A survey in Delay Tolerant Networks Andrew Steinberg and Rafael Papa

Outline What is Delay Tolerant Networks (DTN)? The Problem The Routing in DTN DTN Routing Protocols Comparative analysis based on papers information

What is DTN?

Delay Tolerant Networks (DTN) Delay tolerant network (or DTN) is specific type of network where the connectivity among the participants nodes do not exist 100% of the time. Main characteristic: cannot guarantee connectivity between end-to-end (E2E) points Challenges: Extremely large E2E Delays There is no guarantee of a reliable delivery It demands a lot of resource allocation (communication overhead) Scalability If mobility is considered, there is no way do determine nodes position

The Problem

Delay Tolerant Networks (DTN) The problem How to route a packet from one node to another if the network cannot guarantee connectivity between end-to-end (E2E) points?

Routing in DTN

Flooding Strategy Multiple copies of each message will be spread out over the network Ex: Epidemic Routing, Spray and Wait Store-and-Forward Strategy The message will be stored locally in the node until the next opportunity to be forward to other node. There is no message replication. Ex: PRoPHET, CCODR (Space Networks)

DTN Routing Protocols

Epidemic Routing [1] It floods applications messages through the connected portion of the network, then relies upon carriers meeting one another occasionally to spread the msg; Advantage Very efficient delivery rate Disadvantage Excessive amount of message copies (overhead)

Epidemic Routing (Broadcast + ACK) [2] Multiple Messages + ACKs Relies upon Markov Chain to keep track of message copies The Markov chain state, (Cm, Am): Cm: message copies Am: broadcasting ACKs Advantage Improve the delivery rate by decreasing the number of message copies Disadvantage Buffer overhead

Spray and Wait [3] Epidemic does serious flooding in the network. Causes overhead How can we improve? Spray and Wait has two stages” Spray Wait Improves overhead

Recent Work in Spray and Wait [4] Spray and Wait reduces flooding however there is still more to extend Improve Scalability (buffers) In general spray and wait drops a message if it is too big for the buffer queue Two Scenarios If message size could fit in the queue, then it was added If message size is too big, then message with the smallest value from the spray phase is dropped or the current biggest message

PRoPHET [5]

Recent Work in PRoPHET [6] PRoPHET reduces overhead and increases delivery rates. Every work always has room for expansion. Improve Resource Allocation (congestion) Improve Delivery Rate Authors set a threshold of the congestion level to determine if it’s good to forward a packet. If not, then drop the packet

Hybrid (Spray and Wait + PRoPHET) [7] Restrict the amount of replications msgs The Spray and Wait Replicate msgs only to nodes with high delivery predictability The PRoPHET Maximum number of replications (L) L = 1 and delivery predictability < threshold value the message needs to be replicated more

Applications

CCODR (Space Networks) [8] An improvement of the EAODR routing algorithm Earliest Arrival Optimal Delivery Ratio Routing (EAODR) Based on Contact Graph Routing (CGR) Construct the path based on earliest contact Congestion control was added to reduce packet loss ratio

Underwater [9] DTN’s can be deployed in rough environments. Underwater setting can cause mobility patterns to be different Q-Learning based Delay Tolerant Routing Predictor Forwarder Performs better than epidemic, spray and wait, and prophet.

Comparative analysis based on papers information

References [1] Amin Vahdat and David Becker. “Epidemic Routing for Partially-Connected Ad Hoc Networks.” Technical Report, 2000 [2] N. Kawabata, Y. Yamasaki and H. Ohsaki, “On Message Delivery Delay of Epidemic DTN Routing with Broadcasting ACKs,” 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC), Turin, 2017, pp [3] T. Spyropoulos, K. Psounis, and C. S. Raghavendra, "Spray and wait: an efficient routing scheme for intermittently connected mobile networks.", In Proceedings of the 2005 ACM SIGCOMM workshop on Delay-tolerant networking, August 2005, pp [4] E. Kim, W. Seo, J. Nam, J. Choi and Y. Cho, "Probability-based spray-and-wait protocol with buffer management in Delay Tolerant Networks," The 20th Asia-Pacific Conference on Communication (APCC2014), Pattaya, 2014, pp [5] A. Lindgren, A. Doria, O. Schelen, "Probabilistic Routing in Intermittently Connected Networks", In Proceedings of the The First International Workshop on Service Assurance with Partial and Intermittent Resources (SAPIR 2004), August 2004, Fortaleza, Brazil [6] G. Wang, J. Tao, H. Zhang and D. Pan, "A improved Prophet routing based on congestion level of nodes in DTN," 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), Chongqing, 2017, pp [7] T. Miyakawa and A. Koyama, “A Hybrid Type DTN Routing Method Using Delivery Predictability and Maximum Number of Replication,” 2015 IEEE 29th International Conference on Advanced Information Networking and Applications Workshops, Gwangiu, 2015, pp [x] Z. Cong, G. Xie and J. Gao, “CCODR: Routing optimization for DTN-based space networks in congestion control,” rd IEEE International Conference on Computer and Communications (ICCC), Chengdu, 2017, pp [x] Tiansi Hu and Yunsi Fei, "An adaptive routing protocol based on connectivity prediction for underwater disruption tolerant networks," 2013 IEEE Global Communications Conference (GLOBECOM), Atlanta, GA, 2013, pp