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Networking and edge
satellite-network
LEO satellite network routing
Starlink
System
Techniques · 4
Primitives · 20
satellite-network
Bipartite matching
graphs · medium: Maximum/weighted bipartite matching (Hopcroft-Karp, Hungarian) for assignment problems
Time varying topology routing
graphs · medium: Shortest paths on a graph whose links change predictably over time (contact plans)
Orbit propagation
numerics · medium: Propagate satellite orbits (Kepler, SGP4, numerical with perturbations) and frame transforms
Spherical harmonic transform
numerics · medium: Fast spherical harmonic transforms via FFT in longitude and Legendre in latitude
Dijkstra's algorithm
graphs · low: Single-source shortest paths with non-negative edge weights by settling vertices in order of distance with a priority queue.
›
BBR congestion control
networking · low: Model-based congestion control that paces at the measured bottleneck bandwidth and caps inflight near one BDP, instead of reacting to loss.
›
Beamforming
signal-processing · low: Phased-array weights that steer radio energy toward a receiver; per-client steering vectors
Forward error correction
signal-processing · low: Add redundancy (LDPC, Reed-Solomon, XOR parity) so receivers repair loss without retransmit
Handover management
signal-processing · low: Moving a session between cells/beams/satellites without dropping it
Tdma scheduling
signal-processing · low: Time-slot scheduling of shared radio links among users/beams
BFS and DFS
graphs · low: The two basic graph traversals; BFS gives hop distances and levels, DFS gives discovery/finish order for cycles, components and topological order.
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Max flow (Dinic)
graphs · low: Maximum s-t flow by BFS level graphs and blocking flows; also gives the min cut, bipartite matching and assignment with capacities.
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Interval tree
data-structures · low: Index of ranges that answers "which intervals overlap this point or range?" in O(log n + k); static sorted-array form is the compact, cache-friendly choice.
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Adaptive Runge-Kutta (Dormand-Princ…
numerics · low: An embedded 5(4) Runge-Kutta pair estimates each step's error for free and resizes the step to meet a tolerance; the default non-stiff solver.
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Rigid-body transforms (SE(3) poses)
robotics · low: Represent, compose, invert, integrate and interpolate 3D poses as unit quaternion plus translation, with exp/log maps for small motions and uncertainty.
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Calendar date arithmetic
systems · low: Civil dates, time zones (tzdb), DST gaps, month-end anchoring and duration math
Fast Fourier transform
numerics · low: Computes the DFT in O(n log n) by recursively splitting into even and odd halves; the basis of fast convolution and spectral methods.
›
Gaussian quadrature
numerics · low: Approximate an integral by a weighted sum of n function values at roots of orthogonal polynomials; exact for polynomials up to degree 2n-1.
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Spherical grids
numerics · low: Lat-lon, cubed-sphere and icosahedral grids for global models; pole and area issues
d-ary heap
data-structures · low: Array heap with d children per node (d = 4 typical): half the binary heap's depth, siblings in one cache line, faster priority queues.
›
+ 4 more primitives
System
Techniques · 4
Primitives · 20
satellite-network
Bipartite matching
graphs · medium: Maximum/weighted bipartite matching (Hopcroft-Karp, Hungarian) for assignment problems
Time varying topology routing
graphs · medium: Shortest paths on a graph whose links change predictably over time (contact plans)
Orbit propagation
numerics · medium: Propagate satellite orbits (Kepler, SGP4, numerical with perturbations) and frame transforms
Spherical harmonic transform
numerics · medium: Fast spherical harmonic transforms via FFT in longitude and Legendre in latitude
Dijkstra's algorithm
graphs · low: Single-source shortest paths with non-negative edge weights by settling vertices in order of distance with a priority queue.
›
BBR congestion control
networking · low: Model-based congestion control that paces at the measured bottleneck bandwidth and caps inflight near one BDP, instead of reacting to loss.
›
Beamforming
signal-processing · low: Phased-array weights that steer radio energy toward a receiver; per-client steering vectors
Forward error correction
signal-processing · low: Add redundancy (LDPC, Reed-Solomon, XOR parity) so receivers repair loss without retransmit
Handover management
signal-processing · low: Moving a session between cells/beams/satellites without dropping it
Tdma scheduling
signal-processing · low: Time-slot scheduling of shared radio links among users/beams
BFS and DFS
graphs · low: The two basic graph traversals; BFS gives hop distances and levels, DFS gives discovery/finish order for cycles, components and topological order.
›
Max flow (Dinic)
graphs · low: Maximum s-t flow by BFS level graphs and blocking flows; also gives the min cut, bipartite matching and assignment with capacities.
›
Interval tree
data-structures · low: Index of ranges that answers "which intervals overlap this point or range?" in O(log n + k); static sorted-array form is the compact, cache-friendly choice.
›
Adaptive Runge-Kutta (Dormand-Princ…
numerics · low: An embedded 5(4) Runge-Kutta pair estimates each step's error for free and resizes the step to meet a tolerance; the default non-stiff solver.
›
Rigid-body transforms (SE(3) poses)
robotics · low: Represent, compose, invert, integrate and interpolate 3D poses as unit quaternion plus translation, with exp/log maps for small motions and uncertainty.
›
Calendar date arithmetic
systems · low: Civil dates, time zones (tzdb), DST gaps, month-end anchoring and duration math
Fast Fourier transform
numerics · low: Computes the DFT in O(n log n) by recursively splitting into even and odd halves; the basis of fast convolution and spectral methods.
›
Gaussian quadrature
numerics · low: Approximate an integral by a weighted sum of n function values at roots of orthogonal polynomials; exact for polynomials up to degree 2n-1.
›
Spherical grids
numerics · low: Lat-lon, cubed-sphere and icosahedral grids for global models; pole and area issues
d-ary heap
data-structures · low: Array heap with d children per node (d = 4 typical): half the binary heap's depth, siblings in one cache line, faster priority queues.
›
Homogeneous transforms
geometry · low: 4x4 affine and projective matrices, homogeneous coordinates, view and projection, normal matrices
Quaternion rotations
geometry · low: Unit quaternions as 3D rotations: 4 floats, cheap composition, no gimbal lock, plus the conversions, interpolation choices and numerical care needed in practice.
›
Runge-Kutta 4
numerics · low: The classic four-stage, fourth-order ODE step; error drops 16× when the step halves, with no derivatives or past steps needed.
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Sparse matrices (CSR)
numerics · low: Compressed sparse row stores only nonzeros as row pointers, column indices and values; SpMV streams them once, so it is memory-bandwidth bound.
›
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