Reduce the amount of data transmitted
Data transmission is one of the most power-intensive operations for IoT devices, especially when using wireless communication protocols such as Wi-Fi, Bluetooth, or cellular networks. The overarching principles to be followed for messaging are to reduce the amount of data transmitted and reduce the distance traveled by that data.
The amount of data transmitted between an IoT device and the cloud can be reduced using message compression, using binary protocols, reducing the frequency at which messages are sent, and using transport and application layer protocols that are efficient.
IoT devices often collect large amounts of sensor data. By storing the data on the device, it can be processed and analyzed in real-time, without the need to transmit it to the cloud for analysis. This can help reduce transmission power and costs, particularly in cases where cellular or satellite connectivity is used. Storing sensor data on the device can provide an additional level of redundancy and fault tolerance, which can reduce the need for human intervention or site visits in case of extended connectivity loss.
Given that most IoT devices are resource constrained, apply compression to data generated by IoT devices, including sensor data, image or video data, and log data. There are many compression techniques available - choose one that fits your device capabilities and the use case.
Compression can not only reduce network bandwidth requirements, but can also improve data storage efficiency by reducing the amount of storage space required for data. This can be particularly useful in scenarios where large amounts of data are generated, such as in video surveillance or industrial IoT applications.
Message formats should be chosen such that they reduce processing as well as storage requirements both locally and in the cloud. It is possible that a single message format or encoding scheme may not be the most optimal for your solution.
One commonly used format is protobuf (Protocol Buffers). Protobuf is a language and platform neutral, extensible mechanism for serializing structured data. It allows efficient binary encoding of device messages with low communication overhead and low CPU usage. Protobuf data structures can change over time with backward compatibility, reducing operational overhead. AWS IoT Core supports the ingestion and translation of protobuf messages natively, making it straightforward for applications to use this feature.
The Concise Binary Object Representation (CBOR) is an IETF defined, self-describing data format designed for constrained devices. It allows for small code size and small message sizes. Each item is preceded by a tag that defines its type, allowing for extensibility without the need for version negotiation. CBOR is based on the JSON data model, which uses numbers, strings, arrays, maps (called objects in JSON), and values such as false, true, and null.
Between the two options, protobuf is the recommended choice for achieving speed and efficient use of resources, while CBOR is preferred for its flexibility and extensibility.
If using MQTT, it is advisable to use MQTT5 topic aliases for frequently used topics. This reduces topic lengths, resulting in reduced transmission time, lower power consumption, decreased communication costs, and improved latency.
