SDSU Research Foundation

Dynamic Adaptive Scheduling in Nanosatellite Constellation Networks – Engineering Support (56-7004 )

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Dept/Proj Name


The purpose of this task is to create distributed optimization algorithms for coordinated scheduling of nanosat (small satellites) and ground node communications. A need for the services of university students to provide technical and/or analytical support in the fields of Computer Engineering or Mechanical Engineering for the Dynamic Adaptive Scheduling in Nanosatellite Constellation Networks project


Interest in low-cost miniaturized simple satellites (nanosats) is rapidly growing as they are expected to find applications in a wide range of defense and commercial applications.  The technological maturity of low-cost nanosats is driving the demonstration of complex space missions.  Although much cheaper and faster to build and launch compared with traditional large complex satellites, these nanosats are not without their challenges. They are intended to work in low earth orbit (LEO) which limits the visibility or access time of a nanosat with a given ground node from approximately ten minutes in the best case to no coverage at all for most of the 16 daily orbits.  The limited availability of ground nodes restricts the contact opportunities with nanosats for centralized planning and coordination of data transmission.  In addition, their size and energy limitations impose restrictions in transferring a large amount of data.  All of these challenges combined with the desire for rapid revisit rates from LEO satellites are driving the development of large constellations with more than 100 small satellites.  Autonomous network management is thus of utmost importance in order to achieve operational efficiency and affordability.  Scheduling at-ground nodes as well as nanosats is an important part of the network management.  The purpose of this project is to create distributed optimization algorithms for coordinated scheduling of nanosat and ground node communications.


  • Reviewing, analyzing and documenting specific operational procedures, and/or performing feasibility studies for nanosatellite constellation networks.
  • Performing literature searches and reviews; compiling and cataloging background material; and/or preparing summaries and bibliographies for the Dynamic Adaptive Scheduling in Nanosatellite Constellation Networks project.  This information will help communication mission planning scenarios that could be run on the computer.
  • Assisting in algorithm development for distributed optimization for coordinated scheduling of nanosat and ground node communications, prototype algorithm implementation, testing and documentation.
  • Designing and testing models utilizing nanosatellites mission planning, simulation, numerical and statistical analyses techniques
  • Creating Master Thesis on nanosatellite constellation network


Minimum Qualification:


Graduate Level 2: Working on a Masters or PhD majoring in Computer Engineering or Mechnical Engineering.


Required Course Work:


Introduction to optimization, Linear programming, Stochastic processes, Industrial and operation modeling or Robotics, Machine learning, Computer Programming, Automation.


Skills Desired:  MATLAB, R, Scheduling, Modeling and simulation.




This is a student position and is limited to working 20 hours per week
This position will remain open until filled
San Diego State University Research Foundation is an EEO/AA/Disability/Vets Employer


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