Gianluigi Morelli

On an Automated Translation of Satellite Procedures Using Triple Graph Grammars

Model transformation based on triple graph grammars (TGGs) is a general, intuitive and formally well defined technique for the translation of models [5,6,2]. While previous concepts and case studies were focused mainly on visual models of software and systems, this article describes an industrial application of model transformations based on TGGs as a powerful technique for software translation using the tool Henshin [1]. The general problem in this scenario is to translate source code that is currently in use into corresponding source code that shall run on a new system. Up to now, this problem was addressed based on manually written converters, parser generators, compiler-compilers or meta-programming environments using term rewriting or similar techniques (see e. g. [4]).

Triple Graph Grammars in the Large for Translating Satellite Procedures

Software translation is a challenging task. Several requirements are important – including automation of the execution, maintainability of the translation patterns, and, most importantly, reliability concerning the correctness of the translation. Triple graph grammars (TGGs) have shown to be an intuitive, welldefined technique for model translation. In this paper, we leverage TGGs for industry scale software translations. The approach is implemented using the Eclipse-based graph transformation tool Henshin and has been successfully applied in a large industrial project with the satellite operator SES on the translation of satellite control procedures. We evaluate the approach regarding requirements from the project and performance on a complete set of procedures of one satellite.

Minimising longest path length in communication satellite payloads via metaheuristics

The size and complexity of communication satellite payloads have been increasing very quickly over the last years and their configuration / reconfiguration have become very difficult problems. In this work, we propose to compare the efficiency of three well-known metaheuristic methods to solve an initial configuration problem, which objective is to minimise the length of the longest channel path. Experiments are conducted on real-world problem instances with realistic operational constraints (e.g., a maximum computation time of 10 minutes) and Wilcoxon test is used to determine with statistical confidence what technique is more suitable and what are its limitations. The results of this work will serve as an initial step in our research to design hybrid approaches to push even further the solving capabilities, i.e., tackling bigger payloads and more channels to activate.

Satellite payload reconfiguration optimisation: an ILP model

The increasing size and complexity of communication satellites has made the manual management of their payloads by engineers through computerised schematics difficult and error prone. This article proposes to optimise payload reconfigurations for current and next generation satellites using a novel Integer Linear Programming model (ILP), which is a variant of network flow models. Experimental results using CPLEX demonstrate the efficiency and scalability of the approach up to realistic satellite payloads sizes and configurations.

Hybridisation Schemes for Communication Satellite Payload Configuration Optimisation

The increasing complexity of current telecommunication satellite payloads has made their manual management a difficult and error prone task. As a consequence, efficient optimisation techniques are re- quired to help engineers to configure the payload. Recent works focusing on exact approaches faced scalability issues while metaheuristics provided unsatisfactory solution quality. This work therefore proposes three hybridisation schemes that combine both metaheuristics and an exact method. We focus on the initial configuration problem case and we consider as objective to minimise the length of the longest channel path. Experimental results on realistic payload sizes demonstrate the advantage of those approaches in terms of efficiency within a strict operational time constraint of ten minutes on a single CPU core.

Optimizing communication satellites payload configuration with exact approaches

The satellite communications market is competitive and rapidly evolving. The payload, which is in charge of applying frequency conversion and amplification to the signals received from Earth before their retransmission, is made of various components. These include reconfigurable switches that permit the re-routing of signals based on market demand or because of some hardware failure. In order to meet modern requirements, the size and the complexity of current communication payloads are increasing significantly. Consequently, the optimal payload configuration, which was previously done manually by the engineers with the use of computerized schematics, is now becoming a difficult and time consuming task. Efficient optimization techniques are therefore required to find the optimal set(s) of switch positions to optimize some operational objective(s). In order to tackle this challenging problem for the satellite industry, this work proposes two Integer Linear Programming (ILP) models. The first one is single-objective and focuses on the minimization of the length of the longest channel path, while the second one is bi-objective and additionally aims at minimizing the number of switch changes in the payload switch matrix. Experiments are conducted on a large set of instances of realistic payload sizes using the CPLEX® solver and two well-known exact multi-objective algorithms. Numerical results demonstrate the efficiency and limitations of the ILP approach on this real-world problem.

Automated Operations of Large GEO Telecom Satellites with Digital Transparent Processors (DTP): Challenges and Lessons Learned

The purpose of this paper is to outline the impact on satellite operations induced by the presence of digital routing technologies in the payl oad of telecommunication satellites. In particular, the cooperation between AIRBUS (the sate llite manufacturer) and SES (the satellite operator, acting as ground system integrator ), along with the key architectural decisions leading to the operational readiness of SES12 and SES-14 digital payload are described. The selected architecture, driven by impor tant operational requirements, allows to maintain efficient and safe operations, than ks to the use of SPELL automation. Several lessons learned are provided along with the co nclusions.

Multi-objective evolutionary approach for the satellite payload power optimization problem

Todays world is a vast network of global communications systems in which satellites provide high-performance and long distance communications. Satellites are able to forward signals after amplification to offer a high level of service to customers. These signals are composed of many different channel frequencies continuously carrying real-time data feeds. Nevertheless, the increasing demands of the market force satellite operators to develop efficient approaches to manage satellite configurations, in which power transmission is one crucial criterion. Not only the signal power sent to the satellite needs to be optimal to avoid large costs but also the power of the downlink signal has to be strong enough to ensure the quality of service. In this work, we tackle for the first time the bi-objective input/output power problem with multi-objective evolutionary algorithms to discover efficient solutions. A problem specific indirect encoding is proposed and the performance of three state-of-the-art multi-objective evolutionary algorithms, i.e. NSGA-II, SPEA2 and MOCell, is compared on real satellite payload instances.