Speculation Management Engine for Faster Cloud Resource Connections
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Solution Overview
Problem
Conventional cloud access management systems lack comprehensive computing logic and infrastructure to provide instant and timely connectivity to cloud-based resources, leading to slower connection times and delays due to overhead in authentication and resource mapping processes, especially in frequent connection scenarios.
Innovation Solution
A speculation management engine that partitions remote connection initialization operations into remote resource resolution and connection configuration operations, executed in parallel, using a multi-dimensional speculation framework to preemptively configure connections based on user data and local client information, anticipating user needs to reduce connection times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional cloud access management systems use standard authentication and resource mapping processes, then connection security and resource accuracy are maintained, but connection times increase and performance deteriorates
Solution Approach 1:
The system performs preliminary actions by speculatively pre-configuring remote resource connections based on user behavior patterns and historical data before actual connection requests are made. This allows the connection configuration to be prepared in advance, reducing the time required during actual connection attempts.
Solution Approach 2:
The connection initialization sequence is divided into two independent sets of operations: remote resource resolution operations and remote resource connection configuration operations. These can be executed in parallel, with the resolution operations identifying the target resource while configuration operations prepare the connection, thereby reducing total connection time.
2Reliability
If the remote client is not active and a virtual machine must be booted, then resource availability is ensured, but connection delays increase
Solution Approach 1:
The system speculatively pre-activates virtual machines and pre-configures connections based on predicted user needs before actual connection requests occur. This preliminary activation ensures resources are available when needed without incurring boot delays during actual connection attempts.
Solution Approach 2:
The system dynamically adjusts resource activation strategies based on user behavior patterns, historical connection data, and current system state. Virtual machines are activated speculatively when prediction algorithms indicate high probability of upcoming access, balancing resource availability with energy consumption.
3Reliability
If comprehensive authentication and connection negotiation operations are performed, then connection security and reliability are maintained, but overhead increases and performance decreases
Solution Approach 1:
Authentication and connection negotiation operations are segmented into distinct phases that can be executed in parallel. Remote resource resolution operations handle identification and initial authentication while connection configuration operations handle detailed negotiation, allowing concurrent processing and improved throughput.
Solution Approach 2:
Initial authentication and resource identification are performed in advance as preliminary actions during the resolution phase. This allows subsequent connection configuration to proceed with pre-validated credentials and known resource targets, reducing the overhead of repeated authentication negotiations.
4Ease of operation
If frequent connection attempts are made, then user accessibility is improved, but cumulative overhead increases and performance deteriorates
Solution Approach 1:
The system maintains persistent pre-configured connection states for frequently accessed resources. When users make repeated connection attempts, the system leverages these pre-configured states rather than performing full authentication and negotiation sequences, dramatically reducing cumulative overhead for frequent connections.
Solution Approach 2:
The system dynamically caches and reuses connection configurations for frequently accessed remote resources. Connection parameters, authentication tokens, and resource identifiers are stored and reused across multiple connection attempts, adapting the connection process to user behavior patterns and minimizing repeated overhead.
Data Source
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AI summary
Methods, systems, and computer storage media for providing speculation management using a speculation management engine of a cloud access management system are described. The speculation management engine operates based on speculation data, a multi-dimensional speculation framework, and two sets of operations defined based on an initialization sequence. In operation, speculation data for a user associated with a local client is accessed. A determination of a plurality of speculated remote resource candidates is made, based on the speculation data associated with the user. Execution of a first set of operations (i.e., remote resource resolution) and a second set of operations (i.e., remote resource connection configuration) are triggered. A determination is made whether a remote resource identified from the remote resource resolution matches a speculated remote resource candidate in the plurality of speculated remote resource candidates. Based on the speculated remote resource candidate, a connection for accessing a remote resource is established.