Chapter 12
Cloud computing systems for smart cities and homes
T. Guelzim*
Abstract
To support this rapid change in information delivery and consumption, cloud computing has evolved from pure technical and narrow field applications to solve higher problem domains in the realms of smart homes and cities. Through standardized system architecture, communication and information exchange, cloud technologies rely on instrumentation and interconnection to provide intelligent feedback and to support new capacities such as digital convergence, energy management or safety and security. Smart homes and cities cannot thrive without data fusion, and mining. Managing, processing, and synthesizing mass flow of information in real time may only be accomplished with state of the art information systems architectures. Cloud computing technologies are a solid foundation to consolidate the physical infrastructure as well as to streamline service delivery platforms.
Keywords
cloud computing
smart city
smart home
big data
data analytics
1. Introduction
In today’s information systems development model, cloud computing has become a de facto platform to enable content delivery to consumers. Cloud-based services have become more pervasive than ever: YouTube, Netflix, DropBox, Facebook, Amazon, and SoundCloud are being created and launched at a rapid pace. Evolving these platforms have allowed to reach mass user base all across the globe; creating communities and sharing key information-consuming patterns, delivering seamless user experience, and hiding all of the complexities behind such systems. Today, these systems have democratized access to information and made it available instantaneously. Everyday gadgets such as set-up boxes, wrist-band watches, athletic gear, and soon glasses to name a few have all been connected and data can be exchanged with a simple touch or a wink of the eye. This marks an initial experimenting era.
The term cloud computing has been used throughout the industry for more than a decade. In the early days, this term has been correlated with applications such as computing grid service, files storage, and early advanced email application. Later, cloud computing has reached a transition point in which every organization is considering cloud as a new cost cutter for its services and business offer [1]. Although considered a novel way of delivering computational resources, cloud computing is not a new technology. It is a delivery model based on internet infrastructure, computing, and storage. This new technological and economic model has attracted massive global investments in various sub areas such as performance, security, usability, and global accessibility [1].
It is undeniable that cloud computing has reached critical mass and become a very important aspect of any modern IT strategy or product development. In a recent study [2], the US government has suggested that 25% of the IT budget should be spent on cloud computing initiatives. It has been suggested that almost 30% of the cost would come from current infrastructure cost reduction.
In this chapter, we discover the basic concepts behind cloud computing and its application in the fields of smart homes and cities.
2. Cloud computing fundamentals
2.1. Cloud computing offerings
There are three major offerings on cloud computing often described in the following pyramidal relation in Fig. 12.1.
Figure 12.1 Cloud Computing Models
Fig. 12.1 shows the three types of cloud computing: SaaS, PaaS, and IaaS. These are the basic building blocks of any cloud computing service and are often used in combination. A description of each one is given subsequently.
2.1.1. SaaS: Software as a Service
Software as a service is the cloud offering that most people interact with today. Whether enterprise or consumer oriented, SaaS offers are accessed via the internet and often eliminates the need to download, install, and configure application on the client side. This deployment model makes it very attractive from a maintenance point of view. In addition, it allows seamless global reach of services to any users provided an internet access. In most cases, SaaS applications are managed by third-party vendors. Users access these services using an account based on a monthly subscription economic model.
2.1.2. PaaS: Platform as a Service
Platform as a service is a software environment used for the development and execution (runtime) of applications. PaaS is defined as a computing platform that allows the creation, testing, and implementation of SaaS applications or other applications without the complexities of setting up or buying expensive infrastructure. For PaaS vendors, many technical aspects need to be managed such as networking, storage, virtualization, middleware, etc. PaaS is bundled as installable units with names that differ from “cartridge” to “workable unit.” PaaS is used to host applications that can later be consumed by a multitude of clients such as mobile, web, smart TV, and setup boxes. Application developers need not to worry about capacity and less about scalability. PaaS offerings allow them to request the allocation of new workable units on demand and also to scale down the system dynamically. Some well-known PaaS platforms are Google App Engine [3] and Microsoft Azule services [4].
2.1.3. IaaS: Infrastructure as a Service
IaaS is one of the most fundamental layers of cloud computing. It also interchangeably referred to as hardware as a service (HaaS). In this layer, the vendor offers virtualized infrastructure, networking as well as storage over the Internet. These resources are often available on demand and can scale linearly and dynamically if demand on the infrastructure increases. This makes it ideal for client and companies that require optimizing the cost of their IT infrastructure.
2.2. Characteristics of cloud computing architecture
Cloud computing, grid computing, and high-performance computing are all computing paradigms that belong to parallel computing [5,6]. To put simply, cluster resources are often located in a single internet domain whilst cloud computing relies on multiple data center that span multiple domains and geographical areas. This characteristic is important in order to optimize resource delivery from the closest and most optimal location. From a client point of view, cloud computing encompasses these characteristics [7]:
• dynamic and elastic computing
• rapid response and scalability
• self-managed, power efficient and self-repair
• weak consistency guarantees (CAP theorem)
• internet as a weak link in the chain
• consumption based billing
• low client investment in hardware for SaaS applications
From a technical perspective, Table 12.1 highlights the major system characteristics of cloud computing in contrast with grid computing:
Table 12.1
Main Differentiating Characteristics Between Cloud Computing and Grid Computing
| Characteristic | Cloud Computing | Grid Computing |
| Service-oriented paradigm |
|
|
| System loose coupling |
|
|
| System fault tolerance |
|
|
| Networking: TCP/IP stack |
|
|
| Infrastructure virtualization |
|
|
Loose coupling is a fundamental system architecture quality attribute of cloud computing. Similar to software components, loose coupling in cloud computing ensures that components are well defined with specific responsibilities and clear interacting interfaces. Loose coupling in cloud computing infrastructure is accomplished partially through virtualization and recently through container-based deployment technology such as Docker. For it to work, infrastructure is separated into logical and physical parts. This separation ensures that the behavior of one part does not affect other parts of the system.
As shown in Fig. 12.2, loose coupling is achieved by separating the physical and the hypervisor layers on top of which sit the various virtual machines. In this schema, a client requests virtual machines that are backed up by infrastructure resources, that is, provisioning. The location and the capacity of resources are transparent to the client and it is possible to dynamically add new resources provided changes in the computational demand.
Figure 12.2 Loose Coupling in Cloud Computing
Another system characteristic of cloud computing is fault tolerance. In the basic definition, fault tolerance describes the ability of the underlying system to withstand errors (physical or software based). These errors can occur in two places as described in Table 12.2.
Table 12.2
Cloud Computing Fault Tolerance Model
| Error Source | Description |
| Provider inner | In this scenario, the fault is fixed by substituting the failed part or by using redundancy mechanism. |
| Provider across | In this scenario, when different providers are aggregated to provide a service, the system attempts to redirect to healthy nodes or service providers in order to provide seamless runtime to clients. This can also be achieved using load balancing. |
A last difference between cloud computing and grid computing is the reliance on virtualization technology. In grid computing, calculation intensive operations rely on physical hardware. Cloud computing, however, thrives on shared resources that can be easily virtualized using technologies such as VMware for enterprise or on other higher technologies such as OpenStack.
2.3. Cloud computing models
Cloud computing models can be categorized into three major types of clouds as shown in Fig. 12.3.
Figure 12.3 Cloud Computing Grids
These models can be summarized as shown in Table 12.3.
Table 12.3
Description of Cloud Computing Types
| Cloud Type | Characteristics |
| Public | Offers pay as you go billing model Supports multiple tenants Services are either shared of dedicated Externally managed Externally designed |
| Private | Self-hosted Self-managed |
| Hybrid | Partner hosted Dedicated environment |
2.4. Cloud computing security
As consumers move their applications and data to cloud computing, it is primordial that the level of security at least matches that offered by the traditional IT departments [8]. Failure in doing so will result in higher costs and potential loss of data, business and consequently clients and thus eliminating the benefits of cloud computing. To do so, cloud providers establish policies and procedures to ensure that tasks are accomplished according to the same standard process. This leads to better governance and predictable overall performance. In a cloud computing migration endeavors, good and effective governance is key quality to preserve trust in IT infrastructure as well. Cloud providers and clients agree on SLA parameters so that each party can take appropriate security assessment, prevention, and control measures [8]. The split of responsibilities with the service provider requires the consumers to secure the operating system, the data put in the cloud and the network stack configuration. Fig. 12.4 illustrates the computing security pillars.
Figure 12.4 Cloud Computing Security Pillars
One additional issue in cloud governance is the jurisdictional protection of personally identifiable information (PII). There is a divergence across many countries on how to access PII data in case of investigation and enforcement. This is very problematic since cloud providers place datacenter in various geographical regions around the globe to optimize disaster recovery. This makes it difficult to know where the data actually resides and how to abide with international subpoenas on data since each piece of the data is governed by the laws of the country in which it resides. Since there is no clear solution on this matter, often governments and big corporations require that the data be hosted in servers inside their jurisdiction.
2.4.1. Effectively manage identities
Consumers need to ensure that the cloud provider has processes that control who can access their data and applications. This access shall be controlled and managed using regular standards. Some well-known standards are:
• Federated Identity Management (FIM)
• Identity Provisioning and Delegation
• Single Sign-On, Single Sign-Off (SSO)
• Identity and Access Audit
• Robust Authentication
• Role entitlement and Policy Management.
Cloud providers shall formalize processes for managing their own employees accessing the cloud infrastructure. It should also be possible to demonstrate to consumers that this is put in place upon demand.
2.5. Key concerns about cloud computing
Although cloud computing has evolved in many areas, there are many concerns that are considered drawbacks for many users:
• Less control: There are still many companies that are uncomfortable with the idea that owned information is stored elsewhere than the local infrastructure servers.
• Data security: Exchange of data across the network increases the risk of unauthorized exposure thus authentication and authorization mechanisms become important.
• Reliability: High availability is increasingly needed because businesses worry about loss of service and thus loss of customers.
• Compliance: In certain fields, regulatory compliance and audit is essential for certain IT infrastructures. Regulations such as HIPPA and SOX prohibit the use of cloud computing services to be used.
• Security management: Providers must provide easy control mechanisms in order to manage their PaaS of IaaS services.
2.6. Major industry players
Table 12.4 summarizes the major cloud computing players.
Table 12.4
Cloud Computing Major Industry Players
| Cloud Model | Industry Player | Description |
| IaaS | Amazon web services | AWS has been around for a while and is key played in elastic and dynamic resource allocation. It is widely used that it is also backbone for many SaaS providers such as spootify for example. |
| Microsoft Azure | The Microsoft offer resembles to AWS in terms of elasticity and ease of use. In addition it boasts predictive analysis and disaster recovery. It supports major business such as Mazda, Lufthansa, and Mark & Spencer | |
| Google Drive | Google Drive is pioneer in cloud storage with “infinite” capacity offered to student and free 15GB offered to every subscribed user. | |
| DaaS | Citrix | Citrix provides virtual desktop solutions along with host management file sync and shared services. |
| VMware | VMware is long known for its hypervisor software that supports multiple OS flavors. VMware through the Horizon suite offers performance remote desktop which are hosted in cloud environments. | |
| SaaS | Salesforce.com | Salesforce is the go to provider for CRM solutions. Its SaaS offer has also extended to PaaS on order to allow companies build other apps on top of its services. |
| PaaS | OpenShift | The RedHat Openshift offers major platform development software to be accessible and provisioned through simple interfaces. This is used by developers and enterprises to host applications in the cloud |
| Heroku | Similar to Openshift, Heroku supports many programming languages and application servers. |
3. Cloud computing applications
Cloud computing is a technically dense topic that has many applications in various business domains. Here is a short list to name a few:
• custom relationship management
• online storage management
• collaboration tools
• financial applications
• human resources and employment services
• smart homes
• smart cities
• Big Data
The subsequent sections describe three major applications where cloud computing is an enabling technology.
3.1. Big Data as an enabling technology for Smart homes and cities
Big data is considered the backbone technology for many applications of cloud computing in the domain of smart cities and homes. The following graph in Fig. 12.5 was produced by searching web search content trends on Google Trends for the following key words: cloud computing, big data, smart homes, and smart cities from 2014.
Figure 12.5 Google Trends Graph for Cloud Computing, Big Data, Smart Cities, and Smart Home Between 2014 and 2015
In Table 12.5, we explore the Google search index weights of cloud computing, smart homes, smart cities and big data by region.
Table 12.5
Google Trends Search Index Weight for the Key Words: Cloud Computing, Smart Homes, Smart Cities and Big Data per Region of Interest
| Cloud Computing | Smart Homes | Smart Cities | Big Data | ||||
| Google search index | Google search index | Google search index | Google search index | ||||
| Malaysia |
 19 |
UK |
 100 |
India |
 100 |
India |
 100 |
| Australia |
 16 |
USA |
 41 |
Spain |
 41 |
Singapore |
 87 |
| UK |
 14 |
UK |
 11 |
Hong Kong |
 69 |
||
| USA |
 14 |
USA |
 7 |
Taiwan |
 48 |
||
| Canada |
 11 |
South Korea |
 46 |
||||
| Indonesia |
 8 |
USA |
 44 |
||||
| Germany |
 8 |
Spain |
 38 |
||||
To the reader, it is notable that Asia and North America are the two global players across all categories in addition to Germany and Spain in Europe. Although there are not too many experiences or players worldwide for smart homes or cities, this can be explained by their reliance on current advances on cloud computing and big data which we see thriving in multiple countries. We shall see major advances in smart homes and cities in the forthcoming years as the former technologies mature.
3.1.1. Big data, data fusion, and data analytics
Cloud computing and big data is a compelling combination. In a nutshell, big data refers to huge data sets in volume, data that is diverse and that include structured, semi structured and unstructured data. In today’s world, this flood of data is produced from a multitude of data sensors and gadgets such phones, RFID tags, homes, hospitals, roads, cars, public spaces, etc. This data in raw form is not easily exploitable and does not give value. In fact, what make it valuable are the insights and analytics it produces when it is analyzed. Current cloud computing systems have demonstrated large capabilities for moving data into the cloud, indexing and searching it as well as coordinating large scale cloud databases analysis. To do so, many supporting algorithms and technologies were developed and enhanced such as Map Reduce, Chord, and Dynamo. These algorithms have been adapted and optimized to serve in the cloud [9–11]. Fig. 12.6 illustrates the map-reduce algorithm in the cloud.
Figure 12.6 Big Data Map Reduce in the Cloud
In a growing number of enterprises that are requiring data analysis (Financial institutions, and scientific laboratories), Information Technology (IT) role is shifting from traditional computing grid based services to brokering cloud based big data analytics services [14] also known as Data as a Service or DaaS. Using cloud infrastructure to analyze big data makes sense for various reasons. To name a few [12]:
• Investing in big data analysis requires large IT budget. Cloud computing provides an appealing case when it comes to resource elasticity
• Data can come from internal as well as external sources. External data is often hosted in cloud stores so it makes perfect case to use the same infrastructure to analyze this data and keep the overall system coherent.
• Data services such as Analytics as a Service (AaaS) are needed to extract value from big data.
Cloud computing models are thus the next logical evolution in the field of scalable analytics solutions and we start to see many start-ups operating in this field. Organization using cloud to provide AaaS can weight many factors such as security, interoperability, workload when implementing such a solution. Often, a hybrid model is used where a private cloud is used to handle and manage in-house data while a public cloud is used as an extension to further provide scalability to the system [12].
3.1.2. Trends in big data as an enabling technology
From current experiences, it is undeniable that cloud computing is a cost-effective delivery model for big data and data analytics. Cloud will enable the enterprise as well as cities to deliver a new generation of agile and innovative solutions. The first generation big data applications were based on textual data. The second or next generation of big data analytics will aggregate data from multiple sources and encodings such as voice data, video stream, car flow and transportation data, hospital data, airline data, grid energy status, homes sensors, and user and objects tracking data, among others.
3.2. Smart cities
Many of the world cities have embarked on smart city projects, including Seoul, New York, Tokyo, and Shanghai. These cities might seem like cities of a future era but with the current advances in technology and especially cloud computing, they are only exploiting to a certain extent what current technology has to offer.
3.2.1. Smart city concept
A smart city is a concept of a knowledge, digital, cyber, and ecofriendly city. Based on the specificities of each city, the following two definitions emerge:
• “A city well performing in a forward-looking way in [economy, people, governance, mobility, environment, and living] built on the smart combination of endowments and activities of self-decisive, independent and aware citizens.” [13]
• “A city that monitors and integrates conditions of all of its critical infrastructures including roads, bridges, tunnels, rails, subways, airports, sea-ports, communications, and water, power. Even major buildings can better optimize its resources, plan its preventive maintenance activities, and monitor security aspects while maximizing services to its citizens.” [14]
• “A city that strategically utilizes many smart factors such as Information and Communication Technology to increase the city’s sustainable growth and strengthen city functions, while guaranteeing citizens’ happiness and wellness.” [15]
Smart cities require a lot of planning in order to create coherence between city services. This can be achieved by many models and most notably a human-centric model that is based on ICT infrastructure. Fig. 12.7 describes this model.
Figure 12.7 Cloud Computing Benefits in the Context of Smart City
The continuous evolution of the Internet and the ability to maximize user activities allowed accelerating the emergence of ideas that attempt to improve the quality of services for communities around the cities [16]. Smart cities are a new perception of what commonly provided services should be in the age of the internet. Smart cities enclose services in diverse business and technological fields such as efficient use of natural resources as electricity, water, and air quality in addition to waste management. There are many examples of smart cities around the world. Each one of these cities is revolutionizing current processes in order to improve the quality of life of their citizens while optimizing the cost of these services [15]. One of the most cheerful and bold moves by the city of Berlin is to consider cloud computing as a natural resource [17].
For smart cities services to take shape, large amounts of data emerging from many sources must be collected, analyzed and synthesized in order to take informed actions and decision automatically and semi-automatically.
3.2.2. Smarter grid
According to the energy information administration, 62% of worldwide energy generation comes from gas and coal, 13% comes from nuclear, 16% from hydraulic systems and only 4% from renewable energies [18]. There is a constant rise in energy demand to levels above 80% until 2030 and by 2040, energy demand from large economic powers such as China will double that of the USA level. Having an outage such as that of 2003 in North America creates disturbances in businesses and the economies at large. These power grid failures could in most cases be prevented if the diagnostic information was available and ready in time.
In Fig. 12.8, we illustrate the smart grid ecosystem with energy efficiency at its center. Energy is stored and distributed to users. Excess energy can be exported to third party for example. There are many challenges and opportunities in smart grids that can be addressed by cloud computing [18,19]. Examples include dynamic energy pricing and shifting potential peak demand to a different time when the price of energy is low, real time massive data streaming and analysis from sensors plugged in the infrastructure [20]. To ensure proper coordination and efficiency in this area, ultraresponsive Supervisory Control and Data Acquisition (SCADA) systems can be used. This is illustrated in Fig. 12.9. New studies suggest that new paradigms need to be devised in order to support optimized production and consumption of power as well as to estimate a wide area state of the grid.
Figure 12.8 Smart Grid Ecosystem
Figure 12.9 Cloud Enabled Big Data Analytics
3.3. Smart home
3.3.1. Concept
The idea of moving home automation to cloud infrastructure is to provide a simple deployment model for client when deciding to install home automation devices [23]. From usability point of view, any new installation shall be easy to use, vendor agnostic as well as interoperable between devices providing the same or complementary data. IBM in [23] has defined three major characteristics of new smart home appliances:
• Instrumented: having the ability to sense and monitor changing conditions.
• Interconnected: having the ability to interact with people, systems and other objects.
• Intelligent: having the ability to make decision on data and produce a better outcome.
A smart home defines and offers many new capabilities. Here are few examples to name a few:
• entertainment and smart TVs
• energy management
• safety and security
• health and convenience
• user recognition and home profile management
• automatic contact of emergency services
• automatic virtual shopping
• practical data display
Cloud computing provides and intelligent platform to connect interoperating services [23].
As illustrated in Fig. 12.10, smart homes will be equipped with a variety of sensors such as power meters and monitoring devices. These devices will communicate together and contact services running in the cloud to provide the desired functionality. Table 12.6 illustrates how home devices will become smarter [23].
Figure 12.10 A Connected Smart Home
Table 12.6
Example of Smart Devices
| Home Device | Description in a Smart Home Context |
| Home energy distributer | On the basis of the activities in the home and the surrounding building, energy usage by other home appliances will be adaptive to optimize the cost of the KWH as well as the load of the grid. This adaptive information is extracted through continuous sensor data collection from the home as well as continuous behavior analysis and comparison with other relevant data from the cloud |
| TV set | Propose programs and content on the basis of user watch list history Propose targeted ads on the basis of content |
| Refrigerator | Adjust the thermostat on the basis of the volume of the food items it contains |
| Washer and dryer | Determine the water temperature in the wash/rinse/dry cycle on the basis of the load volume, dirt level, etc. |
| Water heater | Water heater that turns on to heat the water when the cost of energy is cheap and let the water cool off when this water is not needed |
| Air conditioner | It will consume and match usage and climate patterns, power cost and grid state in order to provide the most optimal temperature in the home at an optimal cost |
3.3.2. Smart homes enabled by the cloud
Cloud computing platform offering or PaaS is ideal for providing the basic layer behind home automation. It allows dynamic allocation of resource applications. Provided the standardized web service interfaces, it is possible to enable dynamic composition of solutions in a plug and play mode. Relying on the cloud, smart home solution vendors can easily scale their solutions to millions of users worldwide. It is because we benefit from dynamic provisioning of resources. Using common PaaS and IaaS platforms allows devices to become connected and interoperable with other devices from different vendors. This is due to the expansion of industry wide standards as well as solid consortia of market leaders. The key benefits of using cloud computing to enable smarter home can be summarized as shown below:
• From a consumer point of view, the smart home devices are easier to use especially that the management has been moved to the cloud. This implies that no IT infrastructure needs to be put in place except a broadband network. Connecting smart home devices is only a matter of software adapters at the PaaS provider side. The extensibility of networked services along with the ability to link both existing and new devices provide reliable performance and increase service innovation.
• From a device manufacturer point of view, relying on industry standards through cloud allows creating innovative services as well as reaching large consumer base. Open standards prevent vendors and especially start-ups from being locked out of specific markets where device manufacturers have stroke specific deals. Once the cloud is the platforms, device and service manufacturers can concentrate on delivering added value business features and scale up or out in markets freely and easily.
• From a service provider point of view, providing services on top of standardized device interface allows a shorter time to market, and better pricing due to shared IT infrastructure. Along with device manufacturer, service providers can concentrate on added value services.
3.3.3. Home cloud service delivery platform
The service delivery platform, which sits on top of cloud computing infrastructure, enables the integration and monitoring of services and composites of services. The delivery platform concept has been developed by IBM and improved with deployments in the telecom IT industry in order to provide and reach content to consumers [21].
As illustrated in Fig. 12.11, the service delivery platform is a service-oriented Architecture (SOA)-based modular component services. It provides a controlled way to add new services and by aggregating and composing these services on the cloud and simplifying the consumer based side.
Figure 12.11 Service Provider Cloud Platform
3.3.4. Emerging protocols for smart homes
In order to successfully bring cloud based smart homes to market, it is necessary to ensure proper communication between the smart home devices and the cloud. This communication relies on the following protocols and standards [21]:
• Home gate standard: ISO/IEC 15045
• Wired systems: USB, Ethernet, IEEE 1395
• Low-level wireless protocols such as ZigBee, HomeRF, Wimax, Bluetooth
• Special level interoperability such as OSGi, TAHI, and Cablehome
• Home networking systems such as DVB, DLNA, and UPnP
• Power line such as DS2, X10, and HomePlug
• Specifications: HGI, ITU-T SG-5, ITU-T IPTV-GSI, and IEC TC100 gateway
4. Case study: Seoul smart city
4.1. Presentation
Smart Seoul is one of the largest metropolitan cities in Asia and best known as one the most technological know-how cities in the world according to the UN smart cities survey [22]. Smart Seoul was announced in 2011 to promote Seoul’s reputation as the world ICT leader by demonstrating the use of state of the art technologies. Strictly speaking, smart Seoul is not the first attempt of South Korea to use ICT for the development of a smart city. An initial attempt in 2004 was developed to use pervasive computing technologies in order to enhance the city’s competitiveness and provide ’smart’ services to citizens.
4.2. Cloud based ICT infrastructure
Technological advances in large systems and specifically cloud computing allow the implementation of many concepts. The following are the three components behind Seoul smart city:
• ICT infrastructure and Cloud computing: With the massive amount of data that needs to be analyzed and processed as well as the increasing demand of computing resources in order to deliver services due to the dynamic nature of devices plugged in the smart city infrastructure, cloud computing is the most suitable technology stack.
• Integrated management framework: A management framework is essential to guarantee a cohesive and common layer for managing and monitoring all resources and services. Provided that smart city solutions are created by multiple vendors and in various domains, ICT infrastructure must adhere to common standards in order to ensure interoperability and provide simple interfaces to manage services in the city.
• Smart users: Having a comprehensive smart city plan relies also on tech-savvy users that are able to interact with smart services by increasing access to smart devices.
Provided the scale of such a city, cloud computing has been relied on to solve two major issues:
• Provision resources to public services in the cloud infrastructure
• Aggregate and synthesis the data to provide added value information
Fig. 12.12 depicts a high-level components architecture ICT stack of a smart city.
Figure 12.12 High-Level Components of Smart City ICT Ran on Cloud Computing
From a system architecture point of view, a smart city such as Seoul is a system of systems. This implies that there are many individual and independent systems that when combined create and form a meta-system which in turn becomes a sub system. Cloud computing can scale well to such a complexity. In such a system, mobile applications interact with the infrastructure using services through a public API which in turns hides all the complexity behind data source aggregation. This data is extracted using DaaS services. In order to ensure coherence and control across data access, city governance in the context of smart cities has been evolved. New monitoring tools, frameworks and interfaces are running on the cloud infrastructure to provide live feedback on city resources [23].
4.3. Data and service delivery
With any content delivery system based on cloud infrastructure, strong communication networks are key components to deliver services on time and with high quality. Seoul smart city uses mobile and web technology in order to provide “smart” services to users. A wide range of information is available through mobile applications. Location based services pinpoint to public offices, hospitals, transportation live data, continuous air quality checks, emergency data, live crimes data and statistics, among others.
In order to provide Seoul citizens with useful information, one of the many challenges facing this system is how to aggregate this data from all sorts of databases, data sensors, live feeds, CCTV data, police reports, alerts, etc. It requires the use of unconventional IT systems and computing paradigms. Big data and data analytics are key technologies that are heavily used in this context.
4.4. Open Application Programming Interface (API) and Open Data
As described in earlier sections, Table 12.7 shows the evolution of the data sources in the Seoul smart city ICT system [23].
Table 12.7
Evolution of Data Sources in Seoul’s Smart City Cloud Infrastructure
| Classification | 2011 | 2012 | 2013 | 2014 |
| Accumulated number of databases | 20 | 60 | 100 | 150 |
| Proportion of total (target of 150 DBs at full system scale) | 15% | 40% | 70% | 100% |
With such an increasing number of databases and unbounded number of connecting devices (either data producers or consumers), scalable data access architecture shall be put in place. A common paradigm is the use of public API interfaces, as shown in Fig. 12.13, which abstracts the complexity behind the data access.
Figure 12.13 Smart City Open API
This data is accessible via the internet and can be used either in raw form for application developers or in the form of graphs, augmented maps and sheets to enhance and simplify understanding for citizens.
4.5. PaaS mobile application data access
More than two thirds of Seoul’s population is equipped with mobile phones and devices. Seoul government officials are leveraging this boom in technology as well as the private sector’s activeness in order to accelerate the adoption of public apps and consumption of PaaS services [23]. Seoul metropolitan government has started a program to reward best apps developed by local companies or private developers. Fig. 12.14 depicts PaaS open API infrastructure in the context of smart city.
Figure 12.14 PaaS Open API Infrastructure
A mesh of content provider servers is coordinated to aggregate data and provides endpoint services. These servers are contacted via a common Open API service and mobile or web-accessing apps may represent the data in the adequate and convenient way to the citizen.
5. Summary and concluding remarks
Cloud computing is not a new topic. It is just an evolution of common paradigms in IT infrastructure and delivery based on virtualization and containers. Cloud computing promises agility, innovation, and lower cost by outsourcing traditional IT issues such as hardware maintenance, upgrades to specialized vendors with the benefit of acquiring the capacity that is needed. Although cloud computing has many benefits, it also has some shortcomings that still shall be addressed once the technology matures enough such as data security, compliance, and governance.
There is no doubt that cloud computing will dominate the IT landscape within the years to come. With the adoption of many protocols and standards, cloud providers erase the gap between enterprise expectations and technology maturity. This leads to the emergence of new applications in the consumer realm such as smart homes and smart cities. These applications rely on interconnected devices and software with an exchange of enormous data which need to be analyzed and interpreted in order to present it in a comprehensive form. In this vision enabled by cloud technology, an ecosystem is vital in order to develop new service delivery and business models. Consumer electronics manufacturers lead this movement so as to reach the widest consumer base possible. Once their devices are connected to the cloud, other vendors provide service delivery platforms to aggregate many services and provide valuable data and insights to consumers. In this setup, the cloud infrastructure constitutes the IaaS and the PaaS and other vendors or third party developers can manage in order to provide applications to offer a SaaS layer. All of these layers and technologies are interconnected in a seamless and simple manner.