WebSockets are used for two-way communication over a single, long-lived connection between a client and a server. This makes them popular within WSNs as they provide low-latency communication between devices while keeping connections simple and efficient. This helps reduce the power consumption within devices as the number of transmission attempts will be reduced. However, one thing to note is that WebSockets work best when environments have reliable network connections, so the location and the circumstances of how the connection is to be established must be thought through thoroughly. It may not work when there are limitations to bandwidth or where network connections are unreliable.
With that, we have understood how to manage different kinds of APIs. Now, we can look at evaluating different kinds of WSNs and understand how to best build them depending on our use cases.
Evaluating WSNs
As mentioned multiple times in this chapter and throughout this book, one of the most imperative aspects of implementing a network is to understand how it can be best optimized. There are several key ways in which this can be done; one of them is through understanding metrics that are related to such networks and how we can apply them when we’re examining networks that we encounter. We will discuss these metrics and how you can use them to evaluate your WSN deployment, as well as other deployments that you come across to better understand how to optimize your own as well.
Metrics
In this section, we’ll look at different metrics that have to be considered when building WSNs:
Energy consumption: This metric measures the amount of energy that is used up by the WSN and is used to assess the energy efficiency of the network.
Network lifetime: This is a metric that measures the amount of time the WSN can operate before the batteries are depleted. It is closely related to the energy consumption metric and is key to understanding how efficiently your WSN is performing.
Packet loss rate: This is a metric that measures the proportion of packets that are not successfully received by the recipient. This could be between nodes or from a node to the base station. This could indicate problems with the network, such as poor signal quality or congestion.
Latency: This is a metric that measures the time it takes for a packet to transmit from a sender to a receiver.
Throughput: This is a metric that is used to measure the amount of data that is transferred successfully across the network over a given period. It is used to assess the capacity of the network since it’s responsible for large amounts of data.
Mobility: This is a metric that measures how well the network can support devices being added and removed to and from a network. This makes it a very important factor in supporting IoT networks that are very dynamic.
Reliability: This is a metric that measures the consistency and availability of the network over a certain period. This is especially important in workloads that have critical applications, such as within healthcare scenarios.
Scalability: This is a metric that measures how well the network handles an increase in the number of devices with the amount of data being transmitted.
Security: This is a metric that measures the network’s protection over itself and the data it has that is being transmitted within it due to unauthorized access or tampering.
Note that all WSNs have different requirements and constraints imposed on them, so to best evaluate your use case, you should consider your own set of metrics that work best with your considerations and understand how those metrics can help you achieve success and lead you toward the road of improvement that you would like as part of your system.
