Scheduling for Space Tracking and Heterogeneous Sensor Environments

This dissertation draws on the fields of heuristic and meta-heuristic algorithm development, resource allocation problems, and scheduling to address key Air Force problems. The world runs on many schedules. People depend upon them and expect these schedules to be accurate. A process is needed where schedules can be dynamically adjusted to allow tasks to be completed efficiently. For example, the Space Surveillance Network relies on a schedule to track objects in space. The schedule must use sensor resources to track as many high-priority satellites as possible to obtain orbit paths and to warn of collision paths. Any collisions that occurred between satellites and other orbiting material could be catastrophic. To address this critical problem domain, this dissertation introduces both a single objective evolutionary tasker algorithm and a multi-objective evolutionary algorithm approach. The aim of both methods is to produce space object tracking schedules to ensure that higher priority objects are appropriately assessed for potential problems. Simulations show that these evolutionary algorithm techniques effectively create schedules to assure that higher priority space objects are tracked. These algorithms have application to a range of dynamic scheduling domains including space object tracking, disaster search and rescue, and heterogeneous sensor scheduling

Task allocation in group of nodes in the IoT: A consensus approach

The realization of the Internet of Things (IoT) paradigm relies on the implementation of systems of cooperative intelligent objects with key interoperability capabilities. In order for objects to dynamically cooperate to IoT applications' execution, they need to make their resources available in a flexible way. However, available resources such as electrical energy, memory, processing, and object capability to perform a given task, are often limited. Therefore, resource allocation that ensures the fulfilment of network requirements is a critical challenge. In this paper, we propose a distributed optimization protocol based on consensus algorithm, to solve the problem of resource allocation and management in IoT heterogeneous networks. The proposed protocol is robust against links or nodes failures, so it's adaptive in dynamic scenarios where the network topology changes in runtime. We consider an IoT scenario where nodes involved in the same IoT task need to adjust their task frequency and buffer occupancy. We demonstrate that, using the proposed protocol, the network converges to a solution where resources are homogeneously allocated among nodes. Performance evaluation of experiments in simulation mode and in real scenarios show that the algorithm converges with a percentage error of about±5% with respect to the optimal allocation obtainable with a centralized approach

Sensor Networks in the Low Lands

This paper provides an overview of scientific and industrial developments of the last decade in the area of sensor networks in The Netherlands (Low Lands). The goal is to highlight areas in which the Netherlands has made most contributions and is currently a dominant player in the field of sensor networks. On the one hand, motivations, addressed topics, and initiatives taken in this period are presented, while on the other hand, special emphasis is given to identifying current and future trends and formulating a vision for the coming five to ten years. The presented overview and trend analysis clearly show that Dutch research and industrial efforts, in line with recent worldwide developments in the field of sensor technology, present a clear shift from sensor node platforms, operating systems, communication, networking, and data management aspects of the sensor networks to reasoning/cognition, control, and actuation

Optimal planning of space surveillance network and automatic data processing

Nowadays, more than 17; 000 objects greater than 10 cm in diameter are tracked and available in public catalog. Just nearly a thousand and a half are active spacecraft. In low Earth orbit (LEO), the increasing of Cube-Sat missions launched in last years is contributing to the growth of the space object population. Furthermore, large constellations to LEO are under development. Such constellations will lead to an unprecedented, step increase in the number of satellites in LEO. Consequently, to prevent the generation of debris in the short-term and the growth of the debris population over the longer-term is mandatory to avoid Kessler syndrome. Therefore, due to the continuous growth of number of operative satellites and the consequent risk of impact among them, an improvement in the observation is constantly demanding. The presented solution to provide a reliable and timely response in case of contingencies is the development of a worldwide sky-coverage network. In the framework of the Italian Space Agency (ASI) – Sapienza University of Rome Agreement (N.2013-078-C.O) for scientific cooperation at the Broglio Space Center (BSC) in Malindi (Kenya), S5Lab research team is developing a network of optical observatories. The presented thesis deals with the development of the network composed by an Italian observatory named MITO (Mid-latitude Italian Observatory), located near Rome and an equatorial observatory called EQUO (Equatorial Italian Observatory). The combinatorial explosion in the number of intervals to be scheduled has been caused by the increasing number of space debris to be observed with optical ground station. Therefore, new scheduling approach are needed to provide a solution to the new requests. In the framework of the Agreement between Italian Space Agency (ASI) and National Institute of Astrophysics (INAF) Supporto alle attività IADC e validazione pre-operativa per SST (N.2015-028-R.0) a scheduler has been developed to manage the network. The presented thesis outlines the developed software called NICO (Networked Instrument Coordinator for space debris Observations) designed to allocate visibility windows to each optical sensor of the network by solving priority conflicts of the scheduling tasks. NICO goal is the harmonization of the different requests by taking care also of external limitations such as astronomical constraints and weather conditions. The development of a network of observatories and a scheduler to manage and organize the data acquisition routine has triggered the problem on how to manage the acquired data. Due to the increasing of the number of the observatory involved in data acquisition and the number of taken images per night, a new automated image processing tool for light-curves measurements was needed. This thesis presents the development and application of the automated software designed to process light curves acquisition. These are used to determine the dynamical state of the target in terms of attitude by processing the light reflected from the metallic surface of the object. Rapid changes in brightens of the response are investigated to reconstruct rapid changes in the attitude in the scale of a second or less. These data are extremely valuable to detect and investigate the attitude of an orbiting object and its evolution especially for future Active Debris Removal (ADR) missions

Rate adaptive resource allocation with fairness control for OFDMA networks

The use of opportunistic radio resource allocation techniques in order to efficiently manage the resources generates a low fairness among the users in a cellular system due to uneven Quality of Service (QoS) distribution. Some classic rate adaptive policies tried to tackle this problem for OFDMA systems by proposing solutions to maximize capacity, maximize fairness, or find a static trade-off between these two objectives. This work generalizes these classic policies and propose a dynamic fairness/rate adaptive technique based on dynamic sub-carrier assignment and equal power allocation that considers a new fairness constraint in the optimization problem. By means of extensive system-level simulations, it is demonstrated that the proposed technique is able to provide an instantaneous (short-term) fairness control, which provides to the network operator the flexibility to operate on any desired trade-off point.Peer ReviewedPostprint (published version

Semantic Description of IoT Security for Smart Grid

Master's thesis Information- and communication technology IKT590 - University of Agder 2017This research work proposed, developed and evaluated IoT Security ontology for smart home energy management system (SHEMS) in smart grids. The ontology description includes infrastructure, attacks, vulnerabilities and counter measures for the main components of SHEMS such as Smart Meter, Smart Appliance, Home Gateway, and Billing data. The ontology extends the SAREF energy management ontology with security features. We have two main reasons for selecting SAREF ontology to base our work on. First, SAREF is standardized by ETSI. Second, it is specifically designed for energy management and efficiency. We checked the correctness of our ontology by running SWRL rules and SPARQL queries. Our test results showed that our ontology is useful to analyse and infer IoT security for smart home and can be extended to more complex reasoning of IoT security features. Keyword: IoT, Security, Smart Grid, Smart Home, Ontology, Energy Managemen