Literature review on Internet of Things – Main themes

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Theoretical framework

This section covers the theoretical framework of this thesis. In the literature review the main themes were established: Origins of IoT, enabling trends and technologies, transformational potential, communication models and challenges of IoT. The applied methodology in presented in the 3rd chapter. The results of literature review are divided into three main parts: the first about Internet of Things, second about the Walled garden approach, the third about an open platform approach.

Literature review on Internet of Things – Main themes

While conducting the literature review, several general topics were identified: Origins of IoT, enabling trends and technologies, transformational potential, communication or connectivity model used by IoT implementations and challenges IoT might raise.

Origins of IoT

According to Rowland, Goodman, Charlier, Light, & Lui(2015) the term “Internet of Things” (IoT) was first used in 1999 by a technology pioneer Kevin Ashton, while suggesting supply chain management improvements to his at that time employer, Procter & Gamble. Ashton’s vision was to use radio-frequency identification(RFID) to identify and track products. This improvement would save a huge amount of human work entering manually data into computers.
Holler et al.,(2014) suggests that although the term “Internet of Things” is relatively new, the idea of merging networks and computer in order to track and manage devices has been around for decades. In the 90s “machine-to-machine” (M2M) solutions were used on a broad scale in enterprise and industry. However, many of this early solutions were based on closed built systems or industry specific standards, rather than Internet Protocol or Internet standards.
As stated by Rose, Eldridge, & Chapin, (2015) the first Internet “device” was an IP-enabled toaster that could be turned on and off over the Internet- was featured at an Internet conference in 1990. This turned out to be the starting point of a research field called “smart object networking”, which laid foundation for the present Internet of things (Arkko, McPherson, Tschofenig, & Thaler, 2015). The Trojan Room coffee pot is another example of connect devices. It was a coffee machine located in the University of Cambridge, England in 1991. Its purpose was to avoid the disappointment to find the coffee machine empty, so a camera was set up, and was streaming live on all the desktops on the office network. It can be seen that the concept of making devices communicate to each other is not recently discovered, but why is then Internet of Things such a popular topic in present?

Enabling trends and technologies

According to Rose et al., (2015) the convergence of the technology and the market trends is making it possible to connect different size devices more inexpensive and easier. The authors identified the following trends and technology:
• Ubiquitous Connectivity—Low–priced, fast emerging, widely spread connectivity, this makes almost any device connectable.
• Widespread adoption of IP–based networking— IP turned out to be the most influential global standard for networking, which provides a well–defined platform of software and tools that can be integrated into a broad spectrum of devices quickly and affordable.
• Computing Economics— this trend is based on Moore’s law (1965) which states that “the number of transistors per square inch on integrated circuits doubles every two years”. With today industry’s investments in R&D and manufacturing, this law continues to be relevant to present situation. Every year are developed products with higher computing power and less cost.
• Miniaturization— today’s innovation in the computing sector allows manufacturing and deployment of very small devices and sensors. Matched with greater computing economics it resulted in the improvement of small and low-cost sensor devices, which supply many IoT ssytems.
• Advances in Data Analytics— development of new algorithms, accelerated development in the fields of data storage, computing power and cloud service empowers the collection and analysis of big data. Making it easier to extract useful knowledge.
• Rise of Cloud Computing– Cloud computing advantages computing resources to analyze, manage and save collected data. This permits devices to communicate, with the ability to analyze and control the data.
From this perspective, a wide range of industry sectors are considering the potential for incorporating IoT technology into their products and services.
Manyika, Chui, Bisson, & Woetzel (2015) describe in their report the wide range of applications where IoT is expected to create value for industry and users.

Transformational Potential

While the number of network-connected devices increases, the amount of traffic generated will rise as well. Cisco estimated that the Internet traffic generated by non-PC devices will increase from 40% in 2014 to 70% in 2019. They also estimate that the M2M connections (including IoT ecosystem) will grow from 24% of all connected devices in 2014 to 43% in 2019 (Index, 2015). According to Lucas, Ballay, & McManus (2012) in ten years we could be the witness of a shift of information centricity. From the information being in the machine to the applications, people, environments and devices being “in” the information. As of now the web experience can be characterized by the users downloading and generating content trough their computers and smartphones.
IoT on the other hand can lead to a shift in thinking. It can lead to a “hyperconnected world”, where there are no boundaries for devices or services that can make use of technology.

Communication models

Arkko et al., (2015) outlines a framework of four common communication models used by IoT devices. This models will be described as follows.
Device-to-Device Communication
This model represents the communication between two or more connected devices. The interaction between these devices is possible by using distinctive types of network, as for example IP networks. Beside this, they can start a direct connection by using protocols like Z-Wave, ZigBee or Bluetooth, as can be seen in Figure 2.
Figure 2. Example of device-to-device communication model.
These device-to-device networks are frequently adopted in settings like home controllers, the devices and sensors used in these systems mostly communicate through small amounts of information. IoT equipment like thermostats, light bulbs and light switchers usually forward to each other small data packets of information.
Oftentimes the communication protocols for this model, are not suitable. From the customer’s perspective, it often can limit the user’s ability to choose between vendors. For instance, ZigBee devices are not compatible with Z-Wave family of devices.
Device-to-Cloud Communications
According to Arkko, McPherson, Tschofenig, & Thaler(2015) in a device-to-cloud communication approach, the hardware is connected directly to the Cloud service. This model regularly uses the classical networks, like Wi-Fi or Ethernet, to create a connection among the device and the IP network, that ultimately connects to the Internet cloud service. This can be seen in Figure 3.
Figure 3. Device-to-Cloud communication model diagram.
This communication model is applied by companies and their products like the Nest Labs and its thermostat, also Samsung and its SmartTV. In the matter of Nest Labs, the thermostat passes on the collected information to a database located in the cloud, where the data will be processed. Eventually this data is used to evaluate the home energy consumption. Additionally, the cloud connection grants remote access to the users over devices, via an app or a Web interface. In the case of Samsung technology, the SmartTV records the user’s watching habits and voice and transfer that data to Samsung, by using Internet connection.
Nonetheless, interoperability issues can emerge during connection of devices created by different producers. In case proprietary data protocols are involved, the user might be forced to use a certain cloud provider, the one that is compatible with the device. This frequently is called “Vendor lock-in” (T. Eisenmann, 2008).
Device-to-Gateway Model
Also called the device-to-application-layer gateway(ALG) model, the gadget or the sensor connects to a cloud service by using ALG service as a pipeline. Briefly, it means there is an app running on a local hardware and it is a transitional level between the device and the cloud. This intermediary can act also as a data translation and protocol converter (Ark ko et al., 2015). This model is shown in Figure 4.
Oftentimes, in the role of a gateway is a smartphone using an app that connects with the device and collects relevant info, as a result the stored data is directly sent to the cloud service. This approach is regularly applied in devices like personal fitness trackers (Arkko, McPherson, Tschofenig, & Thaler, 2015). The trackers usually depend on a smartphone app to connect the tracker to the cloud.
Another form of this communication model is the recent evolution of so called “hub” devices. Besides being the local gateway between the devices and the cloud, the “hub” also act as a bridge between different family devices. For instance, the SmartThings hub has Z-wave and Zigbee detection transceivers built in, that way the user can access different families of devices with just one app and a network connection.
Back-End-Data-Sharing Model
This communication model allows the user to merge data from different sources and evaluate it. Also, this is a communication architecture that enables the user to share the data with third parties.
In order for a back-end data model to be effective, it should enable the user to move their data when they switch between IoT services, breaking down data silo barriers. (Arkko et al. 2015) recommend a so called “federated cloud service” approach. This approach merges the resources of different cloud providers, in order to fulfill a bigger business goal. This model suggests that cloud applications programmer interfaces (API) are needed to achieve interoperability of smart devices. This design is shown in Figure 5.

Challenges of IoT

As stated by Castillo & Thierer (2015) the next step for technological innovation will be creating devices embedded with miniature computing devices, and connect them. This will represent a major transformation of how customers interact and are affected by the Internet. Any kind of disruptive innovation raises new issues across user privacy and security, technology and policy (K. Rose et al., 2015). Additionally, IoT will allegedly effect economies and regions, introducing both opportunities and obstacles around the world.
Security
In the Internet of Things environment, each device that is connected might be a potential threat, as it could be a doorway to the IoT framework or personal data (Li, Tryfonas, & Li, 2016). A user is supposed to trust a certain environment; therefore, security is a critical factor for IoT.
According to Rose, Eldridge, & Chapin(2015) as the number of connected devices to the Internet increases, new chances to exploit possible security breaches appear. IoT devices with inferior security could act as opening point for cyberattacks, while poorly designed devices might disclose consumer information to unauthorized third parties. For instance, a refrigerator that is missing malware protection might send hundreds of spam emails to different receivers around the globe, just by connected to the local Wi-Fi network (Starr, 2014).
Another factor to consider is that many IoT devices operate in a manner where the user has no real visibility into working process of the device or the data this device produce and share. When the user doesn’t acknowledge what functions does the device perform and how much information is collected, it can result in security breaches.

Table of contents :

1 Introduction
1.1 Subject of the Research
1.2 Problem Statement & Motivation for the Research
1.3 Research questions
1.4 Research Objectives
1.5 Delimitations
1.6 Definitions
2 Theoretical framework
2.1 Literature review on Internet of Things – Main themes
2.1.1 Origins of IoT
2.1.2 Enabling trends and technologies
2.1.3 Transformational Potential
2.1.4 Communication models
2.1.5 Challenges of IoT
2.2 Walled garden approach
2.3 Open platform approach
3 Research Methods
3.1 Literature review
3.2 Case study
3.3 Data Collection
3.4 Data Analysis
3.4.1 Organizing the content
3.4.2 Content analysis
3.4.3 Creating the report
3.5 Quality evaluation of the research
3.6 Research ethics
4 Results: Case study of Husqvarna Group
4.1 Business ecosystem: Consumer durables segment
4.2 Organization background: Husqvarna Group
4.3 The interview respondents
4.4 Husqvarna Group’s Back end developer
4.4.1 Communication
4.4.2 Security
4.4.3 Compatibility
4.4.4 IoT approach
4.4.5 Internet of Things
4.5 Consultant on back end issues at Cybercom
4.5.1 Communication
4.5.2 Security
4.5.3 Compatibility
4.5.4 IoT approach
4.5.5 Internet of Things
4.6 Back end developer at Cybercom
4.6.1 Communication
4.6.2 Security
4.6.3 Compatibility
4.6.4 IoT approach
4.6.5 Internet of Things
4.7 Gardena Smart System’s Head of software development
4.7.1 Gardena Smart System products
4.7.2 Communication
4.7.3 Security
4.7.4 Compatibility
4.7.5 IoT approach
4.7.6 Internet of Things
5 Analysis
5.1 IoT approach applied in Husqvarna Group
5.1.1 Communication Model
5.1.2 Security and privacy
5.1.3 Compatibility
5.2 Walled garden approach
5.3 Benefits of open platform approach
5.4 Conclusion
6 Discussion
6.1 Result Discussion
6.2 Methods Discussion
6.2.1 Limitations
6.3 Implications for practice and recommendations for Husqvarna Group
6.4 Future Research
7 References
8 Appendices

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