Adaptive Composite Service Orchestration via Dynamic Topology Selection
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Solution Overview
Problem
Existing approaches for orchestrating composite web services are not universally effective in adapting to varying resource availability, particularly in distributed systems with multiple nodes, leading to performance bottlenecks and suboptimal execution due to static partitioning models that fail to adapt to runtime changes in CPU, memory, and network bandwidth.
Innovation Solution
The system dynamically estimates performance metrics based on monitored data such as CPU cycles, memory, bandwidth, and message rates to select the most optimal topology at runtime, routing requests through decentralized topologies that minimize network latency and maximize throughput by using a performance model that accounts for message queues and link bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If static partitioning models are used to orchestrate composite web services, then system structure is simplified and ease of operation is improved, but adaptability to runtime changes in resource availability deteriorates
Solution Approach 1:
The patent implements dynamic topology selection where the orchestration system can switch between different topologies (centralized, decentralized, hybrid) based on runtime resource availability. The system monitors resource metrics and dynamically adjusts the orchestration approach, allowing static partitioning models to be combined with runtime adaptability through configurable topology switching.
2Productivity
If decentralized topologies are used to minimize network data and hops, then network efficiency is improved, but system complexity increases
Solution Approach 1:
The patent segments the orchestration system into multiple independent topologies (centralized, decentralized, hybrid) that can be selectively activated. Each topology is designed to handle specific scenarios optimally, and the system partitions the decision-making process between runtime monitors that track resources and topology selectors that choose the appropriate configuration, thereby managing complexity through modular segmentation.
Solution Approach 2:
The patent creates a universal orchestration framework that can operate in multiple topology modes (centralized, decentralized, hybrid) depending on runtime conditions. The system uses configurable topology selectors and resource monitors that work across all topology types, allowing a single system to provide multiple functions and adapt to different operational requirements without requiring separate systems for each topology.
3Adaptability or versatility
If dynamic reconfiguration is implemented to adapt to runtime resource changes, then adaptability is improved, but system complexity and overhead increase
Solution Approach 1:
The patent implements feedback mechanisms through runtime resource monitors that continuously track resource availability and performance metrics. This feedback is used by configurable topology selectors to determine when and how to switch between topologies. The feedback loop enables adaptive reconfiguration based on actual system state while maintaining controlled complexity through threshold-based decision-making and predefined topology options.
Data Source
AI summary
Decentralized orchestration of composite services results in a number of flow topologies which differ in their messaging patterns and the distribution of flow code amongst different partitions of a topology. Different performance metrics result for different topologies, and this is governed by the availability of resources, such as CPU cycles, memory, network bandwidth, and so on. A performance model is used to evaluate the performance of different topologies based on availability of resources, and dynamically direct client requests between different topologies according to prevailing conditions.