## 2 Problem Background
### Existing OppNet Routing Protocols for Sensed Data Collection
#### 2.2.3 Current State of OppNet Routing Protocols for Sensed Data Collection  
Unfairness remains a general issue among the existing routing protocols and their approaches for computing forwarding utilities. Protocols such as PRoPHET and IPRA utilize forwarding utilities that are based on the frequency of node encounters, and therefore give higher preference to nodes that encounter the destination (or its neighbour) more often. This increases the likelihood of selecting popular nodes as relays since they experience more encounters. This also applies to routing protocols such as SnF, OPF, and TMS that compute their forwarding utilities from the time since the destination (or its neighbour) was last encountered. Exploiting node popularity (e.g., PeopleRank and dLife) or centrality (e.g., Bubble Rap) also steers messages towards popular nodes. Nodes carried by prominent individuals and users that move around frequently are often selected as relays with protocols such as CiPRO and MobySpace, since they exhibit more contextual and movement similarities, respectively. Being relatively fewer in population, these nodes often happen to be network bottlenecks. Inferring forwarding utilities from node location (e.g., [58; 59; 52]) also directs messages towards popular nodes. This is because nodes that regularly visit more locations and experience more encounters in the process are relatively few (e.g., HERO). The same can be said for protocols such as Epidemic and SnW that are not based on forwarding utilities. The reason is that unfairness in OppNets stems from the nature of human movement, and therefore, forwarding messages solely based on encounter opportunities presented by such movement tends to overburden popular nodes. Regarding throughput, delivery guarantees are not only affected by fairness, but also by spatial locality inherent to user movement in sensed data collection scenarios. Under higher degrees of spatial locality, there are less neighbours that can make much progress towards delivering the message through the existing forwarding utilities. Higher spatial displacement between the source and destination nodes reduces the likelihood of meeting relay nodes that often encounter the destination or its neighbours. Under such conditions, node popularity or centrality may not span across the required number of regions to guarantee an encounter with the destination. Protocols that rely on frequency of location visits also face a similar situation due to only few users moving around more frequently. Utilizing similarity of node movement limits throughput as well, since the chances of encountering more suitable relay nodes are less under higher degrees of spatial locality. The approach for computing forwarding utility also has an impact on the achievable throughput in sensed data collection scenarios. Utilizing similarities in node movement patterns or social characteristics may reduce achievable throughput, since gateway nodes are neither mobile nor portray social characteristics. Also, relying on only frequency of location visits may not guarantee an encounter with the destination or its neighbours, as it depends on the span of the geographical area under consideration and coinciding visiting times. The lack of adequate contextual information on gateway nodes limits the applicability of context-aware approaches as well. Maintaining and updating history of encounters, however, can efficiently identify routing paths to gateway nodes [45], thereby making encounter-based routing protocols more suitable for sensed data collection. In summary, unfairness is an issue with existing OppNet routing protocols and their performance under different degrees of spatial locality suggest that locality-awareness is necessary for realizing fair routing solutions that can guarantee acceptable throughput in sensed data collection scenarios.