Seamlessly integrated, but loosely coupled

In this chapter, authority is developed as key concept for analyzing the global governance system. Max Weber’s foundational treatment is used to capture the paradox involved in the notion of “voluntary subordination.” Building on this foundation, the concept of reflexive authority is elaborated in contrast to two other concepts that have prevailed in international relations so far. The argument is laid out against the background of the global governance context, one in which the authority holders are in many respects weaker than most state actors. Two types of reflexive authority are identified: epistemic and political authority. Finally, the interplay between different authorities in global governance is analyzed to identify the major features of the global governance system. It is—to put it in the shortest possible form—a system of only loosely coupled spheres of authorities that is not coordinated by a meta-authority and lacks a proper separation of powers.

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Immunizer: A Scalable Loosely-Coupled Self-Protecting Software Framework using Adaptive Microagents and Parallelized Microservices

2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE) ◽

10.1109/wetice49692.2020.00013 ◽

2020 ◽

Author(s):

Omar Iraqi ◽

Hanan El Bakkali

Keyword(s):

Software Framework ◽

Loosely Coupled

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Simulation and Relationship Strength: Characteristics of Knowledge Flows Among Subjects in a Regional Innovation System

Science Technology and Society ◽

10.1177/09717218211020476 ◽

2021 ◽

pp. 097172182110204

Author(s):

Yi Su ◽

Xuesong Jiang ◽

Zhouzhou Lin

Keyword(s):

Innovation System ◽

Small World ◽

Coupled System ◽

Mean Value ◽

Knowledge Flows ◽

Knowledge Flow ◽

Regional Innovation System ◽

Regional Innovation ◽

Relationship Strength ◽

Loosely Coupled

A small-world simulation model of a regional innovation system combining the strength of the intersubject relationship of the regional innovation system with the loosely coupled system is constructed. We use a simulation to observe knowledge flow within the regional innovation system under relationships of varying strength. The results show that when the relationship between the subjects of the regional innovation system reaches a certain strength, the system will exhibit high module independence and high network integrity, forming a loosely coupled system. The knowledge flow in the system exhibits the emergence of a fast flow rate, a high mean value and little variance. When relationship strength is at other levels, the emergence of knowledge cannot be identified.

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A Survey on Edge Performance Benchmarking

ACM Computing Surveys ◽

10.1145/3444692 ◽

2021 ◽

Vol 54 (3) ◽

pp. 1-33

Author(s):

Blesson Varghese ◽

Nan Wang ◽

David Bermbach ◽

Cheol-Ho Hong ◽

Eyal De Lara ◽

...

Keyword(s):

Large Scale ◽

Future Internet ◽

Coupled Systems ◽

Operational Conditions ◽

Loosely Coupled ◽

Performance Benchmarking ◽

The Past ◽

Geographically Dispersed ◽

Tightly Coupled ◽

History Of

Edge computing is the next Internet frontier that will leverage computing resources located near users, sensors, and data stores to provide more responsive services. Therefore, it is envisioned that a large-scale, geographically dispersed, and resource-rich distributed system will emerge and play a key role in the future Internet. However, given the loosely coupled nature of such complex systems, their operational conditions are expected to change significantly over time. In this context, the performance characteristics of such systems will need to be captured rapidly, which is referred to as performance benchmarking, for application deployment, resource orchestration, and adaptive decision-making. Edge performance benchmarking is a nascent research avenue that has started gaining momentum over the past five years. This article first reviews articles published over the past three decades to trace the history of performance benchmarking from tightly coupled to loosely coupled systems. It then systematically classifies previous research to identify the system under test, techniques analyzed, and benchmark runtime in edge performance benchmarking.

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