## 1 Introduction
#### Some Examples to Illustrate PIN Functionality  
Three examples of specific problems are presented to illustrate the proposed PIN functionality. These scenarios are very different, and were deliberately selected to show the wide variety of possible applications for PIN. The first case is a deliberately simple scenario, with the intent of showing easily the possible application of network processing in the context of smart grids. In a power supply system for a city, data from individual consumption readings of each of the electricity meters are relevant for purposes such as billing (or perhaps attempting to learn what types of devices are connected to the network, to prevent inductive loads affecting the quality of the flow). If only the need to provide energy to a city is considered, the relevant figure is simply the total amount of energy that must be supplied. The traditional solution to this problem is to concentrate all readings in a central processor. The calculation is indeed very simple (most likely a simple sum), but the difficulty is in obtaining all of this information at the central server and possibly also in the size of the server, provided that it is capable of processing such a large volume of information. We might consider a second alternative, where instead of using a single central server, multiple servers are placed on a smaller scale with a distributed approach, which could offer some advantages over the centralised solution. However, in the case of a smart grid, we can consider an alternative in which the network itself makes the aggregation process, eliminating the need for servers. The second example refers to the issue of collaboration in an underwater environment. Most applications for underwater environments (oceanographic data collection, environmental monitoring, navigation, tactical surveillance) use underwater vehicles that are based on inter-vehicle communications capabilities for the exchange of information and coordination purposes [5]. The enormous diversity and structural complexity of various underwater environments, such as coral reefs, coupled with adverse underwater conditions, impose a difficulty that is inherent in what the scientist can accomplish when attempting to understand and characterise the structure and functionality of the components of the reef. In an environment with a strong need for collaboration between nodes, but with important limitations in communication links, it is necessary to optimise the transmission to the fullest. PIN could be an interesting alternative, first to reduce as far as possible the need for communication, to perform compression, simplification and optimisation before a message is sent. PIN can also be a factor that helps to build relevant and complete information as it travels across a network. We might consider yet another example. It is clear that transfers involved in a critical application of telesurgery, because human life is involved, must comply with stringent QoS requirements. QoS requirements for the primary surgeon will undoubtedly be the most strict, but a telesurgery application might also be considered for other audiences, in which they all receive the same images or video, but each could have different QoS requirements. For example, QoS requirements to other physicians who supervise and advise the surgery could be slightly less stringent than those required for the primary surgeon. For medical students who are watching the operation, the QoS requirements could be even lower. In some cases, it can be considered to be sufficient (and even desirable for reasons of clarity) to have a simplification of the original image or video, which is obtained as a result of a visioning process. Consider, for example, the case of the recognition of objects such as a tumour or an artery, along with their respective elements of location (e.g., position, orientation).