One of the biggest challenges of edge computing is understanding the proper allocation of resources, given its unique setup and the constraints that it provides. Having to set up resources in a decentralized way may seem simple in theory, though they pose a lot of considerations. In the following subsections, we highlight several requirements that are required as part of managing resources and understanding the laws of IoT that govern how we decide to construct our networks.
Resource management
Managing resources within IoT for edge computing is very important, as there are costs to consider as part of the requirements. The following are some common considerations:
Scalability: This refers to having the network address many edge devices with differing capabilities and types, ensuring that they work and interoperate with each other well through the appropriate communication protocols.
Security: Selecting a proper security mechanism is imperative for creating a functioning network that abides by regulations, given that there needs to be much concern for privacy and integrity checks to avoid any breaches that may obtain the data or have any of the data modified.
Heterogeneity: There must be support for heterogeneity within the hardware or software that is deployed.
Volatility: There needs to be much volatile availability that is supported.
Data protection: There needs to be compliance with relevant data protection laws, depending on where you are located, as well as ensuring that data is all kept locally and encrypted both at rest and in transit.
Infrastructure performance: It is important to ensure that high performance on infrastructure is available. This may be in the form of low-latency, lightweight protocols such as Message Queuing Telemetry Transport (MQTT) that are used for communication within the application layer, or using zero-touch provisioning for ease with system upgrades.
Application portability: There must be a holistic architecture via enabling Function-as-a-Service (FaaS) capabilities, given the workloads that we will be processing as we move them toward the edge.
Data analytics: There must be support for data management and analytics within the workloads that are performed, given that we want to transfer those high workloads onto the edge instead of centralizing them: the whole point of edge computing within our networks.
Device management: Managing a large number of devices is a significant challenge, as it involves ensuring all devices are up to date, functioning properly, and efficiently managed across different platforms and locations. This includes monitoring device health, managing software updates, and troubleshooting issues remotely.
Understanding how we can manage our resources for IoT deployments, we can now look at the three laws that govern IoT.
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