There are many options for wireless connectivity, and the most popular ones include Wi-Fi, Bluetooth, ZigBee, and sub-GHz based solutions. Each solution has advantages and disadvantages. In this interconnected world, the above wireless technologies will coexist. However, one of the important driving forces of the Internet of Things is the emergence of low-power wireless sensors, from smart meters to transmission systems, from security systems to building automation, and sensors are increasingly used in a variety of applications. For wireless sensors, attributes such as scalability, range, sleep current, and reliability are critical. Although the data transfer rate required by some terminal nodes is relatively low, real-time report aggregation in large-scale networks means "big data".
In order to better serve end users, utility companies and municipal councils have begun to expand smart metering systems to address the growing problem of real-time data. Through smart meters, utility companies can view customers' energy consumption information more frequently and efficiently, while also quickly identifying, isolating, and solving power failures. Consumers can also access relevant information through interconnection. Indoor network devices report their status and energy consumption in real time and respond to information from utility companies. With smart energy and smart home systems, consumers will be more convenient and efficient, for example, to control the activation of the dishwasher at the lowest electricity rate, or to remind users to add detergent at the right time.
Similarly, in rail transport networks, wireless sensors can be used to remotely monitor a wide range of track networks, and technicians can identify maintenance needs in advance to reduce the cost and delay of manual track tours.
Core requirements for wireless sensor networksScalability is critical to wireless sensor network environments. Some sensors only update the status once per second and only transmit a few bytes of information at a time, but a single building may have tens of thousands of nodes. For example, the Aria Hotel in Las Vegas, USA, deployed more than 70,000 nodes that use ZigBee mesh communication to control Lighting, air conditioning, and many other services around the building. In most applications, the sensor needs to be installed in a location where it cannot be connected to mains or battery only. Therefore, a reliable network architecture requires the ability to handle large amounts of aggregated data, but the sensor nodes themselves must be low power.
The combination of reliability, scalability, and power efficiency clearly defines the communication technology requirements that wireless sensor nodes can employ. System integrators must consider not only the advantages and disadvantages of the chosen topology and wireless protocols, but also the physical properties inherent in wireless technology. Concrete walls and multipath fading are disadvantageous for any wireless system, but there are ways to mitigate the effects. To solve this problem, different countries have different regulations to manage the radio spectrum and the available frequency range.
2.4GHz has become an unlicensed global frequency band, so wireless systems are designed to serve all major markets worldwide. For example, Wi-Fi is based on the 2.4GHz band communication technology, which is good at transferring large amounts of data between two nodes, but at the same time consumes high energy, and in the star configuration, each AP is limited to no more than 15-32 customers. end. Bluetooth is another 2.4 GHz technology for portable devices, primarily as a point-to-point solution that supports only a few nodes. ZigBee shares the same wireless spectrum as Bluetooth and Wi-Fi, but is only used to meet the special needs of low-power wireless sensor nodes. Table 1 summarizes the core features and capabilities of current wireless network technologies.
ZigBee: Optimized solution for wireless mesh networksBased on global standards, ZigBee is an open wireless mesh network technology. Unlike traditional network architectures, such as star and peer-to-peer, mesh networks use the lowest cost node to provide reliable coverage for all locations within a building. ZigBee uses a dynamic, autonomous routing protocol based on AODV (AdHocOn-demandDistanceVector) routing technology. In AODV, when a node needs to connect, it will broadcast a route request message, and other nodes look up in the routing table. If there is a route to the destination node, it feeds back to the source node, and the source node picks a reliable number of hops. The smallest route, and store information to the local routing table for future needs, if a routing line fails, the node can simply choose another alternative routing line. If the shortest line between the source and destination is blocked due to wall or multipath interference, ZigBee can adaptively find a longer but available routing line.
For example, wireless sensor networks based on the SiliconLabsEM35xEmberZigBeeSoC and EmberZNetPRO stacks provide self-configuring and self-healing mesh network connectivity that can extend hundreds or thousands of nodes in a single network. The rapid development of "ZigBee Certified Products" benefited from EmberAppBuilder, which hides the details of the protocol stack and focuses on the development tools implemented by ZAP (ZigBeeApplicaTIonProfiles). Through the graphical interface, developers can quickly select the properties required by the application, and then the AppBuilder automatically generates the required code.
To take advantage of the ZigBee network's flexibility, efficient debugging tools are needed. The complexity of mesh networks makes traditional network analysis tools (such as Packetsniffer) more difficult to use. In fact, since the packet may travel through multiple hops to the destination, many intermediate transmissions are beyond the scope of the analyzer. For this problem, the only solution currently is to use the SiliconLabs Desktop Network Analyzer (DesktopNetworkAnalyzer), which is powerful enough to display the full picture of each packet in the network in a graphical interface, with built-in protocol analysis and visual tracking. Engines, developers can coordinate the tasks of network communications and devices.
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