Section VII: Informatics and Control in Engineering Systems CLOUD TECHNOLOGY: OVERVIEW OF DATABASES AS SERVICE PROVIDING SYSTEMS ON THE BASE OF XEROUND, RDS AND SQL AZURE Yeleu Y.A. Scientific supervisor: Botygin I.A., associate professor Language supervisor: Pichugova I.L., senior teacher Tomsk Polytechnic University, 30, Lenin Avenue, Tomsk, 634050, Russia E-mail: [email protected] is the delivery provisioning often appear to be unlimited and can of computing as a service rather than a product, be appropriated in any quantity at any time. whereby shared resources, software, and 3. On-demand self-service. A consumer can information are provided to computers and other unilaterally get computing capabilities, such as devices as a metered service over server time and network storage, as needed a network (typically the Internet). [1] Cloud automatically without requiring human interaction computing is a model for delivering information with each service provider. technology services where resources are retrieved 4. Broad network access. Capabilities are available from the Internet through web-based tools and over the network and accessed through standard applications, rather than a direct connection to a mechanisms that promote use by heterogeneous server. Data and software packages are stored in thin or thick client platforms (e.g., mobile phones, servers. However, cloud computing structure tablets, laptops, and workstations). allows access to information as long as an 5. Economy of the process.Measured service is electronic device has access to the web. This type used in cloud technology. Cloud systems of system allows employees to work remotely. [2] automatically control and optimize resource use by There is a more common definition. Cloud leveraging a metering capability at some level of computing is a general term for anything that abstraction appropriate to the type of service (e.g., involves delivering hosted services over the storage, processing, bandwidth, and active user Internet. The problem is that everyone has different accounts). Resource usage can be monitored, definition of cloud computing. This is caused by controlled, and reported, providing transparency for high functionality of this technology. But the most both the provider and consumer of the utilized accurate definition is given by Peter Melland service. Timothy Grance from National Institute of There are four deployment models of cloud Standards and Technology (USA): ‘Cloud computing. computing is a model for enabling ubiquitous, 1. Private cloud is infrastructure operated solely for convenient, on-demand network access to a a single organization, whether managed internally shared pool of configurable computing resources or by a third-party and hosted internally or (e.g., networks, servers, storage, applications, and externally. [1] Private cloud functions on a private services) that can be rapidly provisioned and network. It is highly secure released with minimal management effort or 2. Public cloudis one based on the standard cloud service provider interaction’. computing model, in which a service provider General Director of Ltd “EMC Information makes resources, such as applications and Systems CIS” Sergey Karpov said: ‘Cloud storage, available to the general public over the computing is in one sense the evolution of entire IT Internet. Public cloud services may be free or industry in general’. He identifies five offered on a pay-per-usage model. [4] It may be characteristics of cloud computing. owned, managed, and operated by an academic, 1. Resource pooling. The provider’s computing government, or business organization. It exists on resources are pooled to serve multiple consumers the premises of the cloud provider.This type of using a multi-tenant model, with different physical deployment model offers the highest level of and virtual resources dynamically assigned and efficiency. reassigned according to consumer’s demand. 3. Community cloud shares infrastructure between There is a sense of location independence in that several organizations from a specific community the customer generally has no control or with common concerns (security, compliance, knowledge over the exact location of the provided jurisdiction, etc.), whether managed internally or by resources but he may be able to specify location at a third-party and hosted internally or externally. a higher level of abstraction (e.g., country, state, The costs are spread over fewer users than a datacenter). Resources include storage, public cloud (but more than a private cloud), so processing, memory, network bandwidth. only some of the cost savings potential of cloud 2. Dynamics and flexibility. Capabilities can be computing are realized. [1] elastically provisioned and released, in some 4. Hybrid cloud is a composition of two or more cases automatically, to scale rapidly outward and clouds (private, community, or public) that remain inward commensurate with demand. To the unique entities but are bound together, offering the consumer, the capabilities available for benefits of multiple deployment models. It can also 97

XVIII Modern Technique and Technologies 2012 be defined as multiple cloud systems that are DaaS is a managed service, offered on a pay- connected in a way that allows programs and data per-usage basis that provides on-demand access to be moved easily from one deployment system to to a database for the storage of application data. another. [1] This deployment model provides The most popular DaaSs today are SQL Azure, increased efficiency. Amazon RDS and Xeround. All of them There are three service models of cloud arehighlyavailable and scalable computing: IaaS, PaaS, SaaS.[3] services built on SQL Server technologies. 1. By using IaaS model organizations get SQL Azure is a product of Microsoft.It supports infrastructure components: storage capacity, up to a 150 GB maximum size T-SQL-based computing power networks, and other fundamental relational database. Customers are billed based on computing resources where the consumer is able the peak database size in a day. SQL Azure to deploy and run arbitrary software which can Database is charged as a monthly fee for each include operating systems and applications.The database, but that database fee is amortized over consumer has control over operating systems, the month and charged on a daily basis. For storage, and deployed applications and possibly databases greater than 1 GB, you will be billed in limited control of select networking components but the next whole gigabyte increment. But it is very he does not control the underlying cloud expensive to use SQL Azure (1GB≈10$ per month) infrastructure. However, consumer organizations and there are problems with transferability of DB in need to hire the addition staff to manage and cloud from local host. maintain the infrastructure and applications. Key differentiators between Xeround and 2. PaaS model provides organizations with Amazon RDS are as following: platforms or runtime environment to create and 1. Rule-based Auto Scale up & down with no deploy applications. Consumer organization is only downtime vs. Amazon RDS manual scaling with responsible for management, maintenance and down time; development of the applications, butit does not 2. Pay per actual usage vs. pay per instance size, manage or control the underlying cloud resulting in over subscription; infrastructure including network, servers, operating 3. Xeround never fails – even when Amazon’s systems, or storage. instance fails. Xeround offers a highly available, 3. SaaS model. The capability provided to the self-healing, database, with no downtime. Amazon consumer is to use the provider’s applications RDS cannot guarantee downtime, both planned (4 running on a cloud infrastructure. The applications hour / week maintenance) and unplanned are accessible from various client devices through 4. Unlimited database size vs. limited to Amazon either a thin client interface, such as a web RDS instance sizes; browser (e.g., web-based email), or a program 5. Database configuration does not require code interface. The consumer does not manage or changes to your application (replication, etc.); control the underlying cloud infrastructure including 6. Xeround offers up to 700% higher throughput network, servers, operating systems, storage, or and less than 1/10 the latency of RDS for heavy- even individual application capabilities, with the duty MySQL applications. [5] possible exception of limited user-specific When considering all the benefits of a true application configuration settings. [1] cloud database, coupled with competitive pricing, As cloud computing is achieving increased Xeround is the preferred choice of developers and popularity, concerns are being voiced about the businesses for their database application security issues introduced through adoption of this requirements in the cloud. new model. The effectiveness and efficiency of Summing up,it is possible to say that IT stops traditional protection mechanisms are being being a brake on business development due to reconsidered as the characteristics of this cloud technology. By purchasing cloud services by innovative deployment model that is widely Pay-As-You-Go basis companies can avoid capital different from those of traditional architectures. expenditures on additional infrastructure resources Microsoft Security trusted Advisor Bezmaly V.F. and instantly scale up or scale down according to who in his presentation on the subject of cloud their business requirements. security said that more than 3.500 virus signatures were made and more than 30.000 threats References appeared every day. He stressed the fact that use 1. "The NIST Definition of Cloud Computing". of cloud computing is much more secure. National Institute of Standards and Technology. One of the ways of using Cloud Technology is Retrieved 2012.02.09. to put your database in cloud. This is called 2. Investopedia. Definition of Cloud Computing. Database As a Service (DaaS). DaaS solves a lot [Electronic resource] Access mode: of problems of applications which work with http://www.investopedia.com/terms/c/cloud- database for example transplantability of this computing.asp#axzz1lqkCA07l.Retrieved: application and scalability of database (DB) 2012.02.09 especially for web applications. 3. Part 2 of 5 videos on Cloud Computing and Microsoft Offerings. [Electronic resource] Access

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Section VII: Informatics and Control in Engineering Systems mode:http://www.youtube.com/watch?v=uYGQcm 5. Xeround the Cloud Database. [Electronic ZUTaw&feature=related. Retrieved: 2012.02.09 resource] Access mode: Xeround.com/Cloud- 4."Defining "Cloud Services" and "Cloud database-comparison/. Retrieved: 2012.02.16. Computing"". IDC. 2008.09.23. Retrieved 2012.02.09

FEATURES OF THE NEURAL CONTROL SYSTEMS DESIGNING IN A NEURAL NETWORK TOOLBOX PACKAGE (MATLAB) V.A. Faerman, D.G. Nikiforov Scientific Superviser: M.S. Sukhodoev., Ph.D., associate professor Linguistic adviser: I.N. Kuznetsova Tomsk Polytechnic University, Russia, Tomsk, Lenin str., 30, 634034 E-mail: [email protected] Modern industrial processes connected with tissue research. Neurons in artificial network are producing or machining material, energetic and located in different layers and can be connected information flows have high demands on reliability with neurons in other layers as in biological and quality characteristics of control system built in prototype (Fig.1). Layers situated between input technical environment of these processes. The and output ones are usually called hidden. The absence of certainty in characteristics of control artificial neuron has bias (that determines object often has an impact on the quality of activation threshold) and any number of controlling the technological processes that can connections. Each connection has a coefficient lead to consumer properties deterioration that is (weight). Due to the huge number of connections unacceptable. That’s why at present the important (for example networks with 20 neurons located in 3 task is ensuring the stability in characteristics of layers can have thousand connections) selecting controlling processes, especially under conditions right weights and biases allows network to simulate of certainty induced by causes of various natures. a wide range of mathematical functions [1]. Ordinary types of controllers (like proportional (P), proportional – integral (PI), proportional – integral – derivative (PID)) are not usually efficient for solving this problem. On the contrary using of intellectual adaptive or optimal controllers potentially can satisfy the requirements for control processes quality [1]. To implement intellectual controllers Fig. 1. Multi-layer neural network fundamentally different algorithmic methods can be used that usually allow “transmitting” knowledge Modern controllers have enough memory and and experience in process control from operating computing power to implement the neural network specialist to control unit. Range of methods can be control. However, they are not equipped with the basis for the functioning of intellectual software (algorithmic blocks, procedures, etc.) controller. For example, it can be fuzzy logic focused on working with neural networks. This fact methods, methods of using neural networks, complicates the implementation and configuration application of genetic algorithms or various of the controller greatly. In order to save time combinations of these methods. Using of listed during design, controller training and evaluation of methods in programming controllers are often “soft neural network control system efficiency the – computing”. In opposite – stiff adjustment with modeling of the control system with computer- using ordinary control algorithms called “hard – aided design system is used [4]. One of the most computing”. These designations highlight the widespread instruments for neural networks and difference between ways of tuning controller – neural network controllers design is a Neural ability of operating with partial, inaccurate data [2]. Network Toolbox application in Matlab. One of the widespread ways of building Working with neural networks in Neural intellectual controllers is using of neural networks. Network Toolbox has several features This is explained by the fact that the multi-layer distinguishing it from working with structural neural networks are almost universal instrument for schemes of conventional control systems and from control signals generating [3]. Artificial neural working in specialized multidomain modeling network is a structure that consists of simple packages (SimPowerSystems, SimMechanics, computing units called artificial neurons. It was th etc.). There are three features of working with invented in the 20 century during the nervous Neural Network Toolbox: 99