A service orchestration architecture for Fog-enabled infrastructures

Brito, Mathias Santos de; Hoque, Saiful; Magedanz, Thomas; Steinke, Ronald; Willner, Alexander; Nehls, Daniel; Keils, Oliver; Schreiner, Florian

doi:10.1109/fmec.2017.7946419

Cited by 65 publications

(45 citation statements)

References 3 publications

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“…We refer to these dynamic and transient cells and colonies as fluid distributed organisations. A fog node can start autonomously, and become the lead orchestrator or part of a set of distributed orchestrators reaching some quorum before making decisions and dynamically leave the colony without warning [48].…”

Section: Edge and Fog Computingmentioning

confidence: 99%

“…The ETSI NFV Management and Orchestration (MANO) is one of the most solid pieces of work in terms of NFV standardisation [4]. [48] have suggested that NFV should be the starting point for new standardisation efforts beyond NFV, given the need to define, for each application domain, the scope, properties, and requirements of service orchestration concepts is not different in the Fog Computing environment. This suggestion has also been followed by project Tacker in an attempt to integrate a MANO-compliant orchestrator on top of one of the most widely-used cloud management suites, OpenStack 3 .…”

Section: Current Standardisation Effortsmentioning

confidence: 99%

“…The ETSI Mobile Edge Computing (MEC) Reference Architecture [2] emphasises the need to consider a comprehensive set of constraints, and also refers to triggered application instantiation and relocations, one of the characteristics of our solution, similar to a fog orchestrator [48]. However, a detailed specification or/and Reference Architecture for the orchestrator is still missing.…”

Section: Current Standardisation Effortsmentioning

confidence: 99%

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Research challenges in nextgen service orchestration

Vaquero

Cuadrado

Elkhatib

et al. 2019

Future Generation Computer Systems

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Fog/edge computing, function as a service, and programmable infrastructures, like software-defined networking or network function virtualisation, are becoming ubiquitously used in modern Information Technology infrastructures. These technologies change the characteristics and capabilities of the underlying computational substrate where services run (e.g. higher volatility, scarcer computational power, or programmability). As a consequence, the nature of the services that can be run on them changes too (smaller codebases, more fragmented state, etc.). These changes bring new requirements for service orchestrators, which need to evolve so as to support new scenarios where a close interaction between service and infrastructure becomes essential to deliver a seamless user experience. Here, we present the challenges brought forward by this new breed of technologies and where current orchestration techniques stand with regards to the new challenges. We also present a set of promising technologies that can help tame this brave new world.

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Section: Edge and Fog Computingmentioning

confidence: 99%

Section: Current Standardisation Effortsmentioning

confidence: 99%

Section: Current Standardisation Effortsmentioning

confidence: 99%

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Research challenges in nextgen service orchestration

Vaquero

Cuadrado

Elkhatib

et al. 2019

Future Generation Computer Systems

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“…deployment, migration, application of policies) the Orchestrator interacts with the Cloudlets in the environment. However, due to the degree of heterogeneity of the Cloudlets in relation to the security aspects, new challenges arise when carrying out this interaction [98]. The interaction between the Orchestrator and each Cloudlet follows the steps described in the well-known Authentication, Access, and Account (AAA) framework.…”

Section: Authentication Access and Accountmentioning

confidence: 99%

“…The Service Orchestrator Architecture for Fog-enable Infrastructure (SOAFI) is a reference architecture proposed by Brito et al [98]. The development of this architecture was performed to demonstrate the importance of the Orchestrator in a Fog environment.…”

Section: Soafimentioning

confidence: 99%

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

Velásquez

Abreu

Assis

et al. 2018

J Internet Serv Appl

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Recent developments in telecommunications have allowed drawing new paradigms, including the Internet of Everything, to provide services by the interconnection of different physical devices enabling the exchange of data to enrich and automate people's daily activities; and Fog computing, which is an extension of the well-known Cloud computing, bringing tasks to the edge of the network exploiting characteristics such as lower latency, mobility support, and location awareness. Combining these paradigms opens a new set of possibilities for innovative services and applications; however, it also brings a new complex scenario that must be efficiently managed to properly fulfill the needs of the users. In this scenario, the Fog Orchestrator component is the key to coordinate the services in the middle of Cloud computing and Internet of Everything. In this paper, key challenges in the development of the Fog Orchestrator to support the Internet of Everything are identified, including how they affect the tasks that a Fog service Orchestrator should perform. Furthermore, different service Orchestrator architectures for the Fog are explored and analyzed in order to identify how the previously listed challenges are being tackled. Finally, a discussion about the open challenges, technological directions, and future of the research on this subject is presented.

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Fault tolerant resource allocation in fog environment using game theory‐based reinforcement learning

Divya

2021

Concurrency and Computation

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Realtime decision making is associated with an on-demand, latency aware resource allocation. Fog nodes along with cloud infrastructure, when used effectively can ensure real-time decision making. In this article, we propose an efficient resource allocation and fault tolerance mechanism for the fog layer. Our work takes the advantage of game theory, where Nash equilibrium is the initial allocation strategy, which is then passed on to the reinforcement learner. The allocation is done proactively based on the network status and traffic history. The performance of our system is compared with the existing open shortest path first and neural network algorithms. Besides, fault tolerance mechanism has also been proposed which takes the advantage of the fail-over cluster formation to find the link failure and provide an alternate path in the smart switch, which is the networking component of the fog network. The proposed work gives an improved recovery time and average service time in case of failure with a recovery time of 32 ms. The experimental results are justified in terms of improved service time, lower delay, and optimal energy utilization. K E Y W O R D Sdeep reinforcement learning, failover cluster, fog computing, game theory, resource allocation INTRODUCTIONA surge in the importance of sensors and real-time monitoring has brought about the convergence of two major technologies, the cloud and Internet of Things (IoT), which lead to the emergence of cloud of Things. 1 Processing of large streaming data and providing low latent, power-efficient, high accurate decision making has yet again emerged a new technology-Fog Computing, proposed by CISCO. 2,3 This computing layer helps to alleviate congestion in the cloud by the execution of time-sensitive tasks and data filtering near the edge. 4 Researchers use the terms Edge/fog/mist computing based on the distance of the computing layer from the source of data. 5 Our work takes the advantage of the fog layer to execute the latency aware tasks and effectively distribute the load in the fog layer.One of the most commonly used techniques for load distribution is task or code offloading 6 which helps to distribute the load from the cloud to the lower layer. Latency sensitive tasks are offloaded to the intermediate layer near the edge for better performance. 7,8 This helps in a significant reduction of data being transferred to a remote location, thereby saving bandwidth utility.Software-defined network (SDN) plays a major role as the networking component in a fog network creation. The SDN is an intelligent paradigm of networking, which consists of two planes, the data and the control plane to take care of delivery and networking of the application. 9,10 The Open-Flow protocol ensures the communication between the control plane and the data plane, 11 which instructs the data plane reactively or proactively on packet handling.Traffic engineering plays a key role in path-finding and route establishment in a network. A good algorithm enhances the throughput and minimizes the d...

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A service orchestration architecture for Fog-enabled infrastructures

Cited by 65 publications

References 3 publications

Research challenges in nextgen service orchestration

Research challenges in nextgen service orchestration

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

Fault tolerant resource allocation in fog environment using game theory‐based reinforcement learning

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