Storage product networks, systems, complexes and computers
Measuring and computing complexes ICC of the AlphaCENTER AMR system are designed for measuring and accounting of electric energy and power, as well as automatic acquisition, processing and storage of data from electric energy meters and displaying the information obtained in a form convenient for analysis. All the software variants are fully compatible at the level of reference books and data. The AlphaCENTER technology allows creating AMR systems for both small enterprises with 1—5 accounting points and distributed data acquisition and processing systems with thousands of accounting points. The multi-user version of the software enables to organize access to information from dozens of workstations and comprises:. Intended for automatic parallel polling of electric energy meters and controllers involving use of various types of communication channels and communication equipment.VIDEO ON THE TOPIC: The Computer Chronicles - Local Area Networks (1984)
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Moe-Behrens GHG The biological microprocessor, or how to build a computer with biological parts. Computational and Structural Biotechnology Journal. Systemics, a revolutionary paradigm shift in scientific thinking, with applications in systems biology, and synthetic biology, have led to the idea of using silicon computers and their engineering principles as a blueprint for the engineering of a similar machine made from biological parts. Here we describe these building blocks and how they can be assembled to a general purpose computer system, a biological microprocessor.
A biocomputer can be used to monitor and control a biological system. Nature and computers are words that used to mean unrelated things. However, this view changed, starting in the s, when a revolutionary scientific paradigm, systemics based on platonic idealistic philosophy, gained popularity [ 1 ] [ 2 ] [ 3 ].
The roots of philosophical idealism based systemics goes back to Plato. Forms are archetypes, blueprints, the essences of the various phenomena of the same thing.
The superior world consists, due to Plato, of mathematical objects, terms and non-materialistic abstract ideas. Moreover, Plato introduced in his dialogue Philebus a concept called System [ 4 ]. A system is according to Plato a model for thinking about how complex structures are developed.
Another idealistic philosopher, Kant, introduced, in , in his Critique of Judgment the concept of self-organizing [ 5 ]. Idealistic concepts based systemics have become important in contemporary science in order to understand complexity and big data problems.
Bertalanaffy defined the concept of systems. Cybernetics explains complex systems that exist of a large number of interacting and interrelated parts. Wiener and Ashby pioneered the use of mathematics to study systems. This systems theory was further developed in the following years. Important contributions to the field are by Heinz Foerster, whose work focused on cybernetics, the exploration of regulatory systems, and who founded in the Biological Computer Lab BCL at the Department of Electrical Engineering at the University of Illinois [ 8 ].
The work of the BCL was focused on the similarities in cybernetic systems and electronics and especially biology inspired computing [ 9 ]. Other important contributions to systemics are by the Nobel-prize winning work of Ilya Prigogine on self-organization and his systems theory concepts in thermodynamics [ 10 ].
Furthermore: Mitchell Feigenbaums work on Chaos theory [ 11 ]. Contemporary application finds systems theory in bioscience in fields such as systems biology, and its practical application synthetic biology [ 12 ]. The term systems biology was created by Bertalanffy in [ 13 ]. Systems biology focuses on complex interactions in biological systems by applying a holistic perspective [ 12 ].
Altogether, this kind of thinking has led to the identification of ideas behind data processing in nature, but also in machines, such as silicon computers. This idea based thinking led to three distinct, but inter-related approaches, termed natural computing: computing inspired by nature, computer models of nature, and computing with natural materials [ 14 ] Figure 1.
Natural computing: A platonic idea is an archetype, a blueprint, the essence of various phenomena of the same thing.
Systemics and systems biology are such ideas, describing data processing systems in nature in terms of mathematics and formal logic.
Systemic ideas have been used as a blueprint for silicon computing. Ideas derived from the observation of nature have also inspired computer models of nature.
Focusing on information flow can help us to understand better how cells and organisms work [ 15 ]. Data processing can be found in nature all down to the atomic and molecular level. Examples are DNA information storage, and the histone code [ 16 ]. Moreover, cells have the potential to compute, both intra cellular e. Higher order cell systems such as the immune and the endocrine system, the homeostasis system, and the nerve system can be described as computational systems.
The most powerful biological computer we know is the human brain [ 18 ]. General systems theory is an important fundament for computer science [ 1 ]. Interesting work has be done, as discussed above, by the Biological Computer Laboratory led by Heinz Foerster [ 8 ] [ 9 ]. In practical terms, nature inspired to programming paradigms such as cellular automata, artificial neural networks, evolutionary algorithms, evolutionary biology, genetic programming, swarm intelligence, artificial immune systems, membrane computing and amorphous computing [ 14 ] [ 19 ].
The common aim of all these concepts is solving complex problems. The aim of the simulation and emulation of nature in computers is to test biological theories, and provide models that can be used to facilitate biological discovery.
Moreover, these models can potentially be used for computer aided design of artificial biological systems. Systems biology provides theoretical tools to model complex interactions in biological systems [ 12 ]. Design principles of biological circuits have been translated into mathematical models.
These design models find their practical application in synthetic biology in general, and cellular computer especially. The different areas of natural computing clearly influence each other. A breakthrough in the modeling and synthesis of natural patterns and structures was the recognition that nature is fractal [ 14 ].
A fractal is a group of shapes that describes irregular and fragmented patterns in nature, different from Euclidean geometric forms [ 20 ]. Other mathematical systems, as cellular automata, are both inspired by nature and can be used to modulate nature in silico , as some biological processes occur, or can be simulated, by them such as shell growth and patterns, neurons and fibroblast interaction [ 21 ] [ 22 ]. Another computational model of nature is the Lindenmayer-system or L-system , which is used to model the growth process of plant development [ 23 ].
A major step towards the creation of artificial life was recently achieved by Karr et al [ 24 ]. This group reports a whole-cell computational model of the life cycle of the human pathogen Mycoplasma genitalium that includes all of its molecular components and their interactions. This model provides new insight into the in vivo rates of protein-DNA association and an inverse relationship between the durations of DNA replication initiation and replication.
Moreover, model predictions led to experiments which identified previously undetected kinetic parameters and biological functions. Engineering ideas behind silicon computers can be applied to engineering with natural materials in order to gain control over biological systems. This concept started to emerge in the s when Sugita published ground breaking theoretical work where he performed a functional analysis of chemical systems in vivo using a logical circuit equivalent [ 25 ] [ 26 ].
He discussed the idea of a molecular automaton, the molecular biological interpretation of the self-reproducing automata theory, and the chemico-physical interpretation of information in biological systems [ 27 ] [ 28 ]. Sugita made analogies between an enzymatic cascade and logic, values and concentrations, and interactions and circuit wires. The emerging field of synthetic biology has contributed with novel engineering concepts for biological systems [ 29 ] [ 30 ].
Another engineering principle, abstraction hierarchy, deals with the question of how standardized parts build a complex system. Systems systemics are another important engineering paradigm dealing with complexity [ 9 ] [ 33 ]. A system is a set of interacting or independent components forming an integrated whole. Common characteristics of a system are: components, behaviors and interconnectivity. Systems have a structure defined by components. Systems behavior involves input, processing and output of data.
Behavior can be described with terms such as self-organizing, dynamic, static, chaotic, strange attractor, adaptive. Systems have interconnectivity. This means that the parts of the system have functional as well as structural relationships between each other. This kind of thinking represents a move form molecular to modular biology [ 34 ]. The challenge is to define the hierarchical abstraction for such a modular system for biocomputers, and finally actually build such a system.
A breakthrough paper was published in by Leonard Adleman [ 35 ]. For the first time a biocomputer, based on DNA, was built. This system was able to solve a complex, combinatorial mathematical problem, the directed Hamiltonian path problem. This problem is in principle similar to the following: Imagine you wish to visit 7 cities connected by a set of roads.
How can you do this by stopping in each city only once? The solution of this problem, a directed graph was encoded in molecules of DNA. Other papers using DNA computing for solving mathematical problems followed [ 36 ]. Adelman's paper basically kick started the field of biological computers reviewed in [ 17 ] [ 18 ] [ 37 ] [ 38 ] [ 39 ]. A system consists of defined components.
In order to build a biocomputer system, we need to identify these components and standardize them. Although important work is done in synthetic biology in respect to part standardization in general, for biocomputer parts this work is so far rudimentary.
Thus, we will try in the following to identify and classify them. DNA based parts and their application in biocomputing. Representative references are provided. Cell to cell communication based parts and their application in biocomputing. The natural function of DNA is to store hereditary information and regulate the expression of this information [ 40 ].
Following the Adelman paper a wide range of DNA properties suitable for computing were explored. DNA may serve either as a principal structural component, or as a mediator that arranges tethered ligands or particles [ 40 ]. Structural properties of the DNA as the order of nucleotides, recombinational behaviors, self-assembly due to Watson-Crick base paring and storage of free energy have been used for different aspects of computational systems see Table 1.
Nucleotide sequence: The order of nucleotides within a DNA molecule can be used to store information [ 41 ] [ 42 ] [ 43 ] [ 44 ] [ 45 ]. DNA recombination: Recombinational DNA behavior, allowed by specified classes of enzymatic activities, has been described in terms of the formal language theory, a branch of theoretical computer science [ 46 ]. The associated language consists of strings of symbols that represent the primary structures of the DNA molecules that may potentially arise from the original set of DNA molecules under the given enzymatic activities.
Moreover, DNA recombination has been used to [ 47 ] solve a mathematical problem: sorting a stack of distinct objects genetic elements into proper order and orientation site-specific DNA recombination using the minimum number of manipulations [ 47 ].
Self-assembly: DNA can self-assemble through Watson-Crick base pairing to produce an arrangement of tiles shapes that covers the plane [ 48 ]. Computation by tiling is universal, because tiles and matching rules can be designed so that the tilings formed, correspond to a simulation of that device [ 49 ].
This was e. Chemically, the value of a tile, 0 or 1, is denoted by the presence of a restriction site eg Pvu II represents 0, false and EcoR V represents 1, true. Each molecular tile contains a reporter strand in order to extract the answer after self-assembly occurred.
Big Data Reduction Methods: A Survey
Not a MyNAP member yet? Register for a free account to start saving and receiving special member only perks. Among the more significant events in the recent history of long-distance communication have been the building of computer-based communication networks and the development of technologies that have made possible the implementation and exploitation of these networks.
With our high-performance computing solutions, we revolutionize data centers, servers and many other industrial applications by adding more and costefficient computing power, therefore improving the infrastructure. Please send me product and company news via e-mail in the future. For deep learning applications, a single-root complex can use all GPU clusters to focus on large learning processes and the CPU for smaller tasks. For machine-learning, a dual-root complex can assign more tasks to the CPUs and arrange less distributed learning between GPUs.
Computing with biological switches and clocks
A digital network is a transportation system for information. In this network, an "edge" is comprised of servers extended as far out as possible, to reduce the time it takes for users to be expediently served. There are two possible strategies at work here:. In the context of edge computing , the edge is the location on the planet where processors may deliver functionality to customers most expediently. Depending on the application, when one strategy or the other is employed, these processors may end up on one end of the network or the other. Because the Internet isn't built like the old telephone network, "closer" in terms of routing expediency is not necessarily closer in geographical distance. And depending upon how many different types of service providers your organization has contracted with -- public cloud applications providers SaaS , apps platform providers PaaS , leased infrastructure providers IaaS , content delivery networks -- there may be multiple tracts of IT real estate vying to be "the edge" at any one time. The future of both the communications and computing markets may depend on how those points on the geographical map, and the points on the network map, are finally interfaced. Where those points reside, especially as 5G Wireless networks are being built, may end up determining who gets to control them, and who gets to regulate them. There are three places most enterprises tend to deploy and manage their applications and services:.
Computer technology and automated systems have already become an integral part of our society. It is impossible to imagine our lives without smartphones with plenty different applications, PCs, and supercomputers that can beat a person in chess or help us investigate the outer space. Specialists of this sector can develop computer technologies and systems and introduce these developments into various areas of human activities. Such specialists create controllers that help factory machines work, provide elevator control systems to tall buildings, develop control systems for aerospace machinery and robots. With the constant need in new software comes the growing need in the professionals capable of working with it.
The 21st century has seen a number of advancements in technology, including the use of high performance computing. Computing resources are being used by the science and economy fields for data processing, simulation, and modeling. These innovations aid in the support of production, logistics, and mobility processes.
Complex event processing
Product suites, which combine IBM Spectrum Protect with related products, can be an easier way to buy and manage software. The suites include products that can satisfy a range of data protection and recovery requirements, with simplified licensing. The server and backup-archive client components provide basic functions such as backup and restore operations, and archive and retrieve operations for files, directories, and disk images. The product family also includes the products that are listed in the following table.
Moe-Behrens GHG The biological microprocessor, or how to build a computer with biological parts. Computational and Structural Biotechnology Journal. Systemics, a revolutionary paradigm shift in scientific thinking, with applications in systems biology, and synthetic biology, have led to the idea of using silicon computers and their engineering principles as a blueprint for the engineering of a similar machine made from biological parts. Here we describe these building blocks and how they can be assembled to a general purpose computer system, a biological microprocessor. A biocomputer can be used to monitor and control a biological system.
Product family and related products
This is a list of distributed computing and grid computing projects. For each project, donors volunteer computing time from personal computers to a specific cause. While distributed computing functions by dividing a complex problem among diverse and independent computer systems and then combine the result, grid computing works by utilizing a network of large pools of high-powered computing resources. Subprojects also include Seventeen or Bust , and the Riesel problem. These projects attempt to make large physical computation infrastructures available for researchers to use:.
Working on problems that are directly relevant to industry, our faculty are advancing the state of the art in cloud computing and systems for big data, software defined networks, wired and datacenter networking, Internet of Things, wearable computing, mobile computing, multimedia systems, security, privacy, health-care engineering systems, and cyber-physical systems. Our research has also resulted in the creation of several startup companies. We produce creative and innovative students who become faculty at top-ranked schools, researchers at prestigious labs, and who join cutting-edge companies. Tarek Abdelzaher and Timothy M.
Escalation of information system role in provision of enterprise and organization business processes leads to growth of risks connected to unavailability of data and information services vital for the main business processes. The business continuity and performance directly depends on availability of the enterprise information system. Availability of data and information services depends on reliability of all information system elements and organization of their interaction but not limited to it: information system availability level can be influenced by errors or malevolent attacks of users and external factors such as man-made disasters, natural disasters, etc.
Event processing is a method of tracking and analyzing processing streams of information data about things that happen events ,  and deriving a conclusion from them. Complex event processing , or CEP , consists of a set of concepts and techniques developed in the early s for processing real-time events and extracting information from event streams as they arrive. The goal of complex event processing is to identify meaningful events such as opportunities or threats  in real-time situations and respond to them as quickly as possible. These events may be happening across the various layers of an organization as sales leads, orders or customer service calls.
Natural Computing. The complex dynamics of biological systems is primarily driven by molecular interactions that underpin the regulatory networks of cells. These networks typically contain positive and negative feedback loops, which are responsible for switch-like and oscillatory dynamics, respectively. Many computing systems rely on switches and clocks as computational modules.
A complex system is an arrangement of a great number of related but various elements with intricate relationships and interconnections. Complex systems typically have input from many sources and are highly changeable. In the physical world, the earth's weather is one example of a complex system. Chaos theory deals with the apparent lack of order and predictability in complex systems. Chaos, in this context, refers to an apparent lack of order in a system that nevertheless obeys particular laws or rules. Please check the box if you want to proceed.
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