Designing Wireless Sensor Network with Low Cost and Low Power S. S. Sonavanea, V. Kumarb, B. P. Patilc a Department of Electronics and Telecommunication, Rajarshi Shahu College of Engineering, Tathwade, Pune-411033(M.S.), India [email protected] b Department of Electronics and Instrumentation, Indian School of Mines University, Dhanbad-826004, India [email protected] c Department of Electronics Engineering, Maharashtra Academy of Engineering, Alandi, Pune ( M.S.) [email protected] Abstract- Sensor network is receiving considerable attention as one of the key technologies to keep track of the parameters in the industrial field. Wireless sensor networks (WSN) integrate sensor technology, embedded technology, distributed information processing and network communication. The nodes of WSN serve the functions of perceiving and routing. Power consumption is the key factor affecting the longevity of nodes in practice. In this paper, we propose a new WSN node using MSP430 and nRF24L01. This operates in license free 2.4 GHz ISM band.. The node senses the event for small amount of time 7 goes to sleep mode for long interval of time. This methods and ultra low power hardware reduces the WSN power consumption. A low power wireless sensor network node is designed and tested. Result shows that this method is adaptive, feasible prior to the other methods. Index Terms-Wireless sensor consumption, MSP430, nRF24L01. 1. networks, Low power INTRODUCTION Wireless sensor network (WSN) [1] is an emerging concept and technology that opens up new application fields. Applications such as battlefield surveillance, large-scale environmental monitoring and target tracking in a large area are made possible by deploying large number of nodes that are small in size and cost-effective. WSNs integrate sensors, wireless communications, embedded computing, MEMS (Micro Electro Mechanical system), microelectronics and other technology to monitor collaboratively real-time, perceive and collect environmental information [2,3]. Then the information is handled and transmitted to meet the needs of users through specific network technology. The tremendous prospects are arising from the application of the military, industrial, commercial and academic expert’s widespread concern. Network sensor nodes collected information on the spot, after the necessary processing and through the network will feed data to the required target. Sensor technology, sensor network have been 978-1-4244-3805-1/08/$25.00 ⓒ2008IEEE recognized as the most important study. Application of the many special occasions, the sensor network nodes, in particular, wireless sensor network nodes require the use of portable power source (battery) power [4,5]. When the power is exhausted after, if not replacement for charging the battery or power source, longevity depends on the power sensor node. We must try to reduce power consumption of nodes to extend reliably working hours. Low-power design is therefore necessary to focus on network-based sensor design problems [6,7]. The paper is organized as follows. In Section 2, we present the background on wireless sensor networks and relevant system reliability metrics. System powers of sensor nodes are presented as well. The general requirements for the proposed infrastructure are also outlined. Hardware design of low power sensor nodes is explained in Section 3. A case study of a WSN node based on the nRF24L01 controlled by Texas Instrument MSP430 microcontroller family is also examined. 2. BACKGROUND A wireless sensor network Node can contain various sensors and actuators that are used to collect the data and control physical processes. The collected data is transferred to the user through the network that can include Internet segments. Besides collecting the data and controlling actuators, a node may need to perform some computation on the measured data. Direct communication between individual nodes can also be required. The task manager node performs tasks in data storage, analysis and display; in addition the control and the interface to the backbone interconnect. Due to the less stringent limitations, it can perform significantly more complex tasks than WSN nodes. 2.1 System Powers of Sensor Nodes The nodes of WSN are characterized by the limited voltage supply, the limited communication abilities and ICON 2008 computing power. They are closely coupled with the physical world and massive deployment. In order to accurately and timely access to information, we must rely on the collaboration between the nodes. A great number of MEMS sensor nodes can play a role in the integrity and comprehensive only by creating a network of low-power radio communication technologies. So sensor networks as an autonomous system that involves many matters, such as location and time synchronization, coordinated signal processing, communication patterns and protocol, network capacity and longevity, task allocation control, adaptation, middleware and many other issues. Energy is the longevity of practical decisions sensor network, therefore, WSN nodes requires low power consumption. Unlike other networks, the nodes of WSN are allocated in a self-organizing manner. Therefore, the network must have a very strong performance of self-organizing, adaptability robustness. Furthermore, the network protocol and algorithm must be distributed. Also, WSN is a resourceconstrained network in the energy and the nodes has a limited ability in computing power and storage capacity. In particular, the energy is limited, since once the node's power supply depletion will affect the realization of the entire network function. The network nodes are often one-time use, or restrictive conditions, the battery is not always possible to replace sensor nodes. These decisions need to be used several years the network must be designed to improve the energy efficiency of their prime objectives. As a node of a network application, it is necessary for a sensor network to complete the information gathering from the industrial spot but also to receive PC operating instructions and make communications with PC or other nodes. Network sensor module power consumption comes from unit consumption by the sensor signal acquisition of processing modules and power transmission components. 3. HARDWARE DESIGN OF LOW-POWER SENSOR NODE 3.1 Overall Design The sensor nodes consist of the sensor unit, the processor, the wireless communication module and the energy supply unit as shown in Fig.1. Sensor unit is responsible for monitoring regional information collection and data conversion. The processor unit is used for the control of the entire operation of sensor nodes, storage and processing of data collection itself, as well as other data sent to the nodes [8]. The wireless communication module is applied with other sensors for wireless communications and information collection and exchange control data acquisition. The energy supply unit is required for the operation of sensor nodes, usually batteries. Fig.1 Block diagram of the Wireless Sensor Node The power consumption module in the sensor nodes includes sensor modules, processor modules, wireless communication modules. With the advances of integrate circuit technology, processor and sensor modules have a very low power consumption. The majority of power consumptions occur in wireless communication module, as shown in Fig. 2. Information transmission in sensor nodes takes more power consumption than the implementation of calculating. The power caused by one bit of information for 100-metre transmission distance is equivalent to that needs of the implementation of the 3000 instructions calculation. In order to reduce power consumption from the sensor network hardware, it is firstly necessary to select appropriately the sensor system technical specifications. There are many technical performance indexes related to power consumption in a system, such as velocity, drive ability, stability, linearity, etc. The improvement of these indexes is often to raise the power consumption of the circuit. Current (mA) Fig. 2 Current draw of node subsystem Therefore, in accordance with the characteristics and needs of sensors, to select appropriately the indexes, in some cases, even to lower certain non-key targets with the purposes of lower system power consumption. With the indexes identified in the case, we can consider controlling the power sensor network from the two aspects: reducing the power consumption by signal acquisition modules and that by the signal processing [9]. The system hardware architecture diagram is shown in Fig. 3. The nRF24L01 is controlled by the MSP430 microcontroller through the Serial Peripheral Interface (SPI) port and a series of digital I/O lines with interrupt capabilities. The Telos platform features a 10-pin expansion connector with one UART (Universal Asynchronous Receiver Transmitter) and one I2C interface, two generalpurpose I/O lines, and three analog input lines. With the capture function of MSP430, the sensor signals are acquired. After data processing, the signals are preserved into the processor and simultaneous sent to the network through wireless module. When there are no data processing, system will automatically turn into dormancy to reduce power consumption. 3.2 Processor Module Design Processor module is the core for the calculation of wireless sensor nodes. All the equipment control, task scheduling, energy calculations, functional coordination, communication protocols, data integration and data transfer and the process will be completed with the support of this module. Therefore, it is essential to carry out the choice of processor for sensor nodes design. Fig.3 Interfacing of various components with MSP430 In a low energy consumption design [10], the processor used by sensor nodes should meet the low power consumption and support sleep mode. Power consumption from the main processor depends on operating voltage, system clock, the complexity of internal logic and production technology. The consumption is proportional to the higher operating voltage and the faster clock. Sleep mode is directly related to the operation life of nodes. To maintain the normal operation state for a long time is relatively difficult according to the level of development of battery technology. So WSN systems are needed to stop at the waiting time or sleeping time. This requires that the processor must support the ultralow-power consumption sleep mode. The processor used in this paper is MSP430F1611 [11]. The MSP430 series microcontroller integrates a large number of external components. As a outstanding representatives microcontroller with a low voltage, low power consumption and high performance microcontroller of it has been widely applied in the portable power equipment the appliance with battery supply. Therefore, to fully utilize the features of low power MSP430 microcontroller and design of the minimum power MSP430 portable system is the goal that the designers pursue. MSP430 microcontroller has a RISC frame of 16 bytes and integrates a large number of registers and data memories. In this paper, MSP430F1611 (10KB RAM and 48KB FLASH) was adopted and its RAM can also participate in its operations. In terms of operational speed, MSP430F1611 microcontroller can be driven at 8 MHz crystal with 125μs instruction cycle. MSP430F1611 chip can work in the voltage range of 1.83.6 V. Only data in RAM to maintain a low power mode, current consumption is only at 0.1μA. It has five energy saving mode. The current consumption in different modes is between 0.1 to 400μA and only at 0.8μA in the waiting mode. Under normal circumstances CPU can be placed in the waiting mode. The features of MSP430F1611 chip are shown in Table 1. Parameter Min Normal Max Operating voltage for 1.8 3.6 program Execution (V) Operating voltage for 2.7 3.6 Flash memory compiling (V) Working Temperature oC -40 85 Min. Crystal frequency 32.768 (KHz) Operating current at 500 600 Vcc=3V, 1MHz (μA) Idle state of LPM3 2.6 3 Vcc=3V, 32.768 KHz (μA) 6 Wake-up from LPM3 state (power save pattern) (μs) Table1 The performance of MSP430F1611 3.3 New Wireless Standard Along with the rapid development of communication technology, people want to communicate in nearby meters. So the concept of Personal Area Network (PAN) and Lowrate Wireless Personal Area (LR-WPAN) begin to appear. WPAN networks establish wireless connection and communication for the equipments in close-range. we propose new standard for the development the wireless personal area network. The standard aims at low energy consumption, high transmission rate and low cost and designs for families or individuals with different between the low speed Internet equipment to provide uniform standards. features: [1] Data rates of 1 Mbps or 2 Mbps. [2] Two addressing modes; 16-bit short and 64-bit IEEE addressing. [3] CSMA-CA channel access. [4] Fully handshake protocol for transfer reliability. [5] Power management to ensure low power consumption. 3.4 Low Power Design of Communication Module As wireless communications WSN energy accounted for the main part of the whole, therefore, the energy management system for wireless transceiver is very important. It takes the following measures to reduce energy loss of communication module. There are four states (sending, receiving, idle and standby) existing in wireless communication module. Wireless communication module in the idle state will monitor the use of wireless channels, to check whether there are any data to receive and close communication module in the sleep state. As shown from Fig. 2, we can figure out that wireless communication module in the sending mode takes the largest energy consumption, while the energy consumption, which is slightly lower than the sending state, is nearly equal in the idle state and the receiving states. The minimum energy consumption occurs in the sleep time. Time spent in any one of these three states is referred as awake time. In sleep mode, the transceiver consumes significantly less energy. Thus, energy can be significantly saved if the transceiver is kept as much as possible in sleep mode. An important goal of a network protocol is to increase the percentage of sleep time of the radio. Clearly, this goal should not be achieved by completely disregarding delivery rate and communication latency. These metrics are basic to evaluate any network protocol designed for wireless sensor networks. Wireless channel quality plays a great impact on the signal transmission quality. Considering many factors, the energy consumption of communication is proportional to the square root of communication distance. Along with the increase in distance communications, energy consumption will increase drastically. Therefore under the premise of meeting the communication rate, the distance of single-hop communication should be reduced to a minimum. The complete module with the sensor board is shown in Fig.4. Fig.5 Front side of PCB of MSP430 and nRF24L01 As shown if Fig.5, the RF module nRF24L01 is used in this design [12]. When there are no data transmitted, the module automatically enters into the sleep mode to achieve energy saving purposes. Because the data transmission is not strictly required for the delay and rate of the transmission, this design can realize high-functional wireless module. The nRF24L01 is a single chip 2.4 GHz transceiver with an embedded baseband protocol engine (Enhanced ShockBurst), designed for ultra low power wireless applications. The nRF24L01 is designed for operation in the world wide ISM frequency band at 2.400-2.4835GHz. An MCU (microcontroller) and very few external passive components are needed to design a radio system with the nRF24L01. The nRF24L01 is configured and operated through a Serial Peripheral Interface (SPI.) Through this interface the register map is available. The register map contains all configuration registers in the nRF24L01 and is accessible in all operation modes of the chip. The transmitted packet is shown in Fig. 6. PCB1 of MSP430 & nRF24L01 Fig.6 Packet Format of nRF2Ll01 PCB2 of Ultrasonic sensors Fig. 4 Wireless sensor Network Node The embedded baseband protocol engine (Enhanced ShockBurst) is based on packet communication and supports various modes from manual operation to advanced autonomous protocol operation. Internal FIFOs ensure a smooth data flow between the radio front end and the system’s MCU. Enhanced Shock- Burst reduces system cost by handling all the high-speed link layer operations. The radio front end uses GFSK modulation. It has user configurable parameters like frequency channel, output power and air data rate. The air data rate supported by the nRF24L01 is configurable to 2Mbps. The high air data rate is combined with two power saving modes which makes the nRF24L01 very suitable for ultra low power designs. Internal voltage regulators ensure a high Power Supply Rejection Ratio and a wide power supply range. In power down mode nRF24L01 is disabled with minimal current consumption. In power down mode all the register values available from the SPI are maintained and the SPI can be activated. Power down mode is entered by setting the PWR_UP bit in the CONFIG register low. By setting the PWR_UP bit in the CONFIG register to 1, the device enters standby-I mode. Standby-I mode is used to minimize average current consumption while maintaining short start up times. In this mode part of the crystal oscillator is active. This is the mode the nRF24L01 returns to from TX or RX mode when CE is set low. Enhanced ShockBurst is a packet based data link layer. It features automatic packet assembly and timing, automatic acknowledgement and retransmissions of packets. Enhanced ShockBurst enables the implementation of ultra low power, high performance communication with low cost microcontrollers. The features enable significant improvements of power efficiency for bidirectional and unidirectional systems, without adding complexity on the host controller side. The main features of Enhanced ShockBurst are: 1 to 32 bytes dynamic payload length Automatic packet handling Auto packet transaction handling Auto Acknowledgement Auto retransmission 6 data pipe MultiCeiver for 1:6 star networks 4. CONCLUSION In this paper, we presented a low power consumption implementation for wireless sensor networks node using MSP430 & nRF24L01. As a great potential technology, WSN will be widely used in the next few years. Wireless sensor networks are utilized in many applications. This design has the features of low cost which allows its use in many applications needing more than thousand nodes. Another feature of this node is fast start up time of 6 µsec. The nRF24L01 has he facility to vary the output power. This allows the implementation of Adaptive Power based Wireless Sensor network which has the feature of variation in power according to distance. We can set four different levels of power from max 0dB to -16 dB. Another modification is to implement WSN with Adaptive power as well as variable data rate. This will save power to a great extent as the data transmission will take less time reducing ON time of node, which is implemented & tested by us using this architecture. And because energy-saving design located in the core of WSN, low power consumption design standards will continue to rise along with the development of WSN. REFERENCES [1] E. Culler, D. Estrin, and M. B. Srivastava, “Introduction: Overview of Sensor Networks,” IEEE Computer Magazine, vol. 37, pp. 41-49, Aug. 2004. [2] Y.C. Tseng, M.S. Pan, and Y.Y. Tsai, “A Distributed Emergency Navigation Algorithm for Wireless Sensor Networks,” IEEE Computers, vol. 39, No. 7, July 2006, pp. 55-62. [3] T. Basten, M. Geilen, and H. De Groot (Eds.), “Ambient Intelligence: Impact on Embedded System Design”, Springer, Berlin, 2003. [4] F. Zhao, L. Guibas, “Wireless Sensor Networks: An Information Processing Approach”, Morgan Kaufmann, Los Altos, CA, 2004. [5] F. Akyildiz et al., “Wireless Sensor Networks: a survey,” Computer. Networks, vol. 38, pp. 393-422, March 2002 [6] J. Rabaey, M. J. Ammer, J. L. da Silva, D. Patel, and S. Roundy, “Pico- Radio supports ad hoc ultra-low power wireless networking,” IEEEComputer, vol. 33, no. 7, pp. 42-48, Jul. 2000. [7] B. Warneke, M. Last, B. Leibowitz, and K.S.J. Pister, “Smart dust: communicating with a cubic-millimeter computer,” Computer Magazine, vol. 34, pp. 44-51, January 2001. [8] T. van Dam and K. Langendoen, “An adaptive energy-efficient MAC protocol for wireless sensor networks,” in The First ACM Conference on Embedded Networked Sensor Systems, Los Angeles CA, November 2003. [9] S. S. Sonavane, V. Kumar and B. P. Patil, Design Factors, Requirements and Research issues for Wireless Sensor Networks”, International Journal on Engineering Research and Industrial Applications (IJERIA), Vol. I, No.3, pp. 79-93, 2008. [10] S. S. Sonavane, V. Kumar and B. P. Patil, “Component Choice for Low Power Wireless Sensor Networks Node”, International Journal of Computer, Information Technology & Engineering (IJCITAE), June08. [11] http://www.ti.com/msp430/datasheet. [12] http://www.nordicsemiconductor.com/ nrf24L01
