Delay-tolerant mobile network protocol for rice field monitoring using wireless sensor networks Alexandre Guittona , Fr´ed´eric Andresb , Jarbas Lopes Cardoso Jrc , Asanee Kawtrakuld , and Silvio E. Barbine a Clermont b NII
Universit´e, Universit´e Blaise Pascal, LIMOS, BP 10448, F-63000 Clermont-Ferrand, France; CNRS, UMR 6158, LIMOS, F-63173 Aubi`ere, France.
(National Institute of Informatics), 2-1-2 Hitotsubashi, Chiyoda-ku, 101-8430 Tokyo, Japan.
c Department d NAiST, e USP
of CTI, Rodovia Dom Pedro I, Km 143,6 - Amarais, Campinas - SP, 13069-901, Brazil.
Kasetsart University, 50 Ngam Wong Wan Rd., Ladyao, Chatuchak, 10900 Bangkok, Thailand.
(University of Sao Paulo), Av. Prof. Luciano Gualberto, 380, 05508-010 Sao Paulo, SP, Brazil. ABSTRACT
The monitoring of rice fields can improve productivity by helping farmers throughout the rice cultivation cycle, on various issues: when to harvest, when to treat the crops against disease, when to increase the water level, how to share observations and decisions made in a collaborative way, etc. In this paper, we propose an architecture to monitor a rice field by a wireless sensor network. Our architecture is based on static sensor nodes forming a disconnected network, and mobile nodes communicating with the sensor nodes in a delay-tolerant manner. The data collected by the static sensor nodes are transmitted to mobile nodes, which in turn transmit them to a gateway, connected to a database, for further analysis. We focus on the related architecture, as well as on the energy-efficient protocols intended to perform the data collection. Keywords: Rice-field monitoring, wireless sensor network, routing protocol, delay-tolerant protocol.
1. INTRODUCTION The monitoring of rice fields can improve productivity by helping farmers throughout the rice cultivation cycle,1 on various issues: when to harvest, when to treat the crops against disease, when to increase the water level, how to share observations and decisions made in a collaborative way, etc. However, the monitoring of large rice fields often involves costly techniques. In this paper, we propose an architecture to monitor a rice field by a wireless sensor network (WSN). Our architecture consists in deploying few static, battery-powered, sensor nodes in the rice fields (e.g., weather or soil sensors). These sensor nodes are equipped with wireless communication devices with limited capabilities and limited communication range, which is not sufficient to allow the network to be connected. Farmers are equipped with low-weight communication devices (such as smart phones). As farmers work in their fields, they get in range of the static sensor nodes and collect data from then in a transparent manner. The collected data Further author information: (Send correspondence to Alexandre Guitton) Alexandre Guitton: E-mail:
[email protected], Telephone: +33 4 73 17 70 39. Fr´ed´eric Andres: E-mail:
[email protected] Jarbas Lopes Cardoso Jr: Email:
[email protected] Asanee Kawtrakul: Email:
[email protected] Silvio E. Barbin: Email:
[email protected] Remote Sensing for Agriculture, Ecosystems, and Hydrology XVII, edited by Christopher M. U. Neale, Antonino Maltese, Proc. of SPIE Vol. 9637, 96372E © 2015 SPIE · CCC code: 0277-786X/15/$18 · doi: 10.1117/12.2194085 Proc. of SPIE Vol. 9637 96372E-1 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 12/08/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx
is aggregated or compressed, and is exchanged from farmer to farmer using a mobile network protocol, until it reaches a gateway node, located in a nearby village. The collected data is then stored into a database, called the Cyberbrain Platform, and is analyzed. Cyberbrain generates farming advices for farmers, based on the historical data, and these advices are again propagated among the farmers through the mobile network protocol. The main challenges addressed by this paper are the following: (i) how to deal with a disconnected network topology, resulting from a sparse deployment of static sensor nodes, (ii) how to route data using the unpredictable and uncontrollable movements of a few mobile farmers, (iii) how to transfer a relatively large amount of data, especially when the static sensor nodes are not visited often by the farmers. The plan of the paper is the following. In Section 2, we describe the related work on rice fields monitoring using a wireless sensor network. In Section 3, we illustrate our architecture and details its advantages. In Section 4, we describe the proposed protocol: an energy-efficient MAC protocol and a delay-tolerant mobile routing protocols. These protocols are the key component in our proposal. Finally, in Section 5, we conclude our work.
2. RELATED WORK WSNs have recently become a relevant tool for precision agriculture, in order to achieve a low-cost monitoring of crop fields. In the following, we describe a few approaches for crop field monitoring or rice field monitoring. We start by the WSN architectures based on GSM, and then we describe a WSN not based on GSM.
2.1 WSN architectures based on GSM Tummala et al.2 propose an image-processing algorithm to detect plants affected by disease or parasites, using various techniques including color decomposition. The algorithm is able to detect some diseases that farmers cannot detect with the naked eye. They proposed a WSN where all the data is transmitted to a gateway, which uploads it to a database, and notifies the farmer using GSM in case of an alert. Sakthipriya3 proposes to deploy a WSN where farmers can perform several measurements (temperature, humidity, or soil moisture) and collect data locally. The architecture uses the GSM technology to inform the farmer of urgent data, or to allow the farmer to communicate with actuators (such as water valves and water sprinklers). Nirmal et al.4 also propose a WSN to perform several measurements (humidity, water level, temperature, etc.) on a crop field, again with a gateway node having GSM capabilities. Within the WSN, nodes communicate with the ZigBee,5 which is a well-used communication standard for low-power WSNs. The main drawback of these three approaches is the fact that they rely on GSM, which implies the presence of GSM access points, as well as an additional cost paid by the farmer to the GSM operator.
2.2 WSN architecture not based on GSM Simon et al.6, 7 propose a rice field WSN in the the Kuttanad region of India. The WSN has a hierarchical structure organized around clusters. Within each cluster, a cluster-heads collects the data from all its members, and aggregates them. If the data falls into a range of expected values, it is not forwarded. If the data is out of the expected range of values, it is forwarded to the sink. In this way, the authors are able to achieve a good energy-efficiency, due to both the hierarchical structure and the reduction of the number of messages that are forwarded. The main drawbacks of this approach are the following. • It requires a network connected at all time. Moreover, for a farmer to be notified of an event happening in the rice field (for instance, a drop in the water level), there has to be WSN nodes deployed at regular intervals between the rice field and the farmer home, which might not be practical. • The location of the sink node is an issue. As the sink node manages the database and analyzes the data, its energy consumption is larger than the energy consumption of other nodes of the WSN. For this reason, it is usually assumed that the sink has no energy limitation and is connected to the mains. However, being able to connect the sink to the mains is difficult in rice fields that are in remote locations.
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There are other architectures proposed for WSNs that are not connected continuously.8, 9 However, these architectures often assume that the network is composed of few connected components, interconnected temporarily. This is the case when a fleet of mobile robots, each equipped with a WSN, evolves in a large area.
3. PROPOSED ARCHITECTURE Figure 1 depicts a rice field, represented as a dotted rectangle, with four static sensor nodes, represented by circles with names a, b, c and d. Each static sensor node is equipped with weather, soil or water quality sensors, a small battery providing energy autonomy, a processor with memory, and a radio module providing the node with wireless communication capabilities. The communication range of each static sensor node is indicated by a dashed circle. In this example, it can be seen that the network is not connected: none of the sensor nodes can communicate with another. There are also parts of the area that are not within the radio coverage of a sensor node. We believe that this scarcity of nodes is representative of the reality, as it would probably be too expensive to cover a whole rice field.
a
b
d c
Figure 1. Our proposed architecture, with static sensor nodes only. The dotted area represents the field, solid circles represent the sensor nodes, and dashed circles represent the communication range of sensor nodes. It can be seen that the network is not connected.
Figure 2 depicts the same rice field as in Figure 1, but with three mobile nodes m1 , m2 and m3 . These mobile nodes are carried by farmers as they work in the field. These nodes also have a communication range, again depicted with dashed circles. Nodes a and m1 are both in range of each other: they can communicate and exchange data. Nodes b and m3 can also communicate. Notice that m2 is not in range of any static sensor node. However, m3 happens to be in the range of m2 . Thus, m2 and m3 can communicate. As farmers work in the field, the mobile node they carry becomes in range of various static sensor nodes or mobile nodes, and they can benefit from this mobility to exchange data. We assume that when farmers go back to their village (e.g., at the end of the day), they leave their mobile node close to a gateway node, which downloads all the collected data and uploads it to a database on the Internet. All the collected data is stored in a database which is managed by the Cyberbrain Platform. Cyberbrain is a software suite that archives historical data on rice field, analyzes the data, and generates farming advices (for farmers and for governmental use). The advices are downloaded into the mobile nodes, and are shown to the farmers when they get their mobile node back (e.g., in the morning). Mobile nodes also store control packets for static nodes, such as requests to change the monitoring frequency. These control packets are disseminated to the static nodes when the mobile nodes move in range of these nodes.
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m2
a
b m3
m1
d c
Figure 2. Our proposed architecture, with static sensor nodes and mobile nodes. Square nodes represent mobile nodes, solid circles represent the sensor nodes, and solid lines represent possible wireless connections between nodes.
To summarize, we propose the following three-tier architecture: static sensor nodes collect data and communicate with mobile nodes, mobile nodes retrieve the data from static sensor nodes (or reconfigure static sensor nodes according to the control packets from the gateway), propagate it from mobile node to mobile node, until it reaches the gateway, the gateway node downloads data from mobile sensor nodes, communicates with Cyberbrain, and uploads control packets to mobile sensor nodes. Our architecture has the following advantages. • It is low-cost, as it is based on cheap devices (both static sensor nodes and mobile nodes) and does not require a full radio coverage of the rice field, or a connected network. • It is transparent to farmers (apart from the generated advices). Our architecture does not require to control the mobility of farmers, but rather to make use of it. • Our architecture can provide additional services to farmers while they work in the field. For instance, farmers working in groups (such as m2 and m3 on Figure 2) can communicate wirelessly. However, our architecture raises some issues. First, the routing has to be delay-tolerant, due to the low connectivity of the topology. Second, nodes (both static and mobile) have to store a large quantity of data, as they might be isolated for long periods of time. Third, nodes cannot predict in advance how long they should keep the data, as they have no knowledge of when the data reaches the gateway.
4. PROPOSED PROTOCOLS In this section, we describe our two main proposed protocols: an energy-efficient MAC protocol (in Subsection 4.1), and a delay-tolerant mobile routing protocol (in Subsection 4.2).
4.1 MAC protocol In our architecture, static sensor nodes have to stay alive for extended periods (e.g., one year) without specific human maintenance or battery change. Mobile nodes can be recharged frequently, possibly every night, so
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their energy consumption is not as significant. That is why we plan to reduce as much as possible the energy consumption of static sensor nodes, at the cost of a relative increase in the energy consumption of mobile nodes. We assume that nodes are not synchronized. They share the knowledge of a period p, which determines their cycle. At the beginning of each cycle, static sensor nodes broadcast a beacon. The beacon contains their ID and the last sequence number for the data generated by the sensors. After having sent this beacon, the static sensor listens to the channel for activity. If no activity is detected, the static sensor nodes goes back to sleep mode until the beginning of the next cycle, and saves energy. If activity is detected, the static sensor nodes communicates with the mobile node using the unslotted CSMA/CA mechanism of IEEE 802.15.4.10 When both nodes have finished communicating, the static sensor nodes goes back to sleep until the beginning of the next cycle. Algorithm 1 formalizes the description of the MAC protocol, for the static sensor nodes. Variable mb denotes the maximum number of backoffs periods between the reception of a beacon and the transmission of a frame using unslotted CSMA/CA, and is equal to 8 (for one clear channel assessment and at most seven backoff periods). Algorithm 1 MAC protocol used by static sensor nodes at the beginning of each cycle. send beacon (with ID and current sequence number) detect an activity (by performing mb clear channel assessments) if an activity is detected then remain active until one of the following condition occurs: (i) the activity has lasted for the whole cycle, (ii) there is no activity on the channel during mb backoff periods, (iii) the static sensor node has finished communicating with the mobile nodes end if sleep until the beginning of the next cycle Algorithm 2 formalizes the description of the MAC protocol, for the mobile nodes. Variable pr is the probability to sleep during the whole cycle. This probability allows mobile nodes to sleep when they are not in range of static sensor nodes: a large value increases the energy-efficiency of mobile nodes. However, a large probability increases the delay before a mobile node detects a static sensor node in range. Thus, a trade-off between reactivity and energy efficiency has to be achieved by setting correctly probability pr. When a communication is established between a static sensor node and a mobile node, the mobile node starts by sending its control packets to the static sensor node. The number of remaining control packets for this static sensor node is included into the header of the packet. When there is no control packet, a special control packet is sent without payload. Note that it is the responsibility of the mobile node to store information about the control packets that have been delivered to different static sensor nodes. The optimized dissemination of identical control packets through multiple mobile nodes is left for future work. Once the mobile node has finished sending its control packets, the static sensor node starts sending its own data packets. Each data packet contains the ID of the static node and a sequence number. It is the responsibility of the static node to decide to how many mobile nodes the same data packet should be sent. Sending several copies increases the reception probability at the gateway and reduces the end-to-end delay, but also increases the overhead for the network.
4.2 Delay-tolerant mobile routing protocol The network protocol addresses the issues of our architecture by using the following mechanisms. • Static and farmer devices use a periodic announcement mechanism, where the periodicity is adapted to network conditions and gateway proximity (computed using GPS or estimated through the time of last contact). • Farmer devices use a limited flooding mechanism, where each data is sent only to a limited number of neighbors, and for a limited number of hops.
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Algorithm 2 MAC protocol used by mobile nodes at the beginning of each cycle. active ← f alse random ← random value in [0; 1] if random < pr then active ← true end if if there is a static sensor node in range and the communication with this node is not finished then active ← true end if if active is true then send a beacon to announce its presence to other mobile nodes wait for a beacon (during at most one cycle) if a beacon is received then store the ID and the sequence number of the static sensor node if the sequence number is larger than the previous sequence number for this static sensor node or there are control packets for this node then initiate the communication (during at most one cycle) end if end if end if sleep until the beginning of the next cycle • Static and farmer devices use data timestamping as well as aggregation to compress them. They also use a data priority estimation function, in order to decide which data to remove first from the memory of an overloaded device, as well as which data to send first to a new device that comes in range. The routing protocol is the following. Static sensor nodes send their data packets to the first mobile nodes they meet. Once the static sensor node has sent a copy of the data packet to a mobile node (or a few copies to different mobile nodes, as explained earlier), the routing of this packet is out of scope of the static node. Only mobile nodes exchange data packets in order to reach the gateway, and thus they are the only node to fully implement the routing protocol. The first mobile node receiving a packet is called its owner. The owner of a packet floods a limited number of copies of this packet to other mobile nodes it meets. These mobile nodes send this packet a few times until it reaches the gateway or until it expires. However, the data packet never expires for the owner, it can only be deleted once it eventually reaches the gateway. Each packet is associated with two values: a repetition value, and a hop value. The owner sets the repetition value to a parameter r, and the hop value to 0. When a mobile node sends a packet to another mobile node, both values are sent along (in the header of the packet). Upon receiving these values, the receiver halves the repetition value and increases the hop count value. Packets whose hop count exceeds a threshold h are not forwarded anymore. Thus, parameter h allows a limited dissemination of packets to mobile nodes, in terms of number of contacts with the owner of the packet. Parameter r allows a limited flooding of packets to different mobile nodes. When a packet is sent, the sender decreases the repetition value by one. These two values can be changed to achieve a trade-off between delay (when r and h are large), and memory and energy (when r and h are low). Packets might quickly fill the limited memory of mobile nodes. Thus, we implement a priority for packets being in the packet queue. The lowest is the priority, the highest is the chance to be removed of the queue. The priority of packet p is defined according to the following formula priority(p) = h/hop(p) + repetition(p) + α.sequence(p), where sequence(p) is the sequence number of p and α is a small constant (we choose the value 1/100). The formula for the priority of packets gives a larger priority to packets having a small hop count (thus, being close to the owner) or having a large repetition value (thus, having been repeated few times). The sequence number of the packet is also used, so that packets with larger sequence numbers (that is, more recent packets) tend to have higher priority than others (with the factor α limiting the impact of the sequence number on the priority).
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Note that the special case of hop(p) = 0 is treated by having a priority set to +∞, so that the packet is never removed for the queue until it reaches the gateway.
5. CONCLUSION The monitoring of rice fields by a wireless sensor network requires the design of suitable MAC protocols (to address the energy limitations of nodes) and routing protocols (to address the routing challenges). In this paper, we proposed a new architecture based on a network of disconnected static sensor nodes, and a fleet of mobile nodes carried by farmers. We proposed a MAC protocol to ensure that static sensor nodes consume as little energy as possible, while allowing mobile nodes to detect them when they get in range. We also proposed a delay-tolerant routing protocol to route the data among mobile nodes, until data reaches the gateway, or from the gateway to the static sensor nodes in case of control packets.
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