by Network Connectivity: The Foundation of IoT
At the heart of any IoT infrastructure is network connectivity which enables the constant flow of data between billions of devices and the backend systems. As the number of IoT devices expands dramatically, traditional networks are struggling to handle the massive influx of data. This is where new network technologies like 5G, Low Power Wide Area Networks (LPWANs) and private networks are playing a crucial role.
5G networks have significantly higher bandwidth and lower latency compared to previous cellular network standards. This makes 5G ideally suited for applications requiring fast response times like autonomous vehicles. 5G also enables connectivity for a much higher density of devices. On the other hand, LPWAN technologies like LoRa and Sigfox provide long range connectivity solutions that can connect devices over several kilometers using very little power. Such networks are ideal for stationary sensors with low bandwidth requirements.
Many large enterprises are also building their own private networks optimized specifically for their IoT deployments. Private LTE/5G networks give organizations dedicated spectrum and network resources securely within their premises. As ubiquitous connectivity becomes available, it will herald a new era of possibilities for IoT applications.
Edge and Fog Computing to Overcome Cloud Constraints
While cloud infrastructure has been the destination for IoT data aggregation and analytics, it has limitations for applications requiring real-time responses or having intermittent connectivity. This is where edge and fog computing are playing a bigger role in IoT deployments.
Edge computing refers to processing of data close to the data source, at network edges, before sending it to the cloud. Devices like routers, switches, access points and more are being equipped with computing capabilities to run basic analytics and processing of IoT data at the edge locations. This reduces latency issues and also network bandwidth requirements.
Fog computing moves one step further by distributing computing, storage and networking services between end devices and cloud data centers. In a fog architecture, some IoT data processing and analytics can run on intermediate nodes located between IoT devices and the cloud. This helps balance workload between edge and cloud resources.
Together, edge and fog computing bring processing power closer to IoT endpoints, enabling latency-critical and localized applications that need low response times. They reduce backhaul network traffic and also enable applications in low/intermittent connectivity scenarios.
Data Storage and Management Needs
With IoT deployments generating massive volumes of data round the clock, efficient storage and management of this data is critical for maximizing its value. Traditional centralized databases and data warehouses face scalability challenges for analysis of IoT big data.
Distributed ledger technologies like blockchain have emerged as suitable solutions to securely store and share IoT data between multiple stakeholders in a decentralized manner. Blockchain brings trust, transparency and immutability which are crucial for many industrial IoT ecosystems.
Data lakes are also gaining adoption for ingesting, storing and curating massive amounts of raw IoT data in its native format until it is needed. Advanced analytics on this raw data can help gain valuable insights. Conversely, data streaming and messaging systems enable real-time analytics on IoT data streams.
Overall, a hybrid strategy combining multiple data storage technologies is essential to cater to different IoT data types and analytic needs – from real-time to offline analytics. Proper data management is key to deriving optimal value from IoT data assets.
Security: A Top Priority
With billions of globally interconnected devices, security should be a top priority in Iot Infrastructure infrastructure design right from the start. IoT devices are vulnerable targets due to factors like lack of security protocols, constrained hardware resources and inability to run complex security software.
At the device level, manufacturers are focusing more on end-to-end security involving features like encrypted communication, firmware signing, hardware root of trust and more. Standard security protocols and frameworks like TLS, DTLS, IPSec are also becoming common.
Further, new network encryption technologies like 5G ENC (EthernetNetworks Convergence) encrypt data flowing through networking infrastructure using network function virtualization. At the backend, proper access control management, anomaly detection and network segmentation help secure IoT application systems.
Data-centric security practices involving anonymization, hashing and tokenization protect sensitive IoT data. Over-the-air updates ensure devices continue receiving security patches. Finally, blockchain for IoT brings built-in security, traceability and resilience to IoT ecosystems.
*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
