Distributed Memory Pool Aggregation for High-Load Applications
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Solution Overview
Problem
In distributed environments, existing memory management systems are limited by the physical memory of individual servers, making it difficult to execute memory-intensive tasks efficiently across multiple interconnected systems.
Innovation Solution
The system aggregates physical memories of multiple devices to create a centralized memory pool, using semaphores and mutex APIs to manage access and execution, allowing for efficient distribution and parallel processing of tasks across the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If tasks are split into sub-tasks and assigned to multiple systems for execution, then processing capability is improved, but memory availability remains limited by individual server physical memory
Solution Approach 1:
The patent merges physical memory resources from multiple distributed servers into a unified memory pool that can be shared across all systems in the network. This allows memory-intensive tasks to utilize aggregate memory capacity rather than being constrained by individual server memory limits, directly resolving the contradiction between improved processing capability and limited memory availability.
2Power
If multiple servers are used to process huge amount of data, then processing power is improved, but memory management complexity increases
Solution Approach 1:
The patent introduces a memory management intermediary layer that sits between the distributed servers and the applications. This intermediary manages memory allocation, aggregation, and access control across the network, simplifying memory management for individual servers while enabling coordinated use of aggregate memory resources across the distributed system.
3Device complexity
If physical memory of individual servers is used, then system simplicity is maintained, but ability to execute memory-intensive tasks is limited
Solution Approach 1:
The patent creates a universal memory pool that serves multiple functions: it can be dynamically allocated to different applications, scaled by adding or removing servers, and accessed by multiple systems simultaneously. This universal memory infrastructure enables the distributed system to execute memory-intensive tasks while maintaining relative system simplicity through standardized memory access protocols.
Data Source
AI summary
Systems and methods for performing memory management among a plurality of devices in a network are described. In one implementation, the method for performing memory management comprises obtaining memory requirements for execution of an application. The memory requirements indicate memory space needed for executing the application. Further, the method comprises creating at least one memory pool, based on the memory requirements, by aggregating physical memories of the plurality of devices. Further, the method comprises executing the application in the at least one memory pool using semaphores and a mutex application programming interface (API).