Mona Nasr

Cloud Computing: The Future of Big Data Management

The population is living in a complex world at information explosion age. Today in Enterprises, the size and complexity of managing information have been increasing significantly and the demand for cost efficient information storage and processing grows higher. Enterprises need to optimize their IT management and minimize server maintenance costs become greater as usage demands prove to be increasingly unpredictable. Cloud computing offers a promising solution. Cloud computing is a computing model that relies on a large, centralized data center to store and process a great wealth of information. Computing power and storage space are provided on-demand to Enterprises that outsource their IT management to the cloud service provider. The immediate advantage to this computing model is a lower infrastructure maintenance cost. Since Enterprises that use cloud no longer require on-site servers, they eliminate the associated cost in IT management and electrical power.

Business Intelligence in the Cloud

Business Intelligence (BI) deals with integrated approaches to management support. Currently, there are constraints to BI adoption and a new era of analytic data management for business intelligence these constraints are the integrated infrastructures that are subject to BI have become complex, costly, and inflexible, the effort required consolidating and cleansing enterprise data and Performance impact on existing infrastructure / inadequate IT infrastructure. So, in this paper Cloud computing will be used as a possible remedy for these issues. We will represent a new environment atmosphere for the business intelligence to make the ability to shorten BI implementation windows, reduced cost for BI programs compared with traditional on-premise BI software, Ability to add environments for testing, proof-of-concepts and upgrades, offer users the potential for faster deployments and increased flexibility. Also, Cloud computing enables organizations to analyze terabytes of data faster and more economically than ever before. Business intelligence (BI) in the cloud can be like a big puzzle. Users can jump in and put together small pieces of the puzzle but until the whole thing is complete the user will lack an overall view of the big picture. In this paper reading each section will fill in a piece of the puzzle.

Service oriented approach for decision support systems

Decision Support System has been applied to solve variety of agricultural problems. It provides the framework that allows both the decision-makers and farmers to make good decisions. Decision support systems (DSS) use databases, human-machine to combine a large number of models to realize scientific decision-making. The environmental data plays a vital role in agriculture decision, which changes at a rapid rate. Keeping these data updated can be done by using a Service Oriented Approach (SOA). SOA is a kind of designing style which can share information between heterogeneous systems that solve the software integration expansion problem in a distributed environment. This paper presents that SOA used to get precise irrigation schedule for mango trees. Recent years SOA has the focus of attention, due to standards based on Web services that simplify interoperability, loose coupling and reuse. One of the basic business motivations for implementing SOA today is achieving business agility, can help businesses respond more quickly and cost effectively to the dynamic and continues changes in market conditions.

A framework for integrating geospatial information systems and hybrid cloud computing

Abstract Many decisions are made daily based on the simple mental processing. This way of decision making is suitable for the simple personal daily issues. But when decisions are concerned with general and sensitive sectors, this way of decision making is unacceptable. Nowadays, Geospatial Information Systems help in making more accurate decisions in a lot of sections that would be built on accurate information by way of drawing maps and visualizing data to clearly judge which option is the best for that particular situation. This paper raises a framework that integrates the Geospatial Information Systems with the Hybrid Cloud Computing to let them work together and get greater powerful benefits via applying the concept of cloud computing to overcome the flaws related to the desktop GIS including the huge startup cost and the storage capacity and to provide the feature of location independence accessibility where the GIS can be accessed from anywhere and anytime. The hybrid cloud computing was picked to be integrated with the GIS to gain the elasticity and security of dealing with different types of data; private and public data. This integration is presented in three dimensions. The first one is architecture with seven segments that illustrate the main structure for the Hybrid Cloud GIS within a mix of private environment and public environment. The second one is the types of the participants and their workflow within the two environments. The last dimension is a case study for applying this integration in the health sector in Egypt.

A proposed paradigm for tracing the effect of security threats in various mobile agent systems

Many people consider that security is one of the complexes problems for practical use of mobile agents that move around the networks and do their tasks. This complexity is due mainly to the size of the problem, moreover, in open networks, security problems and costs of potential solutions might outweigh the benefits of mobility. The question of security goes both directions. How can data base servers be protected from malicious actions of mobile agents, and conversely, how can mobile agent, packed with private data and information, be protected from servers, and other agents while traveling through cyberspace. This paper presents a survey for the malicious (host /agent) facing Mobile Agent(MA). Platform to Agent P2A (Masquerading, Denial of Service, Eavesdropping, Alteration) Agent to Agent A2A (Masquerading, Denial of Service, Repudiation, Unauthorized Access). This paper, describes MA-based paradigm as a simulation based model for tracing the effect of one of the security threats that has been entirely developed in java programming language. The proposed paradigm considers a range of techniques that provide high degree of security during the mobile agent system life cycle in its simulation environment. This paper highlights the spot to two main design objectives: The importance of including various supportive types of agents within a system e.g., police agents, service agents,...etc. Second: Evaluation analysis and number of checks to be done to trace the MA if masqueraded during its path. eg. evaluation analysis for detecting tolerance differences for the calculated agents route before and during its journey, storing agent transactions, storing snapshots of agent state information, checking from time to time agent status and task completeness and lastly guard agent check the changed variables of migrated agent. During tracing and monitoring MA(s), the initiator node may destroy it and continue with another. In this paper we propose a new paradigm that detects and eliminate with high probability, any degree of tampering within a reasonable amount of time, also provide the ability of scalability of security administration.

A Proposed Model for Using Cloud Computing and Web2.0 in Deploying E-Learning Ecosystem ELES

Research community has believed that an e-learning ecosystem is the next generation of e-learning but has faced challenges in optimizing resource allocations, dealing with dynamic demands on getting information and knowledge anywhere and anytime, handling rapid storage growth requirements, cost controlling and greater flexibility. So, flourish, growing, scalable, available, up to date and strong infrastructure e-learning ecosystems in a productive and cost effective way will be needed to face challenges and rapidly changing in learning environment. This paper work focused on an e-learning ecosystem ELES which supports new technologies is introduced and implemented. An integration between cloud computing and Web 2.0 technologies and services used to support the development of e-learning ecosystems. Cloud computing an adaptable technology for many of the universities with its dynamic scalability and usage of virtualized resources as a service through the Internet and Web 2.0 brings new instruments help building dynamic e-learning ecosystem on the web.

A Proposed Integrated Approach for BI and GIS in Health Sector to Support Decision Makers (BIGIS-DSS)

This paper explores the possibilities of adopting Business Intelligence (BI), and Geographic Information System (GIS) to build a spatial intelligence and predictive analytical approach. The proposed approach will help in solving spatial problem which faces decision makers at health sector. The proposed spatial analytical approach will cover three main health planning issues. These issues are tackling health inequalities through geospatial monitor for inequalities in distribution of health units and its services, support decision-making with predictive analytics for common health indicators, and geoprocessing for input layers through dynamic health map and motion charts to support decision making.

Semantic Conflicts Reconciliation as a Viable Solution for Semantic Heterogeneity Problems

t—Achieving semantic interoperability is a current challenge in the field of data integration in order to bridge semantic conflicts occurring when the participating sources and receivers use different or implicit data assumptions. Providing a framework that automatically detects and resolves semantic conflicts is considered as a daunting task for many reasons, it should preserve the local autonomy of the integrated sources, as well as provides a standard query language for accessing the integrated data on a global basis. Many existing traditional and ontology-based approaches have tried to achieve semantic interoperability, but they have certain drawbacks that make them inappropriate for integrating data from a large number of participating sources. We propose semantic conflicts reconciliation (SCR) framework, it is ontology-based system in which all data semantics explicitly described in the knowledge representation phase and automatically taken into account through the interpretation mediation service phase, so conflicts detected and resolved automatically at the query time.

Dynamic AI-Geo Health Application based on BIGIS-DSS Approach

Public health organizations use GIS on a daily basis for input, storage, manipulation, and output of geographic information which provides a powerful tool for public health assessment and monitoring in remote locations and developing countries (1). Information technology is taking on a new level of importance due to its business intelligence application solutions. Our proposal is aimed at integrating these two different worlds in a single dynamic framework using web technology at health sector. Dynamic AI-Geohealth application based on BIGIS_DSS approach uses GIS tools and techniques to convert geographic information and analysis of data that becomes valuable information to make more informed business decisions and rational. Thus, the approach is not just a technical or business analytical process; But discipline which includes both. This paper explores the adopting Business Intelligence (BI) with Geographic Information System (GIS) to build a spatial artificial intelligence and predictive analytical approach. Also this paper will explores case research for implementation of proposed approach in developing countries like Egypt at health sector as dynamic health map web application. The proposed approach helps in solving spatial problem which faces decision makers at health