C-Band Airport Surface Communications System Standards Development. Phase II Final Report. Volume 1: Concepts of Use, Initial System Requirements, Architecture, and AeroMACS Design Considerations

This report is provided as part of ITT s NASA Glenn Research Center Aerospace Communication Systems Technical Support (ACSTS) contract NNC05CA85C, Task 7: New ATM Requirements-Future Communications, C-Band and L-Band Communications Standard Development and was based on direction provided by FAA project-level agreements for New ATM Requirements-Future Communications. Task 7 included two subtasks. Subtask 7-1 addressed C-band (5091- to 5150-MHz) airport surface data communications standards development, systems engineering, test bed and prototype development, and tests and demonstrations to establish operational capability for the Aeronautical Mobile Airport Communications System (AeroMACS). Subtask 7-2 focused on systems engineering and development support of the L-band digital aeronautical communications system (L-DACS). Subtask 7-1 consisted of two phases. Phase I included development of AeroMACS concepts of use, requirements, architecture, and initial high-level safety risk assessment. Phase II builds on Phase I results and is presented in two volumes. Volume I (this document) is devoted to concepts of use, system requirements, and architecture, including AeroMACS design considerations. Volume II describes an AeroMACS prototype evaluation and presents final AeroMACS recommendations. This report also describes airport categorization and channelization methodologies. The purposes of the airport categorization task were (1) to facilitate initial AeroMACS architecture designs and enable budgetary projections by creating a set of airport categories based on common airport characteristics and design objectives, and (2) to offer high-level guidance to potential AeroMACS technology and policy development sponsors and service providers. A channelization plan methodology was developed because a common global methodology is needed to assure seamless interoperability among diverse AeroMACS services potentially supplied by multiple service providers

SDSF : social-networking trust based distributed data storage and co-operative information fusion.

As of 2014, about 2.5 quintillion bytes of data are created each day, and 90% of the data in the world was created in the last two years alone. The storage of this data can be on external hard drives, on unused space in peer-to-peer (P2P) networks or using the more currently popular approach of storing in the Cloud. When the users store their data in the Cloud, the entire data is exposed to the administrators of the services who can view and possibly misuse the data. With the growing popularity and usage of Cloud storage services like Google Drive, Dropbox etc., the concerns of privacy and security are increasing. Searching for content or documents, from this distributed stored data, given the rate of data generation, is a big challenge. Information fusion is used to extract information based on the query of the user, and combine the data and learn useful information. This problem is challenging if the data sources are distributed and heterogeneous in nature where the trustworthiness of the documents may be varied. This thesis proposes two innovative solutions to resolve both of these problems. Firstly, to remedy the situation of security and privacy of stored data, we propose an innovative Social-based Distributed Data Storage and Trust based co-operative Information Fusion Framework (SDSF). The main objective is to create a framework that assists in providing a secure storage system while not overloading a single system using a P2P like approach. This framework allows the users to share storage resources among friends and acquaintances without compromising the security or privacy and enjoying all the benefits that the Cloud storage offers. The system fragments the data and encodes it to securely store it on the unused storage capacity of the data owner\u27s friends\u27 resources. The system thus gives a centralized control to the user over the selection of peers to store the data. Secondly, to retrieve the stored distributed data, the proposed system performs the fusion also from distributed sources. The technique uses several algorithms to ensure the correctness of the query that is used to retrieve and combine the data to improve the information fusion accuracy and efficiency for combining the heterogeneous, distributed and massive data on the Cloud for time critical operations. We demonstrate that the retrieved documents are genuine when the trust scores are also used while retrieving the data sources. The thesis makes several research contributions. First, we implement Social Storage using erasure coding. Erasure coding fragments the data, encodes it, and through introduction of redundancy resolves issues resulting from devices failures. Second, we exploit the inherent concept of trust that is embedded in social networks to determine the nodes and build a secure net-work where the fragmented data should be stored since the social network consists of a network of friends, family and acquaintances. The trust between the friends, and availability of the devices allows the user to make an informed choice about where the information should be stored using `k\u27 optimal paths. Thirdly, for the purpose of retrieval of this distributed stored data, we propose information fusion on distributed data using a combination of Enhanced N-grams (to ensure correctness of the query), Semantic Machine Learning (to extract the documents based on the context and not just bag of words and also considering the trust score) and Map Reduce (NSM) Algorithms. Lastly we evaluate the performance of distributed storage of SDSF using era- sure coding and identify the social storage providers based on trust and evaluate their trustworthiness. We also evaluate the performance of our information fusion algorithms in distributed storage systems. Thus, the system using SDSF framework, implements the beneficial features of P2P networks and Cloud storage while avoiding the pitfalls of these systems. The multi-layered encrypting ensures that all other users, including the system administrators cannot decode the stored data. The application of NSM algorithm improves the effectiveness of fusion since large number of genuine documents are retrieved for fusion

Architectural Support for High-Performance, Power-Efficient and Secure Multiprocessor Systems

High performance systems have been widely adopted in many fields and the demand for better performance is constantly increasing. And the need of powerful yet flexible systems is also increasing to meet varying application requirements from diverse domains. Also, power efficiency in high performance computing has been one of the major issues to be resolved. The power density of core components becomes significantly higher, and the fraction of power supply in total management cost is dominant. Providing dependability is also a main concern in large-scale systems since more hardware resources can be abused by attackers. Therefore, designing high-performance, power-efficient and secure systems is crucial to provide adequate performance as well as reliability to users. Adhering to using traditional design methodologies for large-scale computing systems has a limit to meet the demand under restricted resource budgets. Interconnecting a large number of uniprocessor chips to build parallel processing systems is not an efficient solution in terms of performance and power. Chip multiprocessor (CMP) integrates multiple processing cores and caches on a chip and is thought of as a good alternative to previous design trends. In this dissertation, we deal with various design issues of high performance multiprocessor systems based on CMP to achieve both performance and power efficiency while maintaining security. First, we propose a fast and secure off-chip interconnects through minimizing network overheads and providing an efficient security mechanism. Second, we propose architectural support for fast and efficient memory protection in CMP systems, making the best use of the characteristics in CMP environments and multi-threaded workloads. Third, we propose a new router design for network-on-chip (NoC) based on a new memory technique. We introduce hybrid input buffers that use both SRAM and STT-MRAM for better performance as well as power efficiency. Simulation results show that the proposed schemes improve the performance of off-chip networks through reducing the message size by 54% on average. Also, the schemes diminish the overheads of bounds checking operations, thus enhancing the overall performance by 11% on average. Adopting hybrid buffers in NoC routers contributes to increasing the network throughput up to 21%

A graph-based approach for modelling quantum circuits

A crucial task for the systematic application of model-driven engineering techniques in the development of quantum software is the definition of metamodels, as a first step towards automatic code generation and integration with other tools. The importance is even greater when considering recent work where the first extensions to UML for modelling quantum circuits are emerging and the characterisation of these extensions in terms of their suitability for a model-driven approach becomes unavoidable. After reviewing the related work, this article proposes a unified metamodel for modelling quantum circuits, together with five strategies for its use and some examples of its application. The article also provides a set of constraints for using the identified strategies, a set of procedures for transforming the models between the strategies, and an analysis of the suitability of each strategy for performing common tasks in a model-driven quantum software development environment. All of these resources will enable the quantum software community to speak the same language and use the same set of abstractions, which are key to furthering the development of tools to be built as part of future model-driven quantum software development frameworks

Large Geographical Area Aerial Surveillance Systems Data Network Infrastructure Managed by Artificial Intelligence and Certified Over Blockchain: a Review

This paper proposes an aerial data network infrastructure for large geographical area surveillance systems. The work presents a review of previous works from the authors, existing technologies in the market and other scientific work, with the goal of creating a data network supported by Autonomous Tethered Aerostat Airships used for sensor fixing, drones deployment base and meshed data network nodes installation. The proposed approach for data network infrastructure supports several independent and heterogeneous services from independent, private and public companies. The presented solution employs Edge Artificial Intelligence (AI) systems for autonomous infrastructure management. The Edge AI used in the presented solution enables the AI management solution to work without the need of a permanent connection to cloud services and is constantly feed by the locally generated sensor data. These systems interact with other network AI services to accomplish coordinated tasks. Blockchain technology services are deployed to ensure secure and auditable decisions and operations, validated by the different involved ledgers

A NOVEL FRAMEWORK FOR SOCIAL INTERNET OF THINGS: LEVERAGING THE FRIENDSHIPS AND THE SERVICES EXCHANGED BETWEEN SMART DEVICES

As humans, we tackle many problems in complex societies and manage the complexities of networked social systems. Cognition and sociability are two vital human capabilities that improve social life and complex social interactions. Adding these features to smart devices makes them capable of managing complex and networked Internet of Things (IoT) settings. Cognitive and social devices can improve their relationships and connections with other devices and people to better serve human needs. Nowadays, researchers are investigating two future generations of IoT: social IoT (SIoT) and cognitive IoT (CIoT). This study develops a new framework for IoT, called CSIoT, by using complexity science concepts and by integrating social and cognitive IoT concepts. This framework uses a new mechanism to leverage the friendships between devices to address service management, privacy, and security. The framework addresses network navigability, resilience, and heterogeneity between devices in IoT settings. This study uses a new simulation tool for evaluating the new CSIoT framework and evaluates the privacy-preserving ability of CSIoT using the new simulation tool. To address different CSIoT security and privacy issues, this study also proposes a blockchain-based CSIoT. The evaluation results show that CSIoT can effectively preserve the privacy and the blockchain-based CSIoT performs effectively in addressing different privacy and security issues

Engage D2.6 Annual combined thematic workshops progress report (series 2)

The preparation, organisation and conclusions from the thematic challenge workshops, two ad hoc technical workshops, a technical session on data and a MET/ENV workshop held in 2019 and 2020 are described. Partly due to Covid-19, two of the 2020 thematic challenge workshops scheduled to take place at the end of 2020 were re-scheduled to January 2021. We also report on the preparation for these two workshops, while the conclusions will be included in the next corresponding deliverable

Contrastive Prompt Learning-based Code Search based on Interaction Matrix

Code search aims to retrieve the code snippet that highly matches the given query described in natural language. Recently, many code pre-training approaches have demonstrated impressive performance on code search. However, existing code search methods still suffer from two performance constraints: inadequate semantic representation and the semantic gap between natural language (NL) and programming language (PL). In this paper, we propose CPLCS, a contrastive prompt learning-based code search method based on the cross-modal interaction mechanism. CPLCS comprises:(1) PL-NL contrastive learning, which learns the semantic matching relationship between PL and NL representations; (2) a prompt learning design for a dual-encoder structure that can alleviate the problem of inadequate semantic representation; (3) a cross-modal interaction mechanism to enhance the fine-grained mapping between NL and PL. We conduct extensive experiments to evaluate the effectiveness of our approach on a real-world dataset across six programming languages. The experiment results demonstrate the efficacy of our approach in improving semantic representation quality and mapping ability between PL and NL

Designing a Framework for Exchanging Partial Sets of BIM Information on a Cloud-Based Service

The rationale behind this research study was based on the recognised difficulty of exchanging data at element or object level due to the inefficiencies of compatible hardware and software. Interoperability depicts the need to pass data between applications, allowing multiple types of experts and applications to contribute to the work at hand. The only way that software file exchanges between two applications can produce consistent data and change management results for large projects is through a building model repository. The overall aim of this thesis was to design and develop an integrated process that would advance key decisions at an early design stage through faster information exchanges during collaborative work. In the construction industry, Building Information Modeling is the most integrated shared model between all disciplines. It is based on a manufacturing-like process where standardised deliverables are used throughout the life cycle with effective collaboration as its main driving force. However, the dilemma is how to share these properties of BIM applications on one single platform asynchronously. Cloud Computing is a centralized heterogeneous network that enables different applications to be connected to each other. The methodology used in the research was based on triangulation of data which incorporated many techniques featuring a mixture of both quantitative and qualitative analysis. The results identified the need to re-engineer Simplified Markup Language, in order to exchange partial data sets of intelligent object architecture on an integrated platform. The designed and tested prototype produced findings that enhanced project decisions at a relatively early design stage, improved communication and collaboration techniques and cross disciple co-ordination