Energy control wsn

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Energy efficient topology control for WSN using Online battery monitoring

Energy efficient topology control for WSN using Online battery monitoring

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  • 1. Chapter 1Analysis of Energy-efficientTopology control for WSN’susing Online BatteryMonitoring1.1 IntroductionWireless Sensor Networks (WSN) offers a broad range of applications, fromindustrial surveillance over security to medical monitoring. Another emerg-ing application of WSN systems is the monitoring of perishable or sensitivefreight in logistics. Energy is a scarce resource for this class of devices.Mostly running on batteries as energy source the improvement of energy-efficiency and power management are becoming ever important researchtopics. Because the power of sensor network for communication among thenodes depends on the battery energy of the node. As the node batterypower is very limited so it is very important to utilize the battery power ofthe sensor node and also life time of the sensor network s depends on thebattery power.1.2 Architecture for Wireless Sensor Network sys- temsThe basic elements of Wireless Sensor Networks are the network nodes ormainly referred to as motes. These motes consist of an RF-transceiver, amicrocontroller for protocol processing and sensor interfacing, sensors formeasuring.The use of flash memory allows the remote nodes to acquire data on com-mand from a base station, or by an event sensed by one or more inputs to 1
  • 2. the node. Furthermore, the embedded firmware can be upgraded throughthe wireless network in the field.The microprocessor has a number of functions including : • Managing data collection from the sensors. • Performing power management functions. • Interfacing the sensor data to the physical radio layer. • Managing the radio network protocol.A key feature of any wireless sensing node is to minimize the power consumedby the system. Generally, the radio subsystem requires the largest amountof power. Therefore, it is advantageous to send data over the radio networkonly when required. Figure 1.1: Wireless sensor node functional block diagram1.3 Energy consumption of WSN componentsA hardware platform based on the commercially available TmoteSky sys-tem by Moteiv Corporation is used here. These systems use the IEEE802.15.4-compliant RFtransceiverCC2420 and the 16-bit low-power micro-controllerMSP430F1611, both from Texas Instruments. The following mea-surements were made for the sending of a data message (41 bytes) and the 2
  • 3. reading of the internal temperature sensor in the microcontroller. The re-sults are shown in Table below : From the table We can say that adaptively Figure 1.2:tuning the output power of the transceiver and decreasing communicationoverhead may drastically improve energy efficiency of a single mote and thismay increase the network lifetime.1.4 Battery technologies for WSN systemsIn this case Batteries are the common energy sources for motes. Althoughenergy harvesting may be an option for certain application where there isenough energy in the surroundings of the WSN system. When sensor nodesare surrounded by air ,light etc then there is enough energy. Consideringlogistics as an application the amount of energy being harvested is much toolow to power a mote sufficiently. If we consider the discharge curves of themost common types of secondary cells, NiCd and NiMH cells behave almostequally with almost flat discharge behaviour while Li-Ion batteries have aconstant negative slope.There is a advantage of this feature of the Li-Ion cells discharge character-istic offers the advantage of computing the remaining capacity of the bat-tery when the actual load and the temperature of the battery are known.Li-Ion batteries are more favourable then using Ni-based batteries becausethe small slopes of Ni-based batteries impose higher demands on the mea-surement of the voltage as small changes in output voltage result in largerchanges in discharge capacity. Therefore, I-Ion cells were selected due totheir higher energy density and their behaviour towards discharge model-ing. 3
  • 4. Figure 1.3: Li-Ion and NiCd/NiMH battery behaviour.1.4.1 Battery monitoringThere are some advantages using Li-Ion batteries. These kind of batteriesare more favourable for modelling due to their higher negative slope. Thisenables the usage of the internal AD-converter of microcontroller of themote. It offers a sufficient resolution of 12 bits for the measurement of thebattery voltage.1.5 Circuitry and MeasurementsIn order to measurement setup it is required minimum additional hardwarefor the mote system. To verify this setup a series of measurements is takenunder controlled temperature using a constant load. As selected battery isThe Panasonic CGA103450A cell with a nominal output voltage of 3.6V.The results for 10 C and 10 C are also shown in figure given below andreflect the temperature dependency of the discharge behaviour.1.6 ModellingBy using these measurements, a simple numeric model is generated by divid-ing the discharge curve into two phases: first is normal operation and secondis post-cut-off. One can get the normal operation for the slightly decreasingslope. Post-cut-off is given just before the battery is empty. Both phases canbe described by a simple linear model as a set of four numerical parameters 4
  • 5. Figure 1.4: Measurement setup and resulting graphs for 10 C and 10 C.Figure 1.5: Approximated discharge characteristics with Varying Tempera-ture 5
  • 6. c0 to c3, the temperature v and the output voltage of the battery Vout inthe following equation :C = (c0 + c1 v) + (c2 + c3 v) Vout. (1) Furthermore a cut-off capacityis defined which clearly marks the border of the two operational phases.Ccutoff = Cbase + c4 .v........................................................... (2)Here Cbase is a numerically found base capacity and constant c4 is theslope of the cut-off capacity with varying temperature ’v’.The switch-overbetween these phases is realized by using a different parameter set (c0 to c3)for Eq. (1). The maximally usable capacity can be calculated by defining anend-point voltage which is used in adding Eqs. (2) and (1) with the cut-offparameters.The endpoint voltage dependable. For example it is dependent on the usedvoltage regulator type and the minimum system supply voltage. It can beobtained by simply subtracting the current capacity from this maximumcapacity, the residual capacity is calculated.1.7 ConclusionIt is an emerging field of research and that is the need for information onresidual energy in wireless sensor networks. The temperature behaviour ofbatteries has strongly affect the residual energy and thereby the performanceof the network. Based on a standard platform, a simple measurement setupand acomputationally simple linear model was developed which is capableof calculating the residual energy as a function of temperature directly onthe mote. 6
  • 7. Bibliography[1] Advances in Radio Science Adv. Radio Sci., 5, 205208, 2007, www.adv- radio-sci.net/5/205/2007/[2] Wireless Sensor Networks: Principles and Applications Chris Townsend, Steven Arms MicroStrain, Inc. 7