# 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  
In forwarding-based routing, one copy of each message is forwarded on an optimised path until it reaches the designated destination. In Reference [74], a Context-aware Adaptive Routing (CAR) is proposed as a solution for problems through intermittent connectivity in random mobility DTNs. CAR estimates the next hop based on the prediction techniques of the Kalman Filter algorithm and the utility function. The prediction techniques used in CAR do not require the nodes to keep track and store information on the history of the encounter with other nodes, an advantage that makes the CAR algorithm suitable for networks with limited resources. The CAR can reduce the transmission overheads when compared with other single-copy protocols, as well as with multi-copy protocols, such as Spray and Wait. In contrast, [PERSON] et al. proposed a novel Expected Minimum Delay (EMD) metric and EMD-based routing protocol that they called Routing in Cyclic MobiSpace (RCM) for networks with periodic mobility [76; 77; 70]. This expected delay time represents the minimum time that is needed for an optimal forwarding scheme to transmit a message over a path to a destination at a certain time in a network that is characterised by its cyclic and intermittent connectivity. Being inspired by the Euclidean space of MobySpace originally introduced in [56], the Cyclic MobiSpace network has been modelled as a probabilistic space-time graph, where each encounter time of a node with other nodes is assumed from historical encounter information or previous awareness regarding the network topology, with an assumption that the mobility pattern will not subsequently change. Proceeding to interpret this network model as a probabilistic state-space-graph, it is comprised of a different state for each encounter of each node to remove the time dimension. Subsequently, the Markov Decision Process (MDP) has been applied to obtain the EMDs of the messages over time. The routing problem in wireless networks that are characterised by predictable mobility is investigated in [73], where these networks suffer from the unavailability of continuous paths between all nodes. The continuous movement of nodes leads to a frequent absence of end-to-end paths between a source and destination at a particular time instant, which in turn makes using ordinary ad hoc routing protocol inappropriate. Although node movements may create a path with the progression of time between any two nodes in the network by using the store, carry, and forward techniques, finding these paths is very challenging, especially in wireless networks with large numbers of nodes. In such a network, anode's mobility can be predicted by a finite time limit or based on the periodic movement of nodes. A space-time graph model was proposed as a solution to this problem of routing in predictable wireless networks [73]. In particular, the routing problem is being resolved by extracting a space-time routing table that was derived from node movement over time to consider the time and place in which a node can forward the message to the next hop or destination where forwarding a message to the next hop becomes a function of both the destination and time. In this model, the network topology is captured over time to determine the connected parts of the network on different time slots. A Shortest Paths in Space and Time (SPST) routing algorithm was designed based on this space-time graph model to specify appropriate next hops and upcoming neighbours to minimise the end-to-end delay. The SPST algorithm was then compared with three other routing algorithms--Hot Potato Routing (HPR), Most Frequent Neighbour Routing (MFN), and Epidemic Routing (ER)--which are based on heuristics. A network of 128 nodes with 61 links was examined with only one message in the network in the first case and with realistic message traffic in the second case.