---
description: Bottleneck research found
---

# Literature review

### [Bottleneck Characterization of Dynamic Web Site Benchmarks](https://scholarship.rice.edu/bitstream/handle/1911/96296/TR02-391.pdf?sequence=1\&isAllowed=y)       (2002. Rice University Computer Science)

A performance evaluation of these benchmarks on commodity hardware identified bottleneck resources for each case.

* The online bookstore's bottleneck was the <mark style="background-color:orange;">database CPU</mark>
* front-end and the back-end a bottleneck. <mark style="color:orange;">With amounts of memory common by today’s standards</mark>, neither the main memory nor the disk proved to be a limiting factor in terms of performance for any of the benchmarks.

### [Measuring bottleneck link speed in packet-switched networks](https://reader.elsevier.com/reader/sd/pii/S0166531696900322?token=5E0B56BDEB848904778746A4A399472DAA413A0256147BBAB6622D552558242D52A373FCB70E3B159ACDFB8E803B22EB\&originRegion=eu-west-1\&originCreation=20230507211051) (2004.Computer Science Department, Boston University)

* For document transfer applications like <mark style="color:orange;">FTP, Gopher, and the World Wide Web, transfer time is directly related to available bandwidth</mark>. This depends on the path capacity between client and server and the competing traffic on that path. <mark style="background-color:orange;">If applications had access to these measurements, they could calculate path utilization and select the best path or server to reduce response time</mark>. This dynamic server selection would be particularly useful in mobile computing environments with frequently changing server availability.

### [Bottleneck Identification and Performance Modeling of OPC UA Communication Models](https://dl.acm.org/doi/abs/10.1145/3297663.3309670) (2019. ACM/SPEC International Conference on Performance Engineering)

* performance measurements with OPC UA client/server and pub/sub communication and created a CPU utilization prediction model based on linear regression that can be used to size hardware environments. We found that the <mark style="background-color:orange;">server CPU is the main bottleneck for OPC UA pub/sub communication</mark>, but allows a throughput of up to 40,000 signals per second on a Raspberry Pi Zero. We also found that the client/server session management <mark style="color:orange;">overhead can severely impact performance, if more than 20 clients access a single server.</mark>

<div align="right"><figure><img src="https://970977003-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F9CSfXent0d8AWRVxR166%2Fuploads%2FBBj0LvidSV1Ewk0h5QQ7%2Fmodel.PNG?alt=media&#x26;token=0a6b13eb-5b3e-409f-bce5-daafe5776dab" alt="Modeling of OPC UA " width="339"><figcaption><p>ref: <a href="https://dl.acm.org/doi/abs/10.1145/3297663.3309670">https://dl.acm.org/doi/abs/10.1145/3297663.3309670</a></p></figcaption></figure></div>

&#x20;

