Adaptive Bloom Filter for 5G Memory Access Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
5G networks require efficient data access algorithms to reduce unnecessary memory operations, such as search time and memory accesses, to enhance system speed and capacity, as they consume resources like time, bandwidth, and power.
Innovation Solution
The implementation of an adaptive Bloom filter that limits unnecessary memory accesses by reducing the false positive rate and key size, utilizing hashing functions to generate keys and compare them with a filter, allowing for efficient data retrieval and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a traditional Bloom filter is used for data access, then memory access efficiency is improved, but the false positive rate increases leading to unnecessary memory accesses
Solution Approach 1:
The patent implements an adaptive Bloom filter that dynamically adjusts the number of hash functions and key length based on the current state of the filter and query patterns. This dynamic adaptation allows the system to optimize between false positive rate and memory access efficiency in real-time, resolving the contradiction by making the filter parameters flexible rather than fixed
Solution Approach 2:
The system changes key parameters (number of hash functions, key length) based on operational conditions and performance metrics. By adjusting these parameters dynamically, the system can reduce false positives when necessary while maintaining high memory access efficiency, thus resolving the contradiction between reliability and productivity
2Reliability
If key length is increased to reduce false positives, then reliability is improved, but search time and processing overhead increase
Solution Approach 1:
The patent makes key length a dynamic parameter that adjusts based on the false positive rate target and current filter state. When lower false positive rates are required, the key length increases; when speed is prioritized, key length decreases. This dynamic adjustment resolves the contradiction between reliability and time loss
Solution Approach 2:
The system actively changes the key length parameter based on performance requirements and operational context. This parameter adaptation allows the system to optimize the trade-off between reducing false positives and minimizing search time, resolving the contradiction by making key length flexible rather than fixed
3Reliability
If the Bloom filter size is increased to reduce false positives, then reliability is improved, but storage space consumption increases
Solution Approach 1:
The patent changes the effective filter capacity by adjusting key length and number of hash functions rather than simply increasing filter size. This allows the system to achieve lower false positive rates through parameter optimization while maintaining efficient storage utilization, resolving the contradiction between reliability and quantity of substance
Data Source
AI summary
A system described herein may use a Bloom filter to reduce unnecessary accesses to memory. The filter may provide constant search time through hashing and use a relatively small amount of space. The filter may utilize hashing functions to generate a key associated with each data item of a set of data items, where the bit length of the key may be calibrated and tuned for selection of a minimum key length (in number of bits) versus a desired false positive rate. Such keys may be combined to form the filter. The resulting filter may be compared to various request keys that are generated using the same hashing functions in order to determine whether a requested item is present in the associated memory. The keys may be compared to the filter by comparing each bit in the key to each bit of the filter at the same location.