In Model-Driven Engineering (MDE) adequate means for collaborative modeling among multiple team members is crucial for large projects. To this end, several approaches exist to identify the operations applied in parallel, to detect conflicts among them, as well as to construct a merged model by incorporating all nonconflicting operations. Conflicts often denote situations where the application of one operation disables the applicability of another operation. Whether one operation disables the other, however, often depends on their application order. To obtain a merged model that maximizes the combined effect of all parallel operations, we propose an automated approach for finding the optimal merging sequence that maximizes the number of successfully applied operations. Therefore, we adapted and used a heuristic search algorithm to explore the huge search space of all possible operation sequences. The validation results on merging various versions of real-world models confirm that our approach finds operation sequences that successfully incorporate a high number of conflicting operations, which are otherwise not reflected in the merge by current approaches.
Mobile Network Operators (MNO) are nowadays facing an exponential growth in their network traffic, as more and more customers are having access to affordable new technologies using smarter and data-based equipments. As new strategies have to be developed and implemented in order to meet those demands in a cost efficient way, the offloading one, with using an alternative network to the macrocell cell network, has been under ongoing discussions and studies. More specifically, the femtocell offloading alternative has been pointed out as a potential cost effective solution regarding many advantageous specificities related to this technology like the the small size and ease of installation, making it easier to deploy than the macro one. In this paper, we will assess the relative costs benefits resulting from deploying the femtocell network, using the Total Cost of Ownership (TCO) as an economical method to have more accurate and up-to-date results regarding those potential benefits. Cost analysis will be performed based on our base case scenario, and discussions on possible future extensions of this work are presented.
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