# DTN and Non-DTN Routing Protocols for Inter-CubeSat Communications: A comprehensive survey
## 4 DTN Routing Protocols in Disjointed Satellite Networks
### DTN Forwarding-Based Techniques
The lack of continuous connectivity between some nodes invalidates traditional ad hoc routing protocols and this path could be repeatedly disrupted, even if there was a path between two nodes. In terms of successful message delivery, SPST is able to deliver almost all of the messages created because, even though the network is not fully connected in certain times, there were space and time paths which form a source and destination connection over time. While these paths were detected by the SPST routing algorithm, it is still possible for SPST to fail in identifying some space-time paths within a particular time horizon. The performance of the other three heuristic algorithms was comparatively insignificant, where, although they disseminate the data through the network until it reaches its destination, they otherwise fully consume the resources of the node. While the performance of the HPR, MFN, and ER could be enhanced by increasing resource capacity, this would be at the expense of increasing resource exploitation. Some structural features of the network topology, such as node density, can also affect the performance of these heuristics. In comparing these routing protocols, the SPST also achieves a higher performance in terms of end-to-end delivery delay, with the authors assuming that the prediction of upcoming links is perfect and the links on the extracted space-time graph are continuously reliable for connection, for example, all of the packets on spatial or temporal links will be delivered and without any errors. In reference [72], the problem of topology control (TC) was studied for DTNs with predictable movements, where the network topology can be known prior based on the predictable mobility of nodes over time. Previous studies have mostly concentrated on routing and data dissemination, however, and, as maintaining the efficient and dynamic topology of the DTN becomes difficult with numerous participants of wireless nodes, the authors modelled the time-evolving of DTN as a directed space-time graph, which can show spatial and temporal data regarding the network nodes. The challenge with the topology control problem is in discerning how to extract a sparse space-time graph from the original directed space-time graph while maintaining the connectivity of the network, such that any two nodes can still communicate with each other. The extracted space-time graph, in this case, will have a minimised total cost when compared to the original one. An example of a DTN network where a sparser structure is needed is the interplanetary space DTN, as it is very expensive to build high-density networks [78]. It is necessary to wisely organise the DTN topology by minimising the number of communication links in order to reduce the energy consumption or any other costs of the network. To that end, the TC problem has primarily proven to be an NP-hard problem by relating it to the directed Steiner tree (DST) problem [79; 72]. Subsequently, the TC problem is defined as a problem of extracting a sparser space-time graph from the original space-time graph while maintaining the network connectivity and minimising the total cost. Accordingly, three greedy-based algorithms were proposed to be able to maintain the connectivity over time, while considerably decreasing the total cost of network topology. These three algorithms were known as: \"Union of Least Cost Path Algorithm\" (ULCP); \"Greedy Algorithm Based on Least Cost Path\"; and, \"Greedy Algorithm Based on Least Density Bunch\". For these algorithms, a group of edges was repetitively added to the topology to link one or more pairs of nodes in the space-time graph. In each iteration, one least-cost path was added to link one pair of nodes, as with the second algorithm or bunch of paths were added to link multiple pairs, as with the third algorithm. The near-optimal solution can be theoretically achieved by the third algorithm.