Real-world execution traces record performance problems that are likely perceived at deployment sites. However, those problems can be rooted subtly and deeply into system layers or other components far from the place where delays are initially observed. To tackle challenges of identifying deeply rooted problems, we propose a new trace-based approach consisting of two steps: impact analysis and causality analysis. The impact analysis measures performance impacts on a component basis, and the causality analysis discovers patterns of runtime behaviors that are likely to cause the measured impacts. The discovered patterns can help performance analysts quickly identify root causes of perceived performance problems. We instantiate our approach to study the performance of device drivers on over 19,500 real-world execution traces. The impact analysis shows that device drivers constitute a non-trivial part (≈ 38%) in the overall system performance, and a big part (≈ 26%) is due to interactions between drivers. The causality analysis effectively discovers highly suspicious and high-impact behavioral patterns in device drivers, examined and confirmed by our automated evaluation, developers, and performance analysts.

Description It was difficult to make a device driven system. Dataset is not available in the web. That’s why I make dataset for this implementation. My solution make a best shortest outcome based on the request. If I want to implement in this system in the device, then it will give some shortest process flow. But the main constrain is I can’t test it on the device. But it will give a shortest process flow. Signature and components define from myself in the dataset.

Limitations No signature is implemented in the system. Signature will be defining myself in the dataset. No practical implementation is here. No device is attached with the system. So dataset created in the file and test the system.

Run this system First make the dataset in the same folder. Then run the program and run the dataset. Step-1: open code blocks Step-2: open implementation Step-3: Open a text file name input and copy the dataset. Step-4: Then run implementation

Dataset Format Dataset created manually. No dataset found in the web or any other source. Though it is device related that’s why I make a dataset manually.

//number of task 6 switch on data connection on browse browser browse mail browse facebook send mail //number of dependency 7 //dependency: first one is dependent on second one. data connection on switch on browse browser switch on browse mail browse browser send mail browse mail browse facebook browse browser browse facebook data connection on browse mail data connection on //number of similarity and they are (For each node): 1 browse browser browse mail

//destination send mail

Reference Xiao Yu, Shi Han, Dongmei Zhang, and Tao Xie. 2014. Comprehending performance from real-world execution traces: a device-driver case. In Proceedings of the 19th international conference on Architectural support for programming languages and operating systems (ASPLOS '14). ACM, New York, NY, USA, 193-206. DOI: http://dx.doi.org/10.1145/2541940.2541968