Resource discovery for distributed computing systems: A comprehensive survey

Large-scale distributed computing environments provide a vast amount of heterogeneous computing resources from different sources for resource sharing and distributed computing. Discovering appropriate resources in such environments is a challenge which involves several different subjects. In this paper, we provide an investigation on the current state of resource discovery protocols, mechanisms, and platforms for large-scale distributed environments, focusing on the design aspects. We classify all related aspects, general steps, and requirements to construct a novel resource discovery solution in three categories consisting of structures, methods, and issues. Accordingly, we review the literature, analyzing various aspects for each category

Applications of Agent-Based Methods in Multi-Energy Systems—A Systematic Literature Review

The need for a greener and more sustainable energy system evokes a need for more extensive energy system transition research. The penetration of distributed energy resources and Internet of Things technologies facilitate energy system transition towards the next generation of energy system concepts. The next generation of energy system concepts include “integrated energy system”, “multi-energy system”, or “smart energy system”. These concepts reveal that future energy systems can integrate multiple energy carriers with autonomous intelligent decision making. There are noticeable trends in using the agent-based method in research of energy systems, including multi-energy system transition simulation with agent-based modeling (ABM) and multi-energy system management with multi-agent system (MAS) modeling. The need for a comprehensive review of the applications of the agent-based method motivates this review article. Thus, this article aims to systematically review the ABM and MAS applications in multi-energy systems with publications from 2007 to the end of 2021. The articles were sorted into MAS and ABM applications based on the details of agent implementations. MAS application papers in building energy systems, district energy systems, and regional energy systems are reviewed with regard to energy carriers, agent control architecture, optimization algorithms, and agent development environments. ABM application papers in behavior simulation and policy-making are reviewed with regard to the agent decision-making details and model objectives. In addition, the potential future research directions in reinforcement learning implementation and agent control synchronization are highlighted. The review shows that the agent-based method has great potential to contribute to energy transition studies with its plug-and-play ability and distributed decision-making process

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

On the Optimization of PV Cells’ Orientation Angles and Their Deployment at Base Stations for Energy-efficient Cellular Networks

The inherent problem of solar-powered base stations (BSs) will be tackled in this thesis, i.e., the problem that the energy generation of the photovoltaic (PV) cells does not match the energy consumption of the BS in time, which results in energy being wasted. In Chapter 1, a comprehensive literature review is given. In Chapter 2, the orientation angles of N PV cells powering one BS are jointly optimized to improve the match between the two profiles on a daily timescale. The energy generation profiles of randomly inclined and oriented PV cells are analytically derived based on the Reindl model. The energy drawn per day from the main grid by the BS given its energy consumption profile is used as the performance metric to determine the optimal set of orientation angels. The main results are that deploying one PV cell (or several PV cells) with the (same) optimized orientation angle is recommended for BSs with an energy consumption profile that has one significant local maximum between sunrise and sunset. Deploying two PV cells (or two equal-sized groups of PV cells) where the two orientation angles (of the two groups) are jointly optimized is recommended for BSs with an energy consumption profile that has significant local maxima in the morning as well as in the afternoon or with a constant energy consumption profile. In Chapter 3, a battery model is added to the system model. The battery model is based on a Markov chain. The effects of different battery capacities on the optimal PV cell orientation angle are investigated. It is shown that PV cell orientation angle optimization should be done for BSs deployed with small batteries. In Chapter 4, the system model is extended to a multi-cell cellular network and a mixed-integer linear programming problem is developed to determine how energy harvesters with anti-correlated energy generation profiles should be deployed to every BS. In Chapter 5, the thesis is concluded