Maritime information sharing environment deployment using the advanced multilayered Data Lake capabilities: EFFECTOR project case study

Establishing an efficient information sharing network among national agencies in maritime domain is of essential importance in enhancing the operational performance, increasing the situational awareness and enabling interoperability among all involved maritime surveillance assets. Based on various data-driven technologies and sources, the EU initiative of Common Information Sharing Environment (CISE), enables the networked participants to timely exchange information concerning vessel traffic, joint SAR & operational missions, emergency situations and other events at sea. In order to host and process vast amounts of vessels and related maritime data consumed from heterogeneous sources (e.g. SAT-AIS, UAV, radar, METOC), the deployment of big data repositories in the form of Data Lakes is of great added value. The different layers in the Data Lakes with capabilities for aggregating, fusing, routing and harmonizing data are assisted by decision support tools with combined reasoning modules with semantics aiming at providing a more accurate Common Operational Picture (COP) among maritime agencies. Based on these technologies, the aim of this paper is to present an end-to-end interoperability framework for maritime situational awareness in strategic and tactical operations at sea, developed in EFFECTOR EU-funded project, focusing on the multilayered Data Lake capabilities. Specifically, a case study presents the important sources and processing blocks, such as the SAT-AIS, CMEMS, UAV components, enabling maritime information exchange in CISE format and communication patterns. Finally, the technical solution is validated in the project’s recently implemented maritime operational trials and the respective results are documented

QoS based Admission Control using Multipath Scheduler for IP over Satellite Networks

This paper presents a novel scheduling algorithm to support quality of service (QoS) for multiservice applications over integrated satellite and terrestrial networks using admission control system with multipath selection capabilities. The algorithm exploits the multipath routing paradigm over LEO and GEO satellites constellation in order to achieve optimum end-to-end QoS of the client-server Internet architecture for HTTP web service, file transfer, video streaming and VoIP applications. The proposed multipath scheduler over the satellite networks advocates load balancing technique based on optimum time-bandwidth in order to accommodate the burst of application traffics. The method tries to balance the bandwidth load and queue length on each link over satellite in order to fulfil the optimum QoS level for each traffic type. Each connection of a traffic type will be routed over a link with the least bandwidth load and queue length at current time in order to avoid congestion state. The multipath routing scheduling decision is based on per connection granularity so that packet reordering at the receiver side could be avoided. The performance evaluation of IP over satellites has been carried out using multiple connections, different file sizes and bit-error-rate (BER) variations to measure the packet delay, loss ratio and throughput

A Secure and Efficient Communications Architecture for Global Information Grid Users via Cooperating Space Assets

With the Information Age in full and rapid development, users expect to have global, seamless, ubiquitous, secure, and efficient communications capable of providing access to real-time applications and collaboration. The United States Department of Defense’s (DoD) Network-Centric Enterprise Services initiative, along with the notion of pushing the “power to the edge,” aims to provide end-users with maximum situational awareness, a comprehensive view of the battlespace, all within a secure networking environment. Building from previous AFIT research efforts, this research developed a novel security framework architecture to address the lack of efficient and scalable secure multicasting in the low earth orbit satellite network environment. This security framework architecture combines several key aspects of different secure group communications architectures in a new way that increases efficiency and scalability, while maintaining the overall system security level. By implementing this security architecture in a deployed environment with heterogeneous communications users, reduced re-keying frequency will result. Less frequent re-keying means more resources are available for throughput as compared to security overhead. This translates to more transparency to the end user; it will seem as if they have a “larger pipe” for their network links. As a proof of concept, this research developed and analyzed multiple mobile communication environment scenarios to demonstrate the superior re-keying advantage offered by the novel “Hubenko Security Framework Architecture” over traditional and clustered multicast security architectures. For example, in the scenario containing a heterogeneous mix of user types (Stationary, Ground, Sea, and Air), the Hubenko Architecture achieved a minimum ten-fold reduction in total keys distributed as compared to other known architectures. Another experiment demonstrated the Hubenko Architecture operated at 6% capacity while the other architectures operated at 98% capacity. In the 80% overall mobility experiment with 40% Air users, the other architectures re-keying increased 900% over the Stationary case, whereas the Hubenko Architecture only increased 65%. This new architecture is extensible to numerous secure group communications environments beyond the low earth orbit satellite network environment, including unmanned aerial vehicle swarms, wireless sensor networks, and mobile ad hoc networks

Data Science, Data Visualization, and Digital Twins

Real-time, web-based, and interactive visualisations are proven to be outstanding methodologies and tools in numerous fields when knowledge in sophisticated data science and visualisation techniques is available. The rationale for this is because modern data science analytical approaches like machine/deep learning or artificial intelligence, as well as digital twinning, promise to give data insights, enable informed decision-making, and facilitate rich interactions among stakeholders.The benefits of data visualisation, data science, and digital twinning technologies motivate this book, which exhibits and presents numerous developed and advanced data science and visualisation approaches. Chapters cover such topics as deep learning techniques, web and dashboard-based visualisations during the COVID pandemic, 3D modelling of trees for mobile communications, digital twinning in the mining industry, data science libraries, and potential areas of future data science development