Showing papers by "Hong-Linh Truong published in 2012"

Potential for High Resolution Systematic Global Surface Soil Moisture Retrieval via Change Detection Using Sentinel-1

Abstract: The forthcoming two-satellite GMES Sentinel-1 constellation is expected to render systematic surface soil moisture retrieval at 1 km resolution using C-band SAR data possible for the first time from space. Owing to the constellation's foreseen coverage over the Sentinel-1 Land Masses acquisition region-global approximately every six days, nearly daily over Europe and Canada depending on latitude-in the high spatial and radiometric resolution Interferometric Wide Swath (IW) mode, the Sentinel-1 mission shows high potential for global monitoring of surface soil moisture by means of fully automatic retrieval techniques. This paper presents the potential for providing such a service systematically over Land Masses and in near real time using a change detection approach, concluding that such a service is-subject to the mission operating as foreseen-expected to be technically feasible. The work presented in this paper was carried out as a feasibility study within the framework of the ESA-funded GMES Sentinel-1 Soil Moisture Algorithm Development (S1-SMAD) project.

DEMODS: A Description Model for Data-as-a-Service

Abstract: Cloud computing based Data-as-a-Service (DaaS) has become popular. Several data assets have been released in DaaSes across different cloud platforms. Nevertheless, there are no well-defined ways to describe DaaSes and their associated data assets. On the one hand, existing DaaS providers simply use HTML documents to describe their service. This simple way of service description requires user to manually perform service lookup by reading the HTML documents to understand DaaSes as well as their provided data assets. On the other hand, existing service description techniques are not suitable for describing DaaSes because they consider only service information. The lack of well-structured/linked model to describe DaaSes hinders the automatic service lookup for DaaSes and the integration of DaaSes into data composition and analytic tools. In this paper, we propose DEMODS, a Description Model for DaaS, which introduces a general linked model to cover all basic information of a DaaS. Besides the basic DaaS description model, we also introduce an extended model that integrates existing work in describing quality of data, data and service contract, data dependency, and Quality of Service (QoS). We present a mechanism to incorporate DEMODS into both new and existing DaaSes. Finally, a prototype of DEMODS has been developed to evaluate the effectiveness of the proposed model.

Quality-aware service-oriented data integration: requirements, state of the art and open challenges

Abstract: With a multitude of data sources available online, data consumers might find it hard to select the best combination of sources for their needs. Aspects such as price, licensing, service and data quality play a major role in selecting data sources. We therefore advocate qualityaware data services as a natural data source model for complex data integration tasks and mash-ups. This paper focuses on requirements, state of the art, and the main research challenges on the way to the realization of such services.

Cloud Computing for Education and Research in Developing Countries

Abstract: Recently cloud computing has offered attractive solutions for academic and research institutions due to several reasons. In this chapter, the authors present a study of how cloud computing can be used for research and teaching activities in higher educational and research institutions in developing countries. Instead of focusing on cloud computing offering for basic IT infrastructures used in daily work of these institutions, the authors concentrate on the use of cloud computing for satisfying ad hoc needs of computing resources in research and teaching activities. Thorough analyses of research and teaching activities, requirements for cloud computing, benefits of utilizing cloud computing, and adoption barriers for these activities are also included. The authors then present the selected challenges in tackling these barriers and discuss possible approaches for solving these challenges and report lessons learned and experiences in utilizing and developing cloud computing solutions for teaching and research activities in Vietnam.

Virtualizing Software and Humans for Elastic Processes in Multiple Clouds– a Service Management Perspective

Abstract: There is a growing trend of combining human-based computation with machine-based com- putation to solve complex problems which cannot be answered with machine-based computation alone. From the computing perspective, integrating machine-based computing elements with human-based computing elements and provisioning them under the same model will facilitate the resource elasticity required by complex applications. Although certain works investigate tech- niques for integrating human-based computing elements with machine-based computing elements, existing computing models for such integrated computing systems are very limited. In fact, the ar- chitectures, interconnections, non-functional parameters of human-based computing elements are very different from that of contemporary machine-based counterparts. Human-based computing elements are built based on social and bio concepts, thus their architectures, interconnects and non- functional parameters are extremely complex and dynamic, compared with that of machine-based computing elements. In this paper, we examine fundamental issues in virtualizing human-based computing elements and machine-based computing elements using service-oriented computing concepts in order to create highly scalable computing systems of hybrid services to support the elasticity of software and people in complex applications. We will outline our Vienna Elastic Com- puting Model which aims at introducing techniques and frameworks to support multi-dimensional elastic processes atop hybrid cloud systems of software-based and human-based services. This paper will analyze several service management issues in order to support the virtualization of machine-based and human-based computing elements to support such elastic processes.

Data contracts for cloud-based data marketplaces

Abstract: Currently, rich and diverse data types have been increasingly provided using the data-as-a-service (DaaS) model, a form of cloud computing services and the core element of data marketplaces. This facilitates the on-the-fly data composition and utilisation for several dataintensive applications in e-science and business domains. However, data offered by DaaS are constrained by several data concerns that, if not automatically being reasoned properly, will lead to a wrong way of using them. In this paper, we support the view that data concerns should be explicitly modelled and specified in data contracts to support concern-aware data selection and utilisation. We perform a detailed analysis of current techniques for data contracts in the cloud. Instead of relying on a specific representation of data contracts, we introduce an abstract model for data contracts that can be used to build different types of data contracts for specific types of data. Based on the abstract model, we propose several techniques for evaluating data contracts that can be integrated into data service selection and composition frameworks. We also illustrate our approach with some real-world scenarios and show how data contracts can be integrated into data agreement exchange services in the cloud.

Who do you call? problem resolution through social compute units

Abstract: Service process orchestration using workflow technologies have led to significant improvements in generating predicable outcomes by automating tedious manual tasks but suffer from challenges related to the flexibility required in work especially when humans are involved Recently emerging trends in enterprises to explore social computing concepts have realized value in more agile work process orchestrations but tend to be less predictable with respect to outcomes In this paper we use IT services management, specifically, incident management for large scale systems, to investigate the interplay of workflow systems and social computing We apply a recently introduced concept of Social Compute Units, and flexible teams sourced based on various parameters such as skills, availability, incident urgency, etc in the context of resolution of incidents in an IT service provider organization Results from simulation-based experiments indicate that the combination of SCUs and workflow based processes can lead to significant improvement in key service delivery outcomes, with average resolution time per incident and number of SLO violations being at times as low as 527% and 273% respectively of the corresponding values for pure workflow based incident management

A novel approach to modeling context-aware and social collaboration processes

Abstract: Companies strive to retain the knowledge about their business processes by modeling them. However, non-routine people-intensive processes, such as distributed collaboration, are hard to model due to their unpredictable nature. Often such processes involve advanced activities, such as discovery of socially coherent teams or unbiased experts, or complex coordination towards reaching a consensus. Modeling such activities requires an expressive formal representation of process context, i.e. related actors and artifacts. Existing modeling approaches do not provide the necessary level of expressiveness to capture it. We therefore propose a novel modeling approach and a graphical notation, demonstrate their applicability and expressivity via several use cases, and discuss their strengths and weaknesses.

Programming hybrid services in the cloud

Abstract: For solving complex problems, we advocate constructing "social computers" which combine software and human services. However, to date, human capabilities cannot be easily programmed into applications in a similar way like software capabilities. Existing approaches exploiting human capabilities via crowds do not support well on-demand, proactive, team-based human computation. In this paper, we explore a new way to virtualize, provision and program human capabilities using cloud computing concepts and service delivery models. We propose novel methods for modeling clouds of human-based services and combine human-based services with software-based services to establish clouds of hybrid services. In our model, we present common APIs, similar to APIs for software services, to access individual and team-based compute units in clouds of human-based services. Based on that, we propose frameworks and programming primitives for hybrid services. We illustrate our concepts via some examples of using our cloud APIs and existing cloud APIs for software.

Programming Directives for Elastic Computing

Abstract: Enabling and controlling the elasticity of cloud computing applications is challenging. The developer must deal with daunting tasks using low-level code to implement strategies trading off costs versus quality of service. Programming directives can substantially reduce this overhead by delegating control of elasticity to middleware systems while allowing developers to focus on defining suitable strategies. This Web extra lists example directives in the Simple-Yet-Beautiful Language (SYBL).

A survey on cloud‐based sustainability governance systems

Abstract: Purpose – The purpose of this paper is to examine how cloud‐based information systems and services can support emerging and future requirements for sustainability governance of facilities.Design/methodology/approach – The authors present basic elements of cloud‐based sustainability governance platforms, conduct a survey of existing industrial platforms and research works, discuss distinguishable and common characteristics of cloud computing platforms for sustainability governance, and give views on future research.Findings – Cloud computing emerges as a potential candidate for supporting sustainability governance. However, several techniques must be provided in order to support multiple stakeholders, complex analysis and compliance processes.Research limitations/implications – The number of industrial platforms and research works in the survey is limited, as is information about industrial platforms. Furthermore, industrial platforms are continuously updated, thus some information might be outdated.Origin...

On Elasticity and Constrainedness of Business Services Provisioning

Abstract: In service-oriented enterprise architecture, provisioning business services is made on top of IT processes, which should be elastic amid the availability of computing resources and the variation of user demand. In addition, the provisioning depends on human resources utilized and is constrained by the business objectives (e.g. a goal) plus coarse-grained constraints (e.g. an order in which business services take place). This elasticity and constrainedness can best be witnessed on nonfunctional properties of the business services being provisioned. In this paper, we propose a novel framework for modeling and reasoning about them. The framework features a methodology for formally expressing the aforementioned factors in services provisioning, an engine to find solutions and a simulation.

Modeling rewards and incentive mechanisms for social BPM

Abstract: Social computing is actively shaping Internet-based business models. Scalability and effectiveness of collective intelligence are becoming increasingly attractive to investors. However, to fully exploit this potential we still have to develop crowd-management frameworks capable of supporting rich collaboration models, smart task division and virtual careers. An important step in this direction is the development of models of rewarding/incentivizing processes. In this paper, we conceptualize and represent rewarding and incentive mechanisms for social business processes. Our techniques enable definition, composition, execution and monitoring of rewarding mechanisms in a generic way.

Statelets: coordination of social collaboration processes

Abstract: Today people work together across time, space, cultural and organizational boundaries. To simplify and automate the work, collaboration employs a broad range of tools, such as project management software, groupware, social networking services, or wikis. For a collaboration to be effective, the actions of collaborators need to be properly coordinated, which requires taking into account social, structural, and semantic relations among actors and processes involved. This information is not usually available from a single source, but is spread across collaboration systems and tools. Providing a unified access to this data allows not only to establish a complete picture of the collaboration environment, but also to automate the coordination decision making by specifying formal rules that reflect social and semantic context effects on the ongoing collaboration processes. In this paper we present Statelets, a coordination framework and language for support and coordination of collaboration processes spanning multiple groupware tools and social networking sites, and demonstrate its suitability in several use cases.

Effective Reuse via Modeling, Managing and Searching of Business Process Assets

Abstract: Cost and competitive pressures are forcing business organizations to reuse assets from repositories, rather than develop them from scratch. But this has been hampered by some issues that have not been addressed so far. First, there is a lack of a mechanism for the representation of business process assets as variants and versions in repositories. Second, there is no formal means to compare between different variants and versions of an asset and determine which is the best to select for reuse. Third, there is a lack of a technique to determine the extent to which a business process asset could be customized for reuse. In this paper, we address the above research issues by presenting an integrated approach for modeling, analyzing, and searching business process assets in a repository for enhancing reuse. We demonstrate our approach on a large repository of business process assets in the insurance domain.

M2M Platform-as-a-Service for sustainability governance

Abstract: Recently, cloud computing technologies have been employed for large-scale machine-to-machine (M2M) systems, as they could potentially offer better solutions for managing monitoring data and analytics applications to support the needs of different consumers. However, there exist complex relationships between monitored objects, monitoring data, analysis features, and stakeholders in M2M that require efficient ways to handle these complex relationships. This paper presents techniques for linking and managing monitored objects, sustainability monitoring data and analytics applications for different stakeholders in cloud-based M2M systems. We describe a Platform-as-a-Service for sustainability governance that implements these techniques. We also illustrate our prototype based on a real-world cloud system for facility monitoring.

Quality of Context and Mobile Systems: Past, Present, and Future

Abstract: Mobile and pervasive environments are characterized by a plethora of handheld computation and communication enabled devices working as a smart assistant for users by collecting context from the environment and adapting to dynamically changing situation in the environment. Their capabilities are heavily affected by the quality of context information that has been considered unsatisfactory since the start of research in context-aware systems. Early context-aware systems have also tried to collect extra information that can make the applications aware of the quality of context information. Subsequently term Quality of Context (QoC) is coined to indicate quality of context information. In this chapter, the authors present an overview of research efforts undertaken to realize QoC parameters. They also present a summary of works that have used QoC parameters to optimize the performance of different tasks in context-aware systems. Finally, the chapter discusses future directions of QoC research efforts.

On analyzing quality of data influences on performance of finite elements driven computational simulations

Abstract: For multi-scale simulations, the quality of the input data as well as the quality of algorithms and computing environments will strongly impact the intermediate results, the final outcome, and the performance of the simulation. To date, little attention has been paid on understanding the impact of quality of data (QoD) on such multi-scale simulations. In this paper, we present a critical analysis of how QoD influences the results and performance of basic simulation building blocks for multi-scale simulations. We analyze the impact of QoD for Finite Element Method (FEM) based simulation building blocks, and study the dependencies between the QoD of input data and results as well as the performance of the simulation. We devise and implement novel QoD metrics for data intensive, FEM-based simulations and show experiments with real-world applications by demonstrating how QoD metrics can be efficiently used to control and tune the execution of FEM-based simulation at runtime.

A Simulation Framework for Socially Enhanced Applications

Abstract: The emergence of complex computational problems, which cannot be solved solely by software and require human contribution, have brought the need of designing systems that efficiently manage a mix of software-based and human-based computational resources. Simulations are very appropriate for research on these systems, because they enable testing different scenarios, while avoiding the cost and time limitations of research in real systems. In this paper, we present a framework that enables the simulation of socially-enhanced applications utilizing both software and human based resources. Our framework addresses challenges in human-software environments, such as identifying relevant comparable metrics for mixed resources, mixed-resource selection, composition and scheduling algorithms, performance monitoring and analysis etc. We show the framework’s usefulness and usability through a use case.