Abstract
The rise of NewSpace provides a platform for small and medium businesses to commercially launch and operate satellites in space. In contrast to traditional satellites, NewSpace provides the opportunity for delivering computing platforms in space. However, computational resources within space are usually expensive and satellites may not be able to compute all computational tasks locally. Computation offloading (CO), a popular practice in Edge/Fog computing, could prove effective in saving energy and time in this resource-limited space ecosystem. However, CO alters the threat and risk profile of the system. In this article, we analyze security issues in space systems and propose a security-aware algorithm for CO. Our method is based on the reinforcement learning technique, deep deterministic policy gradient (DDPG). We show, using Monte-Carlo simulations, that our algorithm is effective under a variety of environment and network conditions and provide novel insights into the challenge of optimized location of computation.
| Original language | English |
|---|---|
| Article number | 9651535 |
| Pages (from-to) | 12351-12363 |
| Number of pages | 13 |
| Journal | IEEE Internet of Things Journal |
| Volume | 9 |
| Issue number | 14 |
| Early online date | 15 Dec 2021 |
| DOIs | |
| Publication status | Published - 15 Jul 2022 |
| Externally published | Yes |
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Keywords
- Satellites
- Space vehicles
- Earth
- Security
- Planetary orbits
- Sensors
- Encryption