## 3 Reducing Transmission Overhead without Compromising Throughput
### Overview of LARep
Locally determining how much progress messages have made towards their destination nodes without frequent metadata transmissions;
3. Dropping messages according to the progress they have made towards their destination nodes; and
4. Varying message replication quota according to the distance between the source and destination nodes, and generating copies based on the progress messages have made towards their destination nodes. This section overviews LARep by presenting the tasks involved in realizing the four subtasks. As shown in Figure 11, the tasks are addressed in four phases. **Phase 1. ** The first phase is concerned with determining the most significant locations visited by nodes. The current location is collected via GPS at fixed intervals and stored in device memory. With this information, the areas a node is mostly found in are interpreted as its significant locations. The major challenge in this phase is how to maintain GPS readings from which the most frequently visited locations can be determined, knowing that the same exact pair of coordinates may never be recorded twice. To address this, we introduce the PoiTrace mechanism, which converts incoming GPS readings into a more stable form and records them in their respective positions in a location table. With this, the locations most frequently visited by a node can be inferred from the set of most recurring pair of coordinates. **Phase 2. ** The second phase focuses on gaining knowledge about the progress messages have made towards their destinations, in order to facilitate replication decisions. The source node embeds in message headers, the relative distance between itself and the destination node, and also associates two properties with each message. Similar to message properties such as hop count, the two new properties are updated whenever a message is transmitted. The main challenge in this phase is how to infer from the available information, how much a message has advanced towards the destination node. To address this, we propose the Message Progress Tracking (MPTrack) mechanism, which with the information in message headers alone, computes a measure from which the progress messages have made towards their respective destination nodes can be inferred. **Phase 3. ** Messages are dropped in order to create space for incoming or newly generated messages. A major issue in high degrees of spatial locality is that messages travelling longer distances require more buffer time to reach their destinations. Unfortunately, the likelihood of losing them increases the longer they remain buffered. In the third phase, we propose the Locality Aware Message Dropping (LAMeD) mechanism, which provides a policy for dropping messages by considering the progress made towards their destination nodes. A node selects a message to drop by comparing the forwarding utility for each message, the spatial displacement between the source and destination nodes and the progress made towards the destination node. As a result, throughput is improved. **Phase 4. ** The fourth phase is concerned with determining the number of copies to generate for each message and when to generate a copy. The optimal replication quota of a message at a given instance depends on current encounter properties of nodes, which may vary due to various physical parameters affecting node movement and encounter rates. Hence, a major challenge in this phase is how to account for instantaneous changes in replication requirements for different messages. To address this, we exploit locality awareness to propose the Locality Aware Spray and Focus (LASnF) algorithm. LASnF introduces two phases and defines new message replication conditions for each phase based on properties in the message header and the forwarding abilities of the concerned nodes. This results in a variable message quota that minimises excessive replication and maximises throughput.