Distributed Hash Table Entry Hunting in Multi-Node Clusters
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Solution Overview
Problem
In multi-node systems, maintaining resource persistency and ensuring that all nodes have the most up-to-date distributed hash table entries is challenging, especially when nodes leave and rejoin the system, leading to outdated copies of entries.
Innovation Solution
A method and system for hunting and updating distributed hash table entries across a cluster of nodes, where each node replicates entries and determines if copies are outdated by checking access or update time, and iteratively requests updates through a replication chain until an up-to-date copy is found.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If entries are replicated to multiple nodes in the cluster, then reliability and availability are improved, but maintaining data consistency and detecting outdated copies becomes more complex
Solution Approach 1:
The patent implements a feedback mechanism where nodes periodically check the freshness of their local entry copies by comparing timestamps or version information with the primary node or other replicas. When a node detects its copy is outdated, it automatically requests an update, creating a closed-loop feedback system that maintains consistency without centralized control.
Solution Approach 2:
The patent introduces timestamp parameters or version counters associated with each distributed hash table entry. These parameters change over time as entries are updated, allowing nodes to quickly determine whether their local copy is current by comparing these parameters, thus simplifying consistency detection.
2Measurement precision
If nodes frequently check for updates to ensure data freshness, then data consistency is improved, but network traffic and processing overhead increase
Solution Approach 1:
Instead of continuous checking, the patent implements periodic update checks where nodes validate their entry copies at scheduled intervals or triggered by specific events (such as when the entry is accessed). This reduces network overhead while maintaining adequate data freshness through time-based or event-based validation.
Solution Approach 2:
Nodes perform self-validation of their entry copies using local timestamp or version information, only initiating network communication when they detect potential staleness. This self-service approach minimizes unnecessary network traffic while ensuring data freshness when needed.
3Adaptability or versatility
If a node leaves and rejoin the system, then system adaptability is improved, but the node may have outdated entries requiring hunting for updates
Solution Approach 1:
Before a node permanently leaves the system, it can proactively push its current entry copies to other replicas or mark its copies as potentially stale. When the node rejoins, this preliminary action reduces the hunting time needed to synchronize, as other nodes are already aware of the node's absence and may have preserved relevant entry information.
Solution Approach 2:
The patent introduces a coordinator node or uses the primary node as an intermediary that tracks node memberships and maintains a directory of current entry locations. When a node rejoins, it queries this intermediary to quickly locate updated entries without having to hunt through all other nodes, significantly reducing synchronization time.
Data Source
AI summary
The present application is directed towards systems and methods of hunting for a hash table entry in a hash table distributed over a multi-node system. More specifically, when entries are created in an ASDR table, the owner node of the entry may replicate the entry onto a non-owner node. The replica can act as a backup of the ASDR table entry in the event the node leaves the multi-mode system. When the node returns to the multi-node system, the node may no longer have the most up to date ASDR table entries, and may hunt to find the existence of the value associated with the entry. Responsive to receiving a request for an entry that may be outdated on the node, the node sends a request down a replication chain for an updated copy of the ASDR table entry from one of the replicas. Responsive to receiving the replica copy of the entry, the node responds to the client's request for the entry.