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

Towards Semantic KPI Measurement

Linked Data (LD) represent a great mechanism towards integrating information across disparate sources. The respective technology can also be exploited to perform inferencing for deriving added-value knowledge. As such, LD technology can really assist in performing various analysis tasks over information related to business process execution. In the context of Business Process as a Service (BPaaS), the first real challenge is to collect and link information originating from different systems by following a certain structure. As such, this paper proposes two main ontologies that serve this purpose: a KPI and a Dependency one. Based on these well-connected ontologies, an innovative Key Performance Indicator (KPI) analysis system is then built which exhibits two main analysis capabilities: KPI assessment and drill-down, where the second can be exploited to find root causes of KPI violations. Compared to other KPI analysis systems, LD usage enables the flexible construction and assessment of any KPI kind allowing experts to better explore the possible KPI space

Knowledge visualizations: a tool to achieve optimized operational decision making and data integration

The overabundance of data created by modern information systems (IS) has led to a breakdown in cognitive decision-making. Without authoritative source data, commanders’ decision-making processes are hindered as they attempt to paint an accurate shared operational picture (SOP). Further impeding the decision-making process is the lack of proper interface interaction to provide a visualization that aids in the extraction of the most relevant and accurate data. Utilizing the DSS to present visualizations based on OLAP cube integrated data allow decision-makers to rapidly glean information and build their situation awareness (SA). This yields a competitive advantage to the organization while in garrison or in combat. Additionally, OLAP cube data integration enables analysis to be performed on an organization’s data-flows. This analysis is used to identify the critical path of data throughout the organization. Linking a decision-maker to the authoritative data along this critical path eliminates the many decision layers in a hierarchal command structure that can introduce latency or error into the decision-making process. Furthermore, the organization has an integrated SOP from which to rapidly build SA, and make effective and efficient decisions.http://archive.org/details/knowledgevisuali1094545877Outstanding ThesisOutstanding ThesisMajor, United States Marine CorpsCaptain, United States Marine CorpsApproved for public release; distribution is unlimited

IEEE Access Special Section Editorial: Big Data Technology and Applications in Intelligent Transportation

During the last few years, information technology and transportation industries, along with automotive manufacturers and academia, are focusing on leveraging intelligent transportation systems (ITS) to improve services related to driver experience, connected cars, Internet data plans for vehicles, traffic infrastructure, urban transportation systems, traffic collaborative management, road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plans, and the development of an effective ecosystem for vehicles, drivers, traffic controllers, city planners, and transportation applications. Moreover, the emerging technologies of the Internet of Things (IoT) and cloud computing have provided unprecedented opportunities for the development and realization of innovative intelligent transportation systems where sensors and mobile devices can gather information and cloud computing, allowing knowledge discovery, information sharing, and supported decision making. However, the development of such data-driven ITS requires the integration, processing, and analysis of plentiful information obtained from millions of vehicles, traffic infrastructures, smartphones, and other collaborative systems like weather stations and road safety and early warning systems. The huge amount of data generated by ITS devices is only of value if utilized in data analytics for decision-making such as accident prevention and detection, controlling road risks, reducing traffic carbon emissions, and other applications which bring big data analytics into the picture

Conceptual modelling for integrated decision-making in process systems

This Thesis addresses the systematic construction of Decision Making Models (DMMs) from the conceptualization stage to its application in specific situations, with special emphasis on !he treatment of scenarios where there is a hierarchy of decision levels, common in the Process Systems (PS). Although the methodologies developed are generic, the scope of this Thesis is limited to the perspective of Process Engineering. The central component required to construct a DMM is the conceptual description of the reality, which supports the system alisation of management procedures . During this description, two different dom ains can be identified: the PS Domain, useful to describe the structure of the process as such (physical reality and the way in which its elements are related), and the Management Domain, identified in this Thesis as associated with the Conceptual Constraints (CC) that describe the restrictions associated with the management of the process . In this way, the PS Domain includes concepts and relationships that appear in the control standards of the process followed by the company: the description of the process to be developed, the description of the physical equipment in which it is developed , and that of its interactions, giving rise to the control of the execution of the procedures; this domain should allow managing the construction, design, operation and control of any manufacturing system. On the other hand, the CC Domain contains the information associated with the concepts and relationships that m ust be fulfilled to ensure a coherent set of decisions, with the purpose of identifying and representing the systematics to follow during the decision-making process, giving rise to the conceptual representation of this system and, finally, the construction of the corresponding DMM. The first challenge addressed in this thesis is associated with the systematisation of conceptual modelling from semantic information, for the construction ofontologies from textual sources and a procedure to verify the interna! coherence of lhese sources. The application of this methodology has been used for the identification of the essential concepts and relationships in the PS Domain, allowing creating a generic, common and shared model, unlike the existing models. In the next step, this PS Domain has been used to solve management problems in systems that comprise multi-level hierarchies. The resulting decision-making process allows integrating the decisions made al each level, ensuring their consistency from an approach that simultaneously considers the management of all available information (data and knowledge). On the other hand, the introduction of the necessary concepts and relationships to ensure the feasibility of the process management decisions, through the CC Domain, allows the development of systematic DMM creation procedures: this domain classifies the constrains (balances, sequence, etc.), adds abstrae! elements to them (e.g.: produced and consumed amounts) and allows to generalize the relation of its compone nis with the information associated to the PS Domain. The last part of this Thesis deals with the integration of the PS and CC Domains, and their application for the generation of new decision-making systems . For this, algorithms have been designed that, starting from the previously identified and classified restrictions, and patterns of DMMs also previously identified from existing cases, exploit the information available through the instances in the PS Domain, to generate new DMMs according to the user's specifications. lts use is illustrated through cases from different environments, demonstrating the generalisation capacity of the created systematics.Esta Tesis aborda la construcción sistemática de Modelos para la toma de Decisiones (DMMs) desde la etapa de conceptualización hasta su aplicación en situaciones concretas, con especial énfasis en el tratamiento de escenarios en los que existe una jerarquía de niveles de decisión, habitual en la Industria de Proceso (PS). Aunque las metodologías desarrolladas son genéricas, el alcance de esta Tesis se limita a la perspectiva de la Ingeniería de Procesos. El componente central requerido para construir un DMMs es la descripción conceptual de la realidad a la que se orienta, que a su vez respalda la sistematización de los procedimientos de gestión. Durante esta descripción, se pueden identificar planteamientos asociados a dos dominios diferentes: el Dominio del Proceso (PS), útil para describir la estructura del proceso como tal (realidad física y forma en la que se relacionan sus elementos), y el Dominio de Gestión, asociado a las Restricciones Conceptuales (CC) que describen las restricciones asociadas a la gestión del proceso. El Dominio PS incluye conceptos y relaciones que aparecen en los estándares de control del proceso que sigue la empresa: la descripción del proceso a desarrollar, la descripción de los equipos físicos en los que se desarrolla, y la de sus interacciones, que dan lugar al control de ejecución de los procedimientos; este dominio debe permitir la construcción, el diseño, la operación y el control de cualquier sistema de fabricación. Por su parte, el Dominio CC contiene la información asociada a los conceptos y las relaciones que deben cumplirse para asegurar un conjunto coherente de decisiones, con el propósito de identificar y representar la sistemática a seguir durante el proceso de toma de decisiones, dando lugar a la representación conceptual de esta sistemática y, finalmente, a la construcción del correspondiente DMM. El primer reto abordado en esta Tesis está asociado a la sistematización del modelado conceptual a partir de información semántica, para construcción de ontologías a partir de fuentes textuales y de un procedimiento para verificar la coherencia interna de dichas fuentes. La aplicación de esta metodología se ha utilizado para la identificación de los conceptos y las relaciones esenciales en el Dominio PS, permitiendo crear un modelo genérico, común y compartido, a diferencia de los modelos existentes. En el siguiente paso, este Dominio PS se ha utilizado para la resolución de problemas de gestión en sistemas que comprenden múltiples niveles de jerarquías funcionales. El proceso de toma de decisiones resultante permite integrar las decisiones tomadas en cada nivel, asegurando su coherencia a partir de un enfoque que contempla simultáneamente la gestión de toda la información disponible (datos y conocimiento). Por su parte, la introducción de los conceptos y relaciones necesarios para asegurar la factibilidad de las decisiones de gestión del proceso, a través del Dominio CC, permite el desarrollo de procedimientos sistemáticos de creación de DMMs: este Dominio clasifica las restricciones (balances, secuencia, etc.), agrega elementos abstractos a dichas restricciones (p.e.: cantidad producida y consumida) y permite generalizar la relación de sus componentes con la información asociada al Dominio PS. En la última parte de esta Tesis se aborda la integración de los Dominios PS y CC, y su aplicación para la generación de nuevos sistemas de toma de decisiones. Para ello, se han diseñado algoritmos que, partiendo de las restricciones anteriormente identificadas y clasificadas, y patrones de DMMs también previamente identificados a partir de casos ya existentes, explotan la información disponible a través de las instancias del Dominio PS, para generar de nuevos modelos de toma de decisión de acuerdo con las especificaciones del usuario. Su utilización se ilustra a través de casos procedentes de diferentes entornos, demostrando la capacidad de generalización de la sistemática creada.Postprint (published version

Promoting Resilience of the Nigerian Aviation Industry Through Management Information System Capability: A Conceptual Model

Organisational resilience commands the attention of scholars and industry gatekeepers due to its attendant outcomes, which include competitiveness, growth, innovativeness and the ability to rebound from crises; and thrive on the edge of a complex and tumultuous business environment. Several studies have been conducted on the nexus between various constructs and organisational resilience. However, there is scant literature that illuminates the path between management information system capability and organisational resilience. Moreover, the concept of resilience has suffered from semantic pluralism, thereby leading to a confusing maze of measures. This paper distills the concept of resilience from literature and concludes that anticipatory ability, robustness, adaptability and agility capture the nuances of organisational resilience. Finally, this paper proposes a theorising logic that infrastructural operation capability, systems development capability, service support maturity and managerial skills are facets of management information system capability which holds the promise of amplifying the resilience of the Nigerian Aviation Industry. The theorising logic of this paper is presented as a conceptual model which opens several windows for testing. Keywords: Management information system capability, organisational resilience, Nigerian aviation industr

Dynamics in Logistics

This open access book highlights the interdisciplinary aspects of logistics research. Featuring empirical, methodological, and practice-oriented articles, it addresses the modelling, planning, optimization and control of processes. Chiefly focusing on supply chains, logistics networks, production systems, and systems and facilities for material flows, the respective contributions combine research on classical supply chain management, digitalized business processes, production engineering, electrical engineering, computer science and mathematical optimization. To celebrate 25 years of interdisciplinary and collaborative research conducted at the Bremen Research Cluster for Dynamics in Logistics (LogDynamics), in this book hand-picked experts currently or formerly affiliated with the Cluster provide retrospectives, present cutting-edge research, and outline future research directions

A vector symbolic approach for cognitive services and decentralized workflows

The proliferation of smart devices and sensors known as the Internet of Things (IoT), along with the transformation of mobile phones into powerful handheld computers as well as the continuing advancement in high-speed communication technologies, introduces new possibilities for collaborative distributed computing and collaborative workflows along with a new set of problems to be solved. However, traditional service-based applications, in fixed networks, are typically constructed and managed centrally and assume stable service endpoints and adequate network connectivity. Constructing and maintaining such applications in dynamic heterogeneous wireless networked environments, where limited bandwidth and transient connectivity are commonplace, presents significant challenges and makes centralized application construction and management impossible. The key objective for this thesis can be summarised as follows: a means is required to discover and orchestrate sequences of micro-services, i.e., workflows, on-demand, using currently available distributed resources (compute devices, functional services, data and sensors) in spite of a poor quality (fragmented, low bandwidth) network infrastructure and without central control. It is desirable to be able to compose such workflows on-the-fly in order to fulfil an ‘intent’. The research undertaken investigates how service definition, service matching and decentralised service composition and orchestration can be achieved without centralised control using an approach based on a Binary Spatter Code Vector Symbolic Architec-ture and shows that the approach offers significant advantages in environments where communication networks are unreliable. The outcomes demonstrate a new cognitive workflow model that uses one-to-many communications to enable intelligent cooperation between self-describing service entities that can self-organise to complete a workflow task. Workflow orchestration overhead was minimised using two innovations, a local arbitration mechanism that uses a delayed response mechanism to suppress responses that are not an ideal match and the holographic nature of VSA descriptions enables messages to be truncated without loss of meaning. A new hierarchical VSA encoding scheme was created that is scaleable to any number of vector embeddings including workflow steps. The encoding can also facilitate learning since it provides unique contexts for each step in a workflow. The encoding also enables service pre-provisioning because individual workflow steps can be decoded easily by any service receiving a multicast workflow vector. This thesis brings the state-of-the-art closer to the ability to discover distributed services on-the-fly to fulfil an intent and without the need for centralised management or the imperative definition of all service steps, including locations. The use of a mathematically deterministic distributed vector representation in the form of BSC vectors for both service objects and workflows enables a common language for all elements required to discover and execute workflows in decentralised transient environments and opens up the possibilities of employing learning algorithms that can advance the state-of-the-art in distributed workflows towards a true cognitive distributed network architectur

Quantify resilience enhancement of UTS through exploiting connect community and internet of everything emerging technologies

This work aims at investigating and quantifying the Urban Transport System (UTS) resilience enhancement enabled by the adoption of emerging technology such as Internet of Everything (IoE) and the new trend of the Connected Community (CC). A conceptual extension of Functional Resonance Analysis Method (FRAM) and its formalization have been proposed and used to model UTS complexity. The scope is to identify the system functions and their interdependencies with a particular focus on those that have a relation and impact on people and communities. Network analysis techniques have been applied to the FRAM model to identify and estimate the most critical community-related functions. The notion of Variability Rate (VR) has been defined as the amount of output variability generated by an upstream function that can be tolerated/absorbed by a downstream function, without significantly increasing of its subsequent output variability. A fuzzy based quantification of the VR on expert judgment has been developed when quantitative data are not available. Our approach has been applied to a critical scenario (water bomb/flash flooding) considering two cases: when UTS has CC and IoE implemented or not. The results show a remarkable VR enhancement if CC and IoE are deploye