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CAP theorem


  1. Consistency
    (all nodes see the same data at the same time)
  2. Availability
    (a guarantee that every request receives a response about whether it was successful or failed)
  3. Partition tolerance
    (the system continues to operate despite arbitrary message loss or failure of part of the system)

Two design philosophies at opposite ends of the consistency-availability spectrum


BASE (Basically Available, Soft state, Eventual consistency)

ACID (Atomicity, Consistency, Isolation, Durability)

How to store device updates?


End devices send heartbeats periodically to the center.


Save all heartbeats in log style.

or

Save all heartbeats in per-device documents.


... depends on HOW TO USE.

Ad-hoc Query


Explicit information

Detail of an entity


Example

Driving history

Analytic/Batch Process


Implicit information

Area trends


Example

Find communication dark zone

Road surface deterioration monitoring

Endpoints for
User/Admin Ad-hoc Query


Low latency, indexed search.

Interfaces for
Analytic/Batch Process


High throughput, sequential scan.

Our Choice in CAP theorem


Eventual consistency

High availability

Partition tolerance

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By Asser Chiu

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