Radio-frequency identification (RFID) is an automatic identification method, relying on storing and remotely retrieving data using devices called RFID tags or transponders.
An RFID tag is an object that can be stuck on or incorporated into a product, animal, or person for the purpose of identification using radiowaves. Some tags can be read from several meters away and beyond the line of sight of the reader.
Most RFID tags contain at least two parts. One is an integrated circuit for storing and processing information, modulating and demodulating a (RF) signal and perhaps other specialized functions. The second is an antenna for receiving and transmitting the signal. A technology called chipless RFID allows for discrete identification of tags without an integrated circuit, thereby allowing tags to be printed directly onto assets at lower cost than traditional tags.
Today, a significant thrust in RFID use is in enterprise supply chain management, improving the efficiency of inventory tracking and management. However, a threat is looming that the current growth and adoption in enterprise supply chain market will not be sustainable. A fair cost-sharing mechanism, rational motives and justified returns from RFID technology investments are the key ingredients to achieve long-term and sustainable RFID technology adoption.
History of RFID tags
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In 1946 Léon Theremin invented an espionage tool for the Soviet Union which retransmitted incident radio waves with audio information. Sound waves vibrated a diaphragm which slightly altered the shape of the resonator, which modulated the reflected radio frequency. Even though this device was a passive covert listening device, not an identification tag, it has been attributed as the first known device and a predecessor to RFID technology. The technology used in RFID has been around since the early 1920s according to one source (although the same source states that RFID systems have been around just since the late 1960s).
A more similar technology such as the IFF transponder was invented by the British in 1939 was routinely used by the allies in World War II to identify airplanes as friend or foe. Transponders are still used by military and commercial aircraft to this day.
Another early work exploring RFID is the landmark 1948 paper by Harry Stockman, titled "Communication by Means of Reflected Power" (Proceedings of the IRE, pp 1196–1204, October 1948). Stockman predicted that "…considerable research and development work has to be done before the remaining basic problems in reflected-power communication are solved, and before the field of useful applications is explored."
Mario Cardullo's U.S. Patent 3,713,148 in 1973 was the first true ancestor of modern RFID; a passive radio transponder with memory. The initial device was passive, powered by the interrogating signal, and was demonstrated in 1971 to the New York Port Authority and other potential users and consisted of a transponder with 16 bit memory for use as a toll device. The basic Cardullo patent covers the use of RF, sound and light as transmission medium. The original business plan presented to investors in 1969 showed uses in transportation (automotive vehicle identification, automatic toll system, electronic license plate, electronic manifest, vehicle routing, vehicle performance monitoring), banking (electronic check book, electronic credit card), security (personnel identification, automatic gates, surveillance) and medical (identification, patient history).
A very early demonstration of reflected power (modulated backscatter) RFID tags, both passive and active, was done by Steven Depp, Alfred Koelle and Robert Freyman at the Los Alamos Scientific Laboratory in 1973. The portable system operated at 915 MHz and used 12 bit tags. This technique is used by the majority of today's UHF and microwave RFID tags.
The first patent to be associated with the abbreviation RFID was granted to Charles Walton in 1983 (U.S. Patent 4,384,288).
RFID tags
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RFID tags come in three general varieties:passive, active", or semi-passive (also known as battery-assisted). Passive tags require no internal power source, whereas semi-passive and active tags require a power source, usually a small battery.
Passive
Passive RFID tags have no internal power supply. The minute electrical current induced in the antenna by the incoming radio frequency signal provides just enough power for the CMOS integrated circuit in the tag to power up and transmit a response. Most passive tags signal by backscattering the carrier wave from the reader. This means that the antenna has to be designed to both collect power from the incoming signal and also to transmit the outbound backscatter signal. The response of a passive RFID tag is not necessarily just an ID number; the tag chip can contain non-volatile EEPROM for storing data.
Passive tags have practical read distances ranging from about 10 cm (4 in.) (ISO 14443) up to a few meters (Electronic Product Code (EPC) and ISO 18000-6), depending on the chosen radio frequency and antenna design/size. Due to their simplicity in design they are also suitable for manufacture with a printing process for the antennas. The lack of an onboard power supply means that the device can be quite small: commercially available products exist that can be embedded in a sticker, or under the skin in the case of low frequency RFID tags.
In 2006, Hitachi, Ltd. developed a passive device called the µ-Chip measuring 0.15×0.15 mm (not including the antenna), and thinner than a sheet of paper (7.5 micrometers). Silicon-on-Insulator (SOI) technology is used to achieve this level of integration. The Hitachi µ-Chip can wirelessly transmit a 128-bit unique ID number which is hard coded into the chip as part of the manufacturing process. The unique ID in the chip cannot be altered, providing a high level of authenticity to the chip and ultimately to the items the chip may be permanently attached or embedded into. The Hitachi µ-Chip has a typical maximum read range of 30 cm (1 foot). In February 2007 Hitachi unveiled an even smaller RFID device measuring 0.05×0.05 mm, and thin enough to be embedded in a sheet of paper. The new chips can store as much data as the older µ-chips, and the data contained on them can be extracted from as far away as a few hundred metres. The ongoing problem with all RFIDs is that they need an external antenna which is 80 times bigger than the chip in the best version thus far developed.
Alien Technology's Fluidic Self Assembly, SmartCode's Flexible Area Synchronized Transfer (FAST)and Symbol Technologies' PICA process are alleged to potentially further reduce tag costs by massively parallel production. Alien Technology and SmartCode are currently using the processes to manufacture tags while Symbol Technologies' PICA process is still in the development phase. Alternative methods of production such as FAST, FSA and PICA could potentially reduce tag costs dramatically, and due to volume capacities achievable, in turn be able to also drive the economies of scale models for various Silicon fabricators as well. Some passive RFID vendors believe that Industry benchmarks for tag costs can be achieved eventually as new low cost volume production systems are implemented more broadly.
Non-silicon tags made from polymer semiconductors are currently being developed by several companies globally. Simple laboratory printed polymer tags operating at 13.56 MHz were demonstrated in 2005 by both PolyIC (Germany) and Philips (The Netherlands). If successfully commercialized, polymer tags will be roll-printable, like a magazine, and much less expensive than silicon-based tags. The end game for most item-level tagging over the next few decades may be that RFID tags will be wholly printed – the same way a barcode is today – and be virtually free, like a barcode. However, substantial technical and economic hurdles must be surmounted to accomplish such an end: hundreds of billions of dollars have been invested over the last three decades in silicon processing, resulting in a per-feature cost which is actually less than that of conventional printing.
Active
Unlike passive RFID tags, active RFID tags have their own internal power source, which is used to power the integrated circuits and broadcast the signal to the reader. Active tags are typically much more reliable (e.g. fewer errors) than passive tags due to the ability for active tags to conduct a "session" with a reader. Active tags, due to their onboard power supply, also transmit at higher power levels than passive tags, allowing them to be more effective in "RF challenged" environments like water (including humans/cattle, which are mostly water), metal (shipping containers, vehicles), or at longer distances. Many active tags today have practical ranges of hundreds of meters, and a battery life of up to 10 years. Some active RFID tags include sensors such as temperature logging which have been used to monitor the temperature of perishable goods like fresh produce or certain pharmaceutical products. Other sensors that have been married with active RFID include humidity, shock/vibration, light, radiation, temperature, and atmospherics like ethylene. Active tags typically have much longer range (approximately 500 m/1500 feet) and larger memories than passive tags, as well as the ability to store additional information sent by the transceiver. The United States Department of Defense has successfully used active tags to reduce logistics costs and improve supply chain visibility for more than 15 years.
Semi-passive
Semi-passive tags are similar to active tags as they have their own power source, but the battery is used just to power the microchip and not broadcast a signal. The RF energy is reflected back to the reader like a passive tag.
Antenna types
The antenna used for an RFID tag is affected by the intended application and the frequency of operation. Low-frequency (LF) passive tags are normally inductively coupled, and because the voltage induced is proportional to frequency, many coil turns are needed to produce enough voltage to operate an integrated circuit. Compact LF tags, like glass-encapsulated tags used in animal and human identification, use a multilayer coil (3 layers of 100–150 turns each) wrapped around a ferrite core.
At 13.56 MHz (High frequency or HF), a planar spiral with 5–7 turns over a credit-card-sized form factor can be used to provide ranges of tens of centimeters. These coils are less costly to produce than LF coils, since they can be made using lithographic techniques rather than by wire winding, but two metal layers and an insulator layer are needed to allow for the crossover connection from the outermost layer to the inside of the spiral where the integrated circuit and resonance capacitor are located.
Ultra-high frequency (UHF) and microwave passive tags are usually radiatively-coupled to the reader antenna and can employ conventional dipole-like antennas. Only one metal layer is required, reducing cost of manufacturing. Dipole antennas, however, are a poor match to the high and slightly capacitive input impedance of a typical integrated circuit. Folded dipoles, or short loops acting as inductive matching structures, are often employed to improve power delivery to the IC. Half-wave dipoles (16 cm at 900 mHz) are too big for many applications; for example, tags embedded in labels must be less than 100 mm (4 inches) in extent. To reduce the length of the antenna, antennas can be bent or meandered, and capacitive tip-loading or bowtie-like broadband structures are also used. Compact antennas usually have gain less than that of a dipole — that is, less than 2 dBi — and can be regarded as isotropic in the plane perpendicular to their axis.
Dipoles couple to radiation polarized along their axes, so the visibility of a tag with a simple dipole-like antenna is orientation-dependent. Tags with two orthogonal or nearly-orthogonal antennas, often known as dual-dipole tags, are much less dependent on orientation and polarization of the reader antenna, but are larger and more expensive than single-dipole tags.
Patch antennas are used to provide service in close proximity to metal surfaces, but a structure with good bandwidth is 3–6 mm thick, and the need to provide a ground layer and ground connection increases cost relative to simpler single-layer structures.
HF and UHF tag antennas are usually fabricated from copper or aluminum. Conductive inks have seen some use in tag antennas but have encountered problems with IC adhesion and environmental stability.
Tag Attachment
Basically, there are three different kinds of RFID tags based on their attachment with identified objects, i.e. attachable, implantable and insertion tags. In addition to these conventional RFID tags, Eastman Kodak Company has filed two patent applications for monitoring ingestion of medicine comprises forming a digestible RFID tag.
Tagging Positions
RFID tagging positions can influence the performance of air interface UHF RFID passive tags and related to the position where RFID tags are embedded, attached, injected or digested.
In many cases, optimum power from RFID reader is not required to operate passive tags. However, in cases where the Effective Radiated Power (ERP) level and distance between reader and tags are fixed, such as in manufacturing setting, it is important to know the location in a tagged object where a passive tag can operate optimally.
R-Spot or Resonance Spot, L-Spot or Live Spot and D-Spot or Dead Spot are defined to specify the location of RFID tags in a tagged object, where the tags can still receive power from a reader within specified ERP level and distance.
From Wikipedia, the free encyclopedia
Saturday, August 25, 2007
Radio-frequency identification
Thursday, August 23, 2007
Grid Computing
From Wikipedia, the free encyclopedia
Grid computing is a phrase in distributed computing which can have several meanings:
-A local computer cluster which is like a "grid" because it is composed of multiple nodes.
-Offering online computation or storage as a metered commercial service, known as utility computing, computing on demand, or cloud computing.
-The creation of a "virtual supercomputer" by using spare computing resources within an organization.
-The creation of a "virtual supercomputer" by using a network of geographically dispersed computers. Volunteer computing, which generally focuses on scientific, mathematical, and academic problems, is the most common application of this technology.
These varying definitions cover the spectrum of "distributed computing", and sometimes the two terms are used as synonyms. This article focuses on distributed computing technologies which are not in the traditional dedicated clusters; otherwise, see computer cluster.
Functionally, one can also speak of several types of grids:
-Computational grids (including CPU Scavenging grids) which focuses primarily on computationally-intensive operations.
-Data grids or the controlled sharing and management of large amounts of distributed data.
-Equipment grids which have a primary piece of equipment e.g. a telescope, and where the surrounding Grid is used to control the equipment remotely and to analyze the data produced.
Grids versus conventional supercomputers
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"Distributed" or "grid computing" in general is a special type of parallel computing which relies on complete computers (with onboard CPU, storage, power supply, network interface, etc.) connected to a network (private, public or the Internet) by a conventional network interface, such as Ethernet. This is in contrast to the traditional notion of a supercomputer, which has many CPUs connected by a local high-speed computer bus.
The primary advantage of distributed computing is that each node can be purchased as commodity hardware, which when combined can produce similar computing resources to a many-CPU supercomputer, but at lower cost. This is due to the economies of scale of producing commodity hardware, compared to the lower efficiency of designing and constructing a small number of custom supercomputers. The primary performance disadvantage is that the various CPUs and local storage areas do not have high-speed connections. This arrangement is thus well-suited to applications where multiple parallel computations can take place independently, without the need to communicate intermediate results between CPUs.
The high-end scalability of geographically dispersed grids is generally favorable, due to the low need for connectivity between nodes relative to the capacity of the public Internet. Conventional supercomputers also create physical challenges in supplying sufficient electricity and cooling capacity in a single location. Both supercomputers and grids can be used to run multiple parallel computations at the same time, which might be different simulations for the same project, or computations for completely different applications. The infrastructure and programming considerations needed to do this on each type of platform are different, however.
There are also differences in programming and deployment. It can be costly and difficult to write programs so that they can be run in the environment of a supercomputer, which may have a custom operating system, or require the program to address concurrency issues. If a problem can be adequately parallelized, a "thin" layer of "grid" infrastructure can cause conventional, standalone programs to run on multiple machines (but each given a different part of the same problem). This makes it possible to write and debug programs on a single conventional machine, and eliminates complications due to multiple instances of the same program running in the same shared memory and storage space at the same time.
Design considerations and variations
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One feature of distributed grids is that they can be formed from computing resources belonging to multiple individuals or organizations (known as multiple administrative domains). This can facilitate commercial transactions, as in utility computing, or make it easier to assemble volunteer computing networks.
One disadvantage of this feature is that the computers which are actually performing the calculations might not be entirely trustworthy. The designers of the system must thus introduce measures to prevent malfunctions or malicious participants from producing false, misleading, or erroneous results, and from using the system as an attack vector. This often involves assigning work randomly to different nodes (presumably with different owners) and checking that at least two different nodes report the same answer for a given work unit. Discrepancies would identify malfunctioning and malicious nodes.
Due to the lack of central control over the hardware, there is no way to guarantee that nodes will not drop out of the network at random times. Some nodes (like laptops or dialup Internet customers) may also be available for computation but not network communications for unpredictable periods. These variations can be accommodated by assigning large work units (thus reducing the need for continuous network connectivity) and reassigning work units when a given node fails to report its results as expected.
The impacts of trust and availability on performance and development difficulty can influence the choice of whether to deploy onto a dedicated computer cluster, to idle machines internal to the developing organization, or to an open external network of volunteers or contractors.
In many cases, the participating nodes must trust the central system not to abuse the access that is being granted, by interfering with the operation of other programs, mangling stored information, transmitting private data, or creating new security holes. Other systems employ measures to reduce the amount of trust "client" nodes must place in the central system such as placing applications in virtual machines.
Public systems or those crossing administrative domains (including different departments in the same organization) often result in the need to run on heterogeneous systems, using different operating systems and hardware architectures. With many languages, there is a tradeoff between investment in software development and the number of platforms that can be supported (and thus the size of the resulting network). Cross-platform languages can reduce the need to make this tradeoff, though potentially at the expense of high performance on any given node (due to run-time interpretation or lack of optimization for the particular platform).
Various middleware projects have created generic infrastructure, to allow various scientific and commercial projects to harness a particular associated grid, or for the purpose of setting up new grids. BOINC is a common one for academic projects seeking public volunteers; more are listed at the end of the article.
CPU scavenging
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CPU-scavenging, cycle-scavenging, cycle stealing, or shared computing creates a "grid" from the unused resources in a network of participants (whether worldwide or internal to an organization). Usually this technique is used to make use of instruction cycles on desktop computers that would otherwise be wasted at night, during lunch, or even in the scattered seconds throughout the day when the computer is waiting for user input or slow devices.
Volunteer computing projects use the CPU scavenging model almost exclusively.
In practice, participating computers also donate some supporting amount of disk storage space, RAM, and network bandwidth, in addition to raw CPU power. Nodes in this model are also more vulnerable to going "offline" in one way or another from time to time, as their owners use their resources for their primary purpose.
Current projects and applications
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Grids offer a way to solve Grand Challenge problems like protein folding, financial modeling, earthquake simulation, and climate/weather modeling. Grids offer a way of using the information technology resources optimally inside an organization. They also provide a means for offering information technology as a utility for commercial and non-commercial clients, with those clients paying only for what they use, as with electricity or water.
Grid computing is presently being applied successfully by the National Science Foundation's National Technology Grid, NASA's Information Power Grid, Pratt & Whitney, Bristol-Myers Squibb, Co., and American Express.
One of the most famous cycle-scavenging networks is SETI@home, which was using more than 3 million computers to achieve 23.37 sustained teraflops (979 lifetime teraflops) as of September 2001.
As of May 2005, Folding@home had achieved peaks of 186 teraflops on over 160,000 machines.
Another well-known project is distributed.net, which was started in 1997 and has run a number of successful projects in its history.
The NASA Advanced Supercomputing facility (NAS) has run genetic algorithms using the Condor cycle scavenger running on about 350 Sun and SGI workstations.
United Devices operates the United Devices Cancer Research Project based on its Grid MP product, which cycle scavenges on volunteer PCs connected to the Internet. As of June 2005, the Grid MP ran on about 3,100,000 machines.
The Enabling Grids for E-sciencE project, which is based in the European Union and includes sites in Asia and the United States, is a follow up project to the European DataGrid (EDG) and is arguably the largest computing grid on the planet. This, along with the LHC Computing Grid (LCG) have been developed to support the experiments using the CERN Large Hadron Collider. The LCG project is driven by CERN's need to handle huge amounts of data, where storage rates of several gigabytes per second (10 petabytes per year) are required. A list of active sites participating within LCG can be found online as can real time monitoring of the EGEE infrastructure. The relevant software and documentation is also publicly accessible .
