A classification of emerging and traditional grid systems

The grid has evolved in numerous distinct phases. It started in the early ’90s as a model of metacomputing in which supercomputers share resources; subsequently, researchers added the ability to share data. This is usually referred to as the first-generation grid. By the late ’90s, researchers had outlined the framework for second-generation grids, characterized by their use of grid middleware systems to “glue” different grid technologies together. Third-generation grids originated in the early millennium when Web technology was combined with second-generation grids. As a result, the invisible grid, in which grid complexity is fully hidden through resource virtualization, started receiving attention. Subsequently, grid researchers identified the requirement for semantically rich knowledge grids, in which middleware technologies are more intelligent and autonomic. Recently, the necessity for grids to support and extend the ambient intelligence vision has emerged. In AmI, humans are surrounded by computing technologies that are unobtrusively embedded in their surroundings. However, third-generation grids’ current architecture doesn’t meet the requirements of next-generation grids (NGG) and service-oriented knowledge utility (SOKU).4 A few years ago, a group of independent experts, arranged by the European Commission, identified these shortcomings as a way to identify potential European grid research priorities for 2010 and beyond. The experts envision grid systems’ information, knowledge, and processing capabilities as a set of utility services.3 Consequently, new grid systems are emerging to materialize these visions. Here, we review emerging grids and classify them to motivate further research and help establish a solid foundation in this rapidly evolving area

Collective IT artifacts: Toward Inclusive Crisis Infrastructures

This paper investigates a previously overlooked phenomenon in crisis response information systems, namely inclusive crisis infrastructure. By expanding the well-acknowledged infrastructure concept with alternatives to understand the nature and scope of inclusive crisis infrastructures, this paper contributes to closing the gap between theory and practice by raising some research questions critical to the study of inclusive crisis infrastructures. The emerging literature on crisis response information systems suggests that external sourcing of information increasingly influences crisis response operations. To contribute to this discourse, the paper draws on Pipek and Wulf’s (2009) definition of work infrastructures and Palen and Liu’s (2007) conceptualization of peer-to-peer communications to develop a better understanding of the crisis response arena as a whole. In doing so, this paper goes beyond the emphasis on event-based technologies that currently dominate the crisis response information systems literature and instead argues why crisis infrastructures need to be both inward-looking and accommodating to technological and social outcomes parallel to formal response contexts. The novel conceptualization captures the fact that the crisis context contains collections of collective IT artifacts that are not aligned or related but that are, for autonomy reasons, interlinked to crisis organizations’ current IT infrastructure and may be of great value to such organizations if infrastructure capability options are considered

Enabling Information Gathering Patterns for Emergency Response with the OpenKnowledge System

Today's information systems must operate effectively within open and dynamic environments. This challenge becomes a necessity for crisis management systems. In emergency contexts, in fact, a large number of actors need to collaborate and coordinate in the disaster scenes by exchanging and reporting information with each other and with the people in the control room. In such open settings, coordination technologies play a crucial role in supporting mobile agents located in areas prone to sudden changes with adaptive and flexible interaction patterns. Research efforts in different areas are converging to devise suitable mechanisms for process coordination: specifically, current results on service-oriented computing and multi-agent systems are being integrated to enable dynamic interaction among autonomous components in large, open systems. This work focuses on the exploitation and evaluation of the OpenKnowledge framework to support different information-gathering patterns in emergency contexts. The OpenKnowledge (OK) system has been adopted to model and simulate possible emergency plans. The Lightweight Coordination Calculus (LCC) is used to specify interaction models, which are published, discovered and executed by the OK distributed infrastructure in order to simulate peer interactions. A simulation environment fully integrated with the OK system has been developed to: (1) evaluate whether such infrastructure is able to support different models of information-sharing, e.g., centralized and decentralized patterns of interaction; (2) investigate under which conditions the OK paradigm, exploited in its decentralized nature, can improve the performance of more conventional centralized approaches. Preliminary results show the capability of the OK system in supporting the two afore-mentioned patterns and, under ideal assumptions, a comparable performance in both cases

A Cloud-based System to Protect Against Industrial Multi-risk Events☆

Abstract Industrial areas frequently present a high concentration of production operations which are source of anthropic risks. For this reason Smart Public Safety is receiving an increasing attention from industry, research and authorities. Moreover, due the consequences of global warming, these areas could be subject to risk events with increased probability with respect to the past. Information technologies enable an innovative approach towards safety management, which relies on the evolution of tools for environmental monitoring and citizens' interaction. This work presents the preliminary results of the Italian research project SIGMA - sensor Integrated System in cloud environment for the Advanced Multi-risk Management. The proposed system includes a continuous monitoring of the different information sources, thus reducing human control as much as possible. At the same time, the communication system manages multiple data flows in a flexible way, adapting itself to different working scenarios, enabling smarter applications. SIGMA intends to acquire, integrate and compute heterogeneous data, coming from various sensor networks in order to provide useful insights for the monitoring, forecasting and management of risk situations through services provided to citizens and businesses, both public and private. Based on the integration of different interoperating components, the system is able to provide a complete emergency management framework through simulations/optimizations and heterogeneous data manipulation tools. The prototype solution is detailed by a use case application in an industrial area located in the region of Sicily, Italy. In particular, web based modular applications connected through SIGMA allow the monitoring of the industrial environment through data gathering from different sensor networks, such as outdoor sensors mounted in the surroundings of large industrial areas, and support of the design of the logistics network aimed at covering the industrial risks

Modeling IoT-Based Solutions Using Human-Centric Wireless Sensor Networks

The Internet of Things (IoT) has inspired solutions that are already available for addressing problems in various application scenarios, such as healthcare, security, emergency support and tourism. However, there is no clear approach to modeling these systems and envisioning their capabilities at the design time. Therefore, the process of designing these systems is ad hoc and its real impact is evaluated once the solution is already implemented, which is risky and expensive. This paper proposes a modeling approach that uses  human-centric wireless sensor networks to specify and evaluate models of IoT-based systems at the time of design, avoiding the need to spend time and effort on early implementations of immature designs. It allows designers to focus on the system design, leaving the implementation decisions for a next phase. The article illustrates the usefulness of this proposal through a running example, showing the design of an IoT-based solution to support the first responses during medium-sized or large urban incidents. The case study used in the proposal evaluation is based on a real train crash. The proposed modeling approach can be used to design IoT-based systems for other application scenarios, e.g., to support security operatives or monitor chronic patients in their homes.Fil: Monares, Álvaro . Universidad de Chile; ChileFil: Ochoa, Sergio F.. Universidad de Chile; ChileFil: Santos, Rodrigo Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación en Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; ArgentinaFil: Orozco, Javier Dario. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación en Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; ArgentinaFil: Meseguer, Roc . Universidad Politecnica de Catalunya; Españ