Fog orchestration for the Internet of Everything: state-of-the-art and research challenges

Velásquez, Karima; Abreu, David Pérez; Assis, Marcio Roberto Miranda; Senna, Carlos; Aranha, Diego F.; Bittencourt, Luiz F.; Laranjeiro, Nuno; Curado, Marília; Vieira, Marco; Monteiro, Edmundo; Madeira, Edmundo Roberto Mauro

doi:10.1186/s13174-018-0086-3

Cited by 79 publications

(51 citation statements)

References 88 publications

(97 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Some mobile applications that perform offloading, such as assisted driving and health monitoring, require resiliency in the communication between mobile devices and fog/cloud. Path splitting and multi-path routing strategies can be applied to provide a certain level of resilience [94]. However, device mobility brings new challenges, in the sense that a mobile device may be connected to different fogs along its path.…”

Section: Mobile Applicationsmentioning

confidence: 99%

The Internet of Things, Fog and Cloud continuum: Integration and challenges

et al. 2018

Self Cite

View full text Add to dashboard Cite

The Internet of Things needs for computing power and storage are expected to remain on the rise in the next decade. Consequently, the amount of data generated by devices at the edge of the network will also grow. While cloud computing has been an established and effective way of acquiring computation and storage as a service to many applications, it may not be suitable to handle the myriad of data from IoT devices and fulfill largely heterogeneous application requirements. Fog computing has been developed to lie between IoT and the cloud, providing a hierarchy of computing power that can collect, aggregate, and process data from/to IoT devices. Combining fog and cloud may reduce data transfers and communication bottlenecks to the cloud and also contribute to reduced latencies, as fog computing resources exist closer to the edge. This paper examines this IoT-Fog-Cloud ecosystem and provides a literature review from different facets of it: how it can be organized, how management is being addressed, and how applications can benefit from it. Lastly, we present challenging issues yet to be addressed in IoT-Fog-Cloud infrastructures. low latency, and mobile applications. The centralized cloud data centers are often physically and/or logically distant from the cloud client, implying communication and data transfers to traverse multiple hops, which introduces delays and consumes network bandwidth of edge and core networks [2].The widespread adoption of cloud computing, combined with the ever increasing ability of edge devices to run heterogeneous applications that generate and consume all kinds of data from a variety of sources, requires novel distributed computing infrastructures that can cope with such heterogeneous application requirements. Computing infrastructures that enact applications at edge devices have started to appear in recent years [3,4], improving aspects such as response time and reducing bandwidth use. Combining the ability of running smaller, localized applications at the edge with the high-capacity from the cloud, fog computing has emerged as an paradigm that can support heterogeneous requirements of small and large applications through multiple layers of a computational infrastructure that combines resources from the edge of the network as well as from the cloud [5].In this paper, we aim at identifying and reviewing the main aspects and challenges that make the combination of fog computing and cloud computing suitable for all kinds of applications leveraged by the Internet of Things. We discuss aspects from the infrastructure (processing, networking, protocols, and infrastructure for 5G support) to applications (smart cities, urban computing, and industry 4.0), passing through the management complexity of the distributed IoT-fog-cloud system (services, resource allocation and optimization, energy consumption, data management and locality, devices federation and trust, and business and service models).In the next section we introduce concepts and definitions for Internet of Things (IoT), cloud computi...

show abstract

Section: Mobile Applicationsmentioning

confidence: 99%

The Internet of Things, Fog and Cloud continuum: Integration and challenges

et al. 2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…This work proposes an architecture which is deemed timely as a platform for combined Fog and IoE networks, also referred to as Fog-of-Everything (FoE) [10] [23]. Initially, cloud computing was deemed the supporting platform for IoE devices with it's inherent on-demand provisioning and elasticity for data storage, processing and UI, however a vast number of IoE use-cases are latency-sensitive and therefore long delays towards cloud providers are unsuitable.…”

Section: Related Work / Motivationmentioning

confidence: 99%

Bioinspired Multiagent Embryonic Architecture for Resilient Edge Networks

Welsh

Benkhelifa

2019

IEEE Trans. Ind. Inf.

View full text Add to dashboard Cite

With the pervasive introduction of IoE technologies, use-cases are frequently being found operating within harsh environmental conditions. This decrees the need for solutions which permit service delivery to operate in a highly-resilient manner. This work presents an architecture for a novel cloud platform designed for resilient service delivery. It supports networks where poor communication links or high node failure will cause services to be delivered in an non-resilient manner. This could be the result of factors such as high-node mobility, poor environmental conditions, unreliable infrastructure from environment disaster or cyber-attack. This biologically inspired architecture uses a purely distributed multi-agent approach to provide self-healing and self-organising properties, modelled on the characteristics of embryonic development and biological cell communication. To permit high-levels of a node churn, this multi-agent approach uses local-only communication. Probabilistic Cellular Automata are used to simulate this architecture and evaluate the efficacy of this approach.

show abstract

“…More recently, Velasquez [21] surveyed the state-of-theart on orchestration beyond services in cloud computing, but also addressing the Internet of Everything and fog computing paradigms. The work of Thramboulidis et al [22] also falls into that category.…”

Section: B Orchestration and Choreography Of Distributed Manufacturimentioning

confidence: 99%

Robust Digital Twin Compositions for Industry 4.0 Smart Manufacturing Systems

Preuveneers

Joosen

Ilie‐Zudor

2018

2018 IEEE 22nd International Enterprise Distributed Object Computing Workshop (EDOCW)

View full text Add to dashboard Cite

Industry 4.0 is an emerging business paradigm that is reaping the benefits of enabling technologies driving intelligent systems and environments. By acquiring, processing and acting upon various kinds of relevant context information, smart automated manufacturing systems can make wellinformed decisions to adapt and optimize their production processes at runtime. To manage this complexity, the manufacturing world is proposing the 'Digital Twin' model to represent physical products in the real space and their virtual counterparts in the virtual space, with data connections to tie the virtual and real products together for an augmented view of the manufacturing workflow. The benefits of such representations are simplified process simulations and efficiency optimizations, predictions, early warnings, etc. However, the robustness and fidelity of digital twins are a critical concern, especially when independently developed production systems and corresponding digital twins interfere with one another in a manufacturing workflow and jeopardize the proper behavior of production systems. We therefore evaluate the addition of safeguards to digital twins for smart cyber-physical production systems (CPPS) in an Industry 4.0 manufacturing workflow in the form of feature toggles that are managed at runtime by software circuit breakers. Our evaluation shows how these improvements can increase the robustness of interacting digital twins by avoiding local errors from cascading through the distributed production or manufacturing workflow.

show abstract

Fog orchestration for the Internet of Everything: state-of-the-art and research challenges

Cited by 79 publications

References 88 publications

The Internet of Things, Fog and Cloud continuum: Integration and challenges

The Internet of Things, Fog and Cloud continuum: Integration and challenges

Bioinspired Multiagent Embryonic Architecture for Resilient Edge Networks

Robust Digital Twin Compositions for Industry 4.0 Smart Manufacturing Systems

Contact Info

Product

Resources

About