An ARTMAP-incorporated Multi-Agent System for Building Intelligent Heat Management

This paper presents an ARTMAP-incorporated multi-agent system (MAS) for building heat management, which aims to maintain the desired space temperature defined by the building occupants (thermal comfort management) and improve energy efficiency by intelligently controlling the energy flow and usage in the building (building energy control). Existing MAS typically uses rule-based approaches to describe the behaviours and the processes of its agents, and the rules are fixed. The incorporation of artificial neural network (ANN) techniques to the agents can provide for the required online learning and adaptation capabilities. A three-layer MAS is proposed for building heat management and ARTMAP is incorporated into the agents so as to facilitate online learning and adaptation capabilities. Simulation results demonstrate that ARTMAP incorporated MAS provides better (automated) energy control and thermal comfort management for a building environment in comparison to its existing rule-based MAS approach

Generic Model and Architecture for Cooperating Objects in Sensor Network Environments

The complexity and heterogeneity of cooperating object applications in ubiquitous environments or of applications in the sensor network domain require the use of generic models and architectures. These architectures should provide support for the following three key issues: flexible installation, management and reconfiguration of components in the system; optimization strategies whose implementation usually involves the proper management of cross-layer information; and proper adaptation techniques that allow for the self-configuration of nodes and components in the system with minimal human intervention. In this paper, we present one possible instance of such a generic model and architecture and show its applicability using Sustainable Bridges, a sensor network application that requires the analysis of complex sensor data to achieve its goal of effectively monitoring bridges for the detection of structural defects

DAS: a data management system for instrument tests and operations

The Data Access System (DAS) is a metadata and data management software system, providing a reusable solution for the storage of data acquired both from telescopes and auxiliary data sources during the instrument development phases and operations. It is part of the Customizable Instrument WorkStation system (CIWS-FW), a framework for the storage, processing and quick-look at the data acquired from scientific instruments. The DAS provides a data access layer mainly targeted to software applications: quick-look displays, pre-processing pipelines and scientific workflows. It is logically organized in three main components: an intuitive and compact Data Definition Language (DAS DDL) in XML format, aimed for user-defined data types; an Application Programming Interface (DAS API), automatically adding classes and methods supporting the DDL data types, and providing an object-oriented query language; a data management component, which maps the metadata of the DDL data types in a relational Data Base Management System (DBMS), and stores the data in a shared (network) file system. With the DAS DDL, developers define the data model for a particular project, specifying for each data type the metadata attributes, the data format and layout (if applicable), and named references to related or aggregated data types. Together with the DDL user-defined data types, the DAS API acts as the only interface to store, query and retrieve the metadata and data in the DAS system, providing both an abstract interface and a data model specific one in C, C++ and Python. The mapping of metadata in the back-end database is automatic and supports several relational DBMSs, including MySQL, Oracle and PostgreSQL.Comment: Accepted for pubblication on ADASS Conference Serie

Using Machine Learning for Handover Optimization in Vehicular Fog Computing

Smart mobility management would be an important prerequisite for future fog computing systems. In this research, we propose a learning-based handover optimization for the Internet of Vehicles that would assist the smooth transition of device connections and offloaded tasks between fog nodes. To accomplish this, we make use of machine learning algorithms to learn from vehicle interactions with fog nodes. Our approach uses a three-layer feed-forward neural network to predict the correct fog node at a given location and time with 99.2 % accuracy on a test set. We also implement a dual stacked recurrent neural network (RNN) with long short-term memory (LSTM) cells capable of learning the latency, or cost, associated with these service requests. We create a simulation in JAMScript using a dataset of real-world vehicle movements to create a dataset to train these networks. We further propose the use of this predictive system in a smarter request routing mechanism to minimize the service interruption during handovers between fog nodes and to anticipate areas of low coverage through a series of experiments and test the models' performance on a test set

Maleren þorstein Illugason Hjaltalin.

It briefly describes the impact of large data era on China’s network policy, but also brings more opportunities and challenges to the network information security. This paper reviews for the internationally accepted basic model and characteristics of network information security, and analyses the characteristics of network information security and their relationship. On the basis of the NIST security model, this paper describes three security control schemes in safety management model and the relationship between the security service and security mechanism in the network information security architecture. On this basis, a network information security system model is proposed, which is composed of three parts, namely, the core layer, the logic layer and the implementation layer. Finally, this paper points out that the network information security protection technology is important, but it is still indispensable that management is in place

An Agent Approach to Spatial Information Grid Architecture Design

Spatial information grid (SIG) is a spatial information infrastructure that has the capability of providing services on-demand. SIG is a distributed network environment, which links spatial data resources, computing resources, storage resources, software, tools and users. SIG can integrate massive distributed heterogeneous spatial information resources, provides uniform management and process, and, furthermore, coordinate different resources to complete large-scale and complex spatial tasks and applications. In this paper, agent technology is adopted to construct a SIG framework, which contains three layers: users/applications layer, agent services layer and information layer. Different applications can get their spatial information via agent services, and agent services make the procedure of navigating and accessing spatial information transparent to users. Also, the implementation issues of the framework are discussed in detail, including Geo-Agents, an agent-based distributed GIS system, spatial information management, collaboration and parallel mechanism, load control strategy, and a sample

Energy efficiency in data collection wireless sensor networks

This dissertation studies the problem of energy efficiency in resource constrained and heterogeneous wireless sensor networks (WSNs) for data collection applications in real-world scenarios. The problem is addressed from three different perspectives: network routing, node energy profiles, and network management. First, the energy efficiency in a WSN is formulated as a load balancing problem, where the routing layer can diagnose and exploit the WSN topology redundancy to reduce the data traffic processed in critical nodes, independent of their hardware platform, improving their energy consumption and extending the network lifetime. We propose a new routing strategy that extends traditional cost-based routing protocols and improves their energy efficiency, while maintaining high reliability. The evaluation of our approach shows a reduction in the energy consumption of the routing layer in the busiest nodes ranging from 11% to 59%, while maintaining over 99% reliability in WSN data collection applications. Second, a study of the effect of the MAC layer on the network energy efficiency is performed based on the nodes energy consumption profile. The resulting energy profiles reveal significant differences in the energy consumption of WSN nodes depending on their external sensors, as well as their sensitivity to changes in network traffic dynamics. Finally, the design of a general integrated framework and data management system for heterogeneous WSNs is presented. This framework not only allows external users to collect data, while monitoring the network performance and energy consumption, but also enables our proposed network redundancy diagnosis and energy profile calculations

Increasing transmission efficiency with advanced signal processing

Optical CDMA is an advanced and flexible communication technology with a potential to offer very energy efficient and highly scalable networking. In addition it can also deliver increased physical layer privacy and on-demand bandwidth sharing management. We have developed, extensively investigated, and experimentally demonstrated highly scalable approach to incoherent OCDMA which can very efficiently increase the number of simultaneous users. In addition, the introduction of an advanced photonic signal processing results in an overall system power budget improvement by nearly 3dB. Error-free operation with the BER less than 10-12 was achieved. We have also shown that with demonstrated approach we can dramatically improve number of simultaneous network users (up to ten times) while keeping the related hardware count unchanged. By comparing this results to DWDM concept, this substantial increase in number of simultaneous users did not require to add any additional wavelength laser sources and was achieved by employing just three communication wavelengths