Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Distributed systems generate a large amount of monitoring data such as log files to track their operational status. Hover, it is hard to correlate such monitoring data effectively across distributed systems and along observation time for system management. In previous work,  proposed a concept named flow intensity to measure the intensity with which internal monitoring data reacts to the volume of user requests.  calculated flow intensity measurements from monitoring data and proposed an algorithm to automatically search constant relationships beten flow intensities measured at various points across distributed systems. If such relationships hold all the time,  regard them as invariants of the underlying systems. Invariants can be used to characterize complex systems and support various system management tasks. Hover, the computational complexity of the previous invariant search algorithm is high so that it may not scale ll in large systems with thousands of measurements. ,  propose two efficient but approximate algorithms for inferring invariants in large-scale systems. The computational complexity of new randomized algorithms is significantly reduced, and experimental results from a real system are also included to demonstrate the accuracy and efficiency of our new algorithms.
['Guofei Jiang', 'Haifeng Chen', 'Kenji Yoshihira']
I am writing a research paper on a idea Efficient and Scalable Algorithms for Inferring Likely Invariants in Distributed Systems
[{"from": "human", "value": "I am writing a research paper on a idea Efficient and Scalable Algorithms for Inferring Likely Invariants in Distributed Systems"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Distributed systems generate a large amount of monitoring data such as log files to track their operational status. Hover, it is hard to correlate such monitoring data effectively across distributed systems and along observation time for system management. In previous work,  proposed a concept named flow intensity to measure the intensity with which internal monitoring data reacts to the volume of user requests.  calculated flow intensity measurements from monitoring data and proposed an algorithm to automatically search constant relationships beten flow intensities measured at various points across distributed systems. If such relationships hold all the time,  regard them as invariants of the underlying systems. Invariants can be used to characterize complex systems and support various system management tasks. Hover, the computational complexity of the previous invariant search algorithm is high so that it may not scale ll in large systems with thousands of measurements. ,  propose two efficient but approximate algorithms for inferring invariants in large-scale systems. The computational complexity of new randomized algorithms is significantly reduced, and experimental results from a real system are also included to demonstrate the accuracy and efficiency of our new algorithms."}]