The Internet of Things (IoT) extends the end node far beyond the human-centric world to encompass specialiSed devices with human-accessible interfaces, such as smart home thermostats and blood pressure monitors. And even those without human interfaces, including industrial sensors, network-connected cameras and traditional embedded systems.
As IoT grows, the need for real-time scalability to handle dynamic traffic bursts also increases. There also may be the need to handle very low bandwidth small data streams, such as a sensor identifier or a status bit on a door sensor or large high-bandwidth streams such as high-def video from a security camera. Consider the following examples and the applicability of network-connected device to IoT.
Homes and offices
Utility meters send complex data packets to service providers where centralised systems provide real-time monitoring to proactively detect and remediate problems such as blackouts, water leaks and circuit overloads.
Data is analysed to improve efficiency by determining needs, spotting trends, and predicting demand. By virtue of its smart IoT fixtures, the city of Oslo reduced energy costs by 62%.
From heartbeat-sensing fitness bands to step-counting smartphone apps, wearables are the public face of IoT. A portable device is connected to a service that aggregates data and, increasingly, shares it across social media, with a doctor or even a gym. The cloud-based services also push back analytics, motivational graphics and music, and location-based maps.
Hospitals utilise several smart devices, both standalone and those wired to nurses’ station monitors. Soon, these will be interconnected through a highly available and secure network with server-based applications that can track patient conditions by correlating all data – not just nurses’ readings – allowing better monitoring, data logging and big data analytics. An IoT-connected network helped St. Luke’s Medical Center reduce patient-bed turnaround time by 51 minutes.
Factories and warehouses
The flow of materials must be monitored and optimized for efficiency. Location sensors are embedded in components moving through assembly lines and inventory systems. The location of forklifts, pallets and workers are tracked as well, while centralised software directs the activity in real time to effectively respond to customer requests.
By implementing predictive maintenance and quality control IoT, BMW reduced auto-warranty costs by 5% and reduced the scrap rate of defective vehicles by 80%.
Dynamic application delivery
Along with these various applications mentioned above, and there are plenty more. When an IoT node performs a service request, such as sending a medical data packet, the ADC (application delivery controller) determines which server, virtual or physical, can handle the request.
The packet is then sent to the appropriate server for processing, while measuring the performance of the application and availability of the server. Application delivery technology can also remember which application server is handling a specific IoT node’s service requests.
When subsequent packets arrive from the same IoT node as part of the same request, the session will continue with the same server, ensuring continuity of the traffic stream and reducing the need for renegotiation.
An application delivery controller also monitors the health of application servers. Common statistics are processor and memory utilisation, server response time, and how different protocols are handled.
When the servers slow down or become unresponsive, advanced load balancers dynamically route traffic to other servers to reduce client interruption.
Evolution of the load balancer
Modern load balancers focused on application delivery are more sophisticated and operate from Layer 4 to the Application Layer 7, making them more in tune with application server software, how the client responses should be handled, and the specific services being requested by IoT end nodes.
ADCs provide packet encryption/decryption, reducing server workload and making it possible to apply advanced policies and processing on secured traffic streams while maintaining end-to-end security.
Global Server Load Balancing (GSLB) allows the intelligent distribution of end-node traffic across private and public clouds based on proximity, performance or manually defined business rules for optimal data handling and communication.
To facilitate the dynamic cloud infrastructure, modern ADCs have also been adapted to integrate into virtual environments.
An IoT application may include millions of participating devices. The number of connections and the amount of data is neither consistent nor predictable.
Here are a few of the more pressing challenges to providing the backend connectivity and customer satisfaction in IoT applications.
Handling huge amounts of traffic
A motion detector video camera maintains a minimal connection to a cloud-based application server, perhaps a periodic ‘heartbeat’ packet that provides operational status.
When the motion detector is tripped, the camera transmits streams of high definition video to be stored and analysed.
IoT systems designers must plan to manage any quantity of data in unpredictable bursts without dropping packets, overloading the network or overwhelming servers – all while accommodating BI analytics software operating in real time.
Maintaining fast response times and quality of service
An embedded industrial applications or warehouse application that directs workers to pick up and deliver materials is a failure if it freezes or if is slow to process location-awareness packets.
The server infrastructure and network design of an IoT application must focus on both maintaining fast response time and ensuring robust quality of service (QoS), especially in real-time location-aware applications.
Security, privacy and regulatory compliance
Whether an IoT application is industrial or consumer, enterprise or personal, data must be protected in transit and at rest.
Applications store current and historical data about an individual’s health, location and finances along with the location and quantity of inventory, business orders and more. Data must be secured against theft and tampering.
This can be challenging when data is transmitted across the Internet or even secured private networks and VPN tunnels.
Government regulations such as HIPAA or restrictions on transporting data across international borders may also apply.
Key IoT security tasks ensure that proper application-level protections, such as DDoS attack mitigation, reach out to end-points and incorporate measures confirming the identity of entities requesting access to data, including multi-factor authentication.
The Internet of Things is now
The Internet of Things includes the connected refrigerator plus thousands of medical devices in hospitals; smart utility meters; GPS-based location systems; fitness trackers; toll readers; motion detector security cameras; smoke detectors; and embedded systems.
Each of those IoT end nodes requires connectivity, processing and storage, some local, some in the cloud. This means scalability, reliability, security, compliance and application elasticity to adapt to dynamic requirements and ever-changing workloads.
Now is the time for network administrators to fully scope out all of their ‘Internets’ and how everything interconnects, from how ERP software systems maintain monitoring rules and governance to how APIs talk to M2M application platforms, to how asset and device management mechanisms orchestrate version control and location metrics.
Sourced from Atchison Frazer, KEMP Technologies