IoT Design Challenges and Solutions


The development of the internet of things architecture is riddled with various challenges. It is important to understand that there is a major difference between designing desktop systems and web applications in comparison to developing an IoT infrastructure as the latter has different hardware and software components. Hence, you cannot use the same traditional approach with your IoT applications which you have been using in the past with web and desktop software. What you can do is that consider the following IoT design challenges and solutions.

1.   Security

One of the key considerations in an IoT ecosystem is security. Users should have trust in their internet of things equipment which can help to share data easily. The lack of secure design means that IoT devices can encounter different types of security vulnerabilities in all of their entry points. As a result of these risks, private and business data can be exposed which can lead to compromise the complete infrastructure.

For example, in 2016, Mirai first arrived on the internet. Mirai is a type of botnet which went on to infect the IoT devices of a major telecommunications company in the US: Dyn. As a consequence, a large number of users were disconnected and they were without any internet connectivity. DDoS was one of the key hacking strategies which were used by hackers.

Solution

A considerable portion of the responsibility to secure IoT devices falls into the hands of the vendors. IoT vendors should incorporate security features in their devices and make sure to update them periodically. For this, they can use automation to perform regular patching. For instance, they can use Ubuntu in tandem with Snap which can help in a quick update of devices. These atomic styles assist developers in the writing and deployment of patches.

Another strategy is to ensure that DDoS attacks are prevented. For this, you have to configure routers so they can drop junk packets. Similarly, irrelevant external protocols like ICMP should be avoided. Lastly, a powerful firewall can do wonders and make sure to update the server rules.

2.   Scalability

By 2020, Cisco predicts that there will be around 50 billion functional IoT devices. Therefore, scalability is a major factor to handle such an enormous number of IoT devices.

Solution

For scalability, there are many IoT solutions which are not only scalable but are also reliable, flexible, and secure. For instance, one of the most common data management infrastructures is Oracle’s Internet of Things. This solution provides many efficient services that help with the connection of a large number of IoT devices. As Oracle is known to be a massive ecosystem with different services and products integrating into its architecture, thus they can help to fix a wide range of concerns.

For mobile development in your IoT ecosystem, you can use Oracle Database Mobile Service—a highly robust solution that helps to create a connection between embedded devices and mobile apps while fitting all the scalability requirements. There is also an option to use a scalable database like Oracle NoSQL Database which can offer you a chance to work on the modern “NoSQL” architecture.

3.   Latency

Latency is the time period which data packets take to move across the network. Usually, latency is measured through RTT: round-trip time. When a data packet goes back and forth from a source to its destination, the time it requires to do this is known as RTT. Milliseconds are needed to measure the latency of data centers where the range is fewer than 5 milliseconds.

IoT ecosystem usually employs several interconnected IoT devices at once. Thus, the latency increases as the network become heavier. The cloud is seen as the edge of the network by the IoT developers. It is necessary to understand that latency issues can affect even routine IoT applications. For instance, if you have an IoT-based automation system in your home and you turn on a fan then latency issues related to cloud processing, gateway processing, wireless transmission, sensing, and internet delivery can arise.

Solution

The latency issue is quite complex. It is imperative that businesses must learn the management of latencies if they plan to use cloud computing effectively. Distributed computing is one of the components which raises the cloud latency’s complexity. Application requirements have changed. Rather than using a local infrastructure for storage, services are distributed internationally. Additionally, the birth of big data and its tools like R and Hadoop are also boosting the distributed computing sector. Internet traffic has made latencies dependent on such scale that they find it hard to utilize similar bandwidth and infrastructure.

Another issue which plagues the developer is the lack of tools that can help with the measurement of the latest applications. Traditionally, connections over the internet were tested via the traditional ping and traceroute. However, this strategy does not bode well today as ICMP is not required for modern-day applications and networks in IoT. Instead, they need protocols like HTTP, FTP, etc.

By traffic prioritization and focusing on QoS (Quality of Services), you can address cloud latency. Before the birth of modern cloud computing, SLAs (Service Level Agreements) and Quality of Services were used to make sure that traffic prioritization was done well and ensure that latency-sensitive applications can use the suitable resources for networking.

Back-office reporting can force applications in accepting decreased uptime but the issue is that a lot of corporate processes cannot sustain the downtime because it causes major damage to the business. Therefore, SLAs should concentrate on specific services by using performance and availability as metrics.

Perhaps, the best option is to connect your IoT ecosystem with a cloud platform. For instance, you can use Windows Azure which is quite is powerful and robust, and can particularly serve those businesses which plan to develop hybrid IoT solutions—in such infrastructure on-premises resources are used for the storage of a considerable amount of data while cloud migration help with other components. Lastly, the collocation of IoT components to third-party data centers can also work out well.

Advertisements

What Should You Know Before Implementing an IoT Project?


By the end of 2019, more and more enterprise IoT projects are expected to be finished. Some of them are in the stage of proof of concept while there are some projects which ended badly. The reason behind this is that project managers were late to understand that they were fast-tracking the implementation of the IoT projects without thinking much. As a consequence, they were left to regret not consulting and analyzing properly.

Different industries and businesses use the internet of things for various applications, however, IoT fundamentals are unchangeable. Before implementing an IoT project, consider the following factors.

Cultural Shift

Organizational and cultural shift emerge as one of the leading issues in the internet of things. For example, take the example of a German cleaning manufacturer: Kärcher. The company’s digital product director, Friedrich Völker, gave a brief explanation of how the company was able to address this issue during its release of an IoT-based fleet management project. He explained that their sales team was struggling in marketing and advertising the software and virtual offerings of the internet of things as they dealt with their customers.

After some time, the sales department refrained from concentrating on a one-off sale. They instead focused their efforts on fostering relationships with the customers to get input on the ongoing performance of the IoT equipment. As a result, they achieved success.

Initiatives related to the internet of things are usually included in the digital transformation of companies which often needs adoption of the agile-based methodology along with the billing procedures for offering support to either pay-per-use based billing or subscription-based customer billing. Therefore, always commit to the efforts of change management in the organization and make use of the agile approach.

Duration of IoT Projects

Businesses need to understand that the implementation of the internet of things needs a considerable amount of time. There are examples where the IoT implementation from the development of the business case to the commercial release took less than a year—the quickest time was 9 months. On average, expect an IoT project to run for at least 24 months.

There are many reasons for such a longer duration of IoT projects. For instance, sometimes the right stakeholders do not have the buy-in. In other cases, there can be a technical problem such as not using an infrastructure which provides scalability support.

Profitability cannot be expected for the initial years; many companies are concentrating on the performance of their internet of things solutions instead. Thus, you have to ensure that the stakeholders are patient and create smaller successes which can provide satisfaction to both the senior management and the shareholders.

Required Skills

Development of end-to-end applications in the internet of things needs a developer to have an extensive set of skills such as cloud architecture, data analytics, application enablement, embedded system design, back-end system integration like ERP, and security design,

However, IoT device manufacturers do not have much experience of the technology stack in the internet of things like AMQP or MQTT protocols, edge analytics, and LPWAN communication. Studies indicate that there is especially a wide gap of skills in the data science domain. To address these concerns, adhere to the following.

  • Map the gap of skills in your IoT project.
  • Make sure that your employees become the jack of all trades .i.e. do not limit them with a single domain—instead encourage a diverse skill set, especially with a focus on the latest IoT technologies.
  • Fill up your experience gap with the help of IoT industry experts so their vast expertise and experience can help you to provide a new level of stability in your project.

Interconnectivity

In this age, users are quite casual with the use of technology; they download and install an application on a smartphone within a few minutes and begin using them without any other thoughts. IoT adopters believe that IoT devices will provide a similar user experience.

On the contrary, one of the most time-consuming aspects in the development of the internet of things solutions is the protocol translation. For instance, in one case, the internet of things implementation for an industrial original equipment manufacturer (OEM) required almost 5 months to design all the relevant and mandatory protocol translations. It was only after such a prolonged time period that the IoT applications and equipment were able to function seamlessly. Therefore, make sure you can create a standardized ecosystem which falls in the scope of your industry and use case.

Scalability

Not many people report it but a large number of IoT devices can generate scalability issues. When such an issue arises, device manufacturers cannot do much as the device is already released and sold in the market.

For instance, once a construction equipment manufacturer designed tidy dashboards for the remote monitoring of machines. After some time, the IoT infrastructure was revamped such that predictive maintenance and the hydraulic systems’ fault analysis could be performed. At this phase, it was first realized that the data model was not supported by the required processing capacity. Similarly, there were instances in which the processing power was weak and restricted the manufacturer into adding different functionalities.

While you should always begin small, your vision and planning should be grand from day one. Design your IoT with a modular approach and challenge your data model and hardware design.

Security

Often, security is cut off from the development of IoT devices. This is because many consider security as merely an afterthought while embarking on a mission to create IoT technologies. However, device and data security have a prominent role in the development of the internet of things development.

For instance, some manufacturers of Connected Medical Devices use the services of an ethical hacker. This hacker looks for any possible security loopholes in the IoT project. To do this, they use a wide range of strategies for rooting IoT equipment, lift, penetrate, and alter its code.