Scalable Stateless Process Network for Statistics Collection
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Solution Overview
Problem
As communications networks grow, the scalability and performance issues lead to delays in statistics data availability due to increased load on data collectors, especially when new network elements are added, causing inefficiencies in data processing and storage.
Innovation Solution
Implementing scalable stateless processes that dynamically add or remove processing power and using a uniquely partitioned database to efficiently store and manage statistics data, allowing for real-time collection and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If network capacity is increased by adding more network elements, then network performance is improved, but statistics collection delay increases
Solution Approach 1:
The patent divides the monolithic statistics collection system into multiple independent, stateless collector processes that can operate in parallel. Each collector handles a subset of network elements, allowing the system to scale horizontally by adding more collectors as the network grows, thereby maintaining timely statistics collection despite increased network capacity
Solution Approach 2:
The system dynamically adjusts the number of stateless collector processes based on network size and load conditions. When network capacity increases, additional collectors are spawned to maintain processing throughput, ensuring that statistics collection delay does not increase even as network performance improves
2Ease of manufacture
If traditional statistics collection methods are used, then implementation simplicity is maintained, but scalability deteriorates
Solution Approach 1:
The stateless collector processes are designed with a universal interface and standardized data collection logic that can handle any network element type. This allows the same simple collector template to be replicated and scaled across diverse network elements, maintaining implementation simplicity while achieving high scalability
Solution Approach 2:
Instead of creating complex, customized collection logic for each network element, the system uses copyable, stateless collector processes that can be instantiated multiple times. Each collector is a self-contained unit that can be replicated to handle additional network elements, simplifying implementation while enabling easy scaling
3Loss of time
If more processing power is allocated to statistics collection, then data availability timeliness is improved, but system complexity increases
Solution Approach 1:
The system uses lightweight, stateless collector processes that can be rapidly created and destroyed. These temporary, disposable processes provide the necessary processing power for statistics collection without requiring permanent, complex infrastructure. Each collector handles its tasks and terminates, allowing the system to scale processing capacity on-demand without increasing long-term system complexity
Data Source
AI summary
A method and apparatus for collecting statistics data over a communications network using scalable stateless processes are disclosed. A process capable of obtaining statistics data, in one embodiment, detects a delay associated with the availability of statistics data in accordance with predefined lag duration, and subsequently, adds one or more stateless processes to a pool of stateless processes to increase capacity of collecting statistics data. Upon enabling a stateless process to collect statistics data from network element (“NE”) in response to a statistics collecting tasks, the statistics data is stored in a database.