energy efficiency in wireless sensor network(ce 16 aniket choudhury)

ENERGY EFFICIENCY IN WIRELESS SENSOR NETWORK

PREPARED BY-ANIKET CHOUDHURY1st Sem ME CE LJIET

TOPICS COVERED IN LAST SESSION…

• INTRODUCTION

• COMPONENT OF SENSOR NODE

• ARHITECTURE OF SENSOR NODE

• GENERAL APPROACHES TO ENERGY CONSERVATION

• ENERGY CONSERVATION SCHEMES

• DUTY CYCLING

DATA DRIVEN APPROCHES…

CONT…


CONT…

DATA PREDICTION[1]

•Data prediction techniques build a model describing the sensed phenomenon, so that queries can be answered using the model instead of the actually sensed data.•There are two instances of a model in the network, one residing at the sink and the other at source nodes.•The model at the sink can be used to answer queries without requiring any communication, thus reducingthe energy consumption.•Source nodes is used to ensure the model effectiveness.


CONT…

Stochastic approaches[1]

• Techniques belonging to the first class derive a stochastic characterization of the phenomenon, i.e. in terms of probabilities and/or statistical properties.

• Two main approaches of this kind are the following. On the one hand, it is possible to map data into a


random process described in terms of a probability density function (pdf). Data prediction is then obtained by combining the computed pdfs with the observed samples.

• On the other hand, a state space representation of the phenomenon can be derived, so that forthcoming samples can be guessed by filtering out a non-predictable component modeled as noise.


CONT…

TIME SERIES FORECASTING[1]

•A typical method to represent time series is given byMoving Average (MA), Auto-Regressive (AR) or a Auto-Regressive Moving Average (ARMA) models.•These models are quite simple, but they can be used in many practical cases with good accuracy.• More sophisticated models have been also developed (as ARIMA and GARCH), but their complexity does not make them suitable for WSN.


CONT…

ALGORITHMIC APPROCH

• Finally, the last class of data prediction techniques relies on a heuristic or a state-transition model describing the sensed phenomenon.

• Such algorithmic approaches drive methods or procedures to build and update the model on the basis of the chosen characterization.

ENERGY EFFICIENT DATA AQUISITION…

CONT…

• An emerging class of applications is actually sensing constrained. This is in contrast with the general assumption that sensing in not relevant from the energy consumption standpoint.

• In fact, the energy consumption of the sensing subsystem not only may be relevant, but it can also be greater than the energy consumption of the radio or even greater than the energy consumption of the rest of the sensor node . This can be due to many different factors.



ADAPTIVE SAMPLING[1]

• As measured samples can be correlated, adaptive sampling techniques exploit such similarities to reduce the amount of data to be acquired from the transducer. For example, data of interest may change slowly with time.

• In this case, temporal correlations (i.e. the fact that subsequent samples do not differ very much between each other) may be exploited to reduce the number of acquisitions.

• A similar approach can be applied when the investigated phenomenon does not change sharply between areas covered by neighbouring nodes. In this case, energy due to sampling (and communication) can be reduced by taking advantage from spatial correlations between sensed data.

• Clearly, both temporal and spatial correlations may be jointly exploited to further reduce the amount of data to be acquired.


HIERARCHICAL SAMPLING[1]

• The hierarchical sampling approach assumes that nodes are equipped with different types of sensors. As each sensor is characterized by a given resolution and its associated energy consumption, this technique dynamically selects which class to activate, in order to get a trade off between accuracy and energy conservation.


MODEL-BASED SAMPLING[1]

• Model-based active sampling takes an approach similar to data prediction. A model of the sensed phenomenon is built upon sampled data, so that future values can be forecasted with a certain accuracy. Model-based active sampling exploits the obtained model to reduce the number of data samples, and also the amount of data to be transmitted to the sink – even though this is not their main goal.


MOBILITY BASED ENERGY CONSERVATION SCHEME

CONT…

SOLAR RECHARGING OF CELLS

CONT…

• Solar cell works on the principle of photovoltaic effect[2]. Sunlight is composed of photons, or "packets" of energy.

• These photons contain various amounts of energy corresponding to the different wavelengths of light.

• When a photon[2] is absorbed, the energy of the photon is transferred to an electron in an atom of the cell.


CONT…

The basic component of a solar cell is pure silicon.


CONT…


CONT…

Specifications Of Charger[3]

• Uses high-efficiency mono crystalline silicon.• Solar panel: 5.5V/1000mA • Output voltage: 5.5V • Output current: 300-550 mA• Time taken to charge mobile phone using the

charger : about 60mintues for typical mobile.


CONT…

BLOCK DIAGRAM:


CONT…

• In the above diagram it is given that the charger is connected to the 5V regulator which in turn is connected to the solar panel.

• The charger is connected to the cells all the time which powers the sensors.

• By doing this the cells of the sensors will be charged constantly.


CONT…

• This will help the cells of the sensors to last long before being dead.

• There are various advantages of using solar panels which are as follows:

• Solar chargers will offer more Battery life as high voltages are not developed.

• Adaptability is high.• Flexibility of Solar mobile charger is high.

GAP ANALYSIS…

CONT…

• After reviewing 5 listed papers we can say that the battery life of the wireless sensors can be improved by Data Driven Approach and by connecting solar panels, so that the battery of the sensor can be continuously charged.

• How ever as ever coin has two sides there are some flaws in these methods as solar panels can increase the cost of the panel.

• Solar panels are inefficient during winters and monsoon time.

REFERENCES

CONT…

1. DATA DRIVEN PERFORMANCE EVOLUATION OF WIRELESS SENSOR NETWORK.

2. SOLAR BATTERY CHARGER FOR NIMH BATTERY.3. SOLAR POWERED BATTERY CHARGING SYSTEM.4. SOLAR POWER FOR WIRELESS SENSOR NETWORK.5. SOLAR POWERED WIRELESS SENSOR NETWORK.

THANK YOU…

energy efficiency in wireless sensor network(ce 16 aniket choudhury)

Engineering