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Min Song 1, Yanxiao Zhao 1, Jun Wang 1, E. K. Park 2 1 Old Dominion University, USA 2 University of Missouri at Kansas City, USA IEEE ICC 2009 A High Throughput.

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Presentation on theme: "Min Song 1, Yanxiao Zhao 1, Jun Wang 1, E. K. Park 2 1 Old Dominion University, USA 2 University of Missouri at Kansas City, USA IEEE ICC 2009 A High Throughput."— Presentation transcript:

1 Min Song 1, Yanxiao Zhao 1, Jun Wang 1, E. K. Park 2 1 Old Dominion University, USA 2 University of Missouri at Kansas City, USA IEEE ICC 2009 A High Throughput Load Balance Algorithm for Multichannel Wireless Sensor Networks

2 Outline Introduction Network Model and Problem Statement Load Balance Algorithm  The Operation of Schedule Period  The Load Balance Algorithm  Throughput Analysis Simulation Results

3 Introduction Multi-channel and multiradio availability have been introduced to be promising ways of improving the performance of wireless sensor networks (WSNs). In multi-channel WSNs  How to allocate multiple channels to achieve efficient global behavior and maximize the contribution of each base station.

4 Introduction Cognitive radio  Sensor node can change its radio operating parameters to communicate efficiently. In a typical WSN  Traffic load is often unevenly distributed among base stations. We propose a cognitive load balance algorithm for single-hop multi-channel sensor networks.

5 Network Model and Problem Statement Association between nodes and base stations 3x25 X1,1 X1,2 … X1,25 X2,1 X2,2 … X2,25 X3,1 X3,2 … X3,25 : All nodes associated with BS b

6 Load Balance Algorithm  The Operation of Schedule Period  The Load Balance Algorithm  Throughput Analysis

7 Load Balance Algorithm The Operation of Schedule Period  (1)BS : beacon message for synchronization  (2)Nodes : sends RTS to BS  (3)BS : broadcasts a schedule message includes transmission order and time (2) (3) (1) i j

8 Load Balance Algorithm The Load Balance Algorithm  The total load of BS on channel i A set of nodes that communicate in channel i : load of node n using channel I at time k i j

9 Load Balance Algorithm The Load Balance Algorithm Situation Average load among all BS : number of BS over-loaded under-loaded i j

10 Node n Load Balance Algorithm The Load Balance Algorithm The switch probability for node n from channel i to channel j. i j The switch load from channel i to channel j.

11 Load Balance Algorithm The Load Balance Algorithm i j New load on channel i after switching load i->j j->i overload overlap

12 Load Balance Algorithm The Load Balance Algorithm  JAIN INDEX i j Load is optimally balanced : JAIN INDEX = 1

13 Load Balance Algorithm The Load Balance Algorithm  JAIN INDEX i j After switching load from BS i to BS j

14 Load Balance Algorithm The Load Balance Algorithm  JAIN INDEX i j

15 Load Balance Algorithm The Load Balance Algorithm  JAIN INDEX i j

16 Load Balance Algorithm Throughput Analysis  Throughput without load balance average lengths of busy slot average lengths of idle slot lengths of schedule period One interval has m time slots. the mean number of packet in Poisson distribution

17 Load Balance Algorithm Throughput Analysis  Throughput with load balance packet arrival rate

18 Simulation Results Base stations and nodes : one radio. Nodes are randomly deployed around base stations. The load traffic of sensor node : Poisson distribution. ξ =0.005

19 Simulation Results ξ = ξ = 0.05

20 Simulation Results 50 nodes 100 nodes ξ = 0.005

21 Simulation Results

22 Conclusion We have presented a novel load-balance algorithm for multi-channel sensor networks. Based on the state of load distribution of all base stations  Algorithm is able to dynamically adjust the communication channel of sensor nodes  From over-loaded channels to under-loaded channels. Both theoretical analysis and simulation results  Algorithm can significantly improve the system throughput


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