Voice over Long Term Evolution (VoLTE)
Networking , Technology & Science / January 16, 2018

Rapid increase in data traffic over cellular network is necessitating deployment of Long Term Evolution (LTE) in the cellular operator’s networks. While LTE provides efficient data traffic handling and high data rates, it lacks native circuit switched voice capability. Mobile operators have begun migrating to fourth-generation (4G) architectures based on the Long-Term Evolution (LTE) standard, including the Evolved Packet Core (EPC) architecture defined by the 3rd Generation Partnership Project (3GPP). According to a recent report from the Global mobile Supplies Association (GSA), LTE has become the fastest-developing mobile communications systems technology. What is Voice over Long Term Evolution (VoLTE)? The data traffic, in telecom system, is growing at a rapid pace. However, presently for any mobile system to be commercially viable, the ability to carry voice traffic is essential. The existing 2G/3G mobile systems use “Circuit Switching” to carry voice traffic. In Circuit Switching a dedicated, end-to-end, channel or circuit is established to carry the voice traffic for the entire duration of a transmission. On the other hand, in case of IP networks, the voice traffic is carried using IP packets over data connection. For this generally “VoIP” or “VoLTE” solutions are used. For mobile communications service providers (CSPs), Voice…

What is Wireless Intelligent Network (WIN)
Networking , Technology & Science / January 15, 2018

Increasing complexity in telecommunications services requires ever more complex standards, and therefore the need for better means to write them. Today’s wireless subscribers are much more sophisticated telecommunications users than they were five years ago. No longer satisfied with just completing a clear call, today’s subscribers demand innovative ways to use the wireless phone. They want multiple services that allow them to handle or select incoming calls in a variety of ways. Wireless Intelligent network is developed to drive intelligent network capabilities such as service independence, separation of basic switching functions from service and application functions and independence of applications from lower-level communication details into wireless networks. Introduction of Wireless Intelligent Network (WIN) Enhanced services are very important to wireless customers. They have come to expect, for instance, services such as caller ID and voice messaging bundled in the package when they buy and activate a cellular or personal communications service (PCS) phone. Whether prepaid, voice/data messaging, Internet surfing, or location-sensitive billing, enhanced services will become an important differentiator in an already crowded, competitive service-provider market. Enhanced services will also entice potentially new subscribers to sign up for service and will drive up airtime through increased usage of PCS or…

Understanding of Geographic Information System (GIS)

Geographical Information System (GIS) is a technology that provides the means to collect and use geographic data to assist in the development of Agriculture. A digital map is generally of much greater value than the same map printed on a paper as the digital version can be combined with other sources of data for analyzing information with a graphical presentation. The GIS software makes it possible to synthesize large amounts of different data, combining different layers of information to manage and retrieve the data in a more useful manner. GIS provides a powerful means for agricultural scientists to better service to the farmers and farming community in answering their query and helping in a better decision making to implement planning activities for the development of agriculture. overview of Geographic Information System (GIS) A Geographical Information System (GIS) is a system for capturing, storing, analyzing and managing data and associated attributes, which are spatially referenced to the Earth. The geographical information system is also called as a geographic information system or geospatial information system. It is an information system capable of integrating, storing, editing, analyzing, sharing, and displaying geographically referenced information. In a more generic sense, GIS is a software tool that…

What is Software Defined Networking
Networking , Technology & Science / January 7, 2018

Today’s Internet applications require the underlying networks to be fast, carry large amounts of traffic, and to deploy a number of distinct, dynamic applications and services. Adoption of the concepts of “inter-connected data centers” and “server virtualization” has increased network demand tremendously. Software Defined Networking (SDN) is an idea which has recently reignited the interest of network researchers for programmable networks and shifted the attention of the networking community to this topic by promising to make the process of designing and managing networks more innovative and simplified compared to the well-established but inflexible current approaches. Definition of Software Defined Networking Software defined networking is not a technology, but an architecture that provides support for virtual machine mobility independent of the physical network. Software Defined Networking (SDN) is an emerging network architecture where network control is decoupled from forwarding and is directly programmable. This migration of control, formerly tightly bound in individual network devices, into accessible computing devices enables the underlying infrastructure to be abstracted for applications and network services, which can treat the network as a logical or virtual entity. The goal of Software Defined Networking (SDN) is to enable cloud and network engineers and administrators to respond quickly to changing…

Introduction of Reinforcement Learning

The idea that we learn by interacting with our environment is probably the first to occur to us when we think about the nature of learning. When an infant plays, waves its arms, or looks about, it has no explicit teacher, but it does have a direct sensorimotor connection to its environment. Reinforcement learning is a computational approach to understanding and automating goal-directed learning and decision-making. It is distinguished from other computational approaches by its emphasis on learning. it is done by an agent from direct interaction with its environment. without relying on exemplary supervision or complete models of the environment. Overview of Reinforcement Learning Reinforcement learning is learning what to do–how to map situations to actions–so as to maximize a numerical reward signal. The learner is not told which actions to take, as in most forms of machine learning, but instead must discover which actions yield the most reward by trying them. In the most interesting and challenging cases, actions may affect not only the immediate reward but also the next situation and, through that, all subsequent rewards. These two characteristics–trial-and-error search and delayed reward–are the two most important distinguishing features of reinforcement learning.  Reinforcement Learning is a type…

Understanding of Distributed System

Networks of computers are everywhere. The Internet is one, as are the many networks of which it is composed. Mobile phone networks, corporate networks, factory networks, campus networks, home networks, in-car networks – all of these, both separately and in combination, share the essential characteristics that make them relevant subjects for study under the heading distributed systems. Distributed computing deals with all forms of computing, information access, and information exchange across multiple processing platforms connected by computer networks. Overview of Distributed System Over the past two decades, advancements in microelectronic technology have resulted in the availability of fast, inexpensive processors, and advancements in communication technology have resulted in the availability of cost effective and highly efficient computer networks. The net result of the advancements in these two technologies is that the price performance ratio has now changed to favor the use of interconnected multiple processors in place of a single, high-speed processor. Distributed systems form a rapidly changing field of computer science. A distributed computer system consists of multiple software components that are on multiple computers, but run as a single system. The computers that are in a distributed system can be physically close together and connected by a local network,…

Rule based System

Knowledge is practical or theoretical understanding of a subject or domain. Thus who possess knowledge are called experts. The human mental process is internal, it is too complex to be represented as an algorithm. However, most experts are capable of expressing their knowledge in the form of rules for problem solving. Rules are the popular paradigm for representing knowledge. A rule based expert system is one whose knowledge base contains the domain knowledge coded in the form of rules. Overview of Rule Based Systems Instead of representing knowledge in a relatively declarative, static way (as a bunch of things that are true), rule based system represent knowledge in terms of a bunch of rules that tell you what you should do or what you could conclude in different situations. A rule-based system consists of a bunch of IF-THEN rules, a bunch of facts, and some interpreter controlling the application of the rules, given the facts Rule-based systems (also known as production systems or expert systems) are the simplest form of artificial intelligence. A rule based system uses rules as the knowledge representation for knowledge coded into the system. The definitions of rule-based system depend almost entirely on expert systems, which…

Introduction of Data Compression

Data Compression is used just about everywhere. Data compression involves the development of a compact representation of information. Most representations of information contain large amounts of redundancy. Redundancy can exist in various forms. Internet users who download or upload files from/to the web, or use email to send or receive attachments will most likely have encountered files in compressed format. Data Compression Overview With the extending use of computer in various disciplines, number of data processing applications is also increasing which requires processing and storage of large volumes of data. Data compression is primarily a branch of information theory which deals with techniques related to minimizing the amount of data to be transmitted and stored. Data compression is often referred to as coding, where coding is a very general term encompassing any special representation of data which satisfies a given need. Information theory is defined to be the study of efficient coding and its consequences, in the form of speed. What is Data Compression ? Today, with the growing demands of information storage and data transfer, data compression is becoming increasingly important. Compression is the process of encoding data more efficiently to achieve a reduction in file size. One type of compression…

What is ACO (Ant Colony Optimization) Algorithm

There are even increasing efforts in searching and developing algorithms that can find solutions to combinatorial optimization problems. In this way, the Ant Colony Optimization Meta-heuristic takes inspiration from biology and proposes different versions of still more efficient algorithms. Ant Colony Optimization (ACO): Overview Ant Colony Optimization (ACO) is a paradigm for designing metaheuristic algorithms for combinatorial optimization problems. The essential trait of ACO algorithms is the combination of a priori information about the structure of a promising solution with a posteriori information about the structure of previously obtained good solutions. ACO is a class of algorithms, whose first member, called Ant System, was initially proposed by Colorni, Dorigo and Maniezzo The main underlying idea, loosely inspired by the behavior of real ants, is that of a parallel search over several constructive computational threads based on local problem data and on a dynamic memory structure containing information on the quality of previously obtained result. The collective behavior emerging from the interaction of the different search threads has proved effective in solving combinatorial optimization (CO) problems. More specifically, we can say that “Ant Colony Optimization (ACO) is a population-based, general search technique for the solution of difficult combinatorial problems which is…

Community Detection : Unsupervised Learning

Advances in technology and computation have provided the possibility of collecting and mining a massive amount of real-world data. Mining such “big data” allows us to understand the structure and the function of real systems and to find unknown and interesting patterns. This section provides the brief overview of the community structure. Introduction of Community Detection In the actual interconnected world, and the rising of online social networks the graph mining and the community detection become completely up-to-date. Understanding the formation and evolution of communities is a long-standing research topic in sociology in part because of its fundamental connections with the studies of urban development, criminology, social marketing, and several other areas. With increasing popularity of online social network services like Facebook, the study of community structures assumes more significance. Identifying and detecting communities are not only of particular importance but have immediate applications. For instance, for effective online marketing, such as placing online ads or deploying viral marketing strategies [10], identifying communities in social network could often lead to more accurate targeting and better marketing results. Albeit online user profiles or other semantic information is helpful to discover user segments this kind of information is often at a coarse-grained level…

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