Design of Wireless Sensor Network Based on Structured Method
The Wireless Sensor Network (WSN) consists of small, low-power nodes that are independent, fully embedded, capable of detecting data from the target environment or controlling the target environment and communicating wirelessly with each other. Detection and control is accomplished through interconnected sensors and actuators that are managed remotely or through embedded applications. The number of these nodes ranges from a dozen to thousands, and a typical system consists of hundreds of nodes distributed throughout the building or outdoor space.
Many wireless sensor networks use private standards for wireless networking, but the recent trend is to gradually evolve toward standardized low-power wireless communications. ZigBee, based on the well-known 802.15.4 specification, is a standard for wireless detection and control. Although the 802.15.4 document only describes the PHY and MAC layers of the protocol, ZigBee built on 802.15.4 also provides network and application layer specifications.
ZigBee has many advantages, including mesh protocols that enable multi-hop routing and data transmission, security specifications, and a full set of parameter settings for application layer interoperability. In summary, ZigBee provides embedded application developers with a higher level of abstraction for managing the network and connecting to other nodes.
Although this article focuses on ZigBee, many of the ideas and conclusions apply equally to other standards that use 802.15.4 MAC and PHY. In order to avoid confusion, it is assumed that our target design involves a multi-hop network using a mesh routing protocol, an 802.15.4 compatible modulation scheme, and a medium access protocol. This article also assumes that the reader has a basic understanding of the ZigBee and 802.15.4 specifications.
Network organization and scaleNetwork organization and scale are perhaps the most important design options, and they often inform and guide the next design process. It also has a binding effect because large networks are often more difficult to design and maintain. Fortunately, there are ways to easily implement and maintain very large networks.
The most advanced ZigBee network is currently between 300 and 500 nodes. This scale does not seem to be large, but imagine that all of these nodes work on the same physical channel, send data at the same time, route data according to the behavior of each node, and try to maintain the integrity of the entire network at the same time (through Send a periodic control message), this is a very noisy and crowded network. Also note that the 802.15.4 specification on which the ZigBee standard is based uses the CSMA/CA (Carrier Sense Multiple Access/Collision Avoidance) protocol, which means that no two nodes can simultaneously "within the respective "hearing" range." speak". If you "talk" at the same time, you will encounter communication failures and you must try again after a delay. If the network is already congested, then these retry attempts will result in cascading transmission failures, and more and more nodes attempting to initiate air access will increase the congestion of the channel.
In fact, one of the main challenges in designing networks with hundreds of nodes or more is how to effectively manage network congestion (another challenge is to optimize system resources for storing internal stack states at runtime). The following sections briefly describe three different strategies for solving congestion problems.
Figure 1: 802.15.4-based ZigBee provides network layer and application layer specifications.
Network densityObviously, the "300-node network" gives us little information about the network organization. Due to the above conflict collision problem, network density is also an important factor affecting network health, that is, how many nodes exist in the hearing range of each node, or in other words, how many other nodes can a common node hear? Expert advice is less than 5 because this number supports redundant designs and relatively non-blocking communication media. A network with more than 7 nodes is likely to have a heavily congested network segment and burden the network.
A related question comes along, how do system designers judge how many nodes can be heard? An obvious strategy is to customize embedded applications. Information about neighboring nodes is actually an important part of the protocol operation in the ZigBee network. In fact, the nodes will actively broadcast their own information, and this information will be received by every other node within the valid range. Adjacent tables can be queried by the resident program and count the number of unique entries. The resident program then sends this diagnostic result to the specified node. Obviously, this only makes sense in a network installation process where network density can still change. Once the network is installed and running, the density information will act as a consultant during the troubleshooting process.
Note that if the size of the adjacent table is less than the number of surrounding nodes, the ZigBee stack will force the table entries to be undone periodically. This revocation can also negatively impact overall network performance because the route is forced to be rediscovered even if no nodes are offline in the path. Therefore, in addition to limiting network density to avoid congestion, network density must also be determined based on system resources such as the size of adjacent tables.
In the case where the physical location of the node is fixed due to application requirements, the network density can be conveniently controlled by reducing the output power of the transceiver in the congested area. Theoretically, reducing output power has the same effect as increasing the distance between nodes and making them less likely to hear each other. Manufacturers tend to set the output power to a maximum to ensure maximum operating range and optimum link quality. According to our experience, the output power can be easily reduced in indoor applications where distance performance is not important. According to experience, the output power is reduced by 3dBm, and the effective distance range can be shortened by 1.5 times.
A final consideration regarding density is that the failure rate increases sufficiently high to trigger the theoretical limit of the cascade failure effect described above. Of course, this parameter depends on the amount of information sent by the application itself. As a rule of thumb, if each node sends a maximum length packet per second, then this limit is about 25 nodes in the hearing range of each node. The density limit seems to be constant, independent of the stack implementation, which means that the density limit is related to the more basic CSMA operation of the MAC layer. For example, we can infer the density limit of a node that sends a packet every n seconds, that is, multiply the maximum density by 1.2n times. This approximation should never be used as an accurate guide for network density, as the actual value will depend on the proportion of routers and end devices in the network.
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