Advancements Towards 4G

ABSTRACT


Currently 2G Technology (GSM), or second generation technology, is widely used worldwide for cell phone networks. The problem with 2G technology is that the data rates are limited. This makes it inefficient for data transfer applications such as video conferencing, music or video downloads. To increase the speed, various new technologies have been in development.
One of these, 4G technology, is mainly made up of high-speed wireless networks designed to carry data, rather than voice or a mixture of the two. 4G transfers data to and from mobile devices at broadband speeds – up to100 Mbps moving and 1Gbps while the phone is stationary. In addition to high speeds, the technology is more robust against interference and tapping guaranteeing higher security. This innovative technology functions with the aid of VoIP, IPv6, and Orthogonal frequency division multiplexing (OFDM).
To cater the growing needs of 4G, mobile data communication providers will deploy multiple antennas at transmitters to increase the data rate. Unlike the 3G networks, which are a mix of circuit switched and packet switched networks, 4G will be based on packet switching only (TCP/IP). This will allow low-latency data transmission. Furthermore, the use of IP to transfer information will require IPv6 to facilitate the use of more cell phone devices. During the presentation, an overview of the various generations of mobile device technologies preceding 4G would be followed by technical aspects of 4G and how it functions, as well as the way it can lead to future innovations in cellular and communication technology.



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Adding Intelligence to Internet

ABSTRACT


Two scaling problems face the Internet today. First, it will be years before terrestrial networks are able to provide adequate bandwidth uniformly around the world, given the explosive growth in Internet bandwidth demand and the amount of the world that is still unwired. Second, the traffic distribution is not uniform worldwide: Clients in all countries of the world access content that today is chiefly produced in a few regions of the world (e.g., North America). A new generation of Internet access built around geosynchronous satellites can provide immediate relief. The satellite system can improve service to bandwidth-starved regions of the globe where terrestrial networks are insufficient and supplement terrestrial networks elsewhere. This new generation of satellite system manages a set of satellite links using intelligent controls at the link endpoints. The intelligence uses feedback obtained from monitoring end-user behavior to adapt the use of resources. Mechanisms controlled include caching, dynamic construction of push channels, use of multicast, and scheduling of satellite bandwidth. This paper discusses the key issues of using intelligence to control satellite links, and then presents as a case study the architecture of a specific system: the Internet Delivery System, which uses INTELSAT’s satellite fleet to create Internet connections that act as wormholes between points on the globe.



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A Search Engine for 3D Models

ABSTRACT


As the number of 3D models available on the Web grows, there is an increasing need for a search engine to help people find them. Unfortunately, traditional text-based search techniques are not always effective for 3D data. In this paper, we investigate new shape-based search methods.
The key challenges are to develop query methods simple enough for novice users and matching algorithms robust enough to work for arbitrary polygonal models. We present a web-based search engine system that supports queries based on 3D sketches, 2D sketches, 3D models, and/or text keywords. For the shape-based queries, we have developed a new matching algorithm that uses spherical harmonics to compute discriminating similarity measures without requiring repair of model degeneracies or alignment of orientations. It provides 46{245% better performance than related shape matching methods during precision-recall experiments, and it is fast enough to return query results from a repository of 20,000 models in under a second. The net result is a growing interactive index of 3D models available on the Web (i.e., a Google for 3D models).



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Artificial Neural Network (ANN)

ABSTRACT


An Artificial Neural Network (ANN) is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, such as pattern recognition or data classification, through a learning process. Learning in biological systems involves adjustments to the synaptic connections that exist between the neurons. This is true of ANNs as well.

Neural network simulations appear to be a recent development. However, this field was established before the advent of computers, and has survived several eras. Many important advances have been boosted by the use of inexpensive computer emulations. The first artificial neuron was produced in 1943 by the neurophysiologist Warren McCulloch and the logician Walter Pitts.

There were some initial simulations using formal logic. McCulloch and Pitts (1943) developed models of neural networks based on their understanding of neurology. These models made several assumptions about how neurons worked. Their networks were based on simple neurons, which were considered to be binary devices with fixed threshold.

Not only was neuroscience, but psychologists and engineers also contributed to the progress of neural network simulations. Rosenblatt (1958) stirred considerable interest and activity in the field when he designed and developed the Perceptron. The Perceptron had three layers with the middle layer known as the association layer. This system could learn to connect or associate a given input to a random output unit.

Another system was the ADALINE (Adaptive Linear Element) which was developed in 1960 by Widrow and Hoff (of Stanford University). The ADALINE was an analogue electronic device made from simple components. The method used for learning was different to that of the Perceptron, it employed the Least-Mean-Squares (LMS) learning rule. Progress during the late 1970s and early 1980s was important to the re-emergence on interest in the neural network field.Significant progress has been made in the field of neural networks-enough to attract a great deal of attention and fund further research. Neurally based chips are emerging and applications to complex problems developing. Clearly, today is a period of transition for neural network technology.

Neural networks, with their remarkable ability to derive meaning from complicated or imprecise data, can be used to extract patterns and detect trends that are too complex to be noticed by either humans or other computer techniques. A trained neural network can be thought of as an “expert” in the category of information it has been given to analyze. This expert can then be used to provide projections given new situations of interest and answer “what if” questions.



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Neural Networks

ABSTRACT


With the dawn of the genome era computational methods in the automatic analysis of biological data have become increasingly important. The explosion in the production rate of expression level data has highlighted the need for automated techniques that help scientists analyze, understand, and cluster (sequence) the enormous amount of data that is being produced. Example of such problems are analyzing gene expression level data produced by microarray technology on the genomic scale, sequencing genes on the genomic scale, sequencing proteins and amino acids, etc. Researchers have recognised Artificial Neural Networks as a promising technique that can be applied to several problems in genome informatics and molecular sequence analysis. This seminar explains how Neural Networks have been widely employed in genome informatics research.



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Grid Network

ABSTRACT


Grid is as an emerging technology for enabling resource sharing and coordinated problem solving in dynamic multi-institutional virtual organizations. In the grid environment, resources may belong to different institutions, have different usage policies and pose different requirements on acceptable requests.

one of the fundamental operations needed to support location independent computing is resource discovery .It is the process of locating relevant resources based on application requirements of a user.

The description of a resource is essential for automated resource discovery and search, selection, matching, composition and interoperation, invocation and execution monitoring; different middle-ware specifies different rules for describing a resource. Hence, the information gathered from these diverse sources tends to be semantically heterogeneous and needs to be correlated.

Efficient resource discovery needs uniform unambiguous resource description. To date there is no universal resource description language common to all state of art grid middleware. Different grid middleware systems have different methods of resource description and it is not yet known how well these can interoperate. Hence, there is a need to utilize semantic matching of these resource descriptions.



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E-Intelligence

ABSTRACT


E-intelligence systems provide internal business users, trading partners, and corporate clients rapid and easy access to the e-business information, applications, and services they need in order to compete effectively and satisfy customer needs. They offer many business benefits to organizations in exploiting the power of the Internet. For example, e-intelligence systems give the organization the ability to:

1. Integrate e-business operations into the traditional business environment, giving business users a complete view of all corporate business operations and information.

2. Help business users make informed decisions based on accurate and consistent e-business information that is collected and integrated from e-business applications. This business information helps business users optimize Web-based offerings (products offered, pricing and promotions, service and support, and so on) to match marketplace requirements and analyze business performance with respect to competitors and the organization’s business-performance objectives.
3. Assist e-business applications in profiling and segmenting e-business customers. Based on this information, businesses can personalize their Web pages and the products and services they offer.
4. Extend the business intelligence environment outside the corporate firewall, helping the organization share internal business information with trading partners. Sharing this information will let it optimize the product supply chain to match the demand for products sold through the Internet and minimizes the costs of maintaining inventory.

5. Extend the business intelligence environment outside the corporate firewall to key corporate clients, giving them access to business information about their accounts.
With this information, clients can analyze and tune their business relationships with other organization, improving client service and satisfaction.

6. Link e-business applications with business intelligence and collaborative processing applications, allowing internal and external users to seamlessly move among different systems.



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IEEE 802.11n –Next Generation Wireless Standard

ABSTRACT


The newest standard in Wireless LAN is called 802.11n. 802.11 is an industry standard for high-speed networking. 802.11n is designed to replace the 802.11a, 802.11b and 802.11g standards. 802.11n equipment is backward compatible with older 802.11gab and it supports much faster wireless connections over longer distances. So-called “Wireless N” or “Draft N” routers available today are based on a preliminary version of the 802.11n. The beta version of this standard is used now in laptops and routers. 802.11n will work by utilizing multiple input multiple output (MIMO) antennas and channel bounding in tandem to transmit and receive data. It contains at least 2 antennas for transmitting data’s. 802.11n will support bandwidth greater than 100 Mbps and in theory it can have a speed of 600 Mbps.It can be used in high speed internets, VOIP, Network Attach Storage (NAS), gaming. The full version will be implemented in the laptops and in the LANs in upcoming years.



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10 GB ETHERNET

ABSTRACT


Since its inception at Xerox Corporation in the early 1970s, Ethernet has been the dominant networking protocol. Of all current networking protocols, Ethernet has, by far, the highest number of installed ports and provides the greatest cost performance relative to Token Ring, Fiber Distributed Data Interface (FDDI), and ATM for desktop connectivity. Fast Ethernet, which increased Ethernet speed from 10 to 100 megabits per second (Mbps), provided a simple, cost-effective option for backbone and server connectivity.

10 Gigabit Ethernet builds on top of the Ethernet protocol, but increases speed tenfold over Fast Ethernet to 10000 Mbps, or 10 gigabit per second (Gbps). This protocol, which was standardized in august 2002, promises to be a dominant player in high-speed local area network backbones and server connectivity. Since10 Gigabit Ethernet significantly leverages on Ethernet, customers will be able to leverage their existing knowledge base to manage and maintain gigabit networks.

The purpose of this technology brief is to provide a technical overview of 10 Gigabit Ethernet. This paper discusses:

• The architecture of the Gigabit Ethernet protocol, including physical interfaces, 802.3x flow control, and media connectivity options
• The 10 Gigabit Ethernet standards effort and the timing for Gigabit Ethernet
• 10 Gigabit Ethernet topologies
• Migration strategies to 10 Gigabit Ethernet



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RESILIENT PACKET RING Networks

ABSTRACT


The main objective of Resilient Packet Ring technology is to enable a true alternative to SONET transport for packet networks, providing carriers with resiliency, fast protection and restoration, and performance monitoring comparable to those of SONET networks.

RPR was designed to combine SONET strengths of high availability, reliability and TDM services support, with Ethernet’s low-cost, superior bandwidth utilization and high service granularity characteristics.

Unlike SONET, RPR provides an Ethernet-like cost curve as well as superior bandwidth utilization, both in its Ethernet-like statistical multiplexing, and in its spatial reuse capabilities. Spatial reuse provides an extremely efficient use of shared media traffic in metro/access rings, since it is expected that in the near future most traffic originating in a metro area will remain within the same metro/access ring.

Unlike next-generation SONET solutions that integrate both transport and data switching in the same network element, RPR is a transport technology that fits into existing carriers’ operations model, this tremendously reduces the required operational expenses in deployment as well as the maintenance expenses associated with the manual provisioning process of today’s transport networks.

Unlike Ethernet transport technology, RPR provides “five-nines” availability using SONET-grade fast protection and restoration, carrier-class fairness, the ability to transparently carry and groom TDM traffic, and SONET-like reliability and performance monitoring capabilities.

RPRs provide a reliable, efficient, and service-aware transport for both enterprise and service-provider networks. Combining the best features of legacy SONET/SDH and Ethernet into one layer, RPR maximizes profitability while delivering carrier-class service. RPR will enable the convergence of voice, video, and data services transport.



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