Augmenting the Backpressure Collection Protocol to Support Multiple Sinks

Varun Shimoga Prakash, Dr. Omprakash GnawaliNetworked Systems Laboratory

Dept. of Computer ScienceUniversity of Houston

Problem Statement

• Enable the Backpressure Routing technique to route packets to multiple sinks within a network.

Expectations from the Solution

• Small Memory Overhead• Packet Delivery Performance• Adherence to conditions imposed by

Backpressure Routing.

Possible Solutions

• Virtualization of Queue Management• Clustering of Network• Feedback based model.

Virtualization of Queue Management

• Each node stores its local backpressure to each of the sink in the network.

• Single Queue of Packets• Backpressure values create a virtual queue for

each sink.• Backpressure values propagated through

beacons or snooping.

Source Node 3

Source Node 4

Source Node 1

Source Node 2

Sink Node 1 Sink Node 3

Sink Node 2

{Sink_1: Active}

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4

3

2

{Sink_2: Active}

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3

2

4

{Sink_1: 1Sink_2: 1} 4

3

2

{Sink_3: Active}

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2

3

4

{Sink_3: 1}

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2

3

{Sink_3: 2Sink_1: 2Sink_2: 2}

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3

{Sink_3: 2Sink_1: 3Sink_2: 3}

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3

Disadvantages

• More the number of sinks, larger the packet header and storage of local backpressure to sinks.

Possible Solutions

• Virtualization of Queue Management• Clustering of Network• Feedback based model.

Clustering of Network

• Create imaginary clusters in the network where sinks are the centroids.

• Controlled Broadcast until packets reach a node in the desired cluster of a sink.

The Network is clustered around eachSink. There is an affiliation of each of theNodes towards the cluster to which it belongs.

Source

Sink

Broadcast Message

Broadcast Message

This node has a gradient sloping towards the local sink. Route messagethrough Backpressure routing.

Disadvantages

• Controlled Broadcasting does not allow Linear Networks.

• Without controlled broadcasting, undesirable redundancy of messages increases.

Possible Solutions

• Virtualization of Queue Management• Clustering of Network• Feedback based model.

Feedback Based Model

• Sink sends feedback to the last node before it.• Feedback propagate to all nodes in network.• Based on feedback and past performance,

nodes choose their next hop.

Source Node 3

Source Node 4

Source Node 1

Source Node 2

Sink Node 1 Sink Node 3

Sink Node 2

Task: Send packets from Source Node 3 to Sink Node 1

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2

3

Initially Broadcastthe packet

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3

Broadcast

Broadcast

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3

Broadcast

Negative Feedback

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3

Broadcast

Negative Feedback

Sink Node 1

Positive Feedback

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2

3

Sink Node 1

Positive Feedback

Sink 1:

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2

3

Sink Node 1

Positive Feedback

Sink 1:

Sink 1:

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2

3

Sink Node 1

Positive Feedback

Sink 1:

Sink 1:

Sink 2:

Sink Node 2

Sink 3:

Disadvantages

• Convergence of the entire network takes more time in case of mobile sinks.

• New weight parameter (feedback) to be considered to calculate weight.