## 3 System Architecture  
Any MAP can be marked as (externally wireless) interfered by testing various measures like beacon detection (in the same or overlapped channels) from external sources, increased channel access time, delays, loss of connectivity, service disruptions, or any other criterion. As stated in Section 1, when a MAP is strongly interfered by external factors, the routing protocol is responsible for redressing their effects. On the other hand, in our background of a backbone delivering a low-requirement sensor-data traffic, it is common for many nodes not to be linked to any active route (hereinafter unused nodes). Our proposed approach intends to take the wireless interfaces of both unused and interfered nodes down. Thus we reach some power savings, as well as interference redress, when managing the routing protocol to prioritize the MAPs not (or only moderately) interfered. This allows for redressing external moderated interference which may ballast the PWMNS traffic in the long term, or furthermore, the reverse interference of PWMNS over external devices of the smart city. This latter redress justifies the term wireless friendly [38] in our PWMNS acronym.  
We show, in Figure 1, a general system-architecture for implementing the communication in a smart city using a single ubiquitous, portable and easily deployable in different contexts mesh-network. We consider accesses from sensing sources linked to any MAP to Internet or any output device.  
Our ubiquitous and portable network is composed of a set of MAPs with at least WiFi connectivity to the other MAPs. Although any routing algorithm could be used [39; 40; 41], OLSR is our candidate (as explained in Section 2) because it has been tested for heterogeneous traffic in MANETs and WMNs. One of the MAPs could have external connectivity, e.g., a wired connection or through a conventional radio access network like General Packet Radio Service (GPRS) or Long Term Evolution (LTE). These MAPs will be considered communication sinks.  
Figure 1: System architecture for sensor data traffic in a smart city.  
It is a challenging task to develop a proposal for improving the behaviour of any wireless network towards external interferences. We focus our approach on wireless networks which only support reduced or relatively low-rate sensor data traffic. This simplifies MAPs operation, especially in connectivity, packet routing, and managing their wireless interface activation and deactivation. Figure 2 illustrates the specific approach which we will follow. It shows various data sources from different sensors. Likewise, it can be observed that several external interferences are influencing MAP5 and this could cause adverse effects on the traffic supported by the routes which use this node that we want to redress. Several measures made in real networks [42] and extended in Section 6 verify the interfering effects among different networks sharing the same technology.  
Figure 2 illustrates how these interferences can affect any MAP in a PWMNS. MAP5 is being interfered by the WiFi devices from building B while it is being used to transport packets between MAP6 and MAP4. Our mechanism will intend to redress these interferences by setting MAP5 wireless interface down. This mechanism will also be applied to any other MAP which are not being used in any route, in order to increase the PWMNS power saving. Although the interference problem can also be solved using other different techniques such as load balancing [43], or multipath routing [44]; we focus on it from a different point of view. Furthermore, unlike [43; 44], we also adopt the objective of achieving a certain level of power saving.