Epidemic Ad Hoc Routing

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Article of Amin Vahdat and David Becker,Departement of Computer science, Duke University Durham,

NC 27708

Epidemic Routing forPartially-Connected Ad Hoc

Student: HENG SotharithInstitution: University of Bretagne Occidendale

Date: 16 November 2011


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Ad Hoc Network

Epidemic Routing System Architecture

System Evalutation

Conclusion

PresentationPlan

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Communication without pre-existing communication infrastructure.

Mobile hosts can be recruited to fill the gap by serving as

intermediate routers.

Common assumption behind existing Ad Hoc routing techniques isthat there is always connected path from source to destination.

Issue of existing technique:

Not always valid when the network

partition exist

Packets are not delivered

AdHocNetwork

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[Ad Hoc Network][Epidemic routing] [System Architecture][System Evaluation][Conclusion]


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Goals:

1. Efficiently distribute message through partially connected network in aprobabilistic fashion

2. Minimize the amount of resources consumed and message deliverylatency

3. Maximize the percentage of message delivery

Assumption about the connectivity:

1. The sender is never in range of any base station

2. The sender does not know where the receiver is currently located or

the best route to follow3. The receiver may also be a roaming wireless host

4. Pair of host (not necessarily the sender and receiver) periodically andrandomly come into communication range of one another throw node

mobility

EpidemicRouting

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Messages delivery

Message are delivered by carriers which are network hosts.

Protocol relies upon carriers coming in to contact with another

connected portions of the network through node mobility and spread

message into additional island of nodes.

Example: Node S transfers a message to node D

EpidemicRouting(Contd)

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Design Issues:

Routing Under Uncertainty: determine whether to transmit a message

when a host comes into range of a potential carrier.

Resource Allocation: balance the conflicting goals of maximizing

message delivery and minimizing resource consumption.

Performance: storing and transmitting messages consumes energy as

well as CPU cycle, memory, and network banwidth, it is important to

balance the resource consumption.

Reliability: some application may require message acknoledgements.

Security: make sure that the message wasnt exposed to unstrustedhost (cryptographic techniques can provide such gurantees).

SystemArchitecture

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Epidemic Routing works as follows:

Each host maintains a buffer consisting of message that it has

originated as well as message that it is buffering on behalf of other host

A hash table indexes this list of messages, keys by a unique message

identifier

Each host stores a bit vector, called the summary vectorthat indicates

which entries in their local hash tables are set.

A Bloom filter would substantially reduce the space overhead

associated with the summary vector.

SystemArchitecture(Contd)

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When two hosts come into communication range of one another, the

host with the smaller identifier initiate an anti-entropy sessionwith the

host with the larger identifier.

To avoid redundant connections, each host maintains a cache of hosts

that it has spoken with recently.

Anti-entropy is not re-initiated with remote hosts that have been

contacted within a configurable time period. During anti-entropy, the two hosts exchange their summary vectors to

determine which messages stored remotely have not been seen by the

local host.

Each host request message that it has not yet seen.

The receiving host maintains total autonomy in deciding whether it will

accept a message.

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SystemArchitecture(Contd)[Ad Hoc Network][Epidemic routing] [System Architecture][System Evaluation][Conclusion]


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Anti-entropy session between A and B

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[Ad H N k][E id i i ] S S C


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Network Message:

Each message is associated with a unique message identifier, a hop

count, and an optional ackrequest.

Message identifier is a unique 32-bit number, a concatenation between the

host'ID and a locally-generated message ID (16 bits each).

Hop count determines the maximum number of epidemic exchanges that a

particular message is subject to (hop count is similar to TTL).

ackrequest signals the destination of a message to provide an

acknowledgement of message delivery.

Buffer size limits the amount of memory that a host uses to store themessage. Host will drop older messages in favor of newer ones upon

reaching their buffer capacity. Buffer size is roughly equal to the expected

number of message in transite. In this work, we implemented FIFO and

intend to investigate WFQ for future work.9


[Ad H N t k][E id i ti ] [S t A hit t ][S t E l ti ][C l i ]


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Using Monarch network simulator. Monarch extend ns with radio propagation that

model signal capture and collision. The simulator also models node mobility, allowing

for experimentation with ad hoc routing protocols. It implement the IEEE 802.11

Medium Access Control protocol.

Each simulated mobile node has an epidemic routing agent layer on top of the

Internet MANET encapsulation (IMEP) layer.

IMEP layer is responsible for notifying the epidemic agent when a new node comes

into radio range, and when a neighboring node moves out of radio range.

This simulator runs with 50 mobile nodes moving in rectangular area 1500 m * 300

m in dimension. Each node pick a random spot in the rectangle and moves with a

speed uniformly distributed between 0-20 m/s (average speed of 10 m/s). Each

message is 1 KB in length.

Subset of 50 nodes are selected as sources/sinks, with each of 45 nodes sending

one message to 44 other node in the system, for a total of 1980 message.

By default, each host allocates a 2000-slot message buffer.

We experiment with limit buffer space.

SystemEvaluation

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The table below shows the robustness of Epidemic Routing to various radio

transmission range. The interesting cases for Epidemic Routing are 25 and

50 meter transmission range. In this case, the existing protocols would be

unable to deliver most messages because they would be unable to locate aconnected path from source to destination. Epidemic Routing, on the other

hand, is able to deliver all messages with average latencies of 618.9 and

153.0 seconds respectively.

SystemEvaluation(Contd)

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We can limit total resource consumption by using higher hop count.

The figure below shows a CDF for message delivery rate for 50 meter

transmission range.

It shows that while lower hop count continue to delivery most messages,average delivery latency climbs significantly. In our scenario, we chose 4

hops because it still maintain the percent of messages delivery and latency.

SystemEvaluation(Contd)[Ad Hoc Network][Epidemic routing] [System Architecture][System Evaluation][Conclusion]



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The figure below shows the message delivery as a function of available buffer space

for 50 meter transmission range and 4 hop count.

The larger buffer size increase percentage of message delivery and decrease latency.

The higher message delivery rates clearly require larger memory resource

A buffer size of between 5-25% of originated messages is sufficient to deliver a high

percentage of messages with reasonable latency for our scenario.

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SystemEvaluation(Contd)[Ad Hoc Network][Epidemic routing] [System Architecture][System Evaluation][Conclusion]



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We developed techniques to allow message delivery in the case

where a connected path from source to destination is never available

in mobile ad hoc network. Throw an implementation in the Monarch simulator, we show that

Epidemic Routing delivers 100% of message with reasonable

aggregate resource consumption for scenarios where existing ad hoc

routing protocols are unable to delivery any message because noend-to-end routes are available.

Conclusion

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Epidemic Ad Hoc Routing