Authorization Framework for Resource Sharing in Grid Environments

This paper presents a Web based portal, which enables intelligent processing of biological data in Grid environments. The deployed software aims at creation of tools for processing data from microarray experiments over the Hellenic Grid infrastructure. Emphasis is given on user interface and access issues, while the paper describes also the data parsing and parallelization of the microarray data processing. The description of the system is oriented to Grid developers and users, since it focuses on the customization and use of the microarray applications over the Grid. Apart from supporting the high performance and economical execution of microarray experiments, the proposed system endeavors to provide access to a distributed repository of experiments information and results.

The management of the magnanimous spatial data needs the distributed cooperative GIS platform. This paper proposed the Peer To Peer and Cooperating Computing Hybrid Discovering Model of Distributed Geospatial Information. Based on the (Spatial Resource Discovery Agent (SRDA) and ordinary neighbor node, Combined with Spatial data model of MAPGIS7.0, this article brings up the geographic structure query language in P2P network (P2PGSQL), and has designed the interpreter of P2PGSQL. In the Peer To Peer and Cooperating Computing Hybrid Discovering Model, this paper has designed the algorithms that construct the distributed hash table and decrease the delay. By discovering and performing the potential swaps that are beneficial to the match between overlay and physical network, it can reduce the average latency and improve the performance of the system. Based on the P2P Cooperating Computing Hybrid Discovering Model, this article has given the method of the P2PGSQL in grid environment and built the mapping model of the global spatial query sentence to the local query sentence. With constituting a global spatial data resource catalog to record the distributing information of all spatial database on each node, P2PGSQL has backed up effective expression of spatial database management mission in grid environment. Hence, P2PGSQL can sustain the query of distribute spatial data in grid environment. This article has extended the grid spatial relation operation (Intersection, Union, Difference) and synthesized operation (Length, Buffer, intersecting region) and so on. The P2PGSQL can reduce the quantity of spatial data transmitting among nodes and enhance the capacity of parallel operation. At the same time, P2PGSQL can also sustain multi-spatial data model by the extension of structure data on the data type. At the end, an experimental instance of P2PGSQL has been carried out based on mapgis7.0 platform.

According to concrete contents and characteristics of 3D geospatial information application field, a grid architecture fit for 3D geospatial information application is firstly proposed in the paper. With the service as the core, the system is designed as 6 layers in which each layer interrelated whose function includes 3D geospatial data access and integration, 3D geospatial data interoperability and 3D geospatial information services. Secondly, the author discussed 3D geospatial information service in grid environment and the key technology. Finally, GridVRMap of 3D geospatial information service grid is introduced.

Experimental Study on Speed-up for Remote Visualization of Large-scale Volume Data in Grid Environments

In this paper, we propose a role-based access control (RBAC) system for data resources in the Storage Resource Broker (SRB). The SRB is a Data Grid management system, which can integrate heterogeneous data resources of virtual organizations (VOs). The SRB stores the access control information of individual users in the Metadata Catalog (MCAT) database. However, because of the specific MCAT schema structure, this information can only be used by the SRB applications. If VOs also have many non-SRB applications, each with its own storage format for user access control information, it creates a scalability problem with regard to administration. To solve this problem, we developed a RBAC system with Shibboleth, which is an attribute authorization service currently being used in many Grid environments. Thus, the administration overhead is reduced because the role privileges of individual users are now managed by Shibboleth, not by MCAT or applications. In addition, access control policies need to be specified and managed across multiple VOs. For the specification of access control policies, we used the Core and Hierarchical RBAC profile of the eXtensible Access Control Markup Language (XACML); and for distributed administration of those policies, we used the Object, Metadata and Artifacts Registry (OMAR). OMAR is based on the e-business eXtensible Markup Language (ebXML) registry specifications developed to achieve interoperable registries and repositories. Our RBAC system provides scalable and fine-grain access control and allows privacy protection. Performance analysis shows that our system adds only a small overhead to the existing security infrastructure of the SRB.

PurposeThe purpose of this paper Computing is a recent emerging cloud model that affords clients limitless facilities, lowers the rate of customer storing and computation and progresses the ease of use, leading to a surge in the number of enterprises and individuals storing data in the cloud. Cloud services are used by various organizations (education, medical and commercial) to store their data. In the health-care industry, for example, patient medical data is outsourced to a cloud server. Instead of relying onmedical service providers, clients can access theirmedical data over the cloud.Design/methodology/approachThis section explains the proposed cloud-based health-care system for secure data storage and access control called hash-based ciphertext policy attribute-based encryption with signature (hCP-ABES). It provides access control with finer granularity, security, authentication and user confidentiality of medical data. It enhances ciphertext-policy attribute-based encryption (CP-ABE) with hashing, encryption and signature. The proposed architecture includes protection mechanisms to guarantee that health-care and medical information can be securely exchanged between health systems via the cloud. Figure 2 depicts the proposed work's architectural design.FindingsFor health-care-related applications, safe contact with common documents hosted on a cloud server is becoming increasingly important. However, there are numerous constraints to designing an effective and safe data access method, including cloud server performance, a high number of data users and various security requirements. This work adds hashing and signature to the classic CP-ABE technique. It protects the confidentiality of health-care data while also allowing for fine-grained access control. According to an analysis of security needs, this work fulfills the privacy and integrity of health information using federated learning.Originality/valueThe Internet of Things (IoT) technology and smart diagnostic implants have enhanced health-care systems by allowing for remote access and screening of patients’ health issues at any time and from any location. Medical IoT devices monitor patients’ health status and combine this information into medical records, which are then transferred to the cloud and viewed by health providers for decision-making. However, when it comes to information transfer, the security and secrecy of electronic health records become a major concern. This work offers effective data storage and access control for a smart healthcare system to protect confidentiality. CP-ABE ensures data confidentiality and also allows control on data access at a finer level. Furthermore, it allows owners to set up a dynamic patients health data sharing policy under the cloud layer. hCP-ABES proposed fine-grained data access, security, authentication and user privacy of medical data. This paper enhances CP-ABE with hashing, encryption and signature. The proposed method has been evaluated, and the results signify that the proposed hCP-ABES is feasible compared to other access control schemes using federated learning.

Much work has been done in the area of data access and integration using various data mapping, matching, and loading techniques. One of the main concerns when integrating data from heterogeneous data sources is data redundancy. The concern is mainly due to the different business contexts and purposes from which the data systems were originally built. A common process for accessing data from integrated databases involves the use of each data source’s own catalogue or metadata schema. In this article, the authors take the view that there is a greater chance of data inconsistencies, such as data redundancies when integrating them within a grid environment as compared to traditional distributed paradigms. The importance of improving the data search and matching process is briefly discussed, and a partial service oriented generic strategy is adopted to consolidate distinct catalogue schemas of federated databases to access information seamlessly. To this end, a proposed matching strategy between structure objects and data values across federated databases in a grid environment is presented.

A model for locating services in grid is described here. It integrates the Grid framework OGSA (Open Grid Services Architecture) [1], using VO (Virtual Organization) [2] concept to divide logic grid services into different organizations based on its establishing purpose and requirement on resources sharing and services providing. The CARP hash-based information caching mechanism and a hierarchy message dissemination arithmetic are presented. A performance evaluation of the algorithm is analyzed theoretically.

Social networking and growing popularity of cloud services have made everyone to communicate each other in an easiest way. File sharing and distribution are the frequently used services provided by cloud service providers, although these facilities reduce cost of data sharing but at the same time data security and access control is the major problem. Many renowned service providers have faced the challenges to secure data and provide better access control, and we know once the data is leaked we cannot recover the data loss. Thus in order to ensure better security we need for focus on the two major problems, and those are access control and encryption policy. Cipher text policy attribute based encryption is the most effective solution for access control in real time scenarios where owner can actually decide the access rights for the end-user, but it comes with key escrow problem. We are proposing our modified escrow-free key issuing protocol to solve the problem of key escrow and our Modified Attribute Based Encryption scheme to achieve all security requirements to get a robust and secure system. Further we evaluate our model on the basis of results and lastly we conclude the paper.

Secure cooperative access control on grid

The access to Grid resources depends on rules defined by the administrators of the physical organizations and of the Grid middleware. This approach does not require support for access control in the middleware, but since changes in the access control policy of the Virtual Organization imply the involvement of one or more administrators, it lacks the flexibility needed in a several application scenarios. In this paper we propose a group-based access control model for Grid environments that increases the flexibility of the access control model offered by state-of-the-art Grid platforms without requiring changes in the middleware. The approach is based on collaboration among Grid users and allows them to exchange access permissions to Virtual Resources without the intervention administrators. We show that our solution can be defined on top of the access control mechanisms offered by state-of-the-art Grid middleware and illustrate how the proposed model can be implemented as a service in a service-oriented Grid environment.

Data grids support distributed data-intensive applications that need to access massive datasets stored around the world. Ensuring efficient access to such datasets is hindered by the high latencies of wide-area networks. To speed up access, files can be replicated so a user can access a nearby replica. Replication also provides improved availability, decreased bandwidth use, increased fault tolerance, and improved scalability. Since a grid environment is dynamic, resource availability, network latency, and user requests may change. To address these issues a dynamic replica placement strategy that adapts to changing behaviour is needed. In this paper, we introduce a highly distributed replica placement algorithm for hierarchical data grids. Our algorithm exploits data access histories to identify popular files and determines optimal replication locations to improve access performance by minimizing replication overhead (access and update) assuming a given traffic pattern. The problem is formulated using dynamic programming. We evaluate our algorithm using the OptorSim simulator and find that it offers shorter execution time and reduced bandwidth consumption compared to other dynamic replica placement methods.

SUMMARYAggregate queries are useful tools in the context of sensor network‐based systems as they retrieve knowledge from huge amounts of summarized readings to be exploited for knowledge discovery purposes. Actually, data representation and query models are problematic issues for managing sensor network data, because streams produced by sensors are theoretically unbounded. In this paper, we present a Grid framework, called SensorGrid, on the basis of data compression and approximation paradigms, which allows us to provide approximate answers to aggregate queries on summarized sensor network data. These queries are the basis for achieving Online Analytical Processing (OLAP) over sensor network readings in Data Grid environments, with both effectiveness and efficiency. We also present our experience in the context of a real‐life system focused on the management of environmental sensor network data. Another contribution of our research is represented by the extensive experimental evaluation and analysis of SensorGrid, which, in more details, focuses on two main classes of aggregate range queries over sensor readings, namely, (i) the window queries, which apply an SQL aggregation operator over a fixed window over the reading stream produced by the sensor network, and (ii) the continuous queries, which instead consider a ‘moving’ window and produce as output a stream of answers. Both classes of queries are extremely useful to extract summarized knowledge to be exploited by OLAP‐like analysis tools over sensor network data. The experimental results, conducted on both synthetic and real‐life data sets, clearly confirm the benefits deriving from embedding data compression and approximation paradigms into Grid‐based sensor network data‐intensive management systems.Copyright © 2013 John Wiley & Sons, Ltd.

M-A model of agricultural remote sensing monitoring metadata based on grid environment

Due to the nowadays increasing applications of grid computing technology, the risks of grid security are growing, such as the problem of access control inter-domain in grid environment. Recently, trust management is considered as an effective approach for enhancing grid security. As the fuzzy feature of trust and the advantage of fuzzy theory for trust representation and reasoning, this paper presents a two-level fuzzy trust model for grid environment as well as an inter-domain access control method based on it. The model adopts fuzzy math theory and considers direct trust and recommended trust comprehensively between domains. Case study and simulation results show that the scheme can realize access control inter-domain in grid environment correctly and effectively.