Mariana Mocanu

Cyberinfrastructure Architecture to Support Decision Taking in Natural Resources Management

The paper presents an integrated information system for monitoring current state of natural resources and providing valuable help by assisting decisions makers in critical situations. The specific case studied is from the domain of water resources management but the architecture is easily adaptable to suit other types of natural resources (e.g. soil, air). The key points of the proposed solutions are standardization, web services and cloud computing.

Analysis of power consumption in heterogeneous virtual machine environments

Reduction of energy consumption in Cloud computing datacenters today is a hot a research topic, as these consume large amounts of energy. Furthermore, most of the energy is used inefficiently because of the improper usage of computational resources such as CPU, storage and network. A good balance between the computing resources and performed workload is mandatory. In the context of data-intensive applications, a significant portion of energy is consumed just to keep alive virtual machines or to move data around without performing useful computation. Moreover, heterogeneity of resources increases the difficulty degree, when trying to achieve energy efficiency. Power consumption optimization requires identification of those inefficiencies in the underlying system and applications. Based on the relation between server load and energy consumption, we study the efficiency of data-intensive applications, and the penalties, in terms of power consumption, that are introduced by different degrees of heterogeneity of the virtual machines characteristics in a cluster.

Cloud-Based Architecture for Farm Management

Cloud Computing technologies can fundamentally contribute to business processes in agriculture, through enhancing traditional farm management systems, by integrating processes like, monitoring, operation farm management, with cloud specific capabilities, which will lead to an increased productivity. Based on this idea we propose, in this paper, a cloud-based architecture that helps creating an integrated intelligent system for improving product quality and business development in the farms field. Farmers cloud access diverse set of information and data related to his farm, in an integrated and unified approach in order to take informed decisions or to be supported in decision taking process.

Composite Application for Water Resource Management

The paper presents the necessity of using modern information technology in water resource management and the current situation of watershed science and management. The advantages of using composite applications, related to the importance of the water resource management systems are outlined. The architecture of Hydro NETWORK portal, developed by the team, and the database and reporting services are further presented. The paper presents the integration in the portal of two other applications for analysis of mutual influence of surface water and groundwater in river basins.

A Bio-Inspired Prediction Method for Water Quality in a Cyber-Infrastructure Architecture

The water quality is critical as it sustains life. In order to avoid catastrophic situations a decision support system in the water pollution scenario must offer reliable and on time information. Prediction plays in this case a very important role. The paper presents a biologically inspired method to predict values of a temporal series and how this can be applied to the specific case of water quality monitoring. Historically, the prediction methods evolved from statistical to biologically inspired. The proposed method is based on neural networks and represents the core part of the prediction module of the decision support system we designed. The experimental data was gathered on a major river in Romania and in this paper we exemplify with values for pH and Turbidity.

Hybrid Algorithm for Workflow Scheduling in Cloud-Based Cyberinfrastructures

Minimizing the application running cost becomes a must in our day when Cloud Computing offers support for a large variety of applications. Being at the confluence with Cyber infrastructures and Big Data platforms, Cloud systems support efficient and effective workflows. Due to the increase in computational power for executing workflows, the need for efficient usage of said power also arises. After a brief overlook of current available workflow scheduling algorithms, such as HLFET - Highest Level First with Estimated Time or MCP - Modified Critical Path, it is clear that, for no specific constraints, they waste CPU resources, with no efficient task allocation. For this reason a new algorithm, called HER (Hybrid Algorithm for Workflow Scheduling in Cloud-based Cyber infrastructures) is proposed in this paper. HER algorithm reduces CPU idle time, with effect on the number of wasted resources and ensure a good load balancing for a cluster of resources available in a Cloud environment. The HER algorithm is exemplified on a number of different workflow scenarios in Cyber Water project - Prototype Cyber infrastructure based System for Decision-Making Support in Water Resources Management. The experimental approach considers several workflows such as decision support, real-time alerts, and visualization that use computational, storage and network resources in Clouds.

Monitoring Watershed Parameters through Software Services

The paper presents the necessity of using modern information technology in water resource management. The advantages of using composite applications, related to the importance of the water resource management systems are outlined. The architecture of the system, designed by the team, and the migration of local sensor applications to Web services are further presented.

Soil Management Services in CLUeFARM

Proper use of land require tools to handle each parcel both in a individual manner, as regard to the activities rolled out on it, and as part of a farm or greenhouse containing several parcels, in order to plan and harness the results of all activities in a farm or greenhouse. The paper presents services related to soil management, within a platform that provides integrated support for greenhouse activities, which are subject of CLUeFARM research project (Information system based on cloud services, accessible through mobile devices, for quality improvement of products and business development în farms).

Integrated Cloud Framework for Farm Management

Smart or intelligent farming is a relatively new concept, but its becoming an important factor for the agricultural sectors, as a way to raise productivity through technology. This article presents a global management and decision system for smart farming. Our system is addressed to farmers and other actors involved in farming operations, such as rural service companies and banks. It can manage up to several groups of smart or technology-based farms. The system is functioning on two levels, local and Cloud. First of all, it must be deployed on the farms local wireless network. And secondly, it uses the Clouds resources and flexibility to offer even more complex services.

Cost efficient cloud-based service oriented architecture for water pollution prediction

River water quality nowadays represents a major concern. Performing water monitoring, in order to detect the pollutant with wireless sensor networks is not enough. Furthermore, the solution to place more sensors for monitoring is not cost efficient as this type of sensors are very expensive. In the case of a pollution accident on a river, it is mandatory to alert people and, more important, to predict the evolution of pollutant concentration, downstream. Also, it is essential to minimize the time-frame to send the alert to the possibly affected people. In this paper, we propose a cost-efficient cloud-based service oriented architecture for water pollution prediction and alert system. The cost efficiency of our approach comes from the three main directions. The first way is represented by the usage of less water monitoring specific sensors due to the usage of complex hydraulic models. The second direction is represented by the construction of a knowledge-base with pre-run scenarios of pollution propagation events. The third direction is represented by the usage of cloud computing services which are proven to be cost effective. The novelty of our approach comes from the integration of different Cloud computing platforms and services, in order achieve scalability, provisioning of resources in real time, to have a simplified deployment and management of resources and applications, and to get a better cost/performance ratio.