Standardization in the Wireless World

The advent of next-generation mobile computing calls for open standards and platforms to enable interoperability. As has been discussed in this chapter, a full spectrum of wireless technologies is set to be integrated to allow roaming in on unprecedented levels. Proprietary technologies do not fit into this new era of convergence, as it would be difficult for them to gain ground to a great extent due to the limited number of vendors and compatible products. On the contrary, open, well-crafted standards for the technology will enable and encourage any interested business parties to engage in developing and manufacturing products or offering services that are guaranteed to be interchangeable or compatible. Open standards essentially provide a solid foundation of framework of a technology as well as design constraints, thereby boosting the spread and acceptance of the technology.

A standard is a specification or definition that has been approved by a recognized standards organization such as ITU, IEEE, and ETSI, or is generally accepted as a de facto model by the industry. In the context of computing, standards exist for computer hardware, communication protocols, programming languages, operating systems, and some applications. Network communications have a wide range of standards, such as IEEE 802.3 Ethernet standard for LANs, IEEE 802.11 and ETSI HIPERLAN for wireless LANs, GSM, and IS-95 and IS136.

In addition to communication standard bodies such as ITU, IEEE, and ETSI, some other standard bodies have been founded for specialized technological fields. The American
National Standards Institute (ANSI) is primarily responsible for software and programming language standardization; it has created ANSI C and C _ _ . HTML and XML have been adopted by the International Organization for Standardization (ISO) and the World Wide Web Consortium (W3C). The Internet Engineering Task Force (IETF) has released a number of requests for comments (RFCs) that serve as the basis of many network protocols. Many computer peripheral standards such as the PCMCIA, Universal Serial Bus (USB), and compact flash have been created by industrial forums or associations.

Cellular Standard Groups
The two standard bodies behind competing cellular technologies are the Third Generation
Partnership Project (3GPP) and Third Generation Partnership Project 2 (3GPP2). 3GPP is an international organization supporting the development of UMTS/WCDMA systems.
3GPP partners include ETSI of Europe, ATIS of the United States, ARIB and TTC of Japan, TTA of Korea, and CCSA of China. 3GPP has released two versions of UMTS standards, namely Release 99 and Release 2000. 3GPP2 is the parallel partnership project for cdma2000 technology. It consists of TIA of the United States, ARIB and TTC of Japan, TTA of Korea, and CCSA of China. ITU is a United Nations organization responsible for maintaining and extending worldwide coordination of different governments and private sectors and managing the radio-frequency spectrum. 3GPP and 3GPP2 are formed under ITU.

IEEE Standards
The Institute of Electrical and Electronic Engineers (IEEE) has been the key standards organization in promoting networking technologies for many years. For wireless technologies, IEEE has established several working groups, mainly under the 802 standard committee.

» IEEE 802.1: LAN/MAN architecture with emphasis on internet working and link security (inactive).
» IEEE 802.2: Logical link control, part of the data-link layer protocol of a LAN.
» IEEE 802.3: Ethernet, the dominating LAN technology.
» IEEE 802.4: Token bus, a LAN technology utilizing token rings over coaxial cables.
» IEEE 802.5: Token ring, another token ring LAN technology (inactive).
» IEEE 802.6: Metropolitan area networks, a specification of MANs using Distributed Queue Dual Bus (DQDB) (inactive).
» IEEE 802.7: Broadband TAG (Technical Advisory Group), a broadband LAN.
» IEEE 802.8: Fiberoptic TAG, a fiber-optic LAN standard (inactive).
» IEEE 802.9: Isochronous LAN, an Isochronous Ethernet (IsoEnet) (inactive).
» IEEE 802.10: Security, specifying key management, access control, and data integrity for LANs and WANs (inactive).
» IEEE 802.11: Wireless LAN, a set of protocols for wireless LANs operating on unlicensed 2.4-GHz and 5-GHz bands.
» IEEE 802.12: Demand priority, 100BaseVG-AnyLAN (inactive).
» IEEE 802.13: Not used (for some reason).
» IEEE 802.14: Cable data, a MAC layer specification for multimedia traffic over hybrid fiber and coaxial networks.
» IEEE 802.15: Wireless PAN, a set of protocols for short-range wireless networks, including Bluetooth (802.15.1).
» IEEE 802.16: Broadband wireless access, PHY and MAC layer protocols for PTM broadband wireless access; WiMax is based on 802.16.
» IEEE 802.17: Resilient packet ring (RPR), a protocol to improve resilience for packet data traffic over fiber rings.
» IEEE 802.20: Mobile Broadband Wireless Access, PHY and MAC layer protocols for mobile data access.

Standards War
Emerging innovational technologies usually imply huge business opportunities. Different groups of industry alliances always attempt to influence the standardization of these technologies in favor of their own business interests. This sometimes leads to serious conflicts within a standardization body which inevitably puts the technology in stalemate and affects the promotion of the underlying technology with respect to providing a unified, interoperable solution framework for interested parties. For instance, the IEEE standardization of UWB (802.15.3) has been deadlocked due to proposals from two rivalry groups: the MBOA Alliance (Intel and TI lead) and UWB Forum (Motorola leads). Each side claims its proposal is superior to the other. Seeing no immediate ratification of a standard, both groups are moving forward to advance their approaches in commercial developments, effectively creating a segmented UWB market. The evolution of cellular networks is another example of a standards war. The lack of a global standard of cellular networks has resulted in two dominating 2G GSM and CDMA systems and two ongoing 3G deployments: UMTS/WCDMA and cdma2000, backed up by two organizations, 3GPP and 3GPP2, respectively. If a united standard agreement cannot be reached by the different groups, it is very likely the market will make the final decision. The standards body will supposedly pick the approach that is the most popular in the marketplace. Interestingly and understandably, it is not always the technically superior approach or system that eventually wins the majority of the market. We have seen this happen with Betamax versus VHS, two competing videotape standards back in the 1990s. It would be interesting to see what will happen to those emerging wireless technology standards.

Source of Information : Elsevier Wireless Networking Complete 2010


One of the emerging applications of WSN is wireless monitoring and control. ZigBee is such an application that uses low-power and low-data-rate networked sensors. It was developed by the ZigBee Alliance, an industry association of semiconductor companies and network equipment companies such as Ember, Honeywell, Mitsubishi Electric, Motorola, Samsung, and Philips. It has to be noted that the term ZigBee refers to the silent communication between honeybees where the bee dances in a zig-zag pattern to tell others the location, distance, and direction of some newly found food. WSN communication somewhat resembles the ZigBee principle in that they must be simple and effective.

The idea is to take advantage of wireless sensors to monitor environments, objects, and human beings and control devices, appliances, and facilities. Wireless sensors make it possible to remotely and conveniently monitor or be notified of operational states or crucial state change of an object, such as a dying battery in a smoke detector and rapidly increasing temperature in a truck carrying frozen goods. WSNs in ZigBee are not designed to carry large data transfer due to the limited capability of wireless communication; however, these sensors are able to form a fully functional network, self-organize for efficient data routing and in-network processing, and self-heal in the case of node failure. The initial target markets of ZigBee products are home control, building control, industrial automation, personal healthcare, consumer electronics, PC and peripherals control, etc. Key specs of ZigBee include the following:

» Frequency bands: 868 MHz, 915 MHz, and 2.4 GHz;
» Data transfer rate up to 250 Kbps;
» Signal transmission range of 10 to 100 m, depending on the sensors being used;
» AES encryption of data;
» Various ZigBee applications can work with each other;
» Low power usage.

Unlike UWB or Bluetooth, ZigBee specifications do not define radio interface and data-link layer protocols; ZigBee simply uses the IEEE 802.15.4 physical radio standard. The ZigBee network application support layer and application profile are the major components that make up the ZigBee specification. Because ZigBee is a proprietary protocol rather than an open standard like those ratified by IEEE, its fate hinges on how it refines itself to become the de facto industry standard. To this end, standardization battles seem inevitable.

Source of Information : Elsevier Wireless Networking Complete 2010

Self-Organized Networks

The physical layer of a WSN is nothing new: radio-frequency transmission at unlicensed bands. LOS is not required. The data-link layer monitors the channels and transmits frames only when the channel is idle. The network layer and transport layer require more discussion. Like ad hoc networks, the routing paths between each two nodes cannot be determined and configured prior to deployment because there is no predefined fixed infrastructure in WSNs. Sensor nodes have to discover multihop routes to relevant nodes themselves. This is often done via routing data dissemination, in which packets that contain the transmitter and the distance to the root are flooded in the network. A sensor node, upon receiving such packets, will be able to find a “ parent ” who is closer to the root; hence, a distribution tree can be generated. Data collection from sensor nodes can be routed back to the root following the distribution tree.

Task or query dissemination throughout a sensor network is data-centric in association with data aggregation, a routing scheme known as directed diffusion. Sensor nodes are not addressed uniformly using numeric identifications; instead, the addressing and naming schemes are correlated with the application. They are identified by “ attribute – value ” pairs in their data. A task in the form of some attribute inquiry is sent out from some nodes in the hope of obtaining relevant data from other nodes, and then all participating nodes form a routing gradient toward the originators. In the case where a WSN is used as a platform of the sensory database, the applications and underlying routing schemes must support declarative queries, thereby making the detail of in-network query processing and optimization transparent to the user. Power consumption is another crucial factor when it comes to in-network aggregation support of query processing. Sophisticated power-aware query processing and packet routing schemes have been devised to reduce the overall power consumption of a WSN.

Sensory data delivery can be performed in several ways. Sensor node can actively report readings periodically to its parent or only report when an event occurs. The delivery procedure can also be initiated by a user issuing a command that is diffused across the network. Depending on the design objectives, a WSN may apply different data delivery models to different sensor nodes. For example, some high-level roots in the distribution tree may employ a request-and-response mechanism for queries, whereas some low-level sensor nodes may simply report data continuously.

Compared with mobile ad hoc network, network communication over WSNs imposes additional constraints other than node mobility and power consumption. Sensors node are more prone to failure, and their computational capability and memory capacity are greatly limited. When designing a protocol stack of a WSN, these constraints have to be taken into account. Specifically, because complete raw data forwarding is not necessary in many circumstances, data aggregation may be conducted at various levels of the distribution tree to reduce the amount of data being transferred upward to the gateway while still providing sufficient information to other nodes. Furthermore, data aggregation can be combined with applications of the WSN to further improve the efficiency of data collection and dissemination schemes. This reflects one of the most important characteristics of WSNs: cross-layer design. The well-known sensor operating system is TinyOS, which is an open-source, event-based embedded operating system developed at the University of California, Berkeley. TinyOS provides a set of components for networking, memory management, and power management, as well as data acquisition and query processing tools. The programming language supported by TinyOS is nesC, a C-like language for embedded network system development.

Source of Information : Elsevier Wireless Networking Complete 2010

Wireless Sensor Node

A sensor node is made up of four basic components: sensing unit, processing unit, transceiver unit, and power unit. The sensing unit usually consists of two components: a sensor and an analog-to-digital converter (ADC). The processing unit acts as a tiny computer: a microprocessor and some RAM. The processing unit runs an embedded operating system and executes WSN applications that control the operations of the sensor and communication between sensor nodes. The transceiver unit is a low-power radio operating on an unlicensed frequency band. The power unit is a battery for regular sensor nodes. Note that in most cases a WSN will have a special sensor node that acts as the gateway for other sensor nodes with respect to ultimate data delivery. The gateway node interfaces to computers via RS232 or Ethernet links. As a result, the gateway node is different from other regular nodes, in both size and processing functionality, thus requiring more power supply.

Following is a list of sensor node characteristics that affect the design of WSN system architectures and applications:

» Size: Sensor nodes are very small, due to advancements in semiconductor technologies.

» Low power: Sensor nodes are expected to operate for a long time before the battery drains out. In many cases, it is prohibitive to replace batteries.

» Autonomous, unattended operations: Once deployed, sensor nodes should selforganize to work as programmed. Remote reprogramming is sometimes possible.

» Inexpensive: Their low cost makes it possible to deploy a large number of sensor notes at a moderate cost.

» Adaptive to environments and themselves: Sensor nodes are able to adapt to environmental and status changes.

Source of Information : Elsevier Wireless Networking Complete 2010

WSN Applications

The wide range of sensors and collective instrumental functionality of WSNs, coupled with the underlying wireless networks, make it possible to provide unprecedented levels of data access and associated intelligence, bringing about a new dimension of application for different industry sectors. WSN applications can be divided into three categories: monitoring space, including objects as part of the space; monitoring operation states of objects; and monitoring interactions between objects and space. The first category represents the most common and basic use of WSNs (dealing with physical environments), whereas the second is mainly concerned with a specific entity rather than its surroundings. The third category encompasses more sophisticated monitoring and control over communications and interactions between objects and between an object and its surroundings. Some pilot projects have explored WSNs for a number of different application scenarios. Many potential applications are being developed to leverage WSNs. Some examples are introduced as follows.

Environmental Sensing
Using a large number of sensor nodes deployed in a target geographic location, it is possible to derive useful patterns and trends based on datasets collected over time. Examples of environmental sensing are light sensing, microclimate monitoring, traffic monitoring, pollution level monitoring, indoor climate control, and habitat monitoring. Very often users are only concerned with independent characteristics of an entity, such as the number of vehicles passing by during a time period or the propagation speed of some contaminant in a river.

Object Sensing
Aside from environmental sensing, sensors can be attached to objects and collect data regarding motion, pressure, or any mechanical, electronic, or biological characteristics of the host. Object sensing is predominantly used in industrial control and maintenance. Examples include structural monitoring of buildings, bridges, vehicles, and airplanes; sensing machinery wear in a factory; industrial asset tracking in warehouses and stores; surveillance in parking lot and streets; crop monitoring; and military-related object sensing in battlefields. In particular, RFID, a scaled-down wireless sensing technology, utilizes small tags of very limited local computing power and storage to identify and inventory objects. Section 13 has presented a detailed introduction to RFID.

Sensing with Intelligence
More challenging application scenarios require embedded intelligence that goes beyond raw data sensing, thus requiring the simultaneous sensing of multiple related quantities and in-network processing so as to detect internal interactions between objects. Examples of this category are monitoring wildlife habitats, telemedicine sensing, context-aware pervasive computing using sensors, and disaster management. For instance, researchers at the University of California, Berkeley, and Intel have developed a successful experimental WSN to monitor petrels on an uninhabited island off the coast of Maine. The birds being observed are Leach’s store petrels, a type of tiny reclusive seabird that burrows in sandy soil and emerges only at night. To ornithologists, monitoring and understanding the comings and goings of these birds in a wild area are not simple tasks, as they would have to dig into the birds ’ burrows for more information. The WSN deployed on the island consists of 190 wireless sensor nodes called motes , some of which are located in burrows and others on the ground, and a solar-powered central computer station that collects sensory data from a gateway mote and reports back to a remote site in real-time via satellite links. Sensors on the motes monitor temperature, humidity, barometric pressure, and ambient light. The temperature reading within a burrow can be used to infer if a petrel is present or not. Other data also contribute to our understanding of the behavior of these petrels and their responses to changes in their surroundings.

Source of Information : Elsevier Wireless Networking Complete 2010

Wireless Sensor Networks

Data communication continues to expand in both scope and complexity, from internal communication among the hardware components of an individual computer to intercomputer network communication via wired or wireless BANs, PANs, LANs, MANs, and WANs. At the same time, computers are becoming more closely related to the physical world and human beings, gathering, monitoring, processing, and analyzing data to allow instrumentation and automation and to facilitate decision-making. Wireless sensor networks (WSNs) represent networks that are embedded into our physical environments. A sensor is a tiny electronic device that can respond to a physical stimulus and convert it into numeric data. A WSN is composed of many low-power, low-cost, autonomous sensor nodes interconnected with wireless communication of sensory data. A myriad of measurements can be done by sensors, including environmental properties such as temperatures, humidity, and air pressure; presence, vibration, and motion detection of objects; chemical properties; radiation levels; GPS; light; and acoustic and seismic activities. Data gathering is conducted intermittently at a specified frequency. A sensor node in a WSN possesses sufficient computing power to process sensory data gathered locally or transmitted from other sensor nodes via wireless links. Furthermore, sensor nodes in a WSN self-organize into a network topology, thereby improving robustness and reducing maintenance costs.

Source of Information : Elsevier Wireless Networking Complete 2010


Global wireless communication comprises two elements: terrestrial communication and satellite communication. Cellular networks are primarily terrestrial-based, consisting of a vast number of base stations across heavily populated areas. In some circumstances, such as research laboratories established in the Antarctic, satellite communication is the only means of communication. Some other applications of satellite communication include military satellite espionage, global television broadcast, satellite radio, meteorological satellite imaging, and GPS. In addition, satellites complement cellular networks in reaching far rural areas and have been integrated into worldwide GSM and CDMA systems.

Satellite Communication
Despite the advantage of providing global coverage, satellite communication is known to have significant drawbacks. For one thing, satellite links introduce greater propagation latency than fiber-optic links due to the much longer distance a signal must travel back and forth between a terminal and a satellite. A delay of even half a second when using a geostationary satellite phone is noticeable. Bandwidth is another downside of satellite communication compared to terrestrial wired or wireless communications. Although a single satellite may cover a large geographical area (known as the “ footprint ” ), the cost of the entire system remains extremely high, making its acceptability by the general public economically impossible.

Satellite Systems
Satellites orbit the Earth at different heights in various periods. The higher the satellite, the longer the period of the satellite will be. The orbits can be circles or eclipses. Earlier satellites were composed of transponders that received signals on one frequency and transmitted them on another. Digital technologies were introduced later to allow improved quality of the signals and more reliable communication. Signals transmitted from a satellite to the Earth attenuate proportional to the square of the distance. A variety of atmospheric conditions also influence satellite signal transmission, such as rain absorption and meteors in the space.

Communication satellites can be divided into four categories based on the orbit of the satellite in space: geostationary (GEO) satellite, medium Earth orbit (MEO) satellite, and low Earth orbit (LEO) satellite.

GEO satellites remain relatively stationary at a height of about 36,000 km. Three of them are required to cover the entire surface of the Earth. The frequency bands allocated for GEO satellite communication by the ITU are L band (1.5-GHz downlink, 1.6-GHz uplink, 15-MHz bandwidth), S band (1.9-GHz downlink, 2.2-GHz uplink, 70-MHz bandwidth), C band (4.0-GHz downlink, 6.0-GHz uplink, 500-MHz bandwidth), Ku band (11-GHz downlink, 14-GHz uplink, 500-MHz bandwidth), and Ka band (20-GHz downlink, 30-GHz uplink, 3500-MHz bandwidth). GEO satellite systems are primarily used for television broadcasting, such as Direct TV and Dish Networks, and mobile communications. The newest member of this family is satellite digital radio, which provides CD-quality music over more than 1000 channels.

MEO satellites orbit the Earth at heights of around 10,000 to 20,000 km. GPS systems use MEO satellites to provide precise location identifi cation with a range of several meters. 24 GPS satellites operated by U.S. Department of Defense orbit the Earth twice a day at a height of about 19,320 km. The civilian use of GPS operates at 1575.42 MHz, part of the L band. A GPS receiver must communicate with at least three GPS satellites in order to compute a specific two-dimensional location via triangulation. With four or more signals from GPS satellites, the receiver is able to calculate a three-dimensional location.

LEO satellites are much closer to the surface of the Earth than MEO and GEO satellites.
Their period can be as short as 1 or 2 h. Because of the considerably shorter distance between LEO satellites and receivers, propagation latency is reduced down to about 10 msec; however, to offer global coverage, many more satellites are needed. For example, the Iridium system was originally designed to have 77 satellites in space (element 77 is iridium). The Teledesic project planed to launch 840 LEO satellites. These numbers had to be scaled back in order to keep costs under control. Aimed at reducing the cost of satellites, another system, Globalstar, has 48 satellites and a large number of ground base stations. (It must be noted that Iridium went bankrupt in 1999 as a result of a small user base and high operational cost.) The data rate offered by LEO satellite systems varies from kilobits per second to megabits per second, depending on the target applications.

Source of Information : Elsevier Wireless Networking Complete 2010

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