CoralReef is a comprehensive software suite developed by CAIDA for collecting and analyzing data from passive Internet traffic monitors in real time or from trace files. The package also includes programming APIs for C and Perl, and applications for capture, analysis, and Web report generation.
CBLM is a high performance latency (one-way and round-trip), packet loss, and jitter monitoring probe. When run on two or more servers, a full mesh of connections is automatically set up between the probes, between which UDP packets are transmitted. Statistics are collected and stored within a MySQL database.
CHIRP is a tool for automating the creation of configuration trees for Cricket. It supports a plugin architecture for adding drivers which produce Cricket configuration files and supports automatic detection of device types. When a network device is identified, CHIRP dynamically associates a driver with it to produce the configuration file.
CLIChart is intended for quick summarization and visualization of data, especially from system logs. It provides tools to extract and manipulate tabular summary data from text files, and to generate and view simple charts from tabular data on the command line. Charts can be displayed in a window and/or saved.
COSA and SRP are synchronous serial boards for ISA bus which have two channels. Each channel can be set up to one of the X.21, V.24, V.35 and V.36 hardware interfaces. The Linux kernel driver and user-space tools serve for setting up and using the COSA and SRP boards under Linux. It allows you to use it with the following link-level protocols: Cisco HDLC , synchronous PPP, or as the frame-based character device.
CRM114 is a Controllable Regex Mutilator and Smart Filter, designed for easy creation of filters for things like incoming email redirection, spam filtering, system logs, or monitoring processes. Filtering rules can be either hard-coded (such as regexes), soft-coded (calculated at runtime or read from an external file or process), or learned dynamically by phrase matching (as in Bayesian filtering, Markovian matching, Winnowing, or Hyperspatial classification). This makes it possible to create very accurate filters with very little actual work. Accuracies over 99.9% are achievable.