Unit-3 IoT Architectural Overview PDF

Unit-3 IoT-An Architectural Overview What is IoT Architecture? IoT architecture refers to the tangle of components such as sensors, actuators, cloud services, Protocols, and layers that make up IoT networking systems. In general, it is divided into layers that allow administrators to evalua...

Unit-3 IoT-An Architectural Overview What is IoT Architecture? IoT architecture refers to the tangle of components such as sensors, actuators, cloud services, Protocols, and layers that make up IoT networking systems. In general, it is divided into layers that allow administrators to evaluate, monitor, and maintain the integrity of the system. The architecture of IoT is a four-step process through which data flows from devices connected to sensors, through a network, and then through the cloud for processing, analysis, and storage. With further development, the Internet of Things is poised to grow even further, providing users with new and improved experiences. IoT-An Architectural Overview IoT can be classified into a four or five-layered architecture which gives you a complete overview of how it works in real life. The various components of the architecture include the following: Four-layered architecture: this includes media/device layer, network layer, service and application support layer, and application layer. Five-layered architecture: this includes perception layer, network layer, middleware layer, application layer, and business layer. IoT-An Architectural Overview Functions of Each Layer Sensor/Perception layer: This layer comprises of wireless devices, sensors, and radio frequency identification (RFID) tags that are used for collecting and transmitting raw data such as the temperature, moisture, etc. which is passed on to the next layer. Network layer: This layer is largely responsible for routing data to the next layer in the hierarchy with the help of network protocols. It uses wired and wireless technologies for data transmission. Middleware layer: This layer comprises of databases that store the information passed on by the lower layers where it performs information processing and uses the results to make further decisions. IoT-An Architectural Overview Service and application support layer: This layer involve business process modeling and execution as well as IoT service monitoring and resolution. Application layer: It consists of application user interface and deals with various applications such as home automation, electronic health monitoring, etc. Business layer: this layer determines the future or further actions required based on the data provided by the lower layers. Different layers of IoT Architecture IoT Architecture 1)Perception/Sensing Layer: The first layer of any IoT system involves “things” or endpoint devices that serve as a conduit between the physical and the digital worlds. Perception refers to the physical layer, which includes sensors and actuators that are capable of collecting, accepting, and processing data over the network. Sensors and actuators can be connected either wirelessly or via wired connections. The architecture does not limit the scope of its components nor their location. IoT Architecture 2) Network Layer: Network layers provide an overview of how data is moved throughout the application. This layer contains Data Acquiring Systems (DAS) and Internet/Network gateways. A DAS performs data aggregation and conversion functions (collecting and aggregating data from sensors, then converting analog data to digital data, etc.). It is necessary to transmit and process the data collected by the sensor devices. That’s what the network layer does. It allows these devices to connect and communicate with other servers, smart devices, and network devices. As well, it handles all data transmissions for the devices. IoT Architecture 3) Processing Layer: The processing layer is the brain of the IoT ecosystem. Typically, data is analyzed, pre-processed, and stored here before being sent to the data center, where it is accessed by software applications that monitor and manage the data as well as prepare further actions. This is where Edge IT or edge analytics enters the picture. 4) Application Layer:User interaction takes place at the application layer, which delivers application-specific services to the user. An example might be a smart home application where users can turn on a coffee maker by tapping a button in an app or a dashboard that shows the status of the devices in a system. There are many ways in which the Internet of Things can be deployed such as smart cities, smart homes, and smart health. Building an IoT Architecture: BUILDING BLOCKS of IoT Four things form basic building blocks of the IoT system –sensors, processors, gateways, applications. Each of these nodes has to have its own characteristics in order to form a useful IoT system. Simplified block diagram of the basic building blocks of the IoT BUILDING BLOCKS of IoT Sensors: These form the front end of the IoT devices. These are the so-called “Things” of the system. Their main purpose is to collect data from its surroundings (sensors) or give out data to its surrounding (actuators). These have to be uniquely identifiable devices with a unique IP address so that they can be easily identifiable over a large network. These have to be active in nature which means that they should be able to collect real-time data. These can either work on their own (autonomous in nature) or can be made to work by the user depending on their needs (user-controlled). Examples of sensors are gas sensor, water quality sensor, moisture sensor, etc. BUILDING BLOCKS of IoT Processors: Processors are the brain of the IoT system. Their main function is to process the data captured by the sensors and process them so as to extract the valuable data from the enormous amount of raw data collected. In a word, we can say that it gives intelligence to the data. Processors mostly work on real-time basis and can be easily controlled by applications. These are also responsible for securing the data – that is performing encryption and decryption of data. Embedded hardware devices, microcontroller, etc are the ones that process the data because they have processors attached to it. BUILDING BLOCKS of IoT Gateways: Gateways are responsible for routing the processed data and send it to proper locations for its (data) proper utilization. In other words, we can say that gateway helps in to and from communication of the data. It provides network connectivity to the data. Network connectivity is essential for any IoT system to communicate. LAN, WAN, PAN, etc are examples of network gateways. BUILDING BLOCKS of IoT Applications: Applications form another end of an IoT system. Applications are essential for proper utilization of all the data collected. These cloud- based applications which are responsible for rendering the effective meaning to the data collected. Applications are controlled by users and are a delivery point of particular services. Examples of applications are home automation apps, security systems, industrial control hub, etc. Main design principles of IoT 1. Do your research When designing IoT-enabled products, designers might make the mistake of forgetting why customers value these products in the first place. Assume the perspective of your customers to understand what they need and how your IoT implementation can solve their pain points. Research your target audience deeply to see what their existing experiences are and what they wish was different about them. 2. Concentrate on value Early adopters are eager to try out new technologies. But the rest of your customer base might be reluctant to put a new solution to use. They may not feel confident with it and are likely to be cautious about using it. If you want your IoT solution to become widely adopted, you need to focus on the actual tangible value it’s going to deliver to your target audience. Note that the features the early tech adopters might find valuable might turn out to be completely uninteresting for the majority of users. That’s why you need to carefully plan which features to include and in what order, always concentrating on the actual value they provide. Main design principles of IoT 3. Don’t forget about the bigger picture One characteristic trait of IoT solutions is that they typically include multiple devices that come with different capabilities and consist of both digital and physical touchpoints. Your solution might also be delivered to users in cooperation with service providers. Develop a conceptual model of how users will perceive and understand the system. All the parts of your system need to work seamlessly together. Only then you’ll be able to create a meaningful experience for your end-users 4. Remember about the security Don’t forget that IoT solutions aren’t purely digital. They’re located in the real-world context, and the consequences of their actions might be serious if something goes wrong. At the same time, building trust in IoT solutions should be one of your main design drivers. Also, consider data security and privacy as a key aspect of your implementation. Users need to feel that their data is safe, and objects located in their workspaces or home can’t be hacked. That’s why quality assurance and testing the system in the real-world context are so important. Main design principles of IoT 5. Build with the context in mind And speaking of context, it pays to remember that IoT solutions are located at the intersection of the physical and digital world. The commands you give through digital interfaces produce real-world effects. Unlike digital commands, these actions may not be easily undone. In a real-world context, many unexpected things may happen. That’s why you need to make sure that the design of your solution enables users to feel safe and in control at all times. 6. Make good use of prototypes IoT solutions are often difficult to upgrade. Once the user places the connected object somewhere, it might be hard to replace it with a new version – especially if the user would have to pay for the upgrade. From the design perspective, it means that prototyping and rapid iteration will become critical in the early stages of the project. Standards consideration for IoT Alliances have been formed by many domestic and multinational companies to agree on common standards and technology for the IoT. However, no universal body has been formed yet. While organizations such as Institute of Electrical and Electronics Engineers (IEEE), Internet Engineering Task Force (IETF), International Telecommunication Union Telecommunication Standardization Sector (ITU-T), one Machine-to- Machine Partnership Project (OneM2M), Third Generation Partnership Project (3GPP), etc., are active at international level Telecommunication Standards Development Society, India (TSDSI), Global ICT Standardization Forum for India (GISFI), Bureau of Indian Standards (BIS), Korean Agency for Technology and Standards (KATS), and so on, are active at national level European Telecommunications Standards Institute (ETSI) in the regional level for standardization. M2M and IoT Technology Fundamentals-Devices and gateways Device: A device is a hardware unit that can sense aspects of it’s environment and/or actuate, i.e. perform tasks in its environment. A device can be characterized as having several properties, including: Microcontroller: 8-, 16-, or 32-bit working memory and storage. Power Source: Fixed, battery, energy harvesting, or hybrid. Sensors and Actuators: Onboard sensors and actuators, or circuitry that allows them to be connected, sampled, conditioned, and controlled. Communication: Cellular, wireless, or wired for LAN and WAN communication. Operating System (OS): Main-loop, event-based, real-time, or full featured OS. Applications: Simple sensor sampling or more advanced applications. User Interface: Display, buttons, or other functions for user interaction. Device Management (DM): Provisioning, firmware, bootstrapping, and monitoring. Execution Environment (EE): Application lifecycle management and Application Programming Interface (API). Device Device types: 1. Basic Devices: Devices that only provide the basic services of sensor readings and/or actuation tasks, and in some cases limited support for user interaction. LAN communication is supported via wired or wireless technology, thus a gateway is needed to provide the WAN connection 2. Advanced Devices: In this case the devices also host the application logic and a WAN connection. They may also feature device management and an execution environment for hosting multiple applications. Gateway devices are most likely to fall into this category. Device Deployment scenarios for devices Deployment can differ for basic and advanced deployment scenarios. Example deployment scenarios for basic devices include: Home Alarms: Such devices typically include motion detectors, magnetic sensors, and smoke detectors. A central unit takes care of the application logic that calls security and sounds an alarm if a sensor is activated when the alarm is armed Smart Meters: The meters are installed in the households and measure consumption of, for example, electricity and gas. A concentrator gateway collects data from the meters, performs aggregation, and periodically transmits the aggregated data to an application server over a cellular connection Device Deployment scenarios for devices Examples for advanced devices, meanwhile, include: Onboard units in cars that perform remote monitoring and configuration over a cellular connection. Robots and autonomous vehicles such as unmanned aerial vehicles that can work both autonomously or by remote control using a cellular connection Video cameras for remote monitoring over 3G and LTE Oil well monitoring and collection of data points from remote devices Connected printers that can be upgraded and serviced remotely. Gateways A gateway serves as a translator between different protocols, e.g. Between IEEE 802.15.4 or IEEE 802.11, to Ethernet or cellular. There are many different types of gateways, which can work on different levels in the protocol layers. Most often a gateway refers to a device that performs translation of the physical and link layer, but application layer gateways (ALGs) are also common. Some examples of ALGs include the ZigBee Gateway Device (ZigBee Alliance 2011), which translates from ZigBee to SOAP and IP, or gateways that translate from Constrained Application Protocol (CoAP) to HyperText Transfer Protocol/Representational State Transfer (HTTP/REST). Gateways For very basic gateways, the hardware is typically focused on simplicity and low cost, but frequently the gateway device is also used for many other tasks, such as data management, device management, and local applications. Data management: Typical functions for data management include performing sensor readings and caching this data, as well as filtering, concentrating Local applications: Examples of local applications that can be hosted on a gateway include closed loops, home alarm logic, and ventilation control, or the data management function. The benefit of hosting this logic on the gateway instead of in the network is to avoid downtime in case of WAN connection failure, minimize usage of costly cellular data, and reduce latency. Gateways Device management: Device management (DM) is an essential part of the IoT and provides efficient means to perform many of the management tasks for devices: Provisioning: Initialization (or activation) of devices in regards to configuration and features to be enabled. Device Configuration: Management of device settings and parameters. Software Upgrades: Installation of firmware, system software, and applications on the device. Fault Management: Enables error reporting and access to device status. Examples of device management standards include TR-069 and OMA-DM. In the simplest deployment, the devices communicate directly with the DM server. M2M communication M2M refers to those solutions that allow communication between devices of the same type and a specific application, all via wired or wireless communication networks. M2M solutions allow end-users to capture data about events from assets, such as temperature or inventory levels. Typically, M2M is deployed to achieve productivity gains, reduce costs, and increase safety or security. M2M has been applied in many different scenarios, including the remote monitoring and control of enterprise assets, or to provide connectivity of remote machine-type devices. M2M solutions, however, do not generally allow for the broad sharing of data or connection of the devices in question directly to the Internet. A typical M2M solution overview A typical M2M system solution consists of M2M devices, communication networks that provide remote connectivity for the devices, service enablement and application logic, and integration of the M2M application into the business processes provided by an Information Technology (IT) system of the enterprise, as illustrated below in Figure. Figure. A Generic M2M system solution M2M solution The system components of an M2M solution are as follows: ❑ M2M Device. This is the M2M device attached to the asset of interest, and provides sensing and actuation capabilities. The M2M device is here generalized, as there are a number of different realizations of these devices, ranging from low-end sensor nodes to high-end complex devices with multimodal sensing capabilities. ❑ Network. The purpose of the network is to provide remote connectivity between the M2M device and the application-side servers. Many different network types can be used, and include both Wide Area Networks (WANs) and Local Area Networks (LANs), sometimes also referred to as Capillary Networks or M2M Area Networks. Examples of WANs are public cellular mobile networks, fixed private networks, or even satellite links. ❑ M2M Service Enablement. Within the generalized system solution outlined above, the concept of a separate service enablement component is also introduced. This component provides generic functionality that is common across a number of different applications. Its primary purpose is to reduce cost for implementation and ease of application development. ❑ M2M Application. The application component of the solution is a realization of the highly specific monitor and control process. The application is further integrated into the overall business process system of the enterprise. The process of remotely monitoring and controlling assets can be of many different types, for instance, remote car diagnostics or electricity meter data management. Key application areas of M2M Figure. Summarized cellular M2M market situation Key application areas of M2M The largest segment is currently Telematics for cars and vehicles. Typical applications include navigation, remote vehicle diagnostics, pay-as-you-drive insurance schemes, road charging, and stolen vehicle recovery. Metering applications, meanwhile, include primarily remote meter management and data collection for energy consumption in the electricity utility sector, but also for gas and water consumption. Remote monitoring is more generalized monitoring of assets, and includes remote patient monitoring as one prime example. Fleet management includes a number of different applications, like data logging, goods and vehicle positioning, and security of valuable or hazardous goods. Security applications are mainly those related to home alarms and small business surveillance solutions. The final market segment is Automated Teller Machines (ATM) and Point of Sales (POS) terminals Data management (M2M) Some of the key characteristics of M2M data include: Big Data: Huge amounts of data are generated, capturing detailed aspects of the processes where devices are involved. Heterogeneous Data: The data is produced by a huge variety of devices and is itself highly heterogeneous, differing on sampling rate, quality of captured values, etc. Real-World Data: The overwhelming majority of the M2M data relates to realworld processes and is dependent on the environment they interact with. Real-Time Data: M2M data is generated in real-time and overwhelmingly can be communicated also in a very timely manner. Temporal Data: The overwhelming majority of M2M data is of temporal nature, measuring the environment over time. Data management (M2M) Spatial Data: Increasingly, the data generated by M2M interactions are not only captured by mobile devices, but also coupled to interactions in specific locations, and their assessment may dynamically vary depending on the location. Polymorphic Data: The data acquired and used by M2M processes may be complex and involve various data, which can also obtain different meanings depending on the semantics applied and the process they participate in. Proprietary Data: Up to now, due to monolithic application development, a significant amount of M2M data is stored and captured in proprietary formats. However, increasingly due to the interactions with heterogeneous devices and stakeholders, open approaches for data storage and exchange are used. Security and Privacy Data Aspects: Due to the detailed capturing of interactions by M2M, analysis of the obtained data has a high risk of leaking private information and usage patterns, as well as compromising security Managing M2M data The data flow from the moment it is sensed (e.g. by a wireless sensor node) up to the moment it reaches the backend system has been processed manifold (and often redundantly), either to adjust its representation in order to be easily integrated by the diverse applications, or to compute on it in order to extract and associate it with respective business intelligence (e.g. business process affected, etc.). Managing M2M data Managing M2M data Data generation: Data generation is the first stage within which data is generated actively or passively from the device, system, or as a result of its interactions. The sampling of data generation depends on the device and its capabilities as well as potentially the application needs. Data acquisition: Data acquisition deals with the collection of data (actively or passively) from the device, system, or as a result of its interactions. The data acquisition systems usually communicate with distributed devices over wired or wireless links to acquire the needed data, and need to respect security, protocol, and application requirements. Managing M2M data Data validation: Data acquired must be checked for correctness and meaningfulness within the specific operating context. This is usually done based on rules, semantic annotations, or other logic. Data storage: The data generated by M2M interactions is what is commonly referred to as “Big Data.” Machines generate an incredible amount of information that is captured and needs to be stored for further processing. Managing M2M data Data processing: Data processing enables working with the data that is either at rest (already stored) or is in-motion (e.g. stream data). The scope of this processing is to operate on the data at a low level and “enhance” them for future needs. Data remanence: Even if the data is erased or removed, residues may still remain in electronic media, and may be easily recovered by third parties _ often referred to as data remanence. Several techniques have been developed to deal with this, such as overwriting, degaussing, encryption, and physical destruction Data analysis: Data available in the repositories can be subjected to analysis with the aim to obtain the information they encapsulate and use it for supporting decision-making processes. The analysis of data at this stage heavily depends on the domain and the context of the data. IoT The IoT is a widely used term for a set of technologies, systems, and design principles associated with the emerging wave of Internet-connected things that are based on the physical environment. In many respects, it can initially look the same as M2M communication connecting sensors and other devices to Information and Communication Technology (ICT) systems via wired or wireless networks. In contrast to M2M, however, IoT also refers to the connection of such systems and sensors to the broader Internet, as well as the use of general Internet technologies. In the longer term, it is envisaged that an IoT ecosystem will emerge not dissimilar to today’s Internet, allowing things and real world objects to connect, communicate, and interact with one another in the same way humans do via the web today The IoT is not a new Internet, it is an extension to the existing Internet. IoT is about the technology, the remote monitoring, and control, and also about where these technologies are applied. IoT can have a focus on the open innovative promises of the technologies at play, and also on advanced and complex processing inside very confined and close environments IoT Emerging IoT Applications Difference between IoT and M2M : Local and wide area networking in iot: LAN (Local Area Network) A LAN is a group of computers and other network devices attached within a limited area like a house, a building, an office, an entire campus, etc. It is a widely used network of devices and can be set up in a limited geographical area without investing a huge cost like other networks. In most cases, LAN is used to form a network to share resources like printers, scanners, or files like audio, video, movies, software, games, etc. The simplest kind of LAN example is a connection formed between a computer and a printer within a house. Typically, it is a medium that helps transfer data across devices in a limited range area. Advantages of LAN Few advantages of using a LAN are listed below: -Data can be transferred from one device to another networked device without any issue. -Data can be stored centrally in a single storage disk of the server computer. It will be a lot easier to secure the data in a single disk than all the separate disks. This also helps in data management. -LANs allow administrators to share a single internet connection across all the other connected devices. -Instead of purchasing any paid software for each system, users from different systems can use the same software from the server's main computer over the network. Computer peripherals like hard-disk, Optical Disk Drive, and printer can share local area networks that will reduce the hardware purchases' overall costs. Using LAN, multiple computers can use the same printer or other connected devices. LAN WAN (Wide Area Network) WAN is an essential computer network that extends over a large geographical area. It can cover distances between states or countries. WAN is comparatively much larger than LAN or MAN (Metropolitan Area Network) and relatively more expensive. Because of its cost and complex setup, WANs are not usually owned by one organization. Wide area networks are established using several LANs attached by telephone lines or radio waves. Typically, these types of networks are organized using high-end telecommunication circuits. The Internet, a kind of public network, is an example of the largest wide area network. Advantages of WAN: Few advantages of using a WAN are listed below: -WAN enables users to establish a connection over a large geographical area. This is helpful for the organizations having offices at a large distance. They can communicate with other offices easily. -The data is organized in a centralized manner. It helps users to access or manage the data easily. This is helpful when using emails, files, or backup servers. Users don't have to pay for these resources for each office or branch separately. -WAN allows users to communicate over the instant messaging system. Applications like Whatsapp, Telegram, and Skype, have made it easier for people to connect with their friends or family. -Using WAN, companies work on the live server. Thus, the developers and programmers have instant access to the updated files within seconds. This helps in increasing productivity. -Due to a public network, people can organize their business over the Internet globally. WAN LAN and WAN IoT devices can be connected to the internet through local area networks (LANs) or wide area networks (WANs) to enable communication and data exchange between them. Local area networking in IoT typically involves the use of wireless protocols such as Wi-Fi, Bluetooth, Zigbee, or Z-Wave to connect IoT devices within a confined physical area such as a home, office, or factory. These protocols are designed for short-range communication and can connect devices directly to a local network or through a hub or gateway device. Wide area networking in IoT, on the other hand, involves connecting IoT devices over a large geographical area using cellular networks, satellite, or other long-range wireless communication technologies. WANs enable IoT devices to connect to the internet and communicate with other devices, cloud services, and applications regardless of their physical location. WAN connectivity is critical for IoT applications that require remote monitoring, asset tracking, and real-time data analytics. Cellular networks, in particular, are widely used for IoT connectivity due to their extensive coverage, reliability, and scalability. Overall, both local and wide area networking play important roles in the IoT ecosystem and enable a wide range of applications and services that leverage the power of connected devices and data. Few key differences between LAN and WAN are listed below: -LAN is a computer network established within a small geographic area, such as a house, office or buildings. WAN, on the other side, is a computer network that covers a broad geographical area. -LANs allow users to transfer the data faster, whereas WANs have a comparatively slower data transfer rate. -LAN has a higher speed, whereas WAN has a slower speed. -Designing, setup and maintenance in LANs are relatively easy while designing, setup, maintenance is difficult in WANs. -Fault tolerance is high in LANs, whereas WANs have less fault tolerance. Difference between LAN and WAN Business processes in IoT-Introduction A business process refers to a series of activities, often a collection of interrelated processes in a logical sequence, within an enterprise, leading to a specific result. There are several types of business processes such as management, operational, and supporting, all of which aim at achieving a specific mission objective. Managers and business analysis model an enterprise’s processes in an effort to depict the real way an enterprise operates and subsequently to improve efficiency and quality. Business processes in IoT Figure. The decreasing cost of information exchange between the real-world and enterprise systems with the advancement of M2M Business processes in IoT As depicted in Figure we have witnessed a paradigm change with the dramatic reduction of the data acquisition from the real world; this was attributed mostly to the automation offered by machines embedded in the real world. Initially all these interactions were human-based (e.g. via a keyboard) or human-assisted (e.g. via a barcode scanner); however, with the prevalence of RFID, WSNs, and advanced networked embedded devices, all information exchange between the real-world and enterprise systems can be done automatically without any human intervention and at blazing speeds. In the M2M era, connected devices can be clearly identified, and with the help of services, this integration leads to active participation of the devices to the business processes. Business processes in IoT This direct integration is changing the way business processes are modeled and executed today as new requirements come into play. M2M and IoT empower business processes to acquire very detailed data about the operations, and be informed about the conditions in the real world in a very timely manner. IoT integration with enterprise systems M2M communication and the vision of the IoT pose a new era where billions of devices will need to interact with each other and exchange information in order to fulfill their purpose. In Figure, cross-layer interaction and cooperation can be pursued: ❑at the M2M level, where the machines cooperate with each other (machine-focused interactions) ❑at the machine-to-business (M2B) layer, where machines cooperate also with network-based services, business systems (business service focus), and applications. IoT integration with enterprise systems IoT integration with enterprise systems Several devices in the lowest layer. These can communicate with each other over shortrange protocols (e.g. over ZigBee, Bluetooth), or even longer distances (e.g. over Wi-Fi, etc.). Some of them may host services (e.g. REST services), and even have dynamic discovery capabilities based on the communication protocol or other capabilities (e.g. WS-Eventing in DPWS). Some of them may be very resource constrained, which means that auxiliary gateways could provide additional support such as mediation of communication, protocol translation, etc. Distributed business processes in IoT In Figure, the integration of devices in business processes merely implies the acquisition of data from the device layer, its transportation to the backend systems, its assessment, and once a decision is made, potentially the control (management) of the device, which adjusts its behavior. In future, due to the large scale of IoT, as well as the huge data that it will generate, such approaches are not viable. Enterprise systems trying to process such a high rate of non- or minor-relevancy data will be overloaded. Distributed business processes in IoT Distributed business processes in IoT The first step is to minimize communication with enterprise systems to only what is relevant for business. With the increase in resources (e.g. computational capabilities) in the network, and especially on the devices themselves (more memory, multi-core CPUs, etc.), it makes sense not to host the intelligence and the computation required for it only on the enterprise side, but actually distribute it on the network, and even on the edge nodes (i.e. the devices themselves), as depicted on the right side of Figure. Everything as a service (XaaS) Everything-as-a-Service is a term for services and applications that users can access on the Internet upon request. The Everything-as-a-Service definition may seem unclear at first sight, but actually, it is not difficult to understand. It all started with the cloud computing terms: SaaS (Software-as-a-Service), PaaS (Platform-as-a- Service) and IaaS (Infrastructure-as-a-Service), meaning that ready-made software, a platform for its development, or a comprehensive computing infrastructure could be provided via networks. Gradually, other offerings appeared and now, the designation as-a-Service is associated with various digital components, e.g. data, security, communication, etc Anything-as-a-Service (another name for XaaS) is not confined to digital products. You can get practically everything, from food to medical consultations, without leaving your home or office, by utilizing certain online services. Hence the “Everything” is in the name. Everything as a service (XaaS) Figure. Conceptual Overview of Cloud Computing. Everything-as-a-Service Model Examples Now that we’ve covered the XaaS definition, it’s time to demonstrate some practical -XaaS cases (apart from SaaS, PaaS and IaaS) that are gaining popularity. Everything-as-a-Service Model Examples Hardware-as-a-Service (HaaS) Managed service providers (MSP) own some hardware and install it on customers’ sites on demand. Customers utilize the hardware in accordance with service level agreements. This pay-as-you-go model is similar to leasing and can be compared to IaaS when computing resources are located at MSP’s site and provided to users as virtual equivalents of physical hardware. The Haas model is especially cost-effective for small or mid-sized businesses Everything-as-a-Service Model Examples Communication-as-a-Service (CaaS) This model includes different communication solutions such as VoIP (voice over IP or Internet telephony), IM (instant messaging), video conference applications that are hosted in the vendor’s cloud. A company can selectively deploy communication apps that best suit their current needs for a certain period and pay for this usage period only. Such an approach is cost-effective and reduces expenses for short-time communication needs. Everything-as-a-Service Model Examples Desktop-as-a-Service (DaaS) Desktops are delivered as virtual services along with the apps needed for use. Thus, a client can work on a personal computer, using the computing capacities of third-party servers (which can be much more powerful than those of a PC). A DaaS provider is typically responsible for storing, securing and backing up user data, as well as delivering upgrades for all the supported desktop apps. Security-as-a-Service (SECaaS) This is the model of outsourced security management. A provider integrates their security services into your company’s infrastructure and, as a rule, delivers them over the Internet. Such services may include anti-virus software, encryption, authentication, intrusion detection solutions and more. Everything-as-a-Service Model Examples Healthcare-as-a-Service (HaaS) With electronic medical records (EMR) and hospital information systems (HIS), the healthcare industry is transforming into Healthcare-as-a-Service. Medical treatment is becoming more data-driven and patient-centric. Thanks to the IoT, wearables and other emerging technologies, the following services are available: -Online consultations with doctors -Health monitoring 24/7 -Medicine delivery at your doorstep -Lab samples collection even at home and delivery of results as soon as they are ready -Access to your medical records 24/7 HaaS creates opportunities for almost all categories of citizens to get qualified medical help Everything-as-a-Service Model Examples Transportation-as-a-Service (TaaS) Important trends of modern society are mobility and freedom of transportation at different distances. There are numerous apps popping up connected with transport, so a part of this industry is transforming into an - XaaS model. The most vivid examples are: Carsharing (you can rent a car at any place via a special app and drive anywhere you need, paying for the time you use a car, or for the distance you cover) Uber taxi services (you order a taxi via an app, which calculates the cost of the rout in advance). Uber is planning to test flying taxis and self-driving planes in the near future. TaaS model is not only convenient but also ecologically friendly. Benefits of XaaS: Scalability (outsourcing provides access to unlimited computing capacities, storage space, RAM, etc; a company can quickly and seamlessly scale its processes up and down depending on requirements and doesn’t have to worry about additional deployments or downtimes) Cost- and time-effectiveness (a company doesn’t purchase its personal equipment and doesn’t need to deploy it, saving much time and money; a pay-as-you-go model is also beneficial) Focus on core competencies (there’s no need to set up apps and programs or conduct training for employees; consequently, they can concentrate on their direct duties and achieve better performance) The high quality of services (since professionals support and maintain your infrastructure and systems, they provide the latest updates and all the emerging technologies, guaranteeing the quality of services) Better customer experience (the above-mentioned pros lead to customer satisfaction and increase customer loyalty) However, -XaaS services are not without flaws. The biggest drawbacks are mostly related to end users and concern the security of personal data and risks of massive data loss. Several essential characteristics of cloud computing have been defined by NIST (2011) as follows: On-Demand Self-Service. A consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed, or automatically, without requiring human interaction with each service provider. Broad Network Access. Capabilities are available over the network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g. mobile phones, tablets, laptops, and workstations). Resource Pooling. The provider’s computing resources are pooled to serve multiple consumers using a multi- tenant model, with different physical and virtual resources dynamically assigned and reassigned according to consumer demand. There is a sense of location independence in that the customer generally has no control or knowledge over the exact location of the provided resources, but may be able to specify location at a higher level of abstraction (e.g. country, state, or datacenter). Examples of resources include storage, processing, memory, and network bandwidth. Several essential characteristics of cloud computing have been defined by NIST (2011) as follows: Rapid Elasticity. Capabilities can be elastically provisioned and released, in some cases automatically, to scale rapidly outward and inward commensurate with demand. To the consumer, the capabilities available for provisioning often appear to be unlimited, and can be appropriated in any quantity at any time. Measured Service. Cloud systems automatically control and optimize resource use by leveraging a metering capability, at some level of abstraction, appropriate to the type of service (e.g. storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported, providing transparency for both the provider and consumer of the utilized service. Cloud computing comes in several different service models and deployment options for enterprises wishing to use it. The three main service models may be defined as (NIST 2011): Software as a Service (SaaS): Refers to software that is provided to consumers on demand, typically via a thin client. The end-users do not manage the cloud infrastructure in any way. This is handled by an Application Service Provider (ASP) or Independent Software Vendor (ISV). Examples include office and messaging software, email, or CRM tools housed in the cloud. The end-user has limited ability to change anything beyond user-specific application configuration settings. Platform as a Service (PaaS): Refers to cloud solutions that provide both a computing platform and a solution stack as a service via the Internet. The customers themselves develop the necessary software using tools provided by the provider, who also provides the networks, the storage, and the other distribution services required. Again, the provider manages the underlying cloud infrastructure, while the customer has control over the deployed applications and possible settings for the application-hosting environment (NIST 2011). Infrastructure as a Service (IaaS): In this model, the provider offers virtual machines and other resources such as hypervisors (e.g. Xen, KVM) to customers. Pools of hypervisors support the virtual machines and allow users to scale resource usage up and down in accordance with their computational requirements. Users install an OS image and application software on the cloud infrastructure. The provider manages the underlying cloud infrastructure, while the customer has control over OS, storage, deployed applications, and possibly some networking components. Deployment Models: Private Cloud. The cloud infrastructure is provisioned for exclusive use by a single organization comprising multiple consumers (e.g.business units). It may be owned, managed, and operated by the organization, a third party, or some combination of them, and it may exist on or off premises. Community Cloud. The cloud infrastructure is provisioned for exclusive use by a specific community of consumers from organizations that have shared concerns (e.g. mission, security requirements, policy, and compliance considerations). It may be owned, managed, and operated by one or more of the organizations in the community, a third party, or some combination of them, and it may exist on or off premises. Public Cloud. The cloud infrastructure is provisioned for open use by the general public. It may be owned, managed, and operated by a business, academic, or government organization, or some combination thereof. It exists on the premises of the cloud provider. Hybrid Cloud. The cloud infrastructure is a composition of two or more distinct cloud infrastructures (private, community, or public) that remain unique entities, but are bound together by standardized or proprietary technology that enables data and application portability (e.g. cloud bursting for load balancing between clouds).