on using probabilistic forwarding to improve hec-based data forwarding in opportunistic networks...

On Using Probabilistic Forwarding On Using Probabilistic Forwarding to Improve HEC-based Data to Improve HEC-based Data Forwarding in Opportunistic Forwarding in Opportunistic

NetworksNetworks

Ling-Jyh ChenLing-Jyh Chen11, Cheng-Long Tseng, Cheng-Long Tseng22 and Cheng-Fu Chou and Cheng-Fu Chou22

11Academia SinicaAcademia Sinica22National Taiwan UniversityNational Taiwan University

MotivationMotivation

• There are numerous opportunistic networking applications.– wireless sensor network, underwater sensor

network, pocket switched network, people network, and transportation network

• Traditional data forwarding algorithms are not suitable for opportunistic networks.– Scheduled optimal routing method– Mobile relay approaches (Message ferry)

Related workRelated work

• Replication-based approaches– The messages are replicated. Several

identical copies are transmitted over the networks to mitigate the effects of a single path failure.

– For example:• Epidemic Routing, • Controlled Flooding, • mobility pattern-based scheme (Prophet)

Related workRelated work

• Coding-based approaches– Transforming a message into another

format prior to transmission.– For example:

• Erasure coding (EC), Aggressive Erasure Coding (A-EC), Hybrid Erasure Coding (H-EC)

• Network Coding

Our ContributionOur Contribution

• We propose a message scheduling algorithm, Probabilistic Forwarding, to improve H-EC scheme.

• Using a set of simulations, we show the proposed approach can provide better data delivery performance.

Overview of H-ECOverview of H-EC

• Erasure Coding:– Providing better fault-tolerance by

adding redundancy without the overhead of strict replication.• Reed-Solomon, • Low-Density Parity-Check (LDPC) based

coding (Gallager, Tornado, and IRA codes)

Erasure CodingErasure CodingA B C D

A-1

A-2

A-3

A-4

B-1

B-2

B-3 C-1

C-4

D-1

A B C D

A-1

A-2

A-3

A-4

B-1

B-2

B-3

B-4

C-1

C-2

C-3

C-4

D-1

D-2

D-3

D-4

Lossy Lossy ChannelChannel

(r,n)=(2,4)(r,n)=(2,4)

Overview of H-ECOverview of H-EC

• H-ECH-EC: Hybrid of EC and A-EC– First copy is sent using EC– Second copy is sent using A-EC during the

residual contact duration after sending the first EC block

The Purposed Method: HEC-The Purposed Method: HEC-PFPF

• Probabilistic forwarding– The HEC-PF scheme dost NOT enter the

aggressive forwarding phase unless a newly encountered node has a higher likelihood of successfully forwarding the message to the destination node that the current nodes.

• Delivery Probability

Delivery ProbabilityDelivery Probability

• Based on the observed contact history

• Take the contact frequency and contact volume into consideration.

• The proportion of time that the two nodes are in contact in the last T time units.

Delivery Probability

One-hop delivery probability

The ith Node

The source Node

The Destination

Node

the aggregated contact volume between the node pair Xi and Xj in the last T time units

K: number of nodes in the networkXi: the i-th node tXi;Xj:the aggregated contact volume between the node pair Xi and Xj in the last T time units

Delivery ProbabilityDelivery ProbabilityTwo-hop delivery probability

k-hop delivery probability

Three-hop delivery probability

Probabilistic ForwardingProbabilistic Forwarding

EvaluationEvaluation

• DTNSIM: A Java-based DTN simulator• Performance metric:

– Delay performance– Transmission overhead

• Evaluating Scenarios:

Evaluation I: two-hop Evaluation I: two-hop scenarioscenario

Power-Low Scenario ZebraNet Scenario UCSD Scenario

Evaluate the delay performance of the HEC-PF scheme for message delivery.Maximum message delivery distance (hops) H=2,

The transitive property of message delivery (hops) K=2

Evaluation II: Evaluation II: Variable Variable kk Scenarios Scenarios

ZebraNet Scenario UCSD Scenario

We evaluate the performance with various k values (k = 2,3,4,5)

Evaluation II: Evaluation II: Variable Variable kk Scenarios Scenarios

Evaluation III:Evaluation III:Variable Variable HH Scenarios Scenarios

ZibraNet Scenario UCSD Scenario

We evaluate the performance with various maximum forwarding distance settings (H = 2,3,4,5)

Evaluation II: Evaluation II: Variable Variable HH Scenarios Scenarios

ConclusionConclusion• We purposes a new scheme for data forwarding

by incorporating the basic H-EC scheme with a new feature, Probabilistic Forwarding.

• Using simulations as well as both synthetic and realistic network traces, we show that the proposed has better performance in terms of delivery latency and completion ratio.

• We show that the completion ratio improves as the maximum forwarding distance or the considered hop distance of the delivery probability increases.

Thank You!Thank You!