**Acknowledgements**

Besides, the memory used by the optimized system was lower: the memory use per process in the nonoptimized system can be seen in **Figure 9**, while the memory used in the optimized

These results obtained with the EOD pilot can be related with the new paradigms of the Earth Observation market stated in [1]. **Table 4** describes how an approach of a PDGS system simi-

In this work, the successful implementation of the EOD pilot in an experimental cloud infrastructure with the middleware ENTICE was demonstrated. The pilot was tested and

Costs optimization Cost reduction by means of reduced storage of optimized VMIs, reduced creation time, reduced delivery time and reduced deployment time

Vertical integration Global distributed infrastructure connecting all the stakeholders in an operational

Scalability Elastically autoscale applications on cloud resources based on their fluctuating

Ground stations, ground control centers and data processing centers would take advantage of a rapid, agile, resilient and secure interconnected computer system in cloud

load with optimized VM interoperability across cloud infrastructures and without

lar to the EOD pilot could cover the main requirements of the new EO market.

system can be seen in **Figure 10**.

188 Multi-purposeful Application of Geospatial Data

**5. Conclusions and future work**

**Table 4.** New paradigm requirements vs. EOD pilot approach.

**Figure 10.** Memory use per process in the optimized EOD system.

environment

provider lock-in

**New paradigm requirements EOD pilot**

Multi sensors ground processing systems

This work has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 644179.
