## 2 Message Replication in OppNets for Sensed Data Collection
### Message Replication Guidelines for Collecting Sensed Data with OppNets  
Sensed data collection with OppNets is mainly targeted for Smart City scenarios, and as learned from Section 2.3, the existing message replication techniques are not designed to cope with the characteristics of these scenarios. Feasible and efficient replication techniques need to operate in accordance with network characteristics and guarantee sufficient number of message copies in the network without causing excessive message transmission overhead on the energy constrained nodes. We suggest the following guidelines regarding message replication for collecting sensed data with OppNets:  
1. The number of message copies should not increase at a high rate with node population. In other words, the transmission overhead incurred in high node population should remain relatively low. Messages could be replicated according to the progress they have made towards their respective destinations. However, the progress should be identified without incurring excessive metadata overhead, preferably perceived from existing message properties or new ones that may not incur significant overhead.
2. While message replication can be controlled by selecting optimal thresholds for parameters such as the number of nodes currently in contact or message properties such as remaining TTL, adapting to different network conditions requires more than one optimal value for a threshold. The choice of these thresholds need to be made on the go, and should vary according to changing network conditions. In order to achieve this, network conditions that determine the optimal choice of these thresholds at every point in time need to be identified.
3. The goal of message replication is to maintain an acceptable level of delivery guarantee with minimal message copies. This means that messages need to be replicated sparingly and every generated copy needs to contribute towards maximizing delivery. Achieving this becomes more challenging under higher degrees of spatial locality due to insufficient encounter opportunities between nodes from different regions. Maximizing message delivery with minimal copies may require knowledge about the relationship between spatial locality and encounter opportunities between different sets of nodes.
4. Freeing node buffers of delivered messages is a direct approach towards minimizing redundant replication. However, notifying nodes through anti-packets may cause additional overhead, interfere with data transfer opportunities and may also take too long to disseminate. Optionally, message dropping policies could be designed to first drop messages that are more likely to have been delivered. It is important that such policies approach different messages according to their individual delivery criteria, as some messages may require more hops and buffer time than others to achieve the same delivery guarantees. Nodes also need to retain messages for which they have higher chances of delivery.
5. Assumptions need to be in accordance with realistic node movement, especially one that exhibits spatial and temporal properties of human mobility. The absence of central administration, lack of end-to-end connectivity and highly dynamic network topology should also be considered. It should be noted that global knowledge about the network is almost impractical to acquire locally and the performance of replication techniques should not depend on obtaining information that may become stale too quickly. Also, the performance of replication techniques should not rely on the existence of particular network infrastructure, since their presence in the application scenario may not be guaranteed. Solutions should be able to perform acceptably under varying amounts of infrastructure support or none at all. This is to maintain the ability offload existing mobile networks if need be.  
In the next section, we follow these design guidelines to propose our message replication technique, namely LARep.