Scalable OneM2M IoT Open-Source Platform Evaluated in an SDN Optical Network Controller Scenario

Software Defined Networking represents a mature technology for the control of optical networks, though all open controller implementations present in the literature still lack the adequate level of maturity and completeness to be considered for (pre)-production network deployments. This work aims at experimenting on, assessing and discussing the use of the OneM2M open-source platform in the context of optical networks. Network elements and devices are implemented as IoT devices, and the control application is built on top of an OneM2M-compliant server. The work concretely addresses the scalability and flexibility performances of the proposed solution, accounting for the expected growth of optical networks. The two experiment scenarios show promising results and confirm that the OneM2M platform can be adopted in such a context, paving the way to other researches and studies.

Different roots, intertwined branches: linking International Business and Economic Geography through the Uppsala Model and Global Production Network

PurposeThe aim of this study is to propose a link between international business (IB) and economic geography, which are two streams of thought that have developed without one acknowledging the other. We use the Uppsala model and the Global Production Network as pillars to sustain this link. We expect that this research triggers a collaboration with allied social sciences in important debates surrounding the business-societal interface.Design/methodology/approachWe selected papers produced by Johanson and Vahlne to understand the development of the Uppsala model over 40 years. The same was done with the Global Production Network, where we scrutinized the work of Henderson, Coe, Dicken, Hess and Yeung – scholars from the Manchester School of Geography – in the last twenty years. Based on Humphrey et al. (2019), we applied an inductive and inferential approach to uncover similarities and differences between the Uppsala model and Global Production Network.FindingsThe Uppsala model reinforces the strategic role of network position in the internationalization process, while the Global Production Network aims to explain how the governance of global firms scattered world-wide affects the development and upgrading opportunities of the various regions and firms involved. Despite these clear differences, the geographical nature of IB and shared similarities accounting the network as a channel to foster and provide access to important resources and practices regarding management, coordination and governance of dispersed parts of multinational enterprises give room to using these two theories as pillars to link IB and economic geography.Originality/valueWhile attempts to link IB and economic geography are not new, none of these studies have focused on the Uppsala model and Global Production Network as pillars to create a link. We foresee an intense cross collaboration and an even possible renaissance of IB and economic geography to target the ever-changing business environment and its impact on social and economic development.

Globalization and Trade in the Post-Covid World

The COVID-19 pandemic brought an extraordinary disturbance regarding the worldwide economy and global trade, as creation and utilization downsized. Perhaps the best methodology for addressing this type of emergency is convenient, unspoiled information. An informed public is better established to use wise judgment including on cases recognized for trade. This is the situation, and a devoted page at WTO site has been created. This will provide present data related with trade information. The chapter discusses rising protectionism in course of the last half period, unexpected monetary crises created by the pandemic, disturbances regarding production network movement, and shocks related to market interest. Reporters worldwide have trumpeted the 'finish' of globalization.

Blockchain-Based IoT Devices in Supply Chain Management: A Systematic Literature Review

Through recent progress, the forms of modern supply chains have evolved into complex networks. The supply chain management systems face a variety of challenges. These include lack of visibility of the upstream party (Provider) to the downstream party (Client); lack of flexibility in the face of sudden variations in demand and control of operating costs; lack of reliance on safety stakeholders; ineffective management of supply chain risks. Blockchain (BC) is used in the supply chain to overcome the growing demands for items. The Internet of Things (IoT) is a profoundly encouraging innovation that can help companies observe, track, and monitor products, activities, and processes within their respective value chain networks. Research establishments and logical gatherings are ceaselessly attempting to answer IoT gadgets in supply chain management. This paper presents orderly writing on and reviewing of Blockchain-based IoT advances and their current usage. We discuss the smart devices used in this system and which device is the most appropriate in the supply chain. This paper also looks at future examination themes in blockchain-based IoT, referred to as the executive’s framework production network. The essential deliberate writing audit has been consolidated by surveying research articles circulated in highly reputable publications between 2016 and 2021. Lastly, current issues and challenges are present to provide researchers with promising future directions in IoT supply chain management systems.

Unifying of Steady State and Transient Simulations Methodologies for Increasing Oil Production of Integrated Network of Wells, Pipeline and Topside Processing Equipment

Aging facilities and increasing complexity in operations (e.g., increasing water cut, slugging, sand or wax production) continue to widen the gap between actual production and the full potential of the field. To enable production optimization scenarios within an integrated system comprises of reservoirs, wells and surface facilities, the application of an integrated network modelling has been applied. The highlight of this paper is the synergy of Integrated Production Network Modelling (IPNM) utilizing Steady State Simulator (PROSPER-GAP) and the Transient Simulator (OLGA) tools to identify potential quick gains through gaslift optimization as well as mid and long-term system optimization alternatives. The synergy enables significant reduction in transient simulation time and reduced challenges in OLGA well matching, especially in selecting accurate modelling parameters e.g., well inflow performance (validated well (string) production data, reservoir pressure, temperature and fluid properties and the Absolute Open Flow (AOF) of each well). The paper showcased the successful production gain achieved as well as the workflows and methodologies applied for both Steady State Integrated Production Modelling (IPM Steady State) and Integrated Transient Network Modelling (IPM Transient) as tools for production enhancement. Even though IPM Steady State shows promising results in term of field optimization potential, to increase accuracy and reduce uncertainties, IPM Transient is recommended to be performed to mimic the actual transient phenomena happening in the well to facilities

Companies under stress: the impact of shocks on the production network

In this paper we analyze the effect of shocks in production networks. Our work is based on a rich dataset that contains information about companies from Slovenia right after the financial crisis of 2008. The processed data spans for 8 years and covers the transaction history as well as performance indicators and various metadata of the companies. We define sales shocks at different levels, and identify companies impacted by them. Next we investigate stress, the potential immediate upstream and downstream impact of a shock within the production network. We base our main findings on a matched pairs analysis of stressed companies. We find that both shock and stress are associated with reporting bankruptcy in the future and that stress foremost impacts the future sales of customers. Furthermore, we find evidence that stress not only results in performance losses but the reconfiguration of the production network as well. We show that stressed companies actively seek for new trading partners, and that these new links often share the industry of the shocked company. These results suggest that both stressed customers and suppliers react quickly to stress and adjust their trading relationships.

Adoption of Integrated Asset Modeling Approach to Kick-Start the Corporate Digital Transformation Strategy

The adoption of an integrated asset modeling approach was explored to kick-start the corporate digital transformation strategy for its oil and gas section. Besides the integrated asset model, the digital initiatives included predictive maintenance, well performance optimization, and a flow assurance advisor aimed at daily production operations and maintenance, creating a pathway to the digital oilfield (DOF). The integrated asset model would be the main pillar of DOF realization and implementation, its offered technology aimed at short-term, medium-term, and long-term planning. The adopted well-proven integrated asset modeling methodology enabled a geological complex with a high-fidelity physics reservoir model, multiple interdependent wells, pipeline networks, process facility models to be integrated seamlessly on a single platform for validation of its existing production operation strategy and field development plan. The black-oil reservoir model was history matched, and the production network models had detailed wellbore and pipeline hydraulics calibrated with the latest well-test data. The compositional fluid modeling allowed the capture of any flow assurance issues that arose across the networks, which were mapped to the corresponding process facility models with physical specifications and operational constraints defined. A fully integrated asset model was developed for the studied asset, where liquid/vapor tables were prepared for black-oil delumping (Ghorayeb and Holmes, 2005) of the reservoir models to surface network models (Mora et al. 2015), while fluid models of both production network and process models were validated before mapping to ensure fluid fidelity. The availability of this integrated asset model with an embedded spreadsheet program incorporating some simple economic calculations allowed the flexibility of short-term production optimization and long-term asset planning, which was focused to provide all the vital valuable inputs to better field management, fast and accurate decision making, and optimum safe operation of process units in meeting the sales contract. The integrated asset model offered a platform for engineers from different domains to collaborate with aligned common operational and planning objectives. It empowered assessments of production operation strategy and field development scenarios conducted at full field level from pore to process. The customized reporting, the ability to connect to other tools, and to push results to dashboards helped to kick-start the corporate digital transformation strategy.

The Spreading of Shocks in the North America Production Network and Its Relation to the Properties of the Network

We evaluate the short-run effect of a shock in the manufacturing sector in the North America Production Network. We use input–output data for Canada, Mexico, the USA, and the North America region. With this data we represent the economies as networks and apply a network diffusion model and execute computer simulations according to different escenarios. We then study the relation between the effects of the shock and the structure of the networks by computing structural properties of sectors. Results show the limited effects of a shock on the manufacturing sector, and thus shed light on the heterogeneous impacts of the trade agreement of the region. They provide useful information to design an industrial policy focused on the development of the production network. In particular, we focus on recommendations for the Mexican economy.