CS计算机代考程序代写 scheme ER data mining database Chapter 3

Chapter 3
Enabling Technologies for the Internet of Things
In this chapter, we review the enabling technologies for the internet of things. In particular, recent advancements in hardware development, wireless technologies, data analytic, big data, and cloud computing are discussed. The main focus however is on recent advancements in wireless technologies for the Internet of Things. Other topics such as data analytic and energy will be discussed in later chapters.
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28CHAPTER3. ENABLINGTECHNOLOGIESFORTHEINTERNETOFTHINGS
3.1 Why Architecture?
Standards based approaches are required to enable the IoT industry. This video
u briefly explain why a standard architecture is required for IoT.
Several reference model and architectures have been proposed for IoT so far. In the following, we briefly explain the meaning of these terminologies in the context of IoT. A reference model is a model that describes the main
conceptual entities and how they are related to each other.
The reference architecture aims at describing the main functional compo-
nents of a system as well as how the system works, how the system is deployed, what information the system processes, etc.
An Architectural Reference Model (ARM) is useful as a tool that es- tablishes a common language across all the possible stakeholders of an M2M or IoT system. It can also serve as a starting point for creating concrete ar- chitectures of real systems when the relevant boundary conditions have been applied, for example, stakeholder requirements, design constraints, and design principles.
Several Reference Architectures and Models exist both for M2M and IoT systems:
• European Telecommunications Standards Institute (ETSI)
• International Telecommunication Union- Telecommunication sector view
(ITU-T)
• Internet Engineering Task Force architecture fragments (IETF)
• Open Geospatial Consortium architecture (OGC)
3.1.1 ETSI Architecture
The European Telecommunications Standards Institute (ETSI) in 2009 formed a Technical Committee on M2M topics aimed at producing a set of standards for communication among machines from an end-to-end viewpoint. The ETSI M2M specifications are based on specifications from ETSI as well as other stan- dardization bodies such as the IETF (Internet Engineering Task Force), 3GPP (3rd Generation Partnership Project), OMA (Open Mobile Alliance), and BBF (Broadband Forum). ETSI M2M produced the first release of the M2M stan- dards in early 2012. Fig. 3.1 shows the ESTI architecture for IoT. It mainly divide the whole systems into device and gateway domain and network domain.
3.1.2 ITU-T Reference Model
The Telecommunication sector of the International Telecommunication Union (ITU-T) has been active on IoT standardization since 2005 with the Joint Co- ordination Activity on Network Aspects of Identification Systems (JCA-NID), which was renamed to Joint Coordination Activity on IoT JCA-IoT) in 2011.

3.1. WHY ARCHITECTURE? 29
Figure 3.1: ETSI IoT Architecture.
During the same year apart from this coordination activity on IoT, ITU- T formed the specific IoT Global Standards Initiative (IoT-GSI) activity in order to address specific IoT-related issues. The latest ITU-T Recommendation, Y.2060 (ITU-T 2013) provides an overview of the IoT space with respect to ITU-T. This recommendation describes a high-level overview of the IoT domain model and the IoT functional model as a set of Service Capabilities similar to ETSI-M2M. Fig. ?? shows the proposed ITU-T reference model for IoT.
Figure 3.2: ITU-T Reference Model.

30CHAPTER3. ENABLINGTECHNOLOGIESFORTHEINTERNETOFTHINGS 3.1.3 Internet Engineering Task Force architecture frag-
ments (IETF)
IETF has defined three working groups for addressing M2M and IoT: • 6LoWPAN (IPv6 over Low-power WPAN),
• CoRE (Constrained RESTful Environments), and
• ROLL (Routing Over Low Power and Lossy networks)
The IoT architecture proposed by IETF (see Fig. 3.3) considers a layering structure similar to the OSI stacks with some modifications in some layers.
Figure 3.3: IETF Reference Model.
3.1.4 IoT World Forum Reference Model
This model is based on information flow, Policy and Control from top to bottom, Data exchange from both sides. Devices send and receive data interacting with the Network where the data is transmitted, normalized, and filtered using Edge Computing before landing in Data storage / Databases accessible by Applications which process it and provide it to people who will Act and Collaborate. Fig. 3.4 shows the reference model for IoT.
Figure 3.4: IoT World Forum Reference Model.

3.2. ADVANCEMENTS IN SENSOR AND MICROPROCESSOR DESIGN31 3.2 Advancements in Sensor and Microproces-
sor Design
As chip electronics continue to decline in size and cost and improve in per- formance, the economics of sensor-based applications improve. Analysts are forecasting the market for micro-electromechanical system (MEMS) chips will grow to over $22B by 2018. New sensors are so small, they can be worn or even ingested, and others are so rugged that they can monitor the performance of high-speed rotating machinery, such as jet engines and generator turbines.
Lower costs Economies of scale are enabling a rapid decline in price of all types of electronic components, reducing the cost to embed sensors & micropro- cessors into physical objects. In the last year, more than 80% price decline in MEMS sensors has been observed.
Chip manufacturers, such as Intel (which recently unveiled Xeon processors) are manufacturing up to 15 processor cores per chip. These types of multi- processor chips are giving us more compute power and enabling many more capabilities in smaller form factors. IBM is working on new technology called a SyNAPSE chip. At 5.4 billion transistors, this fully functional and production- scale chip is currently one of the largest CMOS chips ever built, yet, while running at biological real time, it consumes a minuscule 70 milliwatts orders of magnitude less power than a modern microprocessor.
This video u shows a new type of devices and microprocessors which are used to capture and replicate human motions.
3.3 Big Data
As more things (or smart objects) are connected to the IoT, more data is col- lected from them in order to perform analytics to determine trends and associa- tions that lead to insights. For example, an oil well equipped with 20-30 sensors can generate 500,000 data points every 15 seconds, a jetliner with 6,000 sensors generates 2.5 terabytes of data per day, and the more than 46 million smart util- ity meters installed in the U.S. generate more than 1 billion data points each day. Thus, the term “big data” refers to these large data sets that need to be collected, stored, queried, analyzed and generally managed in order to deliver on the promise of the IoT insight.
Further compounding the technical challenges of big data is the fact that IoT systems must deal with not only the data collected from smart objects, but also ancillary data that is needed to properly perform such analytics (e.g., public and private data sets related to weather, GIS, financial, seismic, map, GPS, crime, etc.). Thus, as more smart objects come online, at least three metrics (“the three V’s”) are typically used by IoT operators to describe the big data they handle: volume (i.e., the amount of data they collect from their IoT sensors measured in gigabytes, terabytes and petabytes); velocity (i.e., the speed at which data is collected from the sensors); and variety (i.e., the differing

32CHAPTER3. ENABLINGTECHNOLOGIESFORTHEINTERNETOFTHINGS types of structured and unstructured data collected, especially when compared
to video and picture files as is typical within the consumer Internet).
3.4 Cloud Computing
As the word “cloud” is often used as a metaphor for the Internet, “cloud com- puting” refers to being able to access computing resources via the Internet rather than traditional systems where computing hardware is physically located on the premises of the user and any software applications are installed on such local hardware. More formally, “cloud computing” is defined as:
“[A] model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.”
Cloud computing – and its three service models of Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) – are important to the IoT because it allows any user with a browser and an Internet connection to transform smart object data into actionable intelligence. That is, cloud computing provides “the virtual infrastructure for utility computing integrating applications, monitoring devices, storage devices, analytics tools, visualization platforms, and client delivery [to] enable businesses and users to access [IoT-enabled] applications on demand anytime, anyplace and anywhere.”
3.5 Analytic Software
Within the IoT ecosystem, Application Service Providers (ASPs) – which may or may not di er from the companies who sell and service the smart objects – provide software to companies that can transform “raw” machine (big) data collected from smart objects into actionable intelligence (or insight). Generally speaking, such software performs data mining and employs mathematical models and statistical techniques to provide insight to users. That is, events, trends and patterns are extracted from big data sets in order to present the softwares end- users with insight in the form of portfolio analysis, predictions, risk analysis, automation and corrective, maintenance and optimization recommendations. In many cases, the ASPs may provide general analytical software or software targeting specific industries or types of smart objects.
3.6 Digital Twin
Another consequence of the growing and evolving IoT is the concept of a “digital twin,” introduced in 2003 by John Vickers, manager of NASA’s National Center for Advanced Manufacturing. The concept refers to a digital copy of a physical asset (i.e., a smart object within the IoT), that lives and evolves in a virtual environment over the physical asset’s lifetime. That is, as the sensors within the

3.7. ADVANCES IN CONNECTIVITY AND NETWORKS 33
object collect real-time data, a set of models forming the digital twin is updated with all of the same information. Thus, an inspection of the digital twin would reveal the same information as a physical inspection of the smart object itself – albeit remotely. The digital twin of the smart object can then be studied to not only optimize operations of the smart object through reduced maintenance costs and downtime, but to improve the next generation of its design.
3.7 Advances in Connectivity and Networks
With respect to sending and receiving data, wired and wireless communication technologies have also improved such that nearly every type of electronic equip- ment can provide data connectivity. This has allowed the ever-shrinking sensors embedded in smart objects to send and receive data over the cloud for collection, storage and eventual analysis.
The protocols for allowing IoT sensors to relay data include wireless tech- nologies such as RFID, NFC, Wi-Fi, Bluetooth, Bluetooth Low Energy (BLE), XBee, ZigBee, Z-Wave, Wireless M-Bus, SIGFOX and NuelNET, as well as satellite connections and mobile networks using GSM, GPRS, 3G, LTE, or WiMAX. Wired protocols, useable by stationary smart objects, include Eth- ernet, HomePlug, HomePNA, HomeGrid/G.hn and LonWorks, as well as con- ventional telephone lines.
3.7.1 Wireless Technologies for IoT
The main target for conventional H2H communications is increasing the through- put for only limited applications and services including, data, voice, and mul- timedia. The user terminals in H2H usually have advanced processing and storage capabilities and energy efficiency is not of much concern and regular battery recharging once or twice a day is feasible.
On the other hand, IoT services and applications have diverse requirements and usually a large number of terminals want to communicate with each other or the data transport infrastructure. The terminals in the context of massive IoT are usually of low cost and have limited processing and storage capabilities. The traffic in many IoT applications is completely different than conventional H2H communications, that is IoT terminals usually upload data in either regular or intermittent manner, whilst in H2H communications the user terminals usually download data from the server. Energy efficiency is of utmost importance for IoT application and services as most terminals are battery operated and regular battery replacement and maintenance is not feasible.
Wireless technologies can be mainly categorized into two categories. The first category is capillary wireless technologies which is also referred to short- range (local) wireless technologies. They are suitable for indoor and local IoT applications, where devices or terminals are located within a close distance to each other. Capillary networks are also suitable for power sensitive applications,

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where power efficiency is of concern. Examples of capillary wireless technologies are WiFi, Bluetooth and Zigbee.
The second category, is cellular and wide area wireless technologies for IoT. These technologies provide wireless connectivity over the globe, that is a base station or satellite can service terminal located in distances of over few kilometers. Examples of these technologies are mobile cellular systems, SigFox, and LoRa. Mobile cellular standards, such as 3G, 4G and the recent standards for IoT applications, such as EC-GSM and NB-IoT, have the advantage of global reach and the fact that the infrastructure is already available everywhere, makes it the most suitable candidate for many IoT applications and services.
Wireless networks usually work in two different mode. In the infrastructure- based network the access point or base station coordinate the communications. In the adhoc networks, there is no base station and nodes can only transmit to other nodes within link coverage. The nodes self-organize and route among themselves. Table 3.1 shows different categories of wireless technologies.
Table 3.1: Different modes of communications
Mode
Infrastructure-based
Adhoc
Single Hop
Base station connected to larger wired network (e.g., WiFi wireless LAN, and cellular telephony networks)
No wired network; one node coordinates the transmissions of the oth- ers (e.g., Bluetooth, and ad hoc 802.11)
Multi- hop
Base station exists, but some nodes must relay through other nodes (e.g., wireless sensor networks, and wireless mesh net- works
No base station exists, and some nodes must re- lay through others (e.g., mobile ad hoc networks, like vehicular ad hoc net- works)
RFID
To Enhance the concept of bar-codes for identification of assets (goods, people, animals). RFID tags have been widely used in logistics, asset tracking, and shopping.
A RFID system is made up of two parts: a tag or label and a reader. RFID tags or labels are embedded with a transmitter and a receiver. The RFID component on the tags have two parts: a microchip that stores and processes information, and an antenna to receive and transmit a signal. The tag contains the specific serial number for one specific object. To read the information encoded on a tag, a two-way radio transmitter-receiver called an interrogator or reader emits a signal to the tag using an antenna. The tag responds with the information written in its memory bank. The interrogator will then transmit the read results to an RFID computer program.

3.7. ADVANCES IN CONNECTIVITY AND NETWORKS 35
There are three types of tags, 1) Passive: Operational Power scavenged from reader radiated power, 2) Semi-passive:Operational power provided by battery, and 3) Active: Operational power provided by battery-transmitter built into
tag. This video u gives more detailed explanation for RFID.
Backscatter communications is an extension of this type of communications
for IoT devices.
Zigbee
Zigbee is an IEEE 802.15.4-based specification for a suite of high-level commu- nication protocols used to create personal area networks with small, low-power digital radios.
ZigBee PRO and ZigBee Remote Control (RF4CE), among other available ZigBee profiles, are based on the IEEE802.15.4 protocol, which is an industry- standard wireless networking technology operating at 2.4GHz targeting appli- cations that require relatively infrequent data exchanges at low data-rates over a restricted area and within a 100m range such as in a home or building.
ZigBee/RF4CE has some significant advantages in complex systems offering low-power operation, high security, robustness and high scalability with high node counts and is well positioned to take advantage of wireless control and sensor networks in M2M and IoT applications.
There are three types of node in Zigbee: 1) Full Function Device (FFD) that can send beacons, communicate with other FFDs, route frames, act as PAN co- ordinator, and typically features power supply, 2) Reduced Function Device (RFD) which cannot route frames, cannot communicate with other RFDs, but can communicate with FFD and runs typically on batteries, 3) PAN Coordi- nator which is responsible of a Personal Area Network (PAN) and manages PAN association/de-association. Zigbee supports star, mesh, and cluster tree networking which are suitable options for many IoT applications.
WiFi
WiFi connectivity is often an obvious choice for many developers, especially given the pervasiveness of WiFi within the home environment within LANs. It requires little further explanation except to state the obvious that clearly there is a wide existing infrastructure as well as offering fast data transfer and the ability to handle high quantities of data.
Currently, the most common WiFi standard used in homes and many busi- nesses is 802.11n, which offers serious throughput in the range of hundreds of megabit per second, which is fine for file transfers, but may be too power- consuming for many IoT applications. WiFi currently work in two frequency bands 2.4GHz and 5GHz bands and cover approximately 50m and can support data rates of up to 600 Mbps, with typical data rate of 150-200Mbps. Depend- ing on channel frequency and the number of antennas, latest 802.11-ac standard can offer 500Mbps to 1Gbps.

36CHAPTER3. ENABLINGTECHNOLOGIESFORTHEINTERNETOFTHINGS
A new IoT-friendly version of Wi-Fi called HaLow is coming soon. Des- ignated 802.11ah, it uses the 902-928-MHz license-free band in the U.S. and similar bands just below 1 GHz in other countries. This is good news, as low power can be used over these lower frequencies, thus enabling battery-operated equipment. While most Wi-Fi gear has a maximum range of 100 meters under ideal conditions, HaLow can reach up to a kilometer with the right antenna.
Another new Wi-Fi standard targeting IoT applications is 802.11af. Its de- signed to use TV white spaces or unused TV channels from 54 to 698 MHz. These channels are ideal to support long-range and non-line-of-sight transmis- sion. Data rate per 6-MHz channel maxes out at about 24 Mb/s, though even longer ranges are expected at the lower VHF TV frequencies.
NFC
NFC (Near Field Communication) is a technology that enables simple and safe two-way interactions between electronic devices, and especially applicable for smart phones, allowing consumers to perform contactless payment transactions, access digital content and connect electronic devices. Essentially it extends the capability of contactless card technology and enables devices to share informa- tion at a distance that is less than 10cm. The NFC standars is referred to ISO/IEC 18000-3, the frequency band is 13.56MHz (ISM) and it can support
data rates of 100420kbps within less than 10cm. This video u provides a simple explanation of the NFC concept.
Bluetooth
Bluetooth is an important short-range communications technology that has be- come very important in computing and many consumer product markets. It is expected to be key for wearable products in particular, again connecting to the IoT albeit probably via a smartphone in many cases. The new Bluetooth Low- Energy (BLE) or Bluetooth Smart, as it is now branded- is a significant protocol for IoT applications. Importantly, while it offers similar range to Bluetooth it has been designed to offer significantly reduced power consumption.The version 4.2 via its Internet Protocol Support Profile will allow Bluetooth Smart sensors to access the Internet directly via 6LoWPAN connectivity. This IP connectivity makes it possible to use existing IP infrastructure to manage Bluetooth Smart edge devices. It works in frequency band 2.4GHz (ISM), and support data rates of up to 1Mbps for distances between 50m to 150m.
WirelessHART
This wireless version of the widely used Highway Addressable Remote Trans- ducer (HART) industrial networking technology is used in process monitoring and control, sensor networks, building automation, and transportation. Wire- lessHART is the property of the FieldComm Group. Linear Technology is the

3.7. ADVANCES IN CONNECTIVITY AND NETWORKS 37
leading producer of WirelessHART radios and managers. It has the designa- tion of 802.15.4e. Both 802.15.4e and WirelessHART are based on the time- synchronized channel-hopping MAC developed by Linear Technology’s Dust
Networks. This video u provides and overview of WirelessHART standard. Weightless
The name Weightless was chosen to reflect the light-weight nature of the pro- tocols used within the standard. The data overhead per transmission has been minimised for devices that want to communicate just a few bytes of data. Weightless is an open wireless standard that provides the ability for exchanging data between a base station and machines using radio transmissions in unoccu- pied TV transmission channels – white space.
In terms of the radio interface, the Weightless standard uses either phase shift keying or quadrature amplitude modulation together with a scheme of ’Whitening’ to make the spread the signal and make it look more like white noise to reduce any levels of interference that may be caused. In addition to this this the system uses time division duplex, TDD to enable both uplink and downlink transmissions to use the same channel. Three different versions address different segments of the LPWAN marketplace. The simplest version is Weightless-N for low-cost applications. This version targets simplex or one- way uses such as sensor monitoring. It operates in the sub-1-gigabit license-free ISM. Modulation is differential BPSK using a frequency-hopping technique to minimize interference. A key feature is its 128-bit AES encryption with full authentication. With low data rates and narrow channels, a range up to 5 km is possible. Up to 10 years of battery life is possible thanks to the standards low power consumption.
Z-Wave
Z-Wave is a low-power RF communications technology that is primarily designed for home automation for products such as lamp controllers and sensors among many others. Optimized for reliable and low-latency communication of small data packets with data rates up to 100kbit/s, it operates in the sub-1GHz band and is impervious to interference from WiFi and other wireless technologies in the 2.4-GHz range such as Bluetooth or ZigBee.
It supports full mesh networks without the need for a coordinator node and is very scalable, enabling control of up to 232 devices. Z-Wave uses a simpler protocol than some others, which can enable faster and simpler development, but the only maker of chips is Sigma Designs compared to multiple sources for other wireless technologies such as ZigBee and others.
Z-Wave standard, referred to as Z-Wave Alliance ZAD12837 / ITU-T G.9959 works over the frequency band 900MHz (ISM) and can support data rates
9.6/40/100kbit/s for up to 30m. This video u gives some further details of Z-Wave standard.

38CHAPTER3. ENABLINGTECHNOLOGIESFORTHEINTERNETOFTHINGS Thread
A very new IP-based IPv6 networking protocol aimed at the home automation environment is Thread. Based on 6LowPAN, and also like it, it is not an IoT applications protocol like Bluetooth or ZigBee. However, from an application point of view, it is primarily designed as a complement to WiFi as it recognises that while WiFi is good for many consumer devices that it has limitations for use in a home automation setup.
Launched in mid-2014 by the Thread Group, the royalty-free protocol is based on various standards including IEEE802.15.4 (as the wireless air-interface protocol), IPv6 and 6LoWPAN, and offers a resilient IP-based solution for the IoT. Designed to work on existing IEEE802.15.4 wireless silicon from chip ven- dors such as Freescale and Silicon Labs, Thread supports a mesh network using IEEE802.15.4 radio transceivers and is capable of handling up to 250 nodes with high levels of authentication and encryption. A relatively simple software upgrade should allow users to run thread on existing IEEE802.15.4-enabled de-
vices. This video u gives some useful information about Thread. SigFix
SigFox is a wide-range technology, which in terms of range comes between WiFi and cellular. It uses the ISM bands, which are free to use without the need to acquire licenses, to transmit data over a very narrow spectrum to and from connected objects.
The idea for Sigfox is that for many M2M applications that run on a small battery and only require low levels of data transfer, then WiFi’s range is too short while cellular is too expensive and also consumes too much power. Sigfox uses a technology called Ultra Narrow Band (UNB) and is only designed to handle low data-transfer speeds of 10 to 1,000 bits per second. It consumes only 50μW compared to 5000μW for cellular communication, or can deliver a typical stand-by time 20 years with a 2.5Ah battery while it is only 0.2 years for cellular.
The network offers a robust, power-efficient and scalable network that can communicate with millions of battery-operated devices across areas of several square kilometres, making it suitable for various M2M applications that are expected to include smart meters, patient monitors, security devices, street
lighting and environmental sensors. This video u gives some examples of IoT application using SigFox technology.
LoRa
Similar in some respects to Sigfox, LoRaWAN targets wide-area network (WAN) applications and is designed to provide low-power WANs with features specifi- cally needed to support low-cost mobile secure bi-directional communication in IoT, M2M and smart city and industrial applications. it has been optimized for

3.7. ADVANCES IN CONNECTIVITY AND NETWORKS 39
low-power consumption and supporting large networks with millions and mil- lions of devices, data rates range from 0.3 kbps to 50 kbps for coverages between 2km to 5km and 15 km in suburban environments. A brief explanation of LoRa
technology can be found in this video u.
3.7.2 How to choose the suitable wireless technology?
A number of design factors must be scrutinized when selecting a wireless tech- nology:
1. Data rate of the device: Streaming video, measuring temperature every minute, or something in between.
2. Range or distance to the gateway: A few feet within a room or over a mile in a rural area.
3. The environment: Hazardous surroundings in a factory, outdoors in the weather, noise from electrical equipment or EMI, etc.
4. Need for encryption or authentication: What is the demand for data se- curity?
5. Power consumption: Battery life; energy efficiency; possible need for an AC mains connection.
6. Capacity: Number of connected devices.
7. Quality of service and reliability.
8. Network topology: Star, mesh, or other.
9. Simplex or duplex: One-way vs. two-way communications.
10. Suitable and available spectrum: Licensed or unlicensed.
11. Available ICs, modules, and equipment.
12. Cost: Design, manufacturing, or Internet access service expense.
13. Development platform: Is an OS needed? What other software is required?
14. Internet access: Cellular, DSL, cable, satellite.
15. Licensing conditions of standards available.
3.7.3 A brief comparison between wireless technologies
Fig. 3.5 shows the power requirement and coverage of different wireless tech- nologies which might be suitable for IoT application and services. Table 3.2 provides the main characteristics of some capillary wireless technologies suit- able for many IoT applications.
Table 3.3 shows the main characteristics of wide area wireless technologies for IoT application and services.

40CHAPTER3. ENABLINGTECHNOLOGIESFORTHEINTERNETOFTHINGS Power
Battery is required EH to increase life-time and battery recharge
WiFi Buetooth
EnOce
an Alliance
Wireless HART
LPWAN LoRa SIGFOX NB-IoT LTE-M EC-GSM
Weightless
Battery-less is possible
Zigbee NFC RFID Z-Wave
Is battery-less long-range possible?
THREAD
ANT+
1W
Medium Power
100mW
Low Power
10mW
Very Low Power
1mW
0.1m
Very Short range
1m 10m
Short Range
100m 1km
Medium Range
10km
100km
Coverage
Figure 3.5: Coverage and power requirements of different wireless technologies for IoT applications.
3.8 Further Reading
The following list provide some references for further reading on the topics provided in this chapter.
1. Chapter 5.2 of Computer Networks by Tanenbaum
2. Chapters 1.3 and 3.3 of Computer Networks: A System Approach by Peterson
3. A. Al-Fuqaha, M. Guizani, M. Mohammadi, M. Aledhari and M. Ayyash, ”Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications,” in IEEE Communications Surveys & Tutorials, vol. 17, no. 4, pp. 2347-2376, Fourth quarter 2015.
4. F. K. Shaikh, S. Zeadally and E. Exposito, ”Enabling Technologies for Green Internet of Things,” in IEEE Systems Journal, vol. 11, no. 2, pp. 983-994, June 2017.
5. O. Novo, N. Beijar, M. Ocak, J. Kjllman, M. Komu and T. Kauppinen, ”Capillary networks – bridging the cellular and IoT worlds,” 2015 IEEE 2nd World Forum on Internet of Things (WF-IoT), Milan, 2015, pp. 571- 578.
Long Range
Blootooth LE

3.8. FURTHER READING 41
Table 3.2: Characteristics of different capillary wireless technologies for IoT application and services.
Standard
Frequency band
Max data rate
max range
TX power
Applications
Zigbee (802.15.4)
868/915/2450 MHz
250kbps 100m
1-100mW
Home automation, backhaul for WSN
ULP (802.15.4q)
868/915/2450 MHz
100kbps 100m
5-15mW
Ultra low power ap- plications
Wireless M-Bus
169/433/868 MHz
100kbps 300m
1-100mW
Metering
Z-Wave
908 MHz
100kbps 100m
1-100mW
Home automation
Bluetooth Low En- ergy (BLE)
2450 MHz
1Mbps
30m
1-100mW
eHealth, Sport, Multimedia
WiFi Low Power (802.11.ah)
Sub-1 GHz
7.8Mbps 1000m
10mW-1W
Long range low power applications
Table 3.3: Characteristics of different wide area wireless technologies for IoT application and services.
Technology
Frequency band
Upload rate
Download rate
Packet size
Max range
TX power
SigFix
868-902MHz
≤100b/s
256b/d
≤12B
10-50km
10μW- 100mW
LoRa (EU)
863- 870MHz, 433MHz
250b/s- 50kb/s
250b/s- 50kb/s
≤222B
2-15km
14dBm
LoRa (US)
902-928MHz
9800b/s- 1kb/s
9800b/s- 22kb/s
≤222B
2-15km
20dBm
Weightless (W)
470-790MHz
250b/s- 50kb/s
2.5kb/s- 16Mb/s
≥10B
5km
17dBm
Weightless (N)
sub GHz
250b/s
none
≤20B
3km
17dBm
Weightless (P)
sub GHz
200b/s- 100kb/s
200b/s- 100kb/s
≥10B
2km
17dBm
Ingenu
2450MHz
624kb/s
156kb/s
6B- 10kb
100km
20dBm

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