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Recherche/Raynal18.md

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+# Michel Raynal - FAULT-TOLERANT DISTRIBUTED SERVICES IN MESSAGE-PASSING SYSTEMS
+
+## Connexes
+
+Comprendre la théorie derrière le Failure Detector. __T. D. Chandra and S. Toueg, “Unreliable failure detectors for reliable distributed systems,” J. ACM, vol. 43, no. 2, pp. 225–267, 1996.__
+
+## Definition
+
+Fault-Tolerence: The service remains uninterrupted even if some component in the network fail.
+Distributed System: A collection of computers (or nodes) that communicate amongst themselves [...] to perform a given task.
+Distributed Computing: The use of a Distributed System to solve a computational problems.
+Static system: The system composition is fixed.
+Dynamic system: nodes may enter, leave or move in the system with time.
+FLP impossibility result: It is impossible to design a distributed system that is both asynchronous and fault-tolerant.
+
+ADD (Average Delayed/Dropped): model used to describe realisticly the network.
+
+Data-Strcutures:
+
+- linearizability: a data structure is said to be linearizable if it guarantees that all operations appear to happen at a single pointin time between the invocation and response of the operation.
+- Shared Register: [a data strcuture] that stores a value and has two opérations: read [...] and write.
+- Fault-Tolerent Register: Linearizable (atomic) Shared register.
+
+Attacks:
+
+- crash: a node halts, but was working correctly until it halts.
+- omission: a node fails to receive incoming messages or send outgoing messages.
+- timing: a node's message delivery lies outside of the specified delivery time interval.
+- Byzantine: Malicious attacks, operator mistake, software errors and conventional crash faults.
+- churn: change in system composition due to nodes entering and leaving.
+
+Usefull terms:
+
+- shared memory/message-passing model
+- synchronous/asynchronous systems
+- static/dynamic systems
+
+
+algorithms of sharded registers:
+- RAMBO
+- DynaStore
+- Baldoni et Al.
+
+## Chapter 1
+
+He's began to define the terms of distributed systemsn and the possibles uses cases.
+He define synchronous message-passing systems as giving the best guarantees. Opposite to asynchronous message-passing systems.  
+
+### Failure Detectors
+
+He's defining te concept of Failure Detectors as an oracle able to identify the failed nodes. And how they can be used to circumvent the FLP impossibility result.
+Actually the Failure Detectors needs a certain level of synchronicity to work. And two lines of research are proposed to solve this problem: The first one is to implement the Failure Detector on a increasingly weaker system model. And the second one is to find the weakest Failure Detector.
+
+### Fault-Tolerant Register
+
+He defined a "shared register" and explained how it's complicated to implementing them due to the possibility of faulty nodes. And he present the solution who's the Fault-Tolerant Register. He also present the "linearizability" property and how it's used to define the Fault-Tolerant Register.
+Finally he introduce two implementation of the Fault-Tolerant Register: one who's crash-tolerent and the other one who's Byzantine-tolerent.
+
+## Chapter 2
+
+He precised the context of the implementation. We are on an arbitrary, partitionnable network composed of Average Delayed/Dropped channels (ADD).
+The failure detectors can be defined by their accuracy and completness tel que:
+
+- Strong completeness is satisfied if the failure detector of each node eventually suspects all nodes that are crashed.
+- Eventual strong accuracy is satisfied if the failure detector of every node eventually stops suspecting all nodes that are correct.
+
+He described he's algorithm.
+
+## Chapter 3.1
+
+He purposed a new Fault-Tolerant Register who's crash-tolerent and churn proof.
+The algorithm is tolerent of node who could crash or leave the system.
+There is no hierarchy between the nodes. And the algorithm emulated a shared memory using the message-passing model. 
+
+## Chapter 3.2
+
+He purposed a new Fault-Tolerant Register who's crash-tolerent and churn and Byzantin proof.
+The model add a notion of server in the previous model (where we had only clients). And a system of asymetric signature.
+Also he proved than it's impossible with thiss model to determine the number of Byzantin server as a fraction of the total number of servers.