Edge Agent Control for Distributed Streaming Query Processing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In distributed computer control systems, especially in wide area networks, centralized control models face challenges due to poor accessibility, scalability issues, unreliable network connectivity, variable latency, dynamic sensor changes, and geographic distribution, making it difficult to program devices as agents effectively.
Innovation Solution
The system separates streaming continuous queries into sub-queries and rule sets, distributing them to edge agents for independent evaluation, reducing data transfer and maintaining global rules at higher levels, thus creating tightly coupled subsystems that operate reliably even with unreliable network connectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a centralized control model is used in a wide area network, then control decisions can be made centrally, but network unreliability and variable latency cause system failures and poor accessibility
Solution Approach 1:
The patent divides the centralized control system into distributed edge agents that can independently execute control decisions. Each edge agent is segmented to handle local control autonomously, breaking the monolithic centralized architecture into manageable distributed units that can operate independently when network connectivity is unavailable.
Solution Approach 2:
The system pre-configures edge agents with control rules and decision-making capabilities before deployment. This preliminary action enables edge agents to make control decisions autonomously without real-time centralized coordination, addressing the unreliability of wide area networks by having control logic already in place at the edge.
2Reliability
If control logic is distributed to edge agents, then network connectivity reliability is reduced, but programming and managing distributed agents becomes more difficult
Solution Approach 1:
The patent creates a universal agent framework that handles multiple functions including rule interpretation, decision execution, and adaptive learning. This multi-functional design simplifies agent programming by providing a standardized template that handles complex distributed control tasks through a unified interface, reducing the difficulty of managing diverse edge agents.
Solution Approach 2:
The system implements feedback mechanisms where edge agents report their state and performance to the centralized system, which then adjusts control rules and parameters. This feedback loop simplifies agent programming by allowing centralized optimization of distributed agents based on real-world performance data, reducing the manual programming complexity.
3Speed
If data is transferred centrally for processing, then centralized control is maintained, but latency increases and network bandwidth is consumed
Solution Approach 1:
The patent implements local quality by enabling edge agents to process and act on data locally without constant centralized involvement. Each edge agent has the capability to interpret control rules and execute decisions using local data, eliminating the need to transfer all data to the center and reducing both latency and network overhead.
Solution Approach 2:
The system extracts only the essential control logic and decision rules from the centralized system and places them at the edge agents. This extraction eliminates the need to transfer large volumes of data for processing, as the critical decision-making capability is removed from the centralized system and embedded at the edge, reducing data transfer overhead significantly.
Data Source
AI summary
In an embodiment, an improved computer-implemented method of efficiently determining actions to perform based on data from a streaming continuous queries in a distributed computer system comprises, at a central control computer, receiving a streaming continuous query and a rule-set; wherein the rule-set comprises decision data representing decisions based on attributes produced by the query, and action data representing end actions based on the decisions, wherein the attributes comprise data processed by one or more networked computers; separating the streaming continuous query into a sub-query executable at one or more edge computers; categorizing end actions from the set based on decisions requiring attributes available from the sub-query into a set of one or more edge expressions that are configured to be evaluated at an edge agent to cause an action; providing the set of edge expressions and the sub-query to at least one edge computer with instructions to process visible attributes on the edge computer and to evaluate the set of one or more edge expressions independently from the central control computer; wherein the method is performed by one or more computing devices.