Scalable Routing In Delay Tolerant Networks Mohammad Reza Faghani

An Outer Space Network station Jupiter Mars Mars Mars Earth Can not have direct access

What is Delay Tolerant Networks ? Intermittent link (dis)connection No guarantees on End-to-End path Frequent long duration partitioning C B A D E F

What is Delay Tolerant Networks ? High latency, low data rate Order of hours latency Long queuing times Because of disconnections (Store and Forward) Extremely large (hours, even days) Constraints on end node Limited power, limited buffer How packets route !?

Routing in DTN DTN Routing Challenges. Instantaneous end to end path may not exist. Large queuing delays. Buffer limitations at intermediate nodes. Large messages.

Routing in DTN Routing Goals: Eventual Delivery (delivery ratio) Minimizing delivery delay Scalability Cost-effective

The Routing Problem in DTN Nodes with finite storage capacity Links with dynamic behavior Time varying capacity (c(t)) C(t) = 0, if link is down Message Src, Dst, start-time, size Output: Compute path(s) for every message Objective: Minimize delay Other objectives: message delivery ratio, minimize $$ cost

The Routing Problem in DTN Edge parameterized by Source Destination capacity function delay function. Define link costs and find minimum cost path. Cost varies with time. Compute minimum cost paths over this dynamic cost assignment Modified Dijkstra by taking into account time of arrival

Input variable used in Routing Contacts Complete link time variant datas Contacts summary : Time independent information Average waiting time until the next contact Queuing : Link queues, available storage Traffic Demand

Routing input vs. Performance Input variable used “Performance” Contacts Summary + Local Queuing MED ED EDLQ EDAQ LP distributed Global Traffic Demand

Routing in large networks As the network size grows, number of contacts increases. These algorithms are not scalable for large networks. Using the idea used in static scalable routing. The hierarchical routing

Scalable Routing in DTNs Cong et. al. proposed a simple DTN model. This makes hierarchical routing possible For scalability, defined two contact information compression methods.

Simplified DTN model Static nodes (white) Mobile nodes with repetitive motion Motion cycle: T1=2 mins, T3=T4=3 mins Contact: a time period for communication. Persistent contacts: (2,1), (3,4), & (5,6) Persistent contact: (ni nj - - -) Predicted contacts: (1,3), (3,6), & (4,5) Predicted contact: (ni nj Tij tstart tduration) 6 5 1 3 2 4 As a sample sattelite networks, define contacts by their category, define 0.1 , 0.01

Hierarchical Routing in Static Networks 5 1 4 18 19 20 21 11 10 12 22 23 Hierarchical network Uses multilevel clustering. Offers scalable management of routing tables. Hierarchical routing Uses the hierarchical network as a topology abstraction A top-down process: the decision made in a higher level is more important Clustering & Clusterhead 8 2 6 13 24 14 15

Hierarchical Clustering in Static Networks Level 2 2 3 1 2 7 3 6 4 5 Level 1 Level 0 10 25 11 12 1 1 1 15 19 16 24 2 2 2 7 7 7 22 17 9 13 18 20 21 8 23 3 3 3 6 6 6 14 4 4 4 5 5 5

Hierarchical Clustering in Static Networks 1 Level 2 2 3 1 2 7 3 6 4 5 Level 1 Level 0 10 11 25 12 1 1 15 19 16 24 2 2 7 7 22 17 9 13 18 20 21 8 23 3 3 6 6 14 4 4 5 5

Hierarchical Clustering in Static Networks Before any routing each node in the network needs to obtain the topology information of its clusters in all levels. Source should know the hierarchy address of destination.

Hierarchical Clustering in Static Networks 1 Level 2 2 3 1 2 7 3 6 4 5 Node 61 represents the cluster of nodes 60,80,240 All nodes have their own hierarchy address e.g. node 6 HA equals (13, 22, 61, 80). Level 1 Level 0 10 11 25 12 1 1 15 19 16 24 2 2 7 7 22 17 9 13 18 20 21 8 23 3 3 6 6 14 4 4 5 5 18

Hierarchical Routing in Static Networks 1 Level 2 2 3 1 2 7 3 6 4 5 Level 1 Level 0 10 11 16 12 1 1 15 19 16 24 2 2 7 7 22 17 9 13 18 20 21 8 23 3 3 6 6 14 4 4 5 5 Destination Source 19

Hierarchical Routing in DTNs Similar to that in static networks Multilevel clustering Clusterhead selection Links: contact information aggregation Contact information compression methods

Cluster head Selection Objective Clusterhead: the center (in terms of delay) of a cluster Cluster members are close to their clusterheads Absolute priority D(i,j) is the weighed average delay between nodes i and j Higher if n is closer to the shortest paths among its neighbors Clusterheads that have the highest APs are self-selected. Relative priority Node i selects a nearby clusterhead n who has a high AP

Contact information aggregation Hierarchical links have time-variant delays They contain aggregate contact information Contact information in a level k+1 link are aggregated from the related level k links. 6 5 1 3 2 4

Contact information compression Aggregation level (La ) Above La, each link contain only a constant delay

Contact information Compression Contact information aggregated to link (6,7) is shown in (c). There are two possible shortest paths across the time as shown in (d) & (e) The contact information stored by link (6,7) after contact information removal

Hierarchical Routing in DTNs Similar to Hierarchical Routing in static networks Hop by hop routing A top-down decision making within each hop Step 1: top-down routing When the routing process is above La Step 2: Routing with contact information Routes on the combined contact information in all clusters below La

Simulation An example network Mobile node Static nodes Mobile nodes Whose trajectory travels several random waypoints within a random square bound

Simulation Results Route length Distribution

Simulation Results Hop-count ratio 70/30

Simulation Results Delay ratio 70/30

Simulation Results DHR+CIR Delay ratio 70/50

Simulation Results Storage communication overhead

Summary Summary Routing performance is close to the optimal routing result in terms of hop-count and delay Routing performance improves as aggregation level (La ) increases Routing performance improves as the source and destination distance increases Storage and communication overhead is reduced by the compression methods while desirable routing performance and scalability is achieved.

References [1] Liu C,Wu Jie. Scalable Routing in Delay Tolerant Networks.In proc. of the 8th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), 2007 [2] S. Jain, K.Fall, and R.Patra. Routing in Delay Tolerant networks. In Proc. of ACM SIGCOMM, 2004 [3] Leonard Kleinrock, Farok Kamoun, "Hierarchical Routing for Large Networks, Performance Evaluation and Optimization", Computer Networks, Vol. 1, No. 3, pp. 155–174, January 1977

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