## 4 Advantages entailed by the proposed Approach and Architecture
### Advantages related to flexibility  
1. Thanks to the fact that the Cognitive Managers have the same architecture and work according to the same approach regardless of the underlying/overlying layers, _interoperation procedures among heterogeneous access networks become easier and more natural._
2. The transparency of the proposed Cognitive Middleware layer allows a simple insertion of this layer in any fixed/mobile network entity (e.g. Mobile Terminals, Base Station, Backhaul network entities, Core network entities): _the most appropriate network entities for hosting the Cognitive Managers can be selected case by case._
3. The middleware nature of the Cognitive Managers allows to add/upgrade/delete Cognitive Manager functionalities (and, in particular, the thinking module software) _via Software Defined Radio (SDR) -like techniques._
4. _The thinking modules can be enabled or disabled depending on whether the relevant control tasks are or are not accomplished in an unsatisfactory way by the underlying/overlying layer. So, for instance, a given thinking module can be enabled in order to enhance unsatisfactory performance of a given access network, whilst already existing control functionalities of the underlying access networks can be used (if already satisfactory) in other cases. For an other instance, a given thinking module can be enabled to discover and aggregate contents coming from heterogeneous networks only if the overlying content management architecture does not perform such discovery/aggregation in a satisfactory way._
5. _The aggregated information which form the Present Context serving as key inputs for the thinking modules can be dynamically selected. So, in order to avoid to overwhelm the networks with useless (or scarcely useful) information and taking into account the variability of sensing/actuation functionalities, just a proper dynamically selected subset of the overall potential information will form the Present Context (i.e., will serve as inputs for the thinking modules), namely the one which is considered as a valuable input for the thinking modules._* In a given thinking module in charge of performing a given control task, several algorithms can be simultaneously present for performing the same task in question, but requiring different kinds of sensing functionalities (e.g., the input information can range from no information available, to complete multi-layer, multi-network information) and/or different kinds of actuation functionalities: a dynamic selection of the algorithms which are most suitable is performed. In general, the more advanced are the available sensing and actuation functionalities, the more efficient the thinking algorithms can be. In other words, this issue, considered together with issues (8) and (9) entails that the proposed architecture is able to self-adapt to very different situations concerning the surrounding environment. * Thanks to its transport/content/service independence and to the flexibility degrees offered by issues (7)...(10), the Cognitive Managers could have the same architecture regardless of the underlying/overlying layers, _i.e._, of the specificity of the interfaced transport and content/service layers. * The above-mentioned flexibility issues favors a _smooth migration_ towards the Cognitive Middleware approach. As a matter of fact, it is expected that sensing/actuation functionalities will be gradually inserted in the networks starting from the most critical nodes, that Cognitive Manager functionalities will be consequently embedded in selected network entities and that control functionalities will be gradually delegated to the Cognitive Modules.