The ALMA Common Software (ACS), provides the infrastructure of the distributed software system of ALMA and other projects. ACS, built on top of CORBA and Data Distribution Service (DDS) middleware, is based on a Component- Container paradigm and hides the complexity of the middleware allowing the developer to focus on domain specific issues. The transition of the ALMA observatory from construction to operations brings with it that ACS effort focuses primarily on scalability, stability and robustness rather than on new features. The transition came together with a shorter release cycle and a more extensive testing. For scalability, the most problematic area has been the CORBA notification service, used to implement the publisher subscriber pattern because of the asynchronous nature of the paradigm: a lot of effort has been spent to improve its stability and recovery from run time errors. The original bulk data mechanism, implemented using the CORBA Audio/Video Streaming Service, showed its limitations and has been replaced with a more performant and scalable DDS implementation. Operational needs showed soon the difference between releases cycles for Online software (i.e. used during observations) and Offline software, which requires much more frequent releases. This paper attempts to describe the impact the transition from construction to operations had on ACS, the solution adopted so far and a look into future evolution.
The Cherenkov Telescope Array (CTA) project will be the next generation ground-based very high energy gamma-ray instrument. The success of the precursor projects (i.e., HESS, MAGIC, VERITAS) motivated the construction of this large infrastructure that is included in the roadmap of the ESFRI projects since 2008. CTA is planned to start the construction phase in 2015 and will consist of two arrays of Cherenkov telescopes operated as a proposal-driven open observatory. Two sites are foreseen at the southern and northern hemispheres. The CTA observatory will handle several observation modes and will have to operate tens of telescopes with a highly efficient and reliable control. Thus, the CTA planning tool is a key element in the control layer for the optimization of the observatory time. The main purpose of the scheduler for CTA is the allocation of multiple tasks to one single array or to multiple sub-arrays of telescopes, while maximizing the scientific return of the facility and minimizing the operational costs. The scheduler considers long- and short-term varying conditions to optimize the prioritization of tasks. A short-term scheduler provides the system with the capability to adapt, in almost real-time, the selected task to the varying execution constraints (i.e., Targets of Opportunity, health or status of the system components, environment conditions). The scheduling procedure ensures that long-term planning decisions are correctly transferred to the short-term prioritization process for a suitable selection of the next task to execute on the array. In this contribution we present the constraints to CTA task scheduling that helped classifying it as a Flexible Job-Shop Problem case and finding its optimal solution based on Artificial Intelligence techniques. We describe the scheduler prototype that uses a Guarded Discrete Stochastic Neural Network (GDSN), for an easy representation of the possible long- and short-term planning solutions, and Constraint Propagation techniques. A simulation platform, an analysis tool and different test case scenarios for CTA were developed to test the performance of the scheduler and are also described.
The main task of a scheduler applied to astronomical observatories is the time optimization and the maximization of the scientific return. Scheduling of observations is an example of the classical task allocation problem known as the job-shop problem (JSP) or the flexible-JSP (fJSP). In most cases various mathematical algorithms are usually considered to solve the planning system. We present an analysis of the task allocation problem and the solutions currently in use at different astronomical facilities. We also describe the schedulers for three different projects (TJO, CARMENES and CTA) where the conclusions of this analysis are applied in their development.