A service-oriented middleware for integrated management of crowdsourced and sensor data streams in disaster management

The increasing number of sensors used in diverse applications has provided a massive number of continuous, unbounded, rapid data and requires the management of distinct protocols, interfaces and intermittent connections. As traditional sensor networks are error-prone and difficult to maintain, the study highlights the emerging role of “citizens as sensors” as a complementary data source to increase public awareness. To this end, an interoperable, reusable middleware for managing spatial, temporal, and thematic data using Sensor Web Enablement initiative services and a processing engine was designed, implemented, and deployed. The study found that its approach provided effective sensor data-stream access, publication, and filtering in dynamic scenarios such as disaster management, as well as it enables batch and stream management integration. Also, an interoperability analytics testing of a flood citizen observatory highlighted even variable data such as those provided by the crowd can be integrated with sensor data stream. Our approach, thus, offers a mean to improve near-real-time applications

International conference on software engineering and knowledge engineering: Session chair

The Thirtieth International Conference on Software Engineering and Knowledge Engineering (SEKE 2018) will be held at the Hotel Pullman, San Francisco Bay, USA, from July 1 to July 3, 2018. SEKE2018 will also be dedicated in memory of Professor Lofti Zadeh, a great scholar, pioneer and leader in fuzzy sets theory and soft computing. The conference aims at bringing together experts in software engineering and knowledge engineering to discuss on relevant results in either software engineering or knowledge engineering or both. Special emphasis will be put on the transference of methods between both domains. The theme this year is soft computing in software engineering & knowledge engineering. Submission of papers and demos are both welcome

Tools for distributed application management

Distributed application management consists of monitoring and controlling an application as it executes in a distributed environment. It encompasses such activities as configuration, initialization, performance monitoring, resource scheduling, and failure response. The Meta system is described: a collection of tools for constructing distributed application management software. Meta provides the mechanism, while the programmer specifies the policy for application management. The policy is manifested as a control program which is a soft real time reactive program. The underlying application is instrumented with a variety of built-in and user defined sensors and actuators. These define the interface between the control program and the application. The control program also has access to a database describing the structure of the application and the characteristics of its environment. Some of the more difficult problems for application management occur when pre-existing, nondistributed programs are integrated into a distributed application for which they may not have been intended. Meta allows management functions to be retrofitted to such programs with a minimum of effort

Real-Time Context-Aware Microservice Architecture for Predictive Analytics and Smart Decision-Making

The impressive evolution of the Internet of Things and the great amount of data flowing through the systems provide us with an inspiring scenario for Big Data analytics and advantageous real-time context-aware predictions and smart decision-making. However, this requires a scalable system for constant streaming processing, also provided with the ability of decision-making and action taking based on the performed predictions. This paper aims at proposing a scalable architecture to provide real-time context-aware actions based on predictive streaming processing of data as an evolution of a previously provided event-driven service-oriented architecture which already permitted the context-aware detection and notification of relevant data. For this purpose, we have defined and implemented a microservice-based architecture which provides real-time context-aware actions based on predictive streaming processing of data. As a result, our architecture has been enhanced twofold: on the one hand, the architecture has been supplied with reliable predictions through the use of predictive analytics and complex event processing techniques, which permit the notification of relevant context-aware information ahead of time. On the other, it has been refactored towards a microservice architecture pattern, highly improving its maintenance and evolution. The architecture performance has been evaluated with an air quality case study

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

Domain Computing: The Next Generation of Computing

Computers are indispensable in our daily lives. The first generation of computing started the era of human automation computing. These machine’s computational resources, however, were completely centralized in local machines. With the appearance of networks, the second generation of computing significantly improved data availability and portability so that computing resources could be efficiently shared among the networks. The service-oriented third generation of computing provided functionality by breaking down applications into services, on-demand computing through utility and cloud infrastructures, as well as ubiquitous accesses from wide-spread geographical networks. Services as primary computing resources are far spread from lo- cal to worldwide. These services loosely couple applications and servers, which allows services to scale up easily with higher availability. The complexity of locating, utilizing and optimizing computational resources becomes even more challenging as these resources become more available, fault-tolerant, scalable, better per- forming, and spatially distributed. The critical question becomes how do applications dynamically utilize and optimize unique/duplicate/competitive resources at runtime in the most efficient and effective way without code changes, as well as providing high available, scalable, secured and easy development services. Domain computing proposes a new way to manage computational resources and applications. Domain computing dy- namically manages resources within logic entities, domains, and without being bound to physical machines so that application functionality can be extended at runtime. Moreover, domain computing introduces domains as a replacement of a traditional computer in order to run applications and link different computational resources that are distributed over networks into domains so that a user can greatly improve and optimize the resource utilization at a global level. By negotiating with different layers, domain computing dynamically links different resources, shares resources and cooperates with domains at runtime so applications can more quickly adapt to dynamically changing environments and gain better performance. Also, domain computing presents a new way to develop applications which are resource stateless based. In this work, a prototype sys- tem was built and the performance of its various aspects has been examined, including network throughput, response time, variance, resource publishing and subscription, and secured communications