FCPP oldnbr case study

Implementation in FCPP of the oldnbr-evaluation case study presented in the paper An Enhanced Exchange Operator for XC, submitted to the COORDINATION 2024 event. All commands below are assumed to be issued from the cloned git repository folder. For any issues, please contact Giorgio Audrito.

References

• FCPP main website: https://fcpp.github.io.
• FCPP documentation: http://fcpp-doc.surge.sh.
• FCPP presentation paper: http://giorgio.audrito.info/static/fcpp.pdf.
• FCPP sources: https://github.com/fcpp/fcpp.

Setup

The next sections contain the setup instructions for the various supported OSs. Jump to the section dedicated to your system of choice and ignore the others.

Windows

Pre-requisites:

• MSYS2
• Asymptote (for building the plots)

At this point, run "MSYS2 MinGW x64" from the start menu; a terminal will appear. Run the following commands:

pacman -Syu

After updating packages, the terminal will close. Open it again, and then type:

pacman -Sy --noconfirm --needed base-devel mingw-w64-x86_64-toolchain mingw-w64-x86_64-cmake mingw-w64-x86_64-make git

The build system should now be available from the "MSYS2 MinGW x64" terminal.

Linux

Pre-requisites:

• Xorg-dev package (X11)
• G++ 9 (or higher)
• CMake 3.18 (or higher)
• Asymptote (for building the plots)

To install these packages in Ubuntu, type the following command:

sudo apt-get install xorg-dev g++ cmake asymptote

In Fedora, the xorg-dev package is not available. Instead, install the packages:

libX11-devel libXinerama-devel.x86_6 libXcursor-devel.x86_64 libXi-devel.x86_64 libXrandr-devel.x86_64 mesa-libGL-devel.x86_64

MacOS

Pre-requisites:

• Xcode Command Line Tools
• CMake 3.18 (or higher)
• Asymptote (for building the plots)

To install them, assuming you have the brew package manager, type the following commands:

xcode-select --install
brew install cmake asymptote

Virtual Machines

If you use a VM with a graphical interface, refer to the section for the operating system installed on it.

Warning: the graphical simulations are based on OpenGL, and common Virtual Machine software (e.g., VirtualBox) has faulty support for OpenGL. If you rely on a virtual machine for graphical simulations, it might work provided that you select hardware virtualization (as opposed to software virtualization). However, it is recommended to use the native OS whenever possible.

Execution

The goal of this case study is to count the number of the battery-powered IoT devices in the network, in a scenario with unstable connections. Among the nodes, a single gateway node is connected to electric power, hence it is selected as the source node where the total number of nodes will be computed.

In order to run the case study, type the following command in a terminal:

./make.sh gui run -O [options] <target>

On newer Mac M1 computers, the -O argument may induce compilation errors: in that case, use the -O3 argument instead.

The target can either be:

• graphic, in order to run a single simulation with the graphical user interface (GUI), or
• batch, in order to execute a batch of 1000 simulations without GUI.

If you also provide options, they will be passed to the C++ compiler. Through options you can change the simulation scenario between two usecases:

• SMALL (10 nodes in a rectangle area of 150m by side);
• BIG (default, 100 nodes in a rectangle area of 150m by side).

In order to launch the SMALL usecase, add the option -DAP_USE_CASE=SMALL. The configuration can also be easily changed by editing file lib/case-study.hpp (rows 88-99), in order to try out different settings. The configuration parameters involved are:

• node_num: number of nodes spawned in the rectangle area;
• communication_range: distance between two nodes that allows their communication;
• area_side: dimension of the area where devices are deployed.

Running the make.sh command above, you should first see output about building the executables. Then, the graphical simulation should pop up (if using the graphic target) while the console will show the most recent stdout and stderr outputs of the application, together with resource usage statistics (both on RAM and CPU). During the execution, log files containing the standard input and output will be saved in the output/ repository sub-folder. For the batch target, individual simulation results will be logged in the output/raw/ subdirectory, with the overall resume in the output/ directory.

After the simulation end, PDF plots will be generated in the plot/ repository sub-folder. The metrics used in the plots to benchmark the algorithms, are:

• sacount: total number of nodes as computed by source node;
• aapnod: average of the partial collection result on each node;
• time: simulated time passed (rounds happen every 1 sec on average, with a 10% variance).

Graphical User Interface

Executing a graphical simulation will open a window displaying the simulation scenario, initially still: you can start running the simulation by pressing P (current simulated time is displayed in the bottom-left corner). While the simulation is running, network statistics will be periodically printed in the console. You can interact with the simulation through the following keys:

• Esc to end the simulation
• P to stop/resume
• O/I to speed-up/slow-down simulated time
• L to show/hide connection links between nodes
• G to show/hide the grid on the reference plane and node pins
• M enables/disables the marker for selecting nodes
• left-click on a selected node to open a window with node details
• C resets the camera to the starting position
• Q,W,E,A,S,D to move the simulation area along orthogonal axes
• right-click+mouse drag to rotate the camera
• mouse scroll for zooming in and out
• left-shift added to the camera commands above for precision control
• any other key will show/hide a legenda displaying this list

Hovering on a node will also display its UID in the top-left corner.