications Web-services Mission-Critical Apps

405 views • 20 slides

Leader Election

Leader Election. Let G = (V,E) define the network topology. Each process i has a variable L(i) that defines the leader . ? i,j ? V ? i,j are non-faulty :: L(i) ? V ? L(i) = L(j) ? L(i) is non-faulty Often reduces to maxima (or minima) finding problem. Bully algorithm.

496 views • 19 slides

Leader Election

Leader Election. Let G = (V,E) define the network topology. Each process i has a variable L(i) that defines the leader . ? i,j ? V ? i,j are non-faulty :: L(i) ? V ? L(i) = L(j) ? L(i) is non-faulty Often reduces to maxima (or minima) finding problem. Bully algorithm.

193 views • 19 slides

CS 775/875: Fall 2002

CS 775/875: Fall 2002. Chapter 11: Coordination and Agreement. Failure Assumptions. Each pair of processes is connected by reliable channels---eventually deliver a message Network partition (and a later repair) is a possibility Process failures are fail-stop

205 views • 14 slides

Approximate Consensus with Crash Failures in Asynchronous Systems

Approximate Consensus with Crash Failures in Asynchronous Systems. Approximate Consensus with Crash Failures & Asynchrony. Validity: Output in the convex hull of inputs Agreement: Outputs within ? of each other, for a constant ? > 0. Termination in finite time. Asynchronous system

243 views • 12 slides

Classifying fault-tolerance

Classifying fault-tolerance. Masking tolerance . Application runs as it is. The failure does not have a visible impact. All properties (both liveness & safety) continue to hold. Non-masking tolerance . Safety property is temporarily affected , but not liveness.

140 views • 12 slides