The LEGaTO project leverages task-based programming models to provide a software ecosystem for Made in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC, balanced with the security and resilience challenges. LEGaTO is an ongoing three-year EU H2020 project started in December 2017.
Summary
Due to the variety in available cloud providers along with the frequent changes in strategic objectives of an enterprise, migrating existing software components to the cloud has become a challenging decision in the software maintenance phase. “Financial” and “customer satisfaction” viewpoints are two important strategic objectives of all enterprises that greatly affect the decision about migration to the cloud. Moreover immense number of target cloud services with too many configurations and cost models has made the search space of possible migrations huge. Many existing approaches of software migration to the cloud have modeled the problem as deployment optimization of software components over available platforms, while in this research following a valid migration plan is intended rather than proposing a final optimal migration solution (deployment). A migration plan is a sequence of actions to be taken by the technical team to move the software components to the cloud stepwise. Since at each stage of the migration there might be many valid alternative paths to follow, a recommender module is proposed to direct the management by recommending the best migration plan out of all valid plans in a Labeled Transition System. The recommendation is based on the current state of the enterprise which is estimated using a two‐state Hidden Markovian Model by observing ambient signals. The empirical study showed that particularly in dynamic and changing conditions the proposed adaptive and plan‐oriented method succeeded in posing lower accrued maintenance costs on the enterprise over time with confidence 90% compared to the non‐adaptive method due to its reactive and self‐balancing nature.
Summary
Replacing existing software/hardware components with their equivalent cloud services is an important decision faced by IT managers in today's enterprises. A variety of possible migration targets and cloud services with too many configurations and cost models, disparate and changing strategic objectives of the enterprise management that triggers the migration process, and the complex structure of the legacy applications make software migration to the cloud a challenging issue. In contrast to the existing approaches that model the migration process as an optimization problem to find the optimal deployment of software components on cloud services without presenting a practical migration plan, in this paper, a plan‐oriented migration approach is proposed by which the enterprise management is able to follow migration steps of a valid plan. All valid plans are modeled using a labeled transition system, and a recommender engine directs the management through the possible migration paths using predefined fitness functions. It was observed that, particularly in dynamic and changing conditions that a flexible migration plan is essential, the proposed plan‐oriented method is very much effective in satisfying the enterprise strategic objectives. Evaluations have been performed using two quality indicators: total cost of ownership and scalability index.
The LEGaTO project leverages task-based programming models to provide a software ecosystem for Made in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC, balanced with the security and resilience challenges. LEGaTO is an ongoing three-year EU H2020 project started in December 2017.
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