Network Node Preemption Mechanism for Data Flow Prioritization
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Solution Overview
Problem
Conventional network communication techniques lack the ability to intelligently select and preempt lower-priority data flows to efficiently accommodate higher-priority flows, often disrupting application instances and failing to minimize disruptions across complex network scenarios.
Innovation Solution
Implementing a set of predefined rules across network nodes to deterministically select data flows for preemption, utilizing fate-sharing identifiers to manage and coordinate the termination of data flows, and employing resource reservation protocols like RSVP to allocate resources effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional network communication techniques are used, then network nodes can transport data packets between client nodes, but they lack the ability to intelligently select and preempt lower-priority data flows to accommodate higher-priority flows, causing disruptions to application instances
Solution Approach 1:
The patent applies parameter changes by introducing preemption priority values as a new parameter to differentiate data flows. Network nodes compare preemption priority values of existing data flows with incoming high-priority flows to determine which flows to preempt. This parameter-based differentiation enables intelligent selection of flows for preemption while maintaining reliability by preserving application instance integrity through coordinated preemption across multiple nodes.
2Productivity
If resource reservation protocols like RSVP are implemented, then resources can be allocated effectively, but coordination of preemption across multiple network nodes becomes complex
Solution Approach 1:
The patent applies preliminary action by pre-assigning preemption priority values to data flows before preemption is needed. When a high-priority flow arrives, network nodes can immediately compare priority values and execute preemption without complex real-time coordination. The preemption decision criteria are established in advance, simplifying the coordination process across multiple network nodes while maintaining efficient resource allocation.
3Productivity
If data flows are preempted to accommodate higher-priority flows, then resource allocation is optimized, but application instances may be disrupted
Solution Approach 1:
The patent applies local quality by treating each data flow differently based on its preemption priority value and its relationship to application instances. Instead of uniform preemption, the system selectively preempts only those flows with lower priority values that are safe to terminate. This localized, differentiated approach optimizes resource allocation while preserving application instance continuity by avoiding preemption of critical flows.
Data Source
AI summary
A technique is provided for one or more network nodes to deterministically select data flows to preempt. In particular, each node employs a set of predefined rules which instructs the node as to which existing data flow should be preempted in order to admit a new high-priority data flow. The rules are precisely defined and are common to all nodes configured in accordance with the present invention. Illustratively, a network node not only selects a data flow to preempt, but additionally may identify other “fate sharing” data flows that may be preempted. As used herein, a group of data flows has a fate-sharing relationship if the application instance(s) containing the data flows functions adequately only when all the fate-shared flows are operational. In a first illustrative embodiment, after a data flow in a fate-sharing group is preempted, network nodes may safely tear down the group's remaining data flows. In a second illustrative embodiment, when a data flow is preempted, all its fate-shared data flows are marked as being “at risk.” Because the at-risk flows are not immediately torn down, it is less likely that resources allocated for the at-risk flows may be freed then subsequently used to establish relatively lower-priority data flows instead of relatively higher-priority data flows.