後卓越進度報告後卓越進度報告

蔡育仁老師實驗室2006/11/13

Distribute Source Coding (DSC) in WSNs Distributed source coding (D

SC) is a data compression technique to reduce the redundancy without direct communication among sensor nodes. Sensors are encoders to individually encode their received information related to a single event.

E.g., Slepian-Wolf method is a widely used distributed source coding algorithm.

1X

2XNX

3X

1NX …

…

…

iX : received signal

: Sensor

: Sink

Slepian-Wolf Distributed Source Coding

4 1 2 3, ,H X X X X

3 1 2,H X X X

2 1H X X 1H X

11 ,, NN XXXH

1 1 2, ,N NH X X X

Decoding Order

DSC with Random Access — Assumptions & Goals Performance of a DSC scheme in a slotted ALOHA

WSN has been investigated. Consider a cluster with N sensors and a sink. Node i transmit a

packet in a slot with probability Pi.

If the packet of node i corresponding to an event is received successfully, this node will not transmit other packets for this event again.

The packet of node i can be reconstructed if the packet of node 1 to node i–1 was received successfully.

Goal — Find optimal probability Pi based on Minimize the decoding latency Minimize the decoding loss rate

DSC with Random Access —Analysis

Traffic load analysis Initial total traffic load

The average remainder traffic at the k-th slot can be calculated iteratively and approximately

Average number of successfully reconstructed packets at the K-th slot

0 10 20 30 40 50 60 70 80 90 1000

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Simulation Results Numerical Results

G = 0.5G = 1G = 1.5G = 2

Ave

rage

Tra

ffic

L

oad

Time Slots M

Traffic Load Analysis

DSC with Random Access — Future Work Find the exact analytical form and the statistics of the

decoding delay and decoding loss.

Take packet lengths into consideration to allocate the optimum Pi for packets with different lengths.