## 2 Problem Background
### Fair Routing Guidelines for Collecting Sensed Data with OppNets  
Collecting sensed data with OppNets is mainly intended for Smart City scenarios. As learned from Section 2.4, the existing fair routing techniques are not designed to cope with the characteristics of these scenarios. Hence, there is need to adapt fair routing techniques to achieve a more even distribution of burden among nodes without degrading network performance. We suggest the following guidelines regarding fair routing for collecting sensed data with OppNets:  
1. An economical network model utilizes static gateway nodes, which are basically routers deployed in popular locations that allow sufficient encounter opportunities with user devices. Hence, the approach for computing forwarding utilities should be able to efficiently determine routing paths to destination nodes that are characterised by lack of mobility, limited social characteristics and inadequate contextual information.
2. Gateway nodes are likely to be relatively few in order to minimize procurement, installation and maintenance costs, as well as maintain a manageable level of complexity. Due to their sparse distribution, design assumptions should be in accordance with the concepts of spatial locality inherent to user movement. Since the strength and reliability of social bonds and encounter-based relationships tend to reduce with distance, related metrics may not always perform as expected. Also, achieving acceptable fairness and throughput may require messages to traverse more than the usual number of hops to arrive at more distant destinations.
3. The forwarding utility should be less biased towards global popularity, thereby allowing contribution from a wider range of nodes. For instance, the forwarding utility could be designed so that the encounter-based popularity of nodes cannot be perceived beyond \(H\) hops, where \(H\) represents a relatively small number. This ensures that the forwarding utility of a popular node is not always higher than that of a less popular node, unless the former is within \(H\) hops from the gateway.
4. While allowing a wider range of relay nodes, the forwarding utility should also be able to maximize the contribution of less popular nodes. This requires knowledge about human movement, since less popular nodes may not have strong social ties or encounter-based relationships with gateways nodes. For instance, the regularity embedded in node movement could be exploited to carry messages closer to locations where more suitable relay nodes are likely to be encountered.
5. During an encounter, routing decisions are made by comparing information about the nodes in contact. Knowledge about the relative burden on nodes is therefore necessary to make fair routing decisions. While this knowledge is mostly inferred from buffer information, conditions such as changes in data traffic, unequal buffer capacities and dynamic user behaviour may lead to misinterpretations. Hence, in order to ensure fairness under different network conditions, burden should be determined from properties that are directly related to resource consumption on nodes.  
In the next section, we follow these guidelines to propose our routing technique, namely FLARoute.