ON BOUNDED MESSAGE REPLICATION IN DELAY TOLERANT NETWORKS

Md. Nazmus Sadat, Muhammad Tasnim Mohiuddin, and Md. Yusuf Sarwar Uddin

Presenter: Muhammad Tasnim Mohiuddin

DELAY TOLERANT NETWORKDelay tolerant networks (DTN), also called as intermittently connected mobile networks (ICMN).The probability that there is an end-to-end path from a source to a destination is low.High mobility and low density of the nodes in the network.

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ROUTING IN DTNThe conventional solutions do not generally work in DTNs.Store-carry-and-forward paradigm is used in routing of messages in DTNs.

Routing in DTN

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Store-Carry-and-Forward Paradigm

STRATEGIES Single-Copy: only a single copy of each message exists in the network at any time .

Multiple-Copy: multiple copies of a message may exist concurrently in the network.

MULTI-COPY SCHEMES Epidemic Routing (flooding): Handover a copy to everyone.

Utility-based Flooding: Handover a copy to a node if utility is at least Uth higher than current.

Problems in Flooding Approach: Huge messaging overhead in the network which then causes redundant energy and resource consumption.

SPRAY AND WAIT Significantly reduce transmissions by bounding the total

number of copies/transmissions per message. 2 phases:

Spray phase: spread L message copies to L distinct relays

Wait phase: wait until one of the L relays finds the destination (i.e. use direct transmission).

A Number of different spraying heuristics can be envisioned.Can be defined in terms of a function as follows:

Handover portion of message copies to encountered node

Keeps portion for itself

EXISTING SPRAYING HEURISTICS

EXISTING SPRAYING HEURISTICS Source Spray and Wait: the source node keeps 1 copy for itself and handover the rest to the node it encounters.

Binary Spray and Wait: The source of a message initially starts with L copies; any node A that has n > 1 message copies and encounters another node B (with no copies), hands over to B, n/2 and keeps n/2 for itself; when it is left with only one copy, it switches to direct transmission.

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EXISTING SPRAYING HEURISTIC

Any spraying heuristic can be represented by a binary tree: L

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BINARY SPRAY AND WAIT

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DL = 4 L =

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L = 1

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L = 1 L =

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PROBLEMS OF EXISTING SPRAYING HEURISTICSDo not evaluate the encountered node in terms of delivery predictability. If node A encounters node B which might have never contacted with any other nodes, handing over half of the copies to such a node is very inefficient.

OUR PROPOSED SPRAYING HEURISTICS We proposed three spraying heuristics based on Delivery Predictability of encountered node -

Simple Probabilistic SprayingPredictive Probabilistic SprayingAdaptive Probabilistic Spraying

DELIVERY PREDICTABILITY CALCULATION

The Delivery Predictability calculation is divided into three parts.

When two nodes meet each other, they immediately update the Delivery Predictability as shown in the following equation: ; where is a

initialization constant.

If, for a period of time, a pair of nodes does not encounter each other, then the Delivery Predictability metric is updated by the nodes as shown in this equation: ; where is an aging constant

and k is the timeslot elapsed

DELIVERY PREDICTABILITY CALCULATION

The transitive property affects the Delivery Predictability as shown:

where is a scaling constant.

SIMPLE PROBABILISTIC SPRAYING Let, node A encounters node B and L be the number of copies. Let, D be the destination node. and . Simple probabilistic Spraying heuristic splits L, in the following way:

The number of copies left for node A, .The number of copies for node B, .

Binary tree corresponding to Predictive Probabilistic Spraying L

(1−𝑃 𝐵 )𝐿 𝑃 𝐵𝐿

PREDICTIVE PROBABILISTIC SPRAYING P(node A will not successfully deliver the message) = P(node B will not successfully deliver the message) = P(node A and B both fail to deliver the message) = . So, the probability that both succeed is = .

Binary tree corresponding to Predictive Probabilistic Spraying L

(1−𝑃 𝐴)(1−𝑃 𝐵)𝐿(1− (1−𝑃 𝐴 ) (1− 𝑃𝐵 ))𝐿

ADAPTIVE PROBABILISTIC SPRAYINGWe call this spraying heuristic adaptive because, this heuristic can adapt to the network environment. The intuition behind this heuristic is to hand over more copies to node having lower delivery predictability. A node having higher delivery predictability can successfully deliver message to destination with fewer copies.

Splitting function is dynamically calculated based on current delivery predictability of encountered nodes

ADAPTIVE PROBABILISTIC SPRAYING

SIMULATIONSimulator: Opportunistic Network Environment (ONE) simulator

Mobility Traces: Used two real traces-

Haggle 3 infocom 5Haggle 4 infocom 5

THE ONE SIMULATOR

SETTINGS OF MOBILITY TRACES

Parameter Haggle 3 infocom 5

Haggle 4 infocom 5

Total Time 72 Hours 275 HoursNo of Hosts 41 36Total number of Contacts

44,918 21,282

Node Buffer Size 5M 5M

SIMULATION RESULTS AND EVALUATION We have investigated the performance of Binary Spray and Wait and our proposed spraying heuristics by varying message Time To Live (TTL) and number of initial message copies.

Performance is analyzed on three metrics: Delivery ratioOverhead ratioAverage latency

PERFORMANCE IN TERMS OF DELIVERY RATIO

Delivery Ratio is defined as:

PERFORMANCE IN TERMS OF DELIVERY RATIO

Effect of TTL on Delivery Ratio

For Haggle 3 Dataset For Haggle 4 Dataset

Effect of number of initial copies on Delivery Ratio

For Haggle 3 Dataset For Haggle 4 Dataset

PERFORMANCE IN TERMS OF DELIVERY RATIO

PERFORMANCE IN TERMS OF OVERHEAD RATIO

Overhead Ratio is defined as:

PERFORMANCE IN TERMS OF OVERHEAD RATIO

Effect of TTL on Overhead Ratio

For Haggle 3 Dataset For Haggle 4 Dataset

PERFORMANCE IN TERMS OF OVERHEAD RATIO

Effect of number of initial copies on Overhead Ratio

For Haggle 3 Dataset For Haggle 4 Dataset

PERFORMANCE IN TERMS OF AVERAGE LATENCY

Average Latency is the measure of average time between messages are generated and when it is received by the destination.

PERFORMANCE IN TERMS OF AVERAGE LATENCY

Effect of TTL on Average Latency

For Haggle 3 Dataset For Haggle 4 Dataset

PERFORMANCE IN TERMS OF AVERAGE LATENCY

Effect of number of initial copies on Average Latency

For Haggle 3 Dataset For Haggle 4 Dataset

CONCLUSION We presented three spraying heuristics based on delivery predictability for Spray and Wait routing protocol. We evaluated the proposed heuristics using the ONE simulator in different scenarios. Simulation results show that the adaptive and predictive probabilistic spraying heuristic outperform Binary Spray and Wait in terms of delivery ratio and average latency.