A Hybrid Cloud Computing Approach for Managing Spatial Data: A Case Study for Water Resources in Greece

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1 2014 Fifth International Conference on Computing for Geospatial Research and Application A Hybrid Cloud Computing Approach for Managing Spatial Data: A Case Study for Water Resources in Greece Dimitrios Kallergis 1, Chrysoula Papacharalampou 2, Konstantinos Chimos 1, Thomas Chavakis 1, Christos Douligeris 1 1 Dept. of Informatics 2 Dept. of Mechanical Engineering University of Piraeus University of Bath Piraeus, Greece Bath, UK {D.Kallergis, himosk, mpsp12088, Abstract Global challenges and technology advancements have driven researchers and professionals to demand new tools for solving complex problems in terms of massive data exploitation. This paper describes a system that offers 3D visualisation of data with spatial interest regarding the management of water resources. he Software as a Service (SaaS) delivery is instrumented by a hybrid cloud implementation. public cloud is used for a web service that accommodates the database system and the network traffic load provisioning, whilst a private cloud serves the rest of the web service, along with a custom metering service regarding the hybrid cloud s overall performance. In the context of this work, the geospatial data are exploited similarly to those which will be offered by governmental authorities in Greece conforming to European and National Laws and provide Web Mapping Services through open-access data repositories. Since these data storage solutions are still in an on-going progress, this paper works with private data gathered from professionals in the field of Earth Sciences. The resulted service provides seamless access to the geospatial data which are presented in a 3D web platform. Keywords cloud computing; spatial data; web-mapping services; SaaS; Earth Science I. INTRODUCTION Current implementations on the Cloud offer large-scale developments which utilise a wide range of tools and interconnected applications, overcoming the technological limitations of the Geographical Information Systems (GIS). GIS allow for information mapping and processing and assist decision-making by interrelating spatial and non-spatial data [1]. Similar projects within the EU aim to employ cloud-based infrastructures coupled with the necessary services to provide seamless access to geospatial public sector information [2]. In the context of this study, spatial data are presented in a three dimensional (3D) space through an object-oriented web application using a cloud computing architecture. In particular, we employ private raw data gathered from boreholes of a given geographical location in Greece. Moreover, we plot and visualise them according to the standards and restrictions which are described by the scientists of the relevant field. The users of the application, which is provided by the as a service model, are able to select a geographic region of the country and browse among the geo-referenced boreholes. Then, taking advantage of the three-dimensional representation, they visualise information regarding both the technical elements of the boreholes (depth of drilling, pipes etc.), as well as the aquifers. We use object-oriented tools for code development and customised software methods for visualising geographical information. In a proof of concept implementation, we employ the public cloud computing infrastructure provided by the Greek National Research and Technology Network and then deploy a hybrid Cloud for accommodating sensitive data. The results of the presented work could be classified as interdisciplinary, since we manage to collect, interpret and exploit data related to the broader water sector (environment, economy, infrastructure, society and law) and the application development is designed to approach not only existing but also future challenges associated with water at a systemic level (e.g. watersheds). This paper is organised as follows: Section II presents related work, while section III describes the method followed for the 3D representation of spatial data regarding groundwater resources, in addition to the cloud infrastructure that delivers our service. Section IV concludes this paper. II. RELATED WORK Our implementation addresses the issue of efficiently accessing disparate data repositories (Spatial Data Infrastructure - SDI) and aims to provide mapping services (Web Mapping Services - WMS) to users from both fixed and mobile devices. In the case of mobile users, the specification of service location (Location Based Services LBS) is attempted, /14 $ IEEE DOI /COM.Geo

2 while these users can participate in an ad hoc cloud computing infrastructure in terms of partially providing resources from their devices. Similar applications for the visualisation of geological and spatial data have been reported in the governmental sector [3] as well as in academia [4]. However, these projects represent information in two dimensions. Significant research activity is already being listed towards the use of these technologies in various scientific fields, such as crime recording, disease cluster analysis, and land and water resources management. Novel 3D GIS-based tools and models for an adequate water resources management have been recently developed in the Mediterranean region [5],[6]. Both models are focusing on the groundwater resources, aiming not only to visualize the subterranean environment and the spatial differentiation of aquifers and sedimentary media, but also to identify zones of risk, in terms of pollution or water shortage. These studies highlight the importance of usable geological data, in the sense that larger amounts of included data will result in more realistic models. The 3D models serve as valuable tools, because they provide an original feeling of the natural world and overcome the problem of an abstract symbolic system, such as the ones provided by simple GIS implementations. Hence, the threedimensional representation meet current demands for management, analysis, estimation, decision and visualization, especially in emergency services [7]. The authors in [7],[8] propose the use of 3D GIS in flood modelling by revealing the phenomenon and its dynamic changes in real world. Their method aims to make quick and correct decisions on describing the physical phenomena featured by mass and real-time data in water resources objectively and quickly. The large volume of data, their dispersed character and the need for complex visualisation tools are the main motives that trigger researchers and companies to adopt the cloud computing infrastructure, with its mobile extensions. This late approach aims to ease access for end users [9]. The implementation of distributed repositories using a cloud infrastructure (SDI) results from the evolution of the Grid and has become the dominant emerging trend, due to the vast amount of existing data [10]. Similar efforts have also been made to assist in the dissemination of research results that utilise big data using commercial licensed software [11]. The need for greater intensity in the data volume (i.e. Big Data), the computational power of the systems and the simultaneous access from different locations, leads the scientific community to novel implementations of spatial data on cloud computing (Spatial Cloud Computing - SCC). The realisations are intended to exploit the comparative advantages in terms of flexibility and decision support [12]. Moreover, the existence of implementations and synergetic approaches in 3D modelling in the Cloud should be mentioned as well [13]. However, the network traffic load balancing constitutes a cornerstone of distributed systems infrastructure. Considering that the Clouds is the evolution of these systems, methods for {a} lower costing operating systems, {b} the fastest possible access to large volumes of data, {c} the optimal use of computing power and {d} the higher user satisfaction have been implemented, tested and evaluated [14],[15],[16], [17]. III. METHOD Complying with the requirements of European Directives [18],[19] and the existing Greek legislation [20],[21] we aim to introduce an implementation that will easily be used as a tool for the integrated management of groundwater and surface water bodies at the watershed level. The 3D representation of the spatial extent and the vertical distribution of aquifers, in conjunction with the existing quantitative and qualitative data on groundwater, contributes to a more complete knowledge of the hydrological regime of each catchment, since it allows the input and display of real heterogeneous hydrological elements which assemble a complete and realistic picture of a given natural system. For the purpose of the presented work, we assume that similar data could be retrieved from the database of National Boreholes Registry 1,2 ; an on-going project which is funded by the EU Sectoral Operational Program Environment & Sustainable Development and managed by the Special Secretariat for Water of the Greek Ministry of Environment, Energy & Climate Change. The data from the aforementioned boreholes registry will integrate to open-access databases, such as Open Public Data [22] and Greek Open Data Registry [23]. We exploit these two paradigms in terms of emulating data formatting and accessing by our web service. A. The 3D representation of spatial data regarding water resources The production of the 3D Digital Elevation Model (DEM) can be a result of different implementation paths. In this paper, we convert raster-based data to ASCII files using an openaccess software platform for spatial data. Particularly, we convert them into heightmap images in order to produce the 3D terrain. Figure 1 depicts the three-dimensional surface representation of a given area in Greece. Figure 1. Thrace region, North-Eastern Greece 1 Special Secretary Decision 1042/ Greek Ministry of Environment, Energy & Climate Change, Special Secretariat of Water. 2 Special Secretary Decision / Greek Ministry of Environment, Energy & Climate Change, Special Secretariat of Water. %CE%A9%CE%91%CE%A3 34

3 Our auxiliary custom standalone application aligns the produced terrain while checking the stable pairs of the geographic coordinates. The geo-referencing of the terrain within the 3D graphics engine completes using the DEM of the country, according to the Greek Geodetic Reference System GGRS 87 [24]. This alignment process is implemented according to the aforementioned GRS, aiming to represent each inserted pair of coordinates in the right position. This classification procedure is mandatory because of the importance of the sequential order and direction of the coordinates. Regarding the interconnection between boreholes, a joint use of a custom classification algorithm and a triangulation algorithm [25],[26] of successive points is required. During this process, we calculate the distance between two successive pairs of coordinates; i.e. two successive boreholes sites. Using the calculated data, the triangulation algorithm produces the polygon mesh; i.e. the aquifers. Subsequently, the relative angle between two 3D points is also calculated and hence a dynamically generated grid between them. The final representation of the borehole objects is implemented by scripting an open-source part of a 3D crossplatform engine. Our approach constitutes an experimental method, since the existing variety of triangulation algorithms can lead to different results. Figure 2 illustrates a typical view of our 3D environment. exist. The lighter colour in the vertical line (pipeline) at the border of the shape represents a drifting filter used during the geotechnical process. Figure 3. The triangulation method succeeds with points connection in different angles B. The Cloud The individual sub-systems are deployed on the public cloud infrastructure of the Greek Research and Technology Network 3, aiming to provide the Software as a Service (SaaS) delivery. In order to ensure durability of our service under high demand conditions, we use multiple virtual machines for the 3D visualisation and the geospatial data management. The optimisation of the service delivery requires the servers assessment; i.e. load balancing in the Cloud, by customising and metering their utilisation. Figure 4 illustrates the implementation of our system s infrastructure. Private Cloud Hybrid Cloud Figure 2. Groundwater visualisation in three dimensions As Figure 2 depicts, we manage to plot groundwater (blue), rock type material (dark brown) and bedrock (light brown) in three dimensions space. Additionally, we offer information regarding {a} the borehole s coordinates (Lat., Long.), {b} total depth in meters, {c} water supply in m 3 /h, {d} current coordinated position (X, Y) of the 3D camera. The metrics named GB1 and GB2 are not used here. The triangulation method succeeds in excessive distances within the polygon mesh without producing critical errors in the 3D visual. Additionally, Figure 3 illustrates a closer view of the pipeline, the aquifer and the confined layers (rock material). The ear clipping triangulation method succeeds in producing the mesh of polygons (visualisation of groundwater and rock material) in the cases with different angles in points connection; i.e. no empty spots within the mesh of polygons Public Cloud Figure 4. Hybrid cloud infrastructure exploits spatial data in 3D representation We employ multiple instances of NGinX servers for the 3D representation through the Web and instances of MySQL servers for the spatial database. A load balancing implementation of the NGinX is also used for handling 3 ~Okeanos project, https://okeanos.grnet.gr 35

4 considerable amount of network traffic towards the servers which offer the 3D visualisation. The load balancer, along with most of the 3D-web servers, is deployed in the public cloud; the spatial database lives there, as well. The private cloud environment, which is deployed in the university campus, consists of some instances of the 3Dweb along with a custom metering service that collects data for a further statistical assessment of our service. Apart from the metering service, all other components construct a hybrid cloud environment. We implement this architecture to securely manage our measurements regarding the service and users sensitive data. IV. CONCLUSIONS AND FUTURE WORK The 3D application which is offered as a service presented in this work identifies the spatial differentiation of the aquifers within the boundaries of a catchment. As we aimed to achieve a more accurate assessment regarding the groundwater quantity, spatial distribution and quality, it is essential to use and visualise information regarding the subterranean environment of each catchment. This process is critical for natural resources protection by human activity, as well as the facilitation of new infrastructure construction. Moreover, our study highlighted the importance of usable geological data, in the sense that larger amounts of included data will result in more realistic models. The combined use and 3D depiction of geological and piezomatric maps, data from hydraulic tests and water analyses, as well as stratigraphic and geophysical logs should allow to achieve a more accurate assessment about the quantity of groundwater hosted in the aquifers, to identify the type of rock formations that function as aquifers and to observe changes occurring in protected areas or risk zones. This future perspective of our work highlights the importance of reliable and real data from various scientific fields, as mentioned in recent works [5], [6]. It also stresses the current need to discuss the kind of data required and their specifications, in terms of scale or frequency of measurements with geological interest. The outspread of our cloud infrastructure will leverage the cooperation among researchers and professionals supporting massively distributed and concurrent end-users requests. The private clouds will accommodate in-house repositories for sensitive data regarding the service access measurements or policy-restricted access between regional authorities towards a global collaboration convergence. The public cloud will provide spatial data storages in large volumes. Hence, the query process of Big Data (e.g. spatial data regarding locationbased access to the service, massively stored information for natural phenomena, etc.) is a challenge for further study using state-of-the-art cloud management techniques through spatiotemporal event handling. Regarding the georeferenced data, we will offer an intelligent method for visualising the rock material synthesis and the water chemicals in 3D space. This will allow researchers and professionals to methodologically investigate and evaluate critical circumstances related to physical phenomena. In more detail, in citu computing machinery (e.g. robotics) may be used in order to stream real-time information to the geospatial database. The Cloud infrastructure will accommodate connections to numerous spatial databases and thus provide a Web Mapping System in the three-dimensional space. ACKNOWLEDGMENT The authors sincerely thank Christos K. Papacharalampos for making available the boreholes' data of the study area. REFERENCES [1] Muzafar A. et al. (2011). Cloud Computing: A solution to Geographical Information Systems (GIS), International Journal on Computer Science and Engineering (IJCSE), 3 (2). ISSN: [2] InGeoClouds Project. Inspired Geodata Cloud Services project, Cofunded by the European Commission under the Information and Communication Technologies Policy Support Programme Area: CIP - ICT - PSP Towards a cloud of public service. [online] Available at: [Accessed: 13 April 2014] [3] swisstopo. Geographical reference data for the Federal Dept. of Defence, Civil Protection and Sport of the Swiss Confederation. [online] Available at: [Accessed: 13 April 2014] [4] Hydroscope. National Hydrological and Meteorological Database. [online] Available at: [Accessed: 13 April 2014] [5] Carreno F., Garcia-Martinez C.S., Ramos J.L., Fernandez M., Mabeth- Montoya Colonia R. (2014). Building a 3D geomodel for water resources management: case study in the Regional Park of the lower courses of Manzanares and Jarama Rivers (Madrid, Spain). Environmental Earth Sciences, 71 (1), pp [6] Velasco V., et al. (2013). The use of GIS-based 3D geological tools to improve hydrogeological models of sedimentary media in an urban environment. Environmental Earth Sciences, 68 (2), pp [7] Li R., Sao T., Li G. (2011). Research on Three-dimensional Water Resources Information System Based on ArcGIS. IEEE International Symposium on Water Resource and Environmental Protection (ISWREP2011), May, Xi'an, Shaanxi Province, China, pp [8] Li R., Sao T., Li G. (2011). Application of Three-dimensional GIS to Water Resources, 19th International Conference on Geoinformatics, June, Shanghai, China, pp [9] Lu Y., Mingjin Z. Li T., Yudong G., Naphtali R. (2013). Online Spatial Data Analysis and Visualization System, Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA '13), Horng D., Vreeken J., Van Leeuwen M., and Faloutsos C. (Eds.). ACM, New York, USA, pp [10] Schäffer, B., Baranski, B., Foerster, T. (2010). Towards Spatial Data Infrastructures in the Clouds, In: M. Painho, M. Santos, & H. Pundt (Eds.), Geospatial Thinking. Berlin: Springer Verlag, pp [11] Humphrey M., et al. (2013). CloudDRN: A Lightweight, End-to-End System for Sharing Distributed Research Data in the Cloud International Conference on e-science, Oct., pp [12] Yang C., et al. (2011). Spatial cloud computing: how can the geospatial sciences use and help shape cloud computing?, International Journal of Digital Earth, 4 (4), pp England: Taylor & Francis. [13] Pisu C. and Casu P. (2013). Cloud GIS and 3D Modelling to Enhance Sardinian Late Gothic Architectural Heritage, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-5 (W2), pp [14] Swarkar N. and Shankar R. (2013). A Survey of Load Balancing Techniques in Cloud Computing, International Journal of Engineering Research & Technology (IJERT), 2(8), Aug [15] Arshdeep B. and Madisetti V. (2013). Performance Evaluation Approach for Multi-Tier Cloud Applications, Journal of Software Engineering and Applications (JSEA), vol. 6, pp , [16] Martin R., Lamb D., Taleb-Bendiab A. (2010). A Comparative Study into Distributed Load Balancing Algorithms for Cloud Computing, IEEE 24th International Conference on Advanced Information Networking and Applications Workshops (WAINA), 23 Apr., pp. 551,

5 [17] Piorkowski A., Kempny A., Hajduk A., Strzelczyk J. (2010). Load Balancing for Heterogeneous Web Servers, Trendz in Information Sciences & Computing (TISC), Dec., pp [18] European Commission (2000). Directive 2000/60/EC of the European Parliament of the Council of the 23rd October 2000 establishing a framework for community action in the field of water policy, Official Journal of the European Communities, L327/1, Luxembourg. [19] European Commission (2006). Directive 2006/118/EC of the European Parliament of the Council of the 12nd December 2006 regarding the protection of groundwater against pollution and deterioration, Official Journal of the European Communities, L372/19, Luxemburg. [20] Law 3199/2003. Protection and water management: Transpose of the 2000/60/EC Directive of the European Parliament of the Council of the 23rd October 2000 (Govern. Gazette A 280/ ). [21] Ministerial Decision 39626/2208/ 130/2009. Measurements determination for the protection of groundwater against pollution and deterioration in transposing of the 2006/118/EC Directive of the European Parliament of the Council of the 23rd October 2000 (Govern. Gazette B 2075/ ). [22] Geodata.gov.gr. Greek Government open data repository for the provision of geospatial information. [online] Available at: [Accessed: 13 April 2014] [23] Greek Linked Open Data Cloud. Greek sector of the Open Knowledge Foundation (OKFN). [online] Available at: [Accessed: 13 April 2014] [24] Syggros I. (2004). Transformation of Coordinates for Geographical Data in Greece, 3 rd Pan-Hellenic Conference of Hellenic Corporation for GIS Systems (HellasGI), March. [25] Hartley R. and Sturm P. (1997), Triangulation, Computer Vision and Image Understanding, 68(2). pp [26] Eberly D. (2008). Triangulation by Ear Clipping, Geometric Tools LLC. [online] Available at: [Accessed: 13 April 2014] 37

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