Daibo Liu 1 Daibo Liu 1, Zhichao Cao 2, Xiaopei Wu 2, Yuan He 2, Xiaoyu Ji 3 and Mengshu Hou 1...

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Daibo Liu1, Zhichao Cao2, Xiaopei Wu2, Yuan He2, Xiaoyu Ji3 and Mengshu Hou1

ICDCS, 2015, Columbus

TeleAdjusting: Using Path Coding and Opportunistic Forwarding for Remote Control in WSNs

1 University of Electronic Science and Technology of China2 Tsinghua University

3 Hong Kong University of Science and Technology

Outline• Motivation• Related works and our approach• Design of TeleAdjusting• Implementation and Evaluation• Summary of this work

Motivation

• Practical experience– CitySee: city-wide urban

sensing system– Predefined configurations

VS. changes of network– Expensive manual

maintenance

• Remote control in duty cycled WSNs– Key technique for network management– Challenge to achieve energy efficiency and reliability

Related Works• Remote control protocols in WSNs

– Unstructured approaches• Network-wide flooding• Energy and bandwidth waste, reliability guarantee• Drip, Deluge, Gloosy

– Structured approaches• Along a predefined path• Energy efficiency• Susceptible to network dynamics, hard to guarantee

reliability• E.g., RPL, ORPL

Can we achieve a remote control approach guaranteeing both reliability and efficiency?

Forward through an Optimal Area

• The problems:– For each node, generating the optimal path from sink to it

in distributed manner– Forward downwards along the predefined optimal path– Nodes around the optimal path help to forward– Guarantee both efficiency and reliability

Forwarding downwards means forwarding from sink to an individual node

Our weapons• Path coding

– Encoded optimal path from sink to each node– Binary string implies the relationship between

paths– Prefix-matching process for forwarding selection

• Opportunistic forwarding– Closer and earlier wake-up nodes help to forward

Design of TeleAdjusting• Overview of design

– Generating path code– Exploiting opportunistic forwarding

9Upstream node denotes the next node in the path from it to the sink, and upstream nodes denote all nodes in the path from it to the sink.

Encoding Path• Concept of path code

– Reverse path address– 0-1 bit string with valid code

length – Encoding certain relationship

with other nodes– Parent’s code is the prefix of

children nodes’ codes

One valid bit

A and M are S’s children nodes, they set S’s valid codes as the prefix of their path codes.

The same prefix

The same prefix also indicates they are with the same parent.

• Position allocation

Encoding Path

Allocate a unique position to each children node

Parent node’s path code Position space

• Path code = Prefix code + bit string position– Prefix code: valid path code of parent node– Position: uniquely allocated by parent node

Generating path code

Encoding Path

• Position allocation– Deterministic allocation– Against allocation data loss/new joining child node

• Position request and allocation acknowledgement – Position maintenance– Space extension

Allocating a unique position to each children node

Parent node’s path code Position space

Generating path code

Opportunistic Forwarding• Opportunistic forwarding in TeleAdjusting

– Earlier wake-up & closer to destination will assist to forward

– Metrics : prefix length (logical distance to destination)• Information attached in control packet

– Expected relay (E) and the valid path code length (L), the appointed destination (D) and its path code (πD)

• Formalization– π: path code– F(π A, π B): the identical prefix length of the path codes of

A and B

Opportunistic Forwarding• Forwarding condition: S will relay the overheard control

packet IF any one of the three is satisfied– S == E, where E is the expected relay– F(π S, π D)> F(π E, π D)

– F(π N, π D)> F(π E, π D), N is a neighbor of S

• Forwarding strategies– Along the predefined path– Exploiting available opportunities

• Earlier wake-up relay• Closer to the destination

– Backtrack if a node cannot forward downwards– Against unreachable problem

Forwarding Strategy

• Along the predefined path

– Without exploiting opportunistic forwarding– Traveling along the encoded path

Encoded pathTraveling path

Forwarding Strategy• Exploiting available opportunities Encoded path

Traveling path

– Relay in the encoded path but closer than the expected relay to the destination

– Relay around the encoded path – At least one of the relay’s neighbors is closer to the

destination and in the encoded path

Efficiency: Opportunistic forwarding could exploit the earlier wake-up relays to forward control packet.

Reliability: Exploiting opportunistic forwarding will increase the ability of resisting network dynamics.

Forwarding Strategy• Backtrack

– If a node (E) can’t further forward towards the destination

Operation:• Set its potential relays (C and D) to

unreachable • Set itself to unreachable to the destination

– If unreachable • It will not actively forward the control packet

– Reset to reachable if any potential relay is reachable

Backtrack strategy will eventually find a path to the destination, otherwise, sink will set itself to unreachable.

Forwarding Strategy• Against unreachable problem

– Sink node is set to unreachable– Report to the controller– Controller selects a neighbor (K) of

the destination • Maximum prefix difference

– Sink forwards control packet to the appointed K– K forwards the control packet to the destination by

unicast forwarding

TeleAdjusting in protocol stack

Beneath application layerAbove MAC layerConnecting with link estimator and network layer

• Integrate TeleAdjusting into protocol stack

Implementation and Evaluation• Implementation of TeleAdjusting

– TinyOS-2.1.1– Built upon LPL– Interface for application layer

• Evaluation:– Large-scale simulation in TOSSIM– Indoor testbed, 40 TelosB nodes– Performance: reliability, efficiency– Comparison with Drip, quasi-RPL

Testbed Settings• 40 TelosB sensor nodes

– 22 nodes on the testbed board– 18 nodes scattered around the testbed

• Multi-hop networks• 512ms wakeup interval• Periodical remote control packet (10 minutes)

Simulation results

Path code length almost increases linearly with hop count, no matter tinght-grid or sparse-linear.

• Simulation setup– Sparse-linear: 5×45 grids with low gain– Tight-grid: 15x15 grids with high gain– Network topology construction: CTP+Trickle

Simulation results

• Convergent time = Path code generated time – routing found time

• Reverse path hop count vs. CTP hop count

Nodes can quickly generate its path code and associate different positions to children nodes almost without exceeding 20 beacons time.

For each node, the reverse hop count is very close to its CTP routing hop count.

Evaluation Results• Remote packet delivery ratio

– Two scenarios: interfered (WIFI) channel and clear channel – Comparison with Drip (reliability guarantee), quasi-RPL– Re-Tele is TeleAdjusting dealing with unreachable

problem

Structured approach (RPL) is susceptible to network dynamics, unstructured approach (Drip) guarantees the reliability of remote packet delivery.

The reliability of TeleAdjusting is close to Drip.

Evaluation Results• Transmission hop count vs. CTP hop count

• Average network-wide transmission count

Summary• Ready-to-use remote control protocol;

• Distributed coding based addressing scheme that encodes path information from sink to individual nodes;

• Exploiting opportunistic forwarding to guarantee both reliability and efficiency;

• Implementation of TeleAdjusting in TinyOS;

• Simulation and real testbed evaluation.

Thank you!

Daibo Liu 1 Daibo Liu 1, Zhichao Cao 2, Xiaopei Wu 2, Yuan He 2, Xiaoyu Ji 3 and Mengshu Hou 1...

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