Leveraging and Fusing Civil and Military Sensors to support Disaster Relief Operations in Smart Environments

Natural disasters occur unpredictably and can range in severity from something locally manageable to large scale events that require external intervention. In particular, when large scale disasters occur, they can cause widespread damage and overwhelm the ability of local governments and authorities to respond. In such situations, Civil-Military Cooperation (CIMIC) is essential for a rapid and robust Humanitarian Assistance and Disaster Relief (HADR) operation. These type of operations bring to bear the Command and Control (C2) and Logistics capabilities of the military to rapidly deploy assets to help with the disaster relief activities. Smart Cities and Smart Environments, embedded with IoT, introduce multiple sensing modalities that typically provide wide coverage over the deployed area. Given that the military does not own or control these assets, they are sometimes referred to as gray assets, which are not as trustworthy as blue assets, owned by the military. However, leveraging these gray assets can significantly improve the ability for the military to quickly obtain Situational Awareness (SA) about the disaster and optimize the planning of rescue operations and allocation of resources to achieve the best possible effects. Fusing the information from the civilian IoT sensors with the custom military sensors could help validate and improve trust in the information from the gray assets. The focus of this paper is to further examine this challenge of achieving Civil-Military cooperation for HADR operations by leveraging and fusing information from gray and blue assets

Leveraging Crowdsourcing and Crowdsensing Data for HADR Operations in a Smart City Environment

The future of the world's population concentration lies within the bounds of urban cities. Citizens, or humans, are the most important tangible resources in a smart city environment, and they need to be served as well as protected. The concept of smart cities is trying to accomplish the idea of serving the citizens by leveraging the potential of information and communications technology assets. Citizens have access to smart technologies and applications, and thus they form an indispensable component to complement and supplement a smart city's operation. Especially in humanitarian assistance and disaster recovery (HADR) operations, where a smart city's core infrastructure might be compromised, the assets of citizens can be put to use. This article aims to describe the current state of affairs for safety in cities and humanitarian assistance in emergency situations, which require leveraging situational awareness data. We discuss and propose mechanisms for connecting to and utilizing crowdsourcing and crowdsensing data in a smart city environment, which can assist in efficient HADR operations

MARGOT: Dynamic IoT Resource Discovery for HADR Environments

Smart City services leverage sophisticated IT architectures whose assets are deployed in dynamic and heterogeneous computing and communication scenarios. Those services are particularly interesting for Humanitarian Assistance and Disaster Relief (HADR) operations in urban environments, which could improve Situation Awareness by exploiting the Smart City IT infrastructure. To this end, an enabling requirement is the discovery of the available Internet-of-Things (IoT) resources, including sensors, actuators, services, and computing resources, based on a variety of criteria, such as geographical location, proximity, type of device, type of capability, coverage, resource availability, and communication topology / quality of network links. To date, no single standard has emerged that has been widely adopted to solve the discovery challenge. Instead, a variety of different standards have been proposed and cities have either adopted one that is convenient or reinvented a new standard just for themselves. Therefore, enabling discovery across different standards and administrative domains is a fundamental requirement to enable HADR operations in Smart Cities. To address these challenges, we developed MARGOT (Multi-domain Asynchronous Gateway Of Things), a comprehensive solution for resource discovery in Smart City environments that implements a distributed and federated architecture and supports a wide range of discovery protocols

Learning to Sail Dynamic Networks: The MARLIN Reinforcement Learning Framework for Congestion Control in Tactical Environments

Conventional Congestion Control (CC) algorithms,such as TCP Cubic, struggle in tactical environments as they misinterpret packet loss and fluctuating network performance as congestion symptoms. Recent efforts, including our own MARLIN, have explored the use of Reinforcement Learning (RL) for CC, but they often fall short of generalization, particularly in competitive, unstable, and unforeseen scenarios. To address these challenges, this paper proposes an RL framework that leverages an accurate and parallelizable emulation environment to reenact the conditions of a tactical network. We also introduce refined RL formulation and performance evaluation methods tailored for agents operating in such intricate scenarios. We evaluate our RL learning framework by training a MARLIN agent in conditions replicating a bottleneck link transition between a Satellite Communication (SATCOM) and an UHF Wide Band (UHF) radio link. Finally, we compared its performance in file transfer tasks against Transmission Control Protocol (TCP) Cubic and the default strategy implemented in the Mockets tactical communication middleware. The results demonstrate that the MARLIN RL agent outperforms both TCP and Mockets under different perspectives and highlight the effectiveness of specialized RL solutions in optimizing CC for tactical network environments.Comment: 6 pages, 4 figures, IEEE conferenc

Modeling Digital Twins of Kubernetes-Based Applications

Kubernetes provides several functions that can help service providers to deal with the management of complex container-based applications. However, most of these functions need a time-consuming and costly customization process to address service-specific requirements. The adoption of Digital Twin (DT) solutions can ease the configuration process by enabling the evaluation of multiple configurations and custom policies by means of simulation-based what-if scenario analysis. To facilitate this process, this paper proposes KubeTwin, a framework to enable the definition and evaluation of DTs of Kubernetes applications. Specifically, this work presents an in- novative simulation-based inference approach to define accurate DT models for a Kubernetes environment. We experimentally validate the proposed solution by implementing a DT model of an image recognition application that we tested under different conditions to verify the accuracy of the DT model. The soundness of these results demonstrates the validity of the KubeTwin approach and calls for further investigation

Securing IoT – Enabled Smart City Services – the Military Perspective

The widespread adoption of Internet-of-Things (IoT) driven technologies in Smart Cities is raising significant cybersecurity issues. The military are well aware of the opportunities and challenges brought by large scale IoT adoption, not just in battlefield but also in urban environments, and are exploring how to exploit those assets for Humanitarian Assistance and Disaster Recovery (HADR), counter-terrorism, and mass protection scenarios. To this end, not only they created specific initiatives, such as the NATO IST-147 Research Task Group on Military Applications of the IoT, to investigate the problem, but are also developing innovative methodologies and tools that represent a paradigm shift with respect to currently proposed approaches

Exploring continuous optimization solutions for business-driven IT management problems

Business-driven IT management practices often involve the performance optimization of a system according to business criteria. The increased attention to dynamical aspects of the system behavior, the preference for simulative approaches rather than analytical ones, and the increased level of complexity posed by business-driven performance evaluation significantly complicate the optimization of BDIM systems and demand a radical rethinking of methodologies and tools. This raises the opportunity to devise and implement common methodology and tools that could be used for a large class of different BDIM optimization problems. This paper proposes a generic framework for the dynamic and adaptive optimization of BDIM systems, introduces the Open Source ruby-mhl metaheuristics library, and provides an experimental evaluation in the context of a realistic case study

Generic Architecture for Edge Computing Based on SPF for Military HADR Operations

Internet-of-Things (IoT) devices have led to ubiquitous, remote and autonomous computing at the edge of the networks. These devices offload sensing, actuation and processing tasks away from the core of the network. The concept of Smart Cities tries to leverage Edge Computing based on IoT technologies for remote and distributed computing. Sieve, Process and Forward (SPF) is a Value-of-Information (VoI) based Fog as a Service (FaaS) solution for dynamic IoT applications in Smart City scenarios. The military has been looking to utilize the SPF platform for Edge Computing to assist in Human Assistance and Disaster Recovery (HADR) operations. A recent NATO IST 147 RTG demonstration proved the validity of SPF, but also highlighted the need of extending the current architecture to support specific use-case scenarios for HADR systems. This paper tries to propose a generic architecture based on SPF to enable interoperability between military C2 (Command and Control) and core computing systems to support future HADR operations in Smart City environments

Proceedings of the 11th International Conference on Network and Service Management (CNSM 2015)

The 11th International Conference on Network and Service Management (CNSM) is a selective single-track conference in the network and service management research area. CNSM 2015 covers all aspects of the management of networks and services, pervasive systems, enterprises, and cloud computing environments. The core track is accompanied by a series of workshops, tutorials and poster sessions