International Journal of Computer Engineering and Applications, Volume XII, Special Issue, August 18, ISSN

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1 International Journal of Computer Engineering and Applications, Volume XII, Special Issue, August 18, ISSN PERFORMANCE ANALYSIS OF 6LOWPAN FOR COST EFFECTIVE AUTOMATED IRRIGATION SYSTEM Mani Pareek Department of Computer Science, Banasthali Vidyapith, Tonk, India Sushil Buriya Department of Computer science, Banasthali Vidyapith, Tonk, India Abstract: WSN (wireless sensor networks) highly used technology in IoT space and essential part in IoT applications. Optimal irrigation system in agriculture is required for high production in minimum cost and resources. To optimize irrigation WSN is effective technology. This paper present 6lowpan technology based irrigation system. Contiki OS and Cooja simulator used to simulate 6LoWPAN network. Contiki OS provide facility to analyze performance of network by emulating nodes using Tmote Sky. Smart irrigation system used to optimize water consumption, power consumption and provide controlling and monitoring of irrigation system remotely. Performance of irrigation system with 6LoWPAN standards analyzed with reference to performance metrics such as throughput, latency, energy consumption, packet loss Quality of Service. Keywords- WSN, Irrigation, IoT, 6LoWPAN, throughput, latency, energy consumption, packet loss, QOS, Contiki, Cooja, Tmote Sky I. INTRODUCTION IoT provides communication ability to physical things, so IoT covers large diverse set of application area. Some IoT applications are home automation, smart cities, health monitoring, industrial settings, fitness tracking, environment protection, precision agriculture, waste management, energy conservation. IoT can use in Smart environment and agriculture applications to provide awareness about environment and agriculture which helps to take effective steps toward best results. A farmer can use IoT system in field for efficient production. Some applications of IoT in agriculture are irrigation system, production using greenhouse, to detect pesticide residues in crop production [1]. In agriculture for crop production environment, soil, water some important factors. In a field sensors can used by farmer to measure temperature, humidity and moisture level of soil this can help in efficient production. Irrigation is important part of agriculture. Some water scarcity regions require fresh water for crop production. An irrigation system which optimizes the use of water and optimizes large quantities of consumes energy requires some effort in Mani Pareek and Sushil Buriya 1

2 PERFORMANCE ANALYSIS OF 6LOWPAN FOR COST EFFECTIVE AUTOMATED IRRIGATION SYSTEM research. For irrigation scheduling in farms soil sensors used to measure moisture and humidity level then on the basis of data reduce water consumption [2]. Automated irrigation is an application of IoT in agriculture according to weather condition. For irrigation system wireless sensor network technology can be used which enable small things equipped with embedded sensors connect to the Internet. For communication in smart irrigation system among sensors, actuators and base station, wireless communication standards of IoT are used. Low power Personal Area Network supports low cost, low rate, short range and less power consumption communication standards for connectivity of battery powered devices. IEEE Low power WPAN is a key technology for IoT. LRWPAN (Low rate wireless personal area network) specify by IEEE standard which was founded in This working group defines the physical layer and MAC (medium access control) layer used by least cost, portable wireless networks access technologies for tablets, mobiles and fixed devices. 6LowPAN is the LR-WPAN technology follow IEEE standard, IETF group proposed it. To provide interoperability with IP network and compatibility with different heterogeneous network 6LoWPAN standard will be appropriate for irrigation scheduling system. 6lowpan stands for IPv6 packets transmit over radio link IEEE In agricultural field number of 6LoWPAN sensor nodes deploy with unique IPv6 address. 6LoWPAN communication standard has adaptation layer between PHY/MAC layer and network layer to which perform header compression of IPv6 packet between sizes 40 to 211bytes and connect sensor nodes transparently with the Internet using TCP/IP protocol. 6LoWPAN technology provide some facilities like automatic network configuration through neighborhood discovery, unicasting, multicasting and broadcasting, fragmentation support, RPL-IP routing and link layer mesh topology formation (e.g., IEEE ) [3]. This study presents a multihop WSN for smart system of irrigation that is based on 6lowpan and ContikiRPL including performance analyze of the WSN sensors using throughput, packet loss, latency, QoS and radio duty cycles metrics. This literature arranged as follow: II segment discuss related work. III segment gives architecture and process of system. IV segment covers simulation of system architecture. Segment V discusses results and performance evaluation. In segment VI outlines conclusion and future work. II. RELATED WORK To manage water in crop fields [4] in-field sensor distributed irrigation system proposed for variable rate irrigation to control and monitor irrigation in real time remotely. WSN, Bluetooth and GSM technologies used for wireless communication. The WISC software used to monitor and analyze the performance of system. This proposed system is work for short range due to Bluetooth technology and this is non-ip based system. Amurag D et.al (2008) proposed a WSN for precision agriculture using Zigbee based network with RFID tags to monitor the agriculture parameters and controlling the irrigation and fertigation on the basis of threshold value. Author develop tree based network in Zigbee standard and proposed a static addressing scheme end. In this paper author avert from Zigbee and set up a network layer over the PHY layer and MAC layer of IEEE standard [5]. In 2009, Zhou Y. et al present a wireless solution methodology for minimizing cost of irrigation system in agricultural field using Zigbee based on star topology to set up intelligent irrigation system for large scale to access remotely. Author explains performance of system on the basis of some parameters including node power consumption, communication range and system cost. In this paper only one sensor node used to evaluate power consumption and many actuator nodes are not used. Communication range evaluate through packet error rate. Throughput and latency of sending data packets is not analyzed in this paper [6]. Zeldi S.et al (2011) discusses performance valuation of precision agriculture system based on 6lowpan. This paper focus on IP network in WSN to overcome the difficulties in constructing global infrastructure using non-ip passed WSN. System architecture consist 6lowpan wireless sensor nodes consist temperature and moisture in-built sensors and a gateway-pc with NanoRouter. 6LoWPAN network form by star topology and to request/receive data from sensor nodes, IPv6 client uses an UDP application and Wi-Fi access point used to connect IPv6 client and gateway. Experimental results based on reliability time of data delivery, round trip latency and packet loss based on payloads size [7] Liai G. et al (2013) present irrigation system using fuzzy control and wireless network to resolve the problem of water wasting and soil fertility in crop production. This system consist wireless sensor network, monitoring center, fuzzy controller and author proposed a supply system based on solar modules with lithium batteries. System architecture consist sensor nodes, controller node, soil moisture sensors, irrigation pipe, spray irrigation and irrigation control valves in WSN with Zigbee mesh network topology for communication. Author explains fuzzy control algorithm for intelligent control irrigation. They design the monitoring platform using graphical programming language LABVIEW to monitor the WSN states and test wireless transmission by two methods, point to point and networking communication which gives the reliable data transmission and provide stability to system. Experimental result provide in terms of in data redundancy and a lost packet phenomenon. [8]. Mani Pareek and Sushil Buriya 2

3 International Journal of Computer Engineering and Applications, Volume XII, Special Issue, August 18, ISSN Chikankar (2015) et al proposed a methodology for automatic irrigation system using technology with optimum use of labors, water and power. This paper discusses power consumption issue overcome by using Zigbee technology. Author presents design of system in 5 levels. The proposed system consist three nodes, 2 sensor nodes and 1 receiver node. Zigbee transmit sensed data to receiver node wirelessly then this node delivers data to microcontroller and information show on LCD of destination node or PC. This system work for particular crop by comparing threshold value, if running value exceeds threshold value then automatic irrigation start. Author experimentally analysis the system that it operates automatically monitor the soil content and environmental content accurately and using energy efficiently with Zigbee standard [9]. Bennis I. et al (2015) present a drip irrigation system using WSN with soil moisture, soil temperature and soil pressure sensors to save water resources. They focus on working of system when malfunctions occur like bursting of pipes or the blocking of emitters. They attain high Quality of Service by using priority-based routing protocol and dissimilate two main traffic levels for data send by the WSN. They simulate system over the NS-2 simulator to achieve result based on priority traffic in delay and packet delivery ratio (PDR) [10]. Khelifa B. et al (2015) proposed a smart irrigation system to optimize the water consumption efficiently in water shortage areas. This irrigation system provides control and monitoring of agricultural crop remotely and they use Contiki Cooja simulator to test the proposed system validity. Proposed system consist WSN system using Zigbee technology, 6LoWPAN smart gateway to connect Zigbee network with the internet via mobile communication network. They simulate system to analyze network converged andstabilized using the RPL protocol and implement OF0 of contikirpl [11]. Abedin et. al (2017) present IP-based irrigation system to optimize irrigation scheduling in the crop field using WSN and 6lowpan technology. Author analyzed performance using Cooja simulator and Contiki OS. Round trip time, packet loss and average power consumption considered as performance matrices. III. SYSTEM ARCHITECTURE Fig.1 outline Irrigation system architecture, consist different wireless sensors and actuators deployed in agricultural field, base station consisting controller to control actuators and gateway server to connect with Internet. Low power and low rate PAN consists different 6LoWPAN sensor nodes to measure soil temperature, humidity and power consumption of node. 6lowpan sensor nodes have common IPv6 address, prefix in WSN. This WSN connects to other IP network through 6lowpan router, a gateway. Edge router does neighbor discovery, form routes to manage traffic in to and out from 6lowpan network, and header compression for IP packet transmission in LoWPAN. Different LR-WPAN nodes are identified by different unique IPv6 address to send and receive IPv6 packets. These nodes use ICMPv6 traffic such as ping and UDP as transport protocol. In 6lowpan WSN a sensor node act as edge router and remaining nodes act as source nodes and send the sensing temperature, light and humidity values to sink node. This sink node forward data to server through gateway used to store and analyze data. After processing at server, server send command to base station to controller then controller control actuators as requirement. Gateway deployed between sink node and 6lowpan WSN to connect with Internet. Fig. 1. Irrigation System Architecture RPL is the routing protocol specifies routing requirements for LLN (low power and lossy networks). In RPL routing DAG (Directed acyclic graph) is formed taking sink node as DAG roots which is DODAG root of destination oriented DAG (DAG). This DODAG uses identifier DODAGID and support objective function (OF) for optimization. Parent selection in graph, hop count, expected transmission count, energy, latency such matrices indicated by objective code point (OF identified by an OCP). Position and distance of each node from root can identify by assigning rank number to each node. 6lowpan sensor nodes can use wireless mesh networking to transmit data to any one of its one-hop neighbors. Next-hop neighbor works as router to forward data to destination. Nodes choose shortest route and minimum number of hops to communicate. This topology provides self healing nature and scalability to nodes. Mani Pareek and Sushil Buriya 3

4 PERFORMANCE ANALYSIS OF 6LOWPAN FOR COST EFFECTIVE AUTOMATED IRRIGATION SYSTEM Fig. 2. 6LoWPAN Network 6Lowpan provides interoperability between current IPv4 networks and newly introduced IPv6 networks. Figure 2 depicts the working of 6lowpan WSN network. Sensor nodes, gateway node posses 6lowpan compliant radios based on IEEE PHY and MAC. 6lowpan protocol perform encapsulation and header compression on IPv6 packets to enable transmission (transmit and recieve) from IEEE based network. Each end node send 6lowpan IPv6 packet to gateway and form mesh network. Gateway or edge router work as tunnel between 6lowpan network(contain ipv6 packets) and IP based network(ipv4 packets). Edge router forward data to IPv6 or IPv4 based server with the help of Ethernet interfae. IV. RESULTS AND DISCUSSION The simulation scenario of systems represents real working deployment of system. For irrigation system simulation, Contiki operating system is used with default network Cooja simulator for wsn. Contiki uses uip TCP/IP stack to support IP networking. Cooja simulator provides usable and understandable GUI environment and easy simulation setup and analysis. Cooja is used java as core and develop applications in C language by java native interface. For simulation Tmote Sky used to emulate motes build on MSP430 microcontroller which works on 10 KB RAM and IEEE radio link. In Cooja radio environment Unit Disk Graph medium select for propagation model which show the transmission and interference range of any mote this is useful to decide position of motes in scenario. 6lowpan based 10 RPL sender nodes deployed in network they send temperature and humidity values to sink node as resources from the underlying SHT11 sensor, a LBR (LLN Border Router). These motes derived from uipv6 protocol stack include UDP, SICSLoWPAN IPv6. Border router uses built-in network interface TUNSLIP utility (serial based interface called SLIP) to connect network and Internet. To read current temperature and humidity values HTTP client periodically sends GET requests to server. Fig.3. 6lowpan network simulation Figure 3, 2 to 11 motes are sender nodes and 1 is border router sink node. Node 1 has 8 nodes in 100% transmission range while 4 th and 6 th nodes are in interference range, means they are not capable to receive packets and are not affected by deliver packets. Cooja provide Collect View tool for collecting data from motes. It helps to observe time taken to form first sender-receiver pair in network, time taken to join all nodes with network tree (fully convergence), time taken to stabilize whole network after convergence and time taken for ETX (estimated transmission count) for each node. Figure 4: presents communication between DODAG root (RPL sink node) and DAG roots (RPL sender nodes) with the help of network graph. This network graph is directed graph. It shows that 4 and 6 nodes are required additional hops 9 and 11 respectively to communicate with root. These nodes deployed to establish multi hops network. Table1 showing general in-built parameters used in Cooja simulator for simulation. Fig.4. 6lowpan network simulation Mani Pareek and Sushil Buriya 4

5 International Journal of Computer Engineering and Applications, Volume XII, Special Issue, August 18, ISSN TABLE I. COOJA SIMULATION PARAMETERS Parameters Values Operating System Contiki OS Radio Medium UGDM Mote Type T-mote Sky Carrier Sensing Range 100 m Transmission Range 50 m Physical Layer IEEE Mac Layer Contiki MAC (CSMA, Radio Duty Cycle) Network Layer ContikiRPL (RPL routing), Adaptation (6lowpan) Radio Duty Cycling NULLRDC Bit Rate 250 kbps Startup delay 1000 ms Tx / Rx Ratio 100% / 90% This simulation evaluates five important parameter matrices power consumption, throughput, QoS end to end delay and packet loss for the various motes in the network. received packet then others. Throughput rapidly increases with number of received packets in simulation time. The received packet rate was varied from 1 packet/second up to 100 packets/second in absence of duplicate packet. Get requests were sent to the temperature and humidity sensor running HTTP server. (Number of successful http request/response pairs*(length of request+ length of response in bits))/total simulation time. In figure 6 graph plot between throughput (packets/second) and time in second. In simulation total simulation time is set to 600s and in the beginning of simulation sender nodes start sending packets after construction completion of network topology in 60 seconds. So during 60s packets reception at each node is zero. Fig.5. 6lowpan network simulation A. Throughput Throughput metric is refers as the rate of successfully delivered data to destination node deployed in network divide by convergence area that is calculated in bits per second. The effect of received packets over time and received packet per node on 6LoWPAN throughput present below for the various motes at hops 2 to 11. Figure 5 and 6 show the average number of received packets every second from sender to sink node. Fig.6. Received packets over time in second from 10 nodes Figure 5 showing that all packets are received from nodes and duplicate packets are not received. In simulation time 2 and 9 th node has highest number of Fig.7. Average delay per packet in multihop scenario B. Latency Average end to end delay is the average time taken to reach destination from source. Latency indicates the processing delay. This 6lowpan network has lower end to end delay. The reason is that firstly sender node search for non-congested DODAG root (parent) to forward packets. End to End delay is the sum of 2*max latency and the processing delay. It is calculated with respect to round trip time. Figure 7 plot maximum round trip time for multihop scenario. When all nodes in transmission range with sink node then latency are negligible but when nodes are not in transmission range then average delay per packet change with every instance of time. The round trip time of ICMP ping echo packet used to measure latency and it is dependent on the MAC protocol and when the next channel sample occurs before the MAC can detect the ping packets. C. Packet loss In the simulation scenario, HTTP client sent GET request, if requests are not acknowledged, this is the condition for packet loss. Total number of lost packets per second take place when buffer overflow, in the presence of atmospheric noise and wireless channel loss. In Cooja packet loss can be simulated by varying Mani Pareek and Sushil Buriya 5

6 PERFORMANCE ANALYSIS OF 6LOWPAN FOR COST EFFECTIVE AUTOMATED IRRIGATION SYSTEM the Tx/Rx ratio and can change the position of nodes in network. When Tx/Rx ratio is 100% then there is no packet loss. When distance between sink node and source nodes, especially 10 th and 6 th node increases then packet loss occurs. D. Quality of Service QoS of networks influenced by congestion (network traffic) this also affect network performance. QoS is the considerable objective for network implementation which conflicts with battery lifetime, delay and overall cost of WSN system. To achieve QoS requirements figure 9 gives detailed node information. The duty cycle mechanism and beacon interval has potential to affect the performance of network in terms of QoS. Fig.8. Lost packet ratio over time Fig.9. Average power consumption of network Beacon interval is the interval between two successive beacons, the size of beacon frames in beacon enabled mode of IEEE MAC. Duty cycle of a network operating in beacon enabled slotted CSMA/CA mode is related to beacon interval. Minimum energy consumption from duty cycle and beacon interval increase QoS of system. E. Power Consumption Power consumption considered as transmission and reception of per successful delivered packet in the sender and intermediate nodes. ContikiMAC protocols used to analyze power consumption of nodes taking duty cycle as an estimator. In battery powered sensor nodes duty cycle should be low to increase battery life. Contiki supports wake-up mechanism and fast sleep optimization of nodes for power efficiency this is responsible for dynamic duty cycle of ContikiMAC, a phase-lock mechanism to maintain neighbor list and their respective wake-up phases. Cooja Power tracker tool used to calculate duty cycle. Duty cycle is estimated by time spent in listen, RX, and TX three states by a node and wakeup interval of node. Figure 10 and 11 shows radio duty cycle and average power consumption graph of nodes. In figure 10, node 4 and 6 has maximum duty cycle value than another node in the network as these nodes use middle nodes 9 th and 11 th nodes respectively so they generate more traffic. In figure 11, average power consumption is also more in these to nodes. Mani Pareek and Sushil Buriya 6

7 International Journal of Computer Engineering and Applications, Volume XII, Special Issue, August 18, ISSN indicate less power consumption and long life time of battery. In the future this work will be extended in real time scenario in field. Different communication technologies will also uses for network simulation such as Zigbee, some WLAN and WWAN like Wi-Fi and Lora, Sigfox etc. QoS parameters can also evaluated by using different simulator. REFERENCES Fig.10. Radio duty cycle of nodes Fig.11. Average power consumption of network V. CONCLUSION WITH FUTURE WORK This paper presented a 6lowpan based Irrigation system. Smart irrigation scheduling method provides water and power optimization and better production in agricultural field. 6lowpan network provide better interoperability between LWPAN and gateway. Using this technology irrigation in crop field will be also useful in aspects of low cost and high accuracy. To evaluate performance, we simulate 6lowpan network using Cooja simulator. The aim of paper is to analyze the performance of IP based LR-WPAN in terms of QoS parameters. Overall QoS of 6lowpan network for irrigation system is measured by QoS matrices that are throughput, packet loss, power consumption and latency. Simulation results show that there is high number of packets received with high throughput and average latency. Power consumption and packet loss will increase when number of intermediate nodes increase. When radio duty cycle decrease then beacon interval time is also less for that node which [1] T. Jasper, and GM K. Simon "A survey of technologies in internet of things." Distributed Computing in Sensor Systems (DCOSS), 2014 IEEE International Conference on. IEEE, [2] Abedin, Zainal, et al. "An interoperable IP based WSN for smart irrigation system." Consumer Communications & Networking Conference (CCNC), th IEEE Annual. IEEE, [3] Ma, Xin, and Wei Luo. "The analysis of 6LoWPAN technology." Computational Intelligence and Industrial Application, PACIIA'08. Pacific-Asia Workshop on. Vol. 1. IEEE, [4] Kim, Yunseop, Robert G. Evans, and William M. Iversen. "Remote sensing and control of an irrigation system using a distributed wireless sensor network." IEEE transactions on instrumentation and measurement 57.7 (2008): [5] Anurag, D., Siuli Roy, and Somprakash Bandyopadhyay. "Agro-sense: Precision agriculture using sensor-based wireless mesh networks." Innovations in NGN: Future Network and Services, K-INGN First ITU-T Kaleidoscope Academic Conference. IEEE, [6] Zhou, Yiming, et al. "A wireless design of lowcost irrigation system using ZigBee technology." Networks Security, Wireless Communications and Trusted Computing, NSWCTC'09. International Conference on. Vol. 1. IEEE, [7] Rasin, Zulhani, and Mohd Rizal Abdullah. "Water quality monitoring system using zigbee based wireless sensor network." International Journal of Engineering & Technology9.10 (2009): [8] Gao, Liai, Meng Zhang, and Geng Chen. "An Intelligent Irrigation System Based on Wireless Sensor Network and Fuzzy Control." JNW 8.5 (2013): [9] Chikankar, Pravina B., Deepak Mehetre, and Soumitra Das. "An automatic irrigation system using ZigBee in wireless sensor network." Pervasive Computing (ICPC), 2015 International Conference on. IEEE, [10] Bennis, Ismail, et al. "Drip irrigation system using wireless sensor networks." Computer Science and Information Systems (FedCSIS), 2015 Federated Conference on. IEEE, [11] Khelifa, Benahmed, et al. "Smart irrigation using internet of things." Future Generation Communication Technology (FGCT), 2015 Fourth International Conference on. IEEE, [12] Bragg, G. M., et al. "868MHz 6LoWPAN with ContikiMAC for an Internet of Things environmental sensor network." SAI Computing Conference (SAI), IEEE, Mani Pareek and Sushil Buriya 7

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