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EventuallyConsistentMap

An eventually consistent map provides weaker consistency properties in return for superior read/write performance. All reads are performed on local state and all writes update local state and in the background updates to other replicas in the background. Users can configure this map with a ClockService that will be used to time stamp various update events. The timestamps are used to reorder updates that arrive out of order and thereby ensure that the system state across all replicas eventually converges to the correct state.

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Applications that require stronger consistency guarantees can use the ConsistentMap primitive. ConsistentMap supports java.util.concurrent.ConcurrentMap style conditional update operations and it ensures that all operations for any given key (in the map) are serialized for strong consistency. The underlying protocol that lets us achieve this is RAFT Raft. Furthermore, the entire key space (for the map) is partitioned so as to ensure good scale out characteristic. i.e. each key in the ConsistentMap maps to a single partition or shard. Consistency of each shard is maintained via a separate RAFT Raft consensus cluster. This ensures that operations on keys mapped to different partitions can proceed independently. In a N node cluster, by default we create N shards. The responsibility for each shard lies with 3 different nodes thereby ensuring shard availability even if one of its nodes fails.

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ONOS has a service to facilitate leader election for arbitrary topics. The service ensures that at any given point in time a single controller node acts as a leader for a given topic. There can exist The LeadershipService can at any given point in time facilitate leader election for multiple topics and likewise each controller node can simultaneously be in the leadership race for multiple topics.

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This service is more basic in its functionality and lets a controller instances instance communicate with each others by making RPCs. Each A controller can register handlers for processing incoming messagesthat get invoked when messages of certain type are received. The service supports various cluster wide communication primitives such as: unicast, multicast and broadcast

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This service can be used to know about various controller discover other nodes in the cluster and their current state (alive or dead)

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As the name suggests this is a data structure that provides set semantics in a distributed context.

AtomicCounter (available in Cardinal)

This is similar to AtomicLong but in a distubuted distributed setting. It is useful for vending globally unique counter values.

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