Distributed Agent Hierarchy for Cloud Service Placement
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Solution Overview
Problem
Current techniques for network-aware service placement in cloud computing systems face scalability issues and require accurate, real-time network topology and resource information, which is impractical due to the complexity and variability of cloud networks, leading to inefficiencies and overprovisioning.
Innovation Solution
A decentralized service placement system using a hierarchy of agents that identifies network-optimal placements without relying on centralized resource availability or real-time network information, by receiving solution encodings from intermediate agents and generating cover sets to minimize network traffic and optimize resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If centralized monitoring tools are used to collect real-time network information, then service placement accuracy is improved, but network overhead and memory overhead increase significantly
Solution Approach 1:
The patent extracts the network monitoring function from a centralized tool and distributes it to individual agents running on each server. Each agent locally collects network information and solution encodings, eliminating the need for a centralized monitoring infrastructure and reducing network overhead while maintaining information accuracy.
Solution Approach 2:
The patent introduces solution encodings as an intermediary representation that captures network topology and resource information in a compact form. These encodings are exchanged between agents during the placement process, allowing accurate network-aware decisions without requiring continuous real-time network data collection.
2Reliability
If subgraph matching algorithms are used for service placement, then network efficiency is improved, but scalability to cloud-size graphs deteriorates
Solution Approach 1:
The patent segments the service placement problem into smaller sub-problems by dividing the cloud infrastructure into multiple partitions. Each agent handles placement decisions for its local partition using simplified algorithms, avoiding the need to process the entire cloud graph at once. This enables scalable service placement across cloud-size graphs while maintaining network efficiency.
3Adaptability or versatility
If frequent updates of cloud network information are performed, then service placement optimality is improved, but system overhead increases
Solution Approach 1:
The patent implements a dynamic service placement system where agents continuously update their solution encodings based on changing network conditions and resource availability. The system adapts to dynamic cloud environments by allowing agents to re-evaluate and update placements incrementally rather than requiring frequent complete re-optimizations, reducing system overhead while maintaining optimality.
Data Source
AI summary
Exemplary methods for distributed multi-component network-aware service placement in a resource pool include utilizing a hierarchy of agents associated with computing resources of a cloud architecture. An agent in the hierarchy can merge solution encodings to find cover sets indicating feasible placement solutions that can cover an entire application placement request. The agent can partition the components across its children nodes such that global network traffic is minimized. An application graph is generated with components as vertices and edges indicating connections between the components and having associated weights indicating a data transfer rate between the components. The edges can be sorted, and each cover set can be processed by repeatedly assigning unassigned pairs of components having higher data transfer rates to a common assignment set. If multiple placement solutions are found, determined placement costs for each can be used to identify the preferred placement.