# DTN Trustworthiness for Permafrost Telemetry IoT Network
## 2 Related Work
### Transport Protocols  
The performance of transport protocols for network communications has been a topic under discussion and development since the Internet was conceived [5]. The first extensions of the original Transmission Control Protocol (TCP) were [31] TCP Tahoe, TCP Reno, TCP New-Reno, TCP SACK, and TCP-Vegas, which included new mechanisms such as the fast retransmit, the fast recovery, the packet pair link estimation, the duplicated acknowledgment (DUACK), and the selective acknowledgment (SACK).  
However, these legacy transport protocols suffered performance degradation over some types of networks, including LFNs. The LFN concept and its effects on TCP performance were firstly defined and detailed in the Request For Comments (RFC) 1072, which was obsoleted by the RFC 1323 to finally become the standard RFC 7323. Some TCP variants and other transport protocols developed during the last decade have improved their performance over LFNs [5]. Some of these are Scalable TCP (S-TCP) [32], FAST TCP [33], High-Speed TCP (H-TCP) [34], Binary Increase Control TCP (BIC-TCP) [35], and its evolution: TCP CUBIC [36]. TCP CUBIC (RFC 8312) is the most commonly used transport protocol nowadays, given that it is the TCP variant used by default on most operating systems. However, most of these protocols consider that packet loss always occurs due to network congestion, reducing the congestion window. This assumption is false for wireless links, where packets can also be dropped for other reasons (e.g., fading, channel interference) [11]. Under these circumstances, reducing the congestion windows might also degrade the transmission performance, achieving lower throughput [11].  
For this reason, other transport protocols, such as Performance-oriented Congestion Control (PCC) [37], TCP Veno [38], TCP Westwood+ [39], Dynamic TCP [40], Jitter TCP [41], and Jitter Stream Control Transmission Protocol (JSCTP) [42] are focused on implementing mechanisms to detect if lost packets occur due to network congestion or random channel loss. They only reduce the congestion window in the first case, achieving better performance [11].  
In addition, other modern transport protocols, such as TCP BBR [43], Copa [44], Indigo [45], and Verus [46], can achieve high performance, as proven in several physical tests carried out by Stanford University's platform Pantheon [45]. TCP BBR is one of the top-performance protocols, managing the maximum bandwidth with the minimum RTT. Copa is a practical delay-based protocol that fixes an RTT target and adjusts its congestion windows based on the minimum RTT and the standing RTT measured during data transfers. Indigo is a data-driven protocol that uses a machine-learning congestion control scheme that learns from previous performance data. Verus is a transport protocol oriented to cellular networks that relates the congestion windows with delay variations through short-term RTT measurement.  
Moreover, given that the aforementioned protocols did not meet the performance requirements of our cloud data-sharing use case from previous work [11], we presented the Adaptive and Aggressive Transport Protocol (AATP) [5] and its evolution, the Enhanced AATP (EAATP) [11], which incorporates mechanisms to differentiate the packet losses' cause, fairly adapting its sending rate accordingly to the network circumstances. The performance in these tests was solid, both in simulations and in a physical testbed with an LFN emulator, showing better results than other protocols, maximizing throughput and minimizing packet losses [5; 11]. Figure 2 shows a summary of the tests' results. However, we did not know how these protocols (including ours) could affect the trustworthiness of a system, especially in the use case of this paper. For this reason, we thought that we needed to assess whether using the EAATP in the remote Antarctic WSN use case could improve the system's performance and trustworthiness, especially in congestion situations.