Thermal Management In Biological Wireless Sensor Networks

They are the type of wireless networks that are basically composed of biological sensors which are basically implanted in the bodies of animals and humans and control their biological body movements and are monitored by scientists who determine their body language and the body system. They are basically developed because of the discoveries and new technology in the field of healthcare. They are so mixed in the body as if they are just like enzymes and antibiotics which are already present in the body of the animals and humans. Their temp in many cases increase in the body when they are charged but the amount of heat produced is so minor that the heat can be overcome by the body receptors.

There are many biological sensor which are generally implanted in the body and many are worn outside the body and these sensors are seen by naked eyes. A good example of the above sensor could be geodesic sensor which can be seen by the naked eyes as it is worn over the head in order to monitor the brain monitoring of the patient who may be suffering any problem related to brain. These sensor are generally in the shape of cap and can be easily worn on the top of head of the patient. When it comes to external sensor there are many sensor which are implanted in the body of the patient just like an enzyme or antibiotic in the body. The implanted sensor example could be the glucose biosensor which is used to check the diabetes of the patient. in this case these sensor is implanted in the body of the patient and on monitor the examine the patient condition. Nowadays these sensors are not injected but just takes a sample of blood of the patient and examine it and gives the report. Below is the example of such type of sensor.

There are some drawbacks in Biological sensor wireless network as when they are operated for a long time they just increase the temperature and due to this temp or heat generation can be more hazardous to health as it can damage the cells of the body and can be very very harmful for the body. So in order to decrease this condition we develop some techniques to manage this change in the thermal activity and one such technique is dynamic sensor scheduling which is the best way to reduce this temp change or thermal management.

There is a random channel that is present between biosensors and the base or the area where this data is collected and processed and in this paper there is a discussion about this topic in what manner we can just process the system in order to reduce the thermal conductivity or the thermal change. We develop an MDP model in which we just discuss different mathematical problems to solve the thermal point problem in wireless sensors. The obtained result can be used to maintain the relationship between the temperature change and temperature required to work the wireless sensor system work properly. In this paper the discussion will go in such a way that firstly there will be a discussion on the topic of background information required to solve the problem. Secondly the language and the important terms required and thirdly but not the least the system which is under process will be discussed. Then the MDP model will be presented after that how can the size of MDP can be reduced and at last the result will be displayed in the stats.

BACKGROUND

In this section we mainly consider the topics on mainly focuses temperature change and the calculation required to check the temperature change in the MDP model.

CALCULATION

There are signals namely RF signals which are used for producing communication between wireless networks and the signals that are produced by magnetic lines and electric fields and the working is quite simple ass the reaction gets absorbed and gets converted which can make itself settle in the temperature minimum required by the sensor to work good. There is a big role on the body system of the human as when the temperature of sensor increases and tissue increase there temp which simply results in damage of the tissues and cannot be converted by the the blood system of the body once it extends the temperature. The unit of specific absorption rate(SAR) that is the radiation absorbed by the body is generally calculated in the terms of W/kg(watt per kilogram).

SAR is basically a point quantity as it changes from place to place. It is basically an antenna for the sensor and on research we find that when there is increase in the temp the tissue gets destroyed and 8W/kg is passed for 15 minutes can be very very harmful for the tissues and will surely destroy the tissue. There is a equation namely the pionnet equation is basically used to calculate the temperature in the body due to heating. Basically we just divide the equation in the cells to form and is basically evaluated in the grid of cells. We just consider the cells temp surrounding is equal to 37°C which is just equal to the normal body temperature. The basic model of this is MDP is basically divided into subparts and these parts are responsible for the variation Basically MDP is a time dependent quantity which basically depends on time. The elements are:

• System states
• Possible actions taken at each part
• The cost factor at each system part
• Next possibility of transition

There is a rule at each part for choosing a correct a particular state in the each part of the time t and if it completely depends on state of the system than it is termed as a stationary policy.

There is a interesting class of MDP where there is a terminating state. In order to take the output for this problem or to find the problem’s solution we just optimize the function and we include the lifetime as the one of the parameter. And if we need to find the policy or the equation of we have to solve the following equation Vn(s)=maxa∈A(s)[f(s,a)+∑s′∈Sℙ(s,s′,a)Vn-1(s′)] Where n represents iteration index S is the system states A(s) is the actions that are possible f is the cost P is the the probability state V(s) is the optimal value. The above equation can be solved by the means of the iteration but these algo are of no use when there is large equation or system states are large. Another solution is to use the system aggregation.

SYSTEM MODEL

It shows that there are basically 3 biosensors that are fitted in the body of the patient and in order to maintain the movement of the body or the tissues of the body of the patient. There is a basically wirless network that connects the body with the point where there is information stored. There is a biosensor that is used for the current state and the signals are transferred and they are transferred on the time.

In the initial time a biosensor is selected and a particular time slot is given to it but as the time changes its point gets changes and they are changed on the basis of transmittion energy required which is basically defined by the wireless networks. Due to this the temp of the neighbouring sensors temp increase because of the temp changes in the wireless network and the non neighbours does not have a direct contact with the biosensor and there is no increase in the temperature. We can use pennes equation but due to some restrictions and large equation we cannot put the system here and we can see from the above context that the temperature increase is directly propostional to the change or the consumption of the energy in the biosensor. From the above discussion it can be generated or concluded that the heat generated is basically because of the local radiation and the tissues that are present near it gets destroyed and because of the heat by the biosensors. There are many equations that can be used to calculate the sensor scheduling to thermal management and can be solved by different means either by pennes equation or by different scientists researchers equation to get the final product. There is another type of sensor that is compact and voltage scalable sensor.

As we have discussed above that we want to calculate new accurate modification to calculate the thermal stability or thermal management but when it come to find the accurate type of sensor we are unable to find the exact value or the appropriate value of the sensor stability and in order to find so we have designed this type of sensor known as compact and voltage sensor. If we think that placing the sensor near the hotspot will help the accuracy but it is not good as they have inside blocks. If we think of using on chip sensor that we should know that as the time evolves in semiconductors in last decades but there is also a case that power density has also increased in recent times so there is dynamic thermal management(DTM) which enables the use of multiple transmitters in the form of read only form and converters which convert analog to digital signals and by doing so we just maximize the efficiency of the chip.

Nowadays DTM have low frequency because of the 2 main reasons one is process and voltage variation and another one is difference between hotspot and nearest sensor. Its efficiency can be increased if we improve the changes in temperature and controlling them which will surely reduce the response time and the performance of the circuit will be improved. The accuracy of the themal on chip has a great reference on the reliable DTM. However when it come to in built sensors then they are accompanied by the noise and some fluctuation in the voltage which result in the deviation of the temperature from the actual point. In the worst case temperature value can go to very low point and deviation can be very high. Therefore one cannot blindly trust the sensor network as it is just equivalent to trusting a false alarm.

When there is a unpredictable behavior with the noise which result in the deviation in the temperature, continuously monitor the on chip thermal profile we contruct a on die ring oscillator and is known for around 20 years and it generally contains N inverters and a counter and the output will give the frequency of the oscillator[image: An external file that holds a picture, illustration, etc.