2017 № 4 (37)

Razakova M.G. IDENTIFICATION AND MAPPING OF OIL CONTAMINATION OF SOILS USING REMOTE SENSING DATA
Tarhanova O.Y. APPLICATION OF WIRELESS SENSOR NETWORKS IN PRECISION AGRICULTURE
Perepelkin V.A., Sofronov I.V., Tkacheva A.A. AUTOMATED CONSTRUCTION OF PARALLEL NUMERICAL PROGRAMS WITH SPECIFIED NON-FUNCTIONAL PROPERTIES BASED ON COMPUTATIONAL MODELS
Feoktistov A.G., Sidorov I.F., Gorsky S.A. AUTOMATION OF DEVELOPMENT AND APPLICATION OF DISTRIBUTED APPLIED SOFTWARE PACKAGES

National Center of Space Research and Technology,050010, Almaty, Kazakhstan

IDENTIFICATION AND MAPPING OF OIL CONTAMINATION OF SOILS USING REMOTE SENSING DATA

UDC 528.852.1

Remote sensing can potentially provide important information for identifying contaminated sites, but there is a clear lack of specific approved approaches. In this study, Landsat 8, were used to monitor the spatial and temporal changes of the polluted surfaces at the Ozen oil field. Presently, the affected areas consist of disintegrated tarmacs, black soil and thin vegetation. The use of multisensor datasets provided the opportunity to observe the polluted areas in different wavelengths. The images were numerical enhanced to optimize the visual outlook and improve the information content to determine the surface contaminants. There are suggested the histogram method of tone correction became the basis of automation of objects gradation. In this paper, using Landsat 8 data from May 29, 2016 to the Ozen deposit region, the possibility of obtaining quantitative characteristics of oil contamination by automated decoding methods was considered.

The reflectivity of soils polluted with petroleum products was estimated. Was considered about fifteen contaminated sites of the oilfield zone (pipelines, oil wells, reservoirs, etc.). It was shown that, depending on the level of soil pollution with oil and oil products, the nature of the spectral reflection curve changes in comparison with the background soils, which is mapped by a decrease in reflectivity as the degree of pollution increases

The characteristics of the vegetation cover, the behavior of the soil cover, and the spectral indices in the places of oil spills were studied. In places of oil spills there is a release of toxic substances that, when ingested into the soil, can cause changes in its physico-chemical properties, lead to a decrease in the functional activity of microbiota of soil biocenoses. This effect alters the vegetation cover, which may serve as a sign for the detection of oil pollution using remote sensing data.

On the basis of the studied spectral brightness coefficients, the satellites data were indexed in order to compare the results obtained and to identify oil contamination on the Ozen deposit investigated region.

In connection with the natural features of the study area, i.e. the scarcity of vegetation cover, in conditions of predominance of wormwood-solonchak desert with areas of shrubby vegetation on brown soils: the surface is partially covered with solonchaks, takyr-like solonetzes and sands with extremely rare vegetation; it is necessary to conduct a series of studies to identify areas of actual contamination with oil products. What essentially complicates the task.

The soil in the area of spots is characterized by low values of the vegetative and soil indices. It can also be noted that more than 50 % of the Ozen deposit under study has low NDVI index values from -0.076-0.1. Despite the fact that the acquisition date of image was in the active vegetation season.

The analysis shows that the soil in the spot area is characterized by low values of the vegetative and soil indices. It can also be noted that the contrast of background and contaminated soils is more pronounced. Oil products are dark in tone and when they get onto a ground, they reduce the reflection.

Based on these parameters, a four-channel image was synthesized from the panchromatic channel, SWIR (short-wave infrared channel) and NDVI, SAVI maps. Oil pollution has a greater contrast in the 5-7 channels of Landsat 8 satellite data. In this composite version, with using unsupervised classification (7 classes), the areas of the industrial zone, oil pollution and infrastructure objects are clearly distinguished. Previously, the negative values of the NDVI index were filtered out, to exclude water objects. The indexed images and the short-wave Landsat 8 data channel were normalized relative to each other and synthesized into a three-channel image (RGB -- color model). In general, the calculation of soil and vegetation indices is only addition information to our study, the essence of which is to that parameters strengthen the feature and isolate space for the detection of oil contamination. The algorithm for increasing the gradient between oil contaminated sites and the background is consist in the sequential addition and combination of indexed channels and data in the short-wave infrared zone of the Landsat 8 data spectrum.

The conclusion. As a result of the work, a map of oil spills was created on the area of the Ozen field, which showed that a significant part of the territory is polluted with oil. An algorithm has been developed that makes it possible to apply automatic classification of oil contamination on the earth's surface. Satellite images were enhanced by methods of geoinformation technologies to optimize the information content of remote sensing data to recognition of oil contaminated soil.

Key words: oil contamination of soil, remote sensing.
References
1. Aliev S. A., Gadzhiev D. A. Vliyanie zagryazneniya neftyanym organicheskim veschestvom na aktivnost biologicheskikh processov pochv [Influence of Oil Organic Pollution on the Activity of Biological Soil Processes], Izv. AzSSR. Ser. biol. Nauk. 1977. N 2. P. 46-49 (in Russian).

2. Ammosova Ya. M., Golev M. Yu. Vliyanie neftyanogo zagryazneniya na spectralnuyu otrazhatelnuyu sposobnost dernovo-podzolistykh pochv [Influence of oil pollution on the spectral reflectivity of sod-podzolic soils] // Vestn. Moscow State University. Ser. 17. Pochvovedenie [agrology]. 1998. N 3. S. 31-34 (in Russian).

3. Roy, Waleed and Asem, Samira. Application of GIS for Mapping Oil-Contaminated Soil in Kuwait // AMCIS 2007 Proceedings. Paper 484. [Electron. Res.].: http://aisel.aisnet.org/amcis2007/484

4. Espinosa-Hernandez A., Galvan-Pineda J., Monsivais-Huertero A., Jimenez-Escalona J. C., Ramos-Rodriguez J. M. Delineation of hydrocarbon contaminated soils using optical and radar images in a coastal region // Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International, Melbourne, VIC, Australia. 21-26 July 2013. P. 676-679.

Bibliographic reference: Razakova M.G. Identification and mapping of oil contamination of soils using remote sensing data //journal “Problems of informatics”. 2017, № 4. P. 4-15.

article

Tarhanova O. Y.

Novosibirsk State University, 630090, Novosibirsk, Russia

APPLICATION OF WIRELESS SENSOR NETWORKS IN PRECISION AGRICULTURE

UDC 004.72

The paper gives an overview of the agricultural application of wireless sensor networks. It is one of the promising tools that allows to increase productivity per unit of resources expended andto ensure the reduction of unit cost of production.Nowadays, prices for seeds, fertilizers, equipment, plant protection products and other means of production in agriculture are rising. This leads to the need to improve the efficiency of their use.

The paper notes that wireless sensor networks (WSN) are currently developing intensively as an important segment of wireless networks and as the global Internet in general. This circumstance makes it possible to position technologies of WSN and the networks themselves as one of the system-forming components of the concept of internet-things and other technologies of digitalization of the agrarian sector, the constructive implementation of which in turn is a prerequisite for asecond green revolution -- transition to precision agriculture. The agricultural domain is studied with respect to the application of WSNs in improving the traditional methods of farming. The ubiquitous nature of work and self-organizing small-sized nodes make it possible to use WSN as a potential tool for achieving the goal of automation in agriculture.More attention is paid to one of the most importantagricultural areas -- precision agriculture.Precisionagriculturecan be considered as an integrated high-tech crop management system that takes into account the variability of the plant habitat in the field.This system provides advanced means of recording and collecting data for monitoring the technological process and evaluating performance, automation and intellectualization of decision-making.On the example of precision agriculture together with the WSN, the paper provides a list of other more commonly used basic tools (global positioning and geographic information systems, spatial information collection and satellite monitoring, remote sensing, data analysis, etc.).

It is emphasizedthat the miniaturization of electronic systems and development of wireless technologies contribute to the active implementation of the WSN. Modern technology can reduce the cost of miniature sensors with low power consumption and the possibility of extracting energy from the environment, while maintaining the required functionality. The WSNis characterized as a multi-node system where each node is an inexpensive device equipped with one or more sensors, a processor, a memory, a power supply and a transceiver. These nodes are able to perform preprogrammed algorithms, exchange data with other nodes and interact with the master node. The architecture of the sensor network depends on many factors, such as fault tolerance, working environment, scalability, production costs, hardware limitations, transmission facilities and power consumption. The paper deals with options for ground and underground wireless sensor networks, their opportunities for the development of various types of agriculture. In addition, there are discussed the sensor architectures and various sensors used in the applications. There are sensors that are used to record and control parameters such as temperature, humidity, soil moisture, soil acidity, barometric pressure and illumination, and other characteristics. The analysis of various variants of the classification of WSN architectures that are possible for agricultural application is given: a) relative to the movement of network devices and nodes (stationary, mobile and hybrid architectures); b) by the type of used sensory nodes and associated devices (homogeneous and heterogeneous architectures); c) by the type of hierarchy (single-level and multi-level architecture).

The paper gives a brief overview of wireless technologies and standards that can be applied in agriculture (ZigBee -- with network and application protocols based on IEEE 802.15.4 standards for wireless networks using low-power devices, WiMAX -- a wireless standard related to Interoperational implementations of the IEEE 802.16 family of standards and others).

The paper also analyzes the main characteristics of the WSN, which enabled them to become a potential instrument of automation in the field of agriculture: the intellectual ability to make decisions; configuration of dynamic topology; fault tolerance; contextual awareness; scalability; tolerance to communication failures in harsh environmental conditions, heterogeneity of nodes, autonomous operation.

The final section of paper examines the existing examples of the application of wireless sensor networks in the world for various agricultural needs.

Key words: wireless sensor network, precision agriculture, sensor nodes, architecture, monitoring, agricultural applications.

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article

Perepelkin V.A.*, Sofronov I.V., Tkacheva A.A.*

Institute of Computational Mathematics and Mathematical Geophysics SB RAS, 630090, Novosibirsk, Russian Federation

*Novosibirsk State University, 630090, Novosibirsk, Russian Federation

AUTOMATED CONSTRUCTION OF PARALLEL NUMERICAL PROGRAMS WITH SPECIFIED NON-FUNCTIONAL PROPERTIES BASED ON COMPUTATIONAL MODELS

UDC 00.004.4'24

Implementation of numerical algorithms as parallel programs for distributed memory multicomputers is a complex task, since the program not only has to contain the algorithm implemented, but also deals with a number of other problems of system parallel programming. Those are: organize parallel computational process, synchronize parallel threads and processes, perform communications, distribute and balance computational workload and more. Implementation of such static and dynamic properties of the program requires concerning peculiarities of both multicomputer and application algorithm, or even peculiarities of the input data. Development, debugging and modification of such a parallel program are extremely complex for scientists, who need to implement their numerical models. Moreover, the program also has to be efficient (in terms of computation time, memory consumption, etc.).

To overcome the complexity program construction automation can be useful. A programmer describes the algorithm in a high-level language, and the parallel program is constructed automatically by a programming system. In this case the complexity of parallel program development is hidden from programmer. This approach also allows constructing different parallel program for different multicomputers or input data, which is potentially, allows more efficient programs, than programs, developed for general case.

In this paper we assume, that an application algorithm is described in a high-level programming language, such as LuNA language. The description is functionally decomposed, i.e. consists of functions. Each function has a pre-defined finite number of modules that implement it. The modules differ in the non-functional properties respect (for example, they may have different execution time or memory consumption). These non-functional properties of the modules are considered known. The problem of parallel program construction is considered as the problem of choice of a module for each function. Since each module has different non-functional properties, the resulting program will also have different non-functional properties. The aim is to construct a program with desired non-functional properties.

The complexity of the problem is conditioned by the fact that the dependency between the assembled program's properties and the properties of the modules can be different for different applications or even input data. Therefore, it is important to have a general way of describing the revealed dependences and including them in some knowledge base in a form that allows their automatic usage. In this case, for various limited subject areas and classes of applied algorithms, it is possible to accumulate knowledge in such base. As a result, automatic construction of an acceptable quality program would be provided.

The main point of the proposed solution is to use the computational models (CMs) described in the theory of synthesis of parallel programs on the basis of computational models for organization of such a knowledge base. Information on how the initial description of the computational process is represented in the form of a set of functions, which modules are available for each function, and how the program is assembled from these modules, is described in the CM.

The practical application of the approach implies that the end user has no information about the CM, its composition and structure. Their role is limited to describing the computational process in a high-level language. The CM is described by the developer of the programming system. The algorithm of creating a set of acceptable modules from the CM and the construction of the program is fixed. The advantage of using the CM for solving the problem is the possibility to put in the CM a number of alternatives for designing the program. This leads to the possibility of automatic program construction in a wide range of non-functional properties required for different execution conditions.

To investigate the effectiveness of the proposed solution an explicit finite difference method for 3D Poisson equation solution was chosen as a test application. This problem was chosen as an example, because it has a typical parallel implementation scheme used for a wide class of numerical algorithms on meshes (spatial decomposition with border exchange). Within the framework of this test the one-dimensional spatial decomposition of the three-dimensional computational domain was used. Two series of experiments were conducted: in shared and distributed computing environment. The results demonstrated the desired ability of automated program construction with different non-functional properties, preferred for different execution conditions.

Key words: automated parallel programs synthesis, computational models, program auto-tuning, fragmented programming technology, fragmented programming system LuNA, code generation.

References

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Bibliographic reference: Perepelkin V.A., Sofronov I.V., Tkacheva A.A. Automated construction of parallel numerical programs with specified non-functional properties based on computational models //journal “Problems of informatics”. 2017, № 4. P. 47-60.

article

Feoktistov A.G., Sidorov I.F., Gorsky S.A.

Matrosov Institute for System Dynamics and Control Theory of SB RAS 664033, Irkutsk, Russia

AUTOMATION OF DEVELOPMENT AND APPLICATION OF DISTRIBUTED APPLIED SOFTWARE PACKAGES

UDC 004.4+519.6

We address relevant problems of constructing subject-oriented systems of modular programming (applied software packages) for solving large-scale problems in a heterogeneous distributed computing environment that integrates computational resources of a public access computer center where computational clusters are the main components.

Nowadays, the software that implements computational technologies in high-performance computing systems provides a potential foundation for the mass creation of parallel and distributed applications. However, the analysis of their application in practice makes it possible to detect the following important problems: the complexity of training and applying these tools by end-users (specialists in subject areas), which significantly narrows their number; insufficient support for taking into account the subject area specifics of the tasks being solved; difficulty in reconciling the determined criteria for the effectiveness of their solving (time, cost, security and other restrictions) and the required indicators of resource use (load balancing, reliability, energy consumption, etc.); lack of universal approaches to resource integration; the weak interconnecting of the created applications for data and management.In particular, the above-mentioned problems are actualized when solving tasks in a heterogeneous distributed computing environment, the main components of which are computational clusters, including hybrid clusters with heterogeneous nodes.

An actual approach to solving these problems is the development of distributed applied software packages. The development of distributed computing technologies actualizes the creation of new methods and tools that provide an efficiency degree increase of computational process management in such packages. To this end, we represent two toolkits for automating the creation and application of distributed applied software packages with multi-agent management of their computational jobs that is based on the integrated use of knowledge about both subject domains of tasks and the environment in which they are solved.

The package creation includes the following main stages: structural analysis of subject domains of tasks, conceptual model design for these domains, development of applied software libraries, configuring the system software of packages. The conceptual model describes parameters, operations over the parameter field, program modules (applied software) that realize the operations, computational nodes and other objects of subject domains and computational environment, and relationships between the objects. Thus, it includes several components of a comprehensive knowledge about the environment and subject domains. Using the conceptual model, users formulate their tasks in both procedural and non-procedural form, construct task solving plans and form computational jobs. The job describes the necessary requirements to the computational environment for solving the task. Represented toolkits provide both text and graphic mode of the conceptual model development.

A specialized meta-monitoring system collects information about the distributed computing environment and its resources. It processes and unifies this information. The knowledge thus obtained is transferred to the knowledge base. Package components can to use meta-monitoring system API for knowledge elicitation. The meta-monitoring system is also used for testing the environment nodes, collecting data about their current state, detecting node faults, and diagnosing and to partially repairing these faults.

The system software of packages includes high-level tools for the job management in both homogeneous clusters and heterogeneous distributed computing environment.We propose the task formulation and algorithm of multi-agent management of jobs. The management efficiency is achieved through the resource allocation on the basis of a computational work tender. It is base don a model of the Vickrey auction with one-round bidding. Agents applies the algorithm for the static resource allocation based on economic mechanisms for regulation of resources demand and supply.

The developed multi-agent system has a hierarchical structure, which includes two or more functional levels, and operates on the base of self-organization. At each level, agents play a variety of roles, and perform different functions. The roles may be permanent or temporal. Their changes occur at discrete times when agents need to solve new problems. Each level is related with the conceptual model knowledge layers.Agents can represent users and owners of the resources, and interact themselves with aim to meet their interests.Agents are autonomous, and computing management is based on their interaction. They can be organized in virtual communities. In these communities, agents interact using a cooperation or competition. The formation of virtual communities allows agents to adapt the management process to the new challenges.

The developed toolkits are used in the public access computer center Irkutsk supercomputer center of Siberian Branch of the Russian Academy of Science to develop distributed applied software packages for solving scientific and applied tasks from different subject domains. Examples of solving practical tasks illustrate study results. In particular, we design the distributed applied software package to support modeling of warehouse logistics. Using this package, we solved three optimization tasks for adjusting parameters of a warehouse management system. The practical experiments are focused on the refrigerated warehouse. The developed applications demonstrate high efficiency and scalability capabilities to optimize nine criteria to cope with different production demands.

Key words: distributed computing, modular programming, multi-agent management, toolkits.

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2017 № 4 (37)