## 2 Problem Background
### Existing OppNet Routing Protocols for Sensed Data Collection
#### 2.2.2 OppNet Routing Protocols in Sensed Data Collection Scenarios
To better understand the extent of unfairness in the routing protocols, we record the average percentage of initial energy consumed on the central nodes and the other nodes in Figure 3. For all the routing protocols, the central nodes consume at least three times as much energy as the other nodes under the different degrees of spatial locality. Figure 3: The average percentage of initial energy consumed on the central nodes and the other nodes under (**a**) low locality; (**b**) medium locality; (**c**) high locality. The results in Figure 3 can be translated to a metric that shows the distribution of energy consumption among the two sets of nodes. The metric, denoted by \(\alpha\in[0,1]\), is termed energy distribution, which we define as the ratio between the average percentage of initial energy consumed on the other nodes and the average percentage of initial energy consumed on the central nodes. The energy distribution for each routing protocol is shown in Figure 4. Higher values such as those of HERO and SnF denote more fairness (i.e., less difference between the energy consumed on the two set of nodes), while lower values denote less fairness. It is noticeable from the figure that all the routing protocols have relatively low energy distribution values. This is due to large differences between the energy consumption on the two sets of nodes. Overall, SnF records the highest energy distribution, with the central nodes consuming only about four times as much energy as the other nodes under the different degrees of spatial locality. By greedily spraying message copies, nodes are selected as relays irrespective of their forwarding ability. This distributes the task of finding more suitable relays across a wider range of nodes. Also, energy distribution increases with spatial locality since the chosen number of message copies to spray is increased. In real-world implementation, however, determining the number of copies to spray may require knowledge about global network parameters (e.g., total number of networking nodes). Also, further uncertainties are introduced under realistic human movement patterns that demonstrate high degrees of spatial locality. The relatively high energy distribution demonstrated by HERO under low locality is mainly due to more movement across different geographical regions when spatial locality is low. Since HERO infers the forwarding ability of nodes from their frequency of regional visits, more nodes moving across more regions leads to a less variation in forwarding utilities, hence more fairness. However, as spatial locality increases and nodes visit fewer regions, the few nodes that move across many regions are often  
Figure 4: Energy distribution (a) under low, medium and high degrees of spatial locality. selected as forwarders and energy distribution reduces. Next is dLife, which is able to reduce energy consumed from failed transmission attempts through a utility function that somewhat minimizes the effect of short-lived encounter durations by considering levels of social interaction among nodes. This takes PRoPHET behind dLife in medium and high locality--a reason failed transmission attempts may need to be considered a burden on nodes. With Epidemic, energy consumption is distributed poorly between the central nodes and the other nodes. Epidemic nodes consume the highest amount of energy under each scenario, with the central nodes consuming up to six times more than that of the other nodes. This high rate of energy consumption on the central nodes is mainly due to failed transmissions that result from attempting to transmit buffered messages during each encounter. Although a general issue across the routing protocols, the effect is more pronounced in Epidemic since the central nodes experience more encounters and attempt to transmit every message in their buffer whenever there is an encounter. Finally, Bubble Rap has the lowest energy distribution.