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Concurrent Reading and Writing using Mobile Agents
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bet | 3/7 | Sana | 27.05.2022 | Hajmi | 1.92 Mb. | | #22085 |
Bog'liq taqsimlangan O‘zbekiston respublikasi oliy va o‘rta maxsus ta’lim vazirligi u, 1111 - Leader election
- Mutual exclusion
- Time synchronization
- Distributed snapshot
- Reliable multicast
- Replica management
- Consensus
Implementation - Most of the practical distributed systems have a real network as its backbone.
- However, such systems can also be simulated on a shared-memory multiprocessor, or even on a single processor, or in the cloud.
- (How will you do it? Think of simulating multiple processes, and mailboxes between pairs of communicating processes)
Models - We will reason about distributed systems using models. There are many dimensions of variability in distributed systems. Examples:
- types of processors
- inter-process communication mechanisms
- timing assumptions
- failure classes
- security features, etc
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Models - Models are simple abstractions that help overcome the variability -- abstractions that preserve the essential features, but hide the implementation details and simplify writing distributed algorithms for problem solving
- Optical or radio communication?
- PC or Mac?
- Are clocks perfectly synchronized?
A classification - Client-server model
- Server is the coordinator
- Peer-to-peer model
- No unique coordinator
- In both parallel and distributed systems, the events are
- partially ordered. The distinction between parallel and distributed is not always very clear. In parallel systems, the primarily issues are speed-up and increased data handling capability. In distributed systems the primary issues are fault-tolerance, synchronization, scalability etc.
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