Internet of Things Testing: Decoding Challenges and Solution Approaches for Transformative Enterprises

Predictions suggest Internet of Things (IoT) will proliferate to an extent that there will be 50 billion connected devices in 2020. But, alas, every rose has its thorn. At such a galloping progress, the biggest concern waiting to ensue is seamless data interoperability.

Integrating data from various touchpoints and deriving maximum value out of it is a critical IoT imperative. Various IoT applications are programmed to achieve robust system-to-system data aggregation and consolidation for enabling analytical intelligence within an enterprise. An organization, therefore, must decide if the existing devices and processes meet the IoT interoperability criteria to further determine how compatible the IoT applications will be for data communication.

This is where IoT testing holds water.

The Need & Relevance of IoT Testing

The reliance on IoT for enabling an advanced communication protocol is based on different wireless standards. For software engineers, designing IoT applications on these standards, which pose numerous potential connectivity and infrastructure risks, is a tightrope walk resulting in design and efficiency anomalies. Also, these applications might work differently for different enterprises, or not work at all. This is why it’s important to do real-world testing of IoT applications to determine if they fit well within a specific operational landscape and deliver the anticipated results.

The real problem with IoT applications is their complex architecture and unique characteristics, which aren’t close to the contemporary applications of today. It’s the same characteristics that frustrate IoT testing and implementation attempts and poses a number of challenges.

Here’s a quick point-to-point low-down on the characteristics of IoT applications and the testing challenges they create.

Characteristics of IoT Applications and Why they are a Different Ball Game

The Subsequent Challenges

a) IoT applications are ridden with multiple, real-time scenarios occurring in conjunction, which can be very painstakingly complex.

b) Determining the scale of scalability is always a knotty affair. It’s challenging because there are future upgrade issues.

c) Testing scenarios are heavily controlled and monitored unlike the real-world situations, which are volatile and vulnerable with millions of sensors and different devices working in synchrony. That being so, the IoT applications, which might have scored a perfect ten in testing, might fail to deliver results in the actual ecosystem. Lab results don’t vouch for real outcomes.

d) With IoT expansion, the security concerns over data integrity and safety continue to grow and are compelling test engineers to stick their heads out for corrective steps.

Since most of the IoT technology is immature, hardware quality is always questionable.

Types of IoT Testing

The current challenges of IoT implementation is overwhelming, attributable to the highly complex and unique characteristics of IoT applications. This mandates different test scenarios for normal usage, peak points, and day-long simulations to ascertain if these applications ensure total performance and scalability of the IoT architecture.

Broadly, IoT testing scenarios are categorized into six types:

1. Security Testing: Handling an onslaught of data is fundamental to IoT operations, and therefore, enterprises must conduct security testing to eliminate vulnerabilities and maintain the integrity of data. This includes examining various aspects of the system, including data protection, encryption/decryption, device identity authentication among more.

2. Performance Testing: This covers real-time and far more cumbersome aspects, such as load testing, streaming analytics, time-bound outputs, and timing analysis, to validate and ensure consistent performance of data reading, writing, and data retrieval.

3. Compatibility Testing: This testing assesses if the existing working combination of hardware, software, protocols, and operating systems fall on the IoT interoperability radar, and are compatible with the standards and specifications of conventional IoT industrial framework.

4. Functional Testing: This examines the qualitative and quantitative functional deliverability of deployed IoT applications in the actual conditions. Aspects, like network size, environment conditions, and topologies, are put to test.

5. Regulatory Testing: This testing determines the compliance of IoT applications with privacy regulations.

6. Scalability Testing: This includes the testing of all functional and non-functional use cases to ascertain whether the system is easy to scale to accommodate future upgrades.

The IoT-Led Solutions by Kellton

At Kellton, we are for avant-garde IoT. We are committed to developing qualitative, value-driven strategies to validate IoT applications that deliver a comprehensive data management advantage and meet the need for digitization.

Our testing protocols are intelligently curated using a combination of robust tools, devices, and processes, which stretch the capabilities of IoT applications in the most demanding environments. We integrate various protocols and platforms to deliver two key benefits to transformative enterprises:

a) seamless data interoperability; and
b) technological prowess to meet future needs.

Sanjay Kaushik, Manager - Quality Assurance, Kellton, has written an insightful article for CIO Review India, highlighting the strategic approach towards understanding the IoT challenges, and how to exploit testing in IoT. If you’re an IoT-inspired enterprise innovator, the article is the *gold* you need.