學生 :黃兆祺學號 :79864018教授 :溫志煜

INTRODUCTION

Self-Maintenance Ecological System Of Artificial Ecological System On Sensor Networks

CONCLUSION

The sensor nodes will grow in thousands of number at sensor networks in the future.

In order to save lots of human resource, we need a system to maintain the sensor networks by themselves.

We proposed a model of Ecological Balancing include:

Sensor Nodes Dynamics Model (SNDM)

Sensor Nodes Ecological Model (SNEM)

Population Growth Limit Model (PGLM)

The SNDM is used to implement the diffusion

The SNEM is used to maintain the sensor nodes.

The PGLM can control the sensor network density.

With these models, we can create an ecological balance environment with automatic recharge, recycle and quantity control.

It is desired to keep these sensor nodes reach the blanket coverage and maximize, two species(Predator and Prey) exist and ensure they will not die out.

These are platforms of Predator (left) and Prey (right).

The Prey can reconnoiter and collect information in the environment, like the temperature or humidity.

The Predator can patrol the environment and search the failed or low battery Preys. When the Predator found that, it will take the Prey back to the Recycle Center for repairing or recharging.

Prey Center produces Preys (A).

Predator Center produce Predators (B).

Predators catch the low batter or failed Prey (C).

Predators bring the low battery Prey back to the Recycle Center(D).

The SMES has several logical parts: (1) Preys Produce Center (2) Predators Produce Center (3) Recycle Center (4) Control Center

The Control Center included Predator Produce Center, Prey Produce Center and Recycle Center.

Each Prey node will diffuse into the environment as random by a potential field and keep equilibrium in a fixed distance with each other.

If they found there are some places have not been deployed, they will continue diffuse or call the Prey Produce Center to send more Prey nodes.

Similarly, the Predator nodes will patrol the whole space.

When the energy of the Prey node is lower than the energy level, it will set a “Low Energy” flag. such as an electrical indication or a mechanical indication.

If the Predator receives this flag, it will bring the Prey back to the Recycle Center.

If the Predator’s energy is going to use up, it will back to the Control Center for recharging.

This model use Lennard-Jones potential function based on the molecular dynamics to diffusion Prey nodes.

These nodes can communicate with its neighbors through some wireless communication protocol.

ε is Characteristic energy. σ is characteristic length

rij is described distance form particles i to j.

The beginning deployment of sensor nodes

After 500T

After 1500T

After 7500T

After 43500T

The final status

Q′(t) = aQ(t) – bQ(t)P(t) P′(t) = -cP(t) + vbQ(t)P(t)

Q′(t) is the number of Prey node P′(t) is the number of Predator node

“a” is growth rate of Prey. “b” is the death rate of the Prey node. “c” is the death rate of the Predators. “v” is the conversion efficiency of Prey into Predator.

L1 : a – bP(t) = 0 L2 : -c + vbQ(t) = 0

Region I: the Prey’s population.

Region II: both population of node group’s.

Region III: the Prey’s population decreases while the Predator’s population increases.

Region IV: both node groups’ population.

P0=10, c=0.9, v=0.5 Q0=10, a=1, b=0.1

P0=10, c=0.6, v=0.5 Q0=10, a=1, b=0.1

Q′(t) = aQ(t)[k – Q(t) / k] – bQ(t)P(t) P′(t) = -cP(t) + vbQ(t)P(t)

Q′(t) is the number of Prey node P′(t) is the number of Predator node

“a” is growth rate of Prey. “b” is the death rate of the Prey node. “c” is the death rate of the Predators. “v” is the conversion efficiency of Prey into Predator. “k” is the capacity that represents an upper limit on node

population density.

The population of sensor nodes.

The growth rate of sensor node’s population.

P0=10, c=0.2, v=0.5 Q0=10, a=1, b=0.1, k=50

P0=10, c=0.8, v=0.5 Q0=10, a=1, b=0.1, k=50

A Predator node spends its time on two kinds of actions:

1) Searching for Prey node. 2) Prey node handling which includes:

localization and catch.

T = TSearch + THanding

THanding = QITH

QI = IQ(t)TSearch

T = TSearch + THanding = QITh + QI / ( IQ(t) ) => QI = IQ(t)T / ( 1 + IQ(t)Th )

“QI” is the number of prey consumed by predator. “T” is total available searching time “Th” is Handling time “I” is Searching efficiency

Substituting SNEM and PGLM

Q′(t) = aQ(t)[k – Q(t) / k] – [IQ(t)T / ( 1 + IQ(t)Th )]P(t) P′(t) = -cP(t) + v[IQ(t)T / ( 1 + IQ(t)Th )]P(t)

P0=50, c=0.4, v=0.5 Q0=50, a=0.9, I=0.012, k=200, T=0.5

P0=50, c=0.4, v=0.5 Q0=50, a=0.9, I=0.02, k=200, T=0.5

P0=50, c=0.4, v=0.5 Q0=50, a=0.9, I=0.025, k=200, T=0.5

In this paper we developed an automatic system for managing and maintaining sensor node behavior.

Self-Maintenance Ecological System (SMES) can reach the goal of automatic recharge, recycle and quantity control in order to keep two sensor nodes exist and ensure not die out.

we can save a lot of human resource needed and cost on maintain sensor nodes with quantity control, better blanket coverage, less node number change. We also can update those sensor nodes easily by the SMES.