Abstract

Mechanisms that reduce the capital and operational costs are important for increased participation in astronomy. It is important that capital constrained organizations can engage in astronomy in cost effective manner. Approaches such as telescope conversion and using small satellites reduce the cost of astronomy observations. However, astronomy data observed by converted and small satellite telescopes require storage and processing by high performance computing infrastructure. High performance computing infrastructure acquisition is expensive for capital constrained astronomy organizations. The reduction in costs obtained by using converted and small satellite telescopes is not matched by a corresponding reduction in high performance computing. This paper addresses this challenge and proposes using a software defined space data storage system. The software defined space data storage system considers space telescopes as primary satellites and telecommunication and earth observation satellites as secondary satellites. The primary and secondary satellites are grouped in logical clusters. Secondary satellites are temporal data centers that store the astronomy data that cannot be held on primary satellites. The discussion in this paper presents algorithms that enable the identification of suitable secondary satellites and also influence the entry and exit of secondary satellite into dynamic clusters.

Keywords

Dynamic data storage, Space, Astronomy, Satellites, Duration, Capital constrained astronomy organisations, Dynamic clusters, Infrastructures, Powering and cooling, Radio astronomy, Telescope arrays, Low cost small satellites, Astronomy observations, Network architecture, Serendipitous discovery