Geo-Based Image Analysis Service In Open Source Cloud Computing Environment

Globally, cloud computing is one of huge trends in ICT communities, exerting its influence on the most information application fields including geo-spatial domain. In general, cloud computing services are being regarded as commercial or public internet data center or infrastructure of computing resources. However, there is no limitation for applications of cloud computing. Especially, it is on the early developing stage in geo-based applications. This project is to present a practical application for geo-based image processing and analysis on open source cloud environment. OpenStack Juno version was applied for open source cloud computing environment. On this cloud environment, PostgreSQL and Django were used as open source for metadata server and web framework, respectively. For geo-based image processing server, OTB was used with GDAL for image manipulating. Some image processing algorithms were implemented in this cloud environment, and provides as a web service for public users. Web-accessible users in this cloud service do not need any software installation and downloading data sets. This full open source approach is expected to be an element geo-spatial information processing linked with cloud computing service

Server-Side GNSS Spoofing Detection Challenges for Vehicle Tracking Applications.

This paper focuses on the risks linked to the Global Navigation Satellite System (GNSS) and introduces a scenario involving a data-transmitting device connected to a cloud-based service. We explore potential attackers and the diverse attacks possible during the communication and data processing stages of the scenario. Additionally, we categorize current detection methods based on the information they employ to detect spoofing attacks and discuss their limitations concerning Server-Side detection. Ultimately, we propose solutions and future lines of work to mitigate these problems.This work is part of the research project SECUREDGE (Security Services Platform for the Protection of Edge Scenarios), with PID2019-110565RB-I00, funded by AEI/10.13039/501100011033 Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Linked USDL Agreement: Effectively Sharing Semantic Service Level Agreements on the Web

As the use of services available on the Web is becoming mainstream, contracts and legal aspects of the relationship between providers and consumers need to be formalized. However, current proposals to model service level agreements are mostly focused on technical aspects, do not explicitly provide semantics to agreement terms, and do not follow Web principles. These limitations prevent take-up, automatic processing, and effective sharing of agreements. Linked USDL Agreement is a Linked Data based semantic model to describe and share service agreements that extends Linked USDL, which offers a family of languages to describe various technical and business aspects of services. We followed a use case driven approach, evaluating the applicability of our proposal in a cloud computing scenario, and comparing its expressiveness with existing models. Finally, we show a concrete tool that helps to model and check the validity of agreements.Junta de Andalucía P12-TIC-1867Ministerio de Economía y Competitividad TIN2012-32273Junta de Andalucía P10-TIC-5906Ministerio de Economía y Competitividad IPT- 2013-0890-

Semantics of Data Mining Services in Cloud Computing

M. Parra-Royon holds a "Excelencia" scholarship from the Regional Government of Andaluc a (Spain). This work was supported by the Research Projects P12-TIC-2958 and TIN2016-81113-R (Ministry of Economy, Industry and Competitiveness - Government of Spain).In recent years with the rise of Cloud Computing (CC), many companies providing services in the cloud, are empowering a new series of services to their catalogue, such as data mining (DM) and data processing (DP), taking advantage of the vast computing resources available to them. Different service definition proposals have been put forward to address the problem of describing services in CC in a comprehensive way. Bearing in mind that each provider has its own definition of the logic of its services, and specifically of DM services, it should be pointed out that the possibility of describing services in a flexible way between providers is fundamental in order to maintain the usability and portability of this type of CC services. The use of semantic technologies based on the proposal offered by Linked Data (LD) for the definition of services, allows the design and modelling of DM services, achieving a high degree of interoperability. In this article a schema for the definition of DM services on CC is presented considering all key aspects of service in CC, such as prices, interfaces, Software Level Agreement (SLA), instances or DM work ow, among others. The new schema is based on LD, and it reuses other schemata obtaining a better and more complete definition of the services. In order to validate the completeness of the scheme, a series of DM services have been created where a set of algorithms such as Random Forest (RF) or KMeans are modeled as services. In addition, a dataset has been generated including the definition of the services of several actual CC DM providers, conforming the effectiveness of the schema.P12-TIC-2958 and TIN2016-81113-R (Ministry of Economy, Industry and Competitiveness - Government of Spain

Semantic-JSON: a lightweight web service interface for Semantic Web contents integrating multiple life science databases

Global cloud frameworks for bioinformatics research databases become huge and heterogeneous; solutions face various diametric challenges comprising cross-integration, retrieval, security and openness. To address this, as of March 2011 organizations including RIKEN published 192 mammalian, plant and protein life sciences databases having 8.2 million data records, integrated as Linked Open or Private Data (LOD/LPD) using SciNetS.org, the Scientists' Networking System. The huge quantity of linked data this database integration framework covers is based on the Semantic Web, where researchers collaborate by managing metadata across public and private databases in a secured data space. This outstripped the data query capacity of existing interface tools like SPARQL. Actual research also requires specialized tools for data analysis using raw original data. To solve these challenges, in December 2009 we developed the lightweight Semantic-JSON interface to access each fragment of linked and raw life sciences data securely under the control of programming languages popularly used by bioinformaticians such as Perl and Ruby. Researchers successfully used the interface across 28 million semantic relationships for biological applications including genome design, sequence processing, inference over phenotype databases, full-text search indexing and human-readable contents like ontology and LOD tree viewers. Semantic-JSON services of SciNetS.org are provided at http://semanticjson.org

Foggy clouds and cloudy fogs: a real need for coordinated management of fog-to-cloud computing systems

The recent advances in cloud services technology are fueling a plethora of information technology innovation, including networking, storage, and computing. Today, various flavors have evolved of IoT, cloud computing, and so-called fog computing, a concept referring to capabilities of edge devices and users' clients to compute, store, and exchange data among each other and with the cloud. Although the rapid pace of this evolution was not easily foreseeable, today each piece of it facilitates and enables the deployment of what we commonly refer to as a smart scenario, including smart cities, smart transportation, and smart homes. As most current cloud, fog, and network services run simultaneously in each scenario, we observe that we are at the dawn of what may be the next big step in the cloud computing and networking evolution, whereby services might be executed at the network edge, both in parallel and in a coordinated fashion, as well as supported by the unstoppable technology evolution. As edge devices become richer in functionality and smarter, embedding capacities such as storage or processing, as well as new functionalities, such as decision making, data collection, forwarding, and sharing, a real need is emerging for coordinated management of fog-to-cloud (F2C) computing systems. This article introduces a layered F2C architecture, its benefits and strengths, as well as the arising open and research challenges, making the case for the real need for their coordinated management. Our architecture, the illustrative use case presented, and a comparative performance analysis, albeit conceptual, all clearly show the way forward toward a new IoT scenario with a set of existing and unforeseen services provided on highly distributed and dynamic compute, storage, and networking resources, bringing together heterogeneous and commodity edge devices, emerging fogs, as well as conventional clouds.Peer ReviewedPostprint (author's final draft

Technical considerations towards mobile user QoE enhancement via Cloud interaction

This paper discusses technical considerations of a Cloud infrastructure which interacts with mobile devices in order to migrate part of the computational overhead from the mobile device to the Cloud. The aim of the interaction between the mobile device and the Cloud is the enhancement of parameters that affect the Quality of Experience (QoE) of the mobile end user through the offloading of computational aspects of demanding applications. This paper shows that mobile user’s QoE can be potentially enhanced by offloading computational tasks to the Cloud which incorporates a predictive context-aware mechanism to schedule delivery of content to the mobile end-user using a low-cost interaction model between the Cloud and the mobile user. With respect to the proposed enhancements, both the technical considerations of the cloud infrastructure are examined, as well as the interaction between the mobile device and the Cloud