Deployment orchestration of microservices with geographical constraints for Edge computing

Villari, Massimo; Celesti, Antonio; Tricomi, Giuseppe; Galletta, Antonino; Fazio, Maria

doi:10.1109/iscc.2017.8024599

Cited by 23 publications

(12 citation statements)

References 5 publications

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“…Orchestration solutions with reference implementations At the level of more concrete reference implementations, there are several research efforts that concentrate on the orchestration of microservices for the fog and edge layers. Notable examples include [63][64][65][66][67][68][69]. These efforts typically apply Docker containers to deliver services and utilise either Docker Swarm [63,64] or Kubernetes for container orchestration [66].…”

Section: Application-level Cloud-to-edge Orchestrationmentioning

confidence: 99%

“…These efforts typically apply Docker containers to deliver services and utilise either Docker Swarm [63,64] or Kubernetes for container orchestration [66]. The authors in [65] present an ad-hoc OpenStackbased Heat Orchestration Template (HOT) service manifest for deploying microservices to selected fog computing nodes. However, unlike MiCADO-Edge, this solution does not support run-time management of resources and services.…”

Section: Application-level Cloud-to-edge Orchestrationmentioning

confidence: 99%

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MiCADO-Edge: Towards an Application-level Orchestrator for the Cloud-to-Edge Computing Continuum

et al. 2021

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Automated deployment and run-time management of microservices-based applications in cloud computing environments is relatively well studied with several mature solutions. However, managing such applications and tasks in the cloud-to-edge continuum is far from trivial, with no robust, production-level solutions currently available. This paper presents our first attempt to extend an application-level cloud orchestration framework called MiCADO to utilise edge and fog worker nodes. The paper illustrates how MiCADO-Edge can automatically deploy complex sets of interconnected microservices in such multi-layered cloud-to-edge environments. Additionally, it shows how monitoring information can be collected from such services and how complex, user- defined run-time management policies can be enforced on application components running at any layer of the architecture. The implemented solution is demonstrated and evaluated using two realistic case studies from the areas of video processing and secure healthcare data analysis.

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Section: Application-level Cloud-to-edge Orchestrationmentioning

confidence: 99%

Section: Application-level Cloud-to-edge Orchestrationmentioning

confidence: 99%

MiCADO-Edge: Towards an Application-level Orchestrator for the Cloud-to-Edge Computing Continuum

et al. 2021

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“…The containerization has been employed to deploy microservice-based applications on the Edge and hybrid Cloud-Edge infrastructures [19,20]. There are also studies using OpenStack Heat [36] and TOSCA [37]. The key focus of these works is on the deployment of the applications while satisfying deployment constraints such as geographical constraints and inbound network communication restrictions.…”

Section: Related Workmentioning

confidence: 99%

SODALITE@RT: Orchestrating Applications on Cloud-Edge Infrastructures

Kumara

Mundt²,

Tokmakov

et al. 2021

J Grid Computing

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IoT-based applications need to be dynamically orchestrated on cloud-edge infrastructures for reasons such as performance, regulations, or cost. In this context, a crucial problem is facilitating the work of DevOps teams in deploying, monitoring, and managing such applications by providing necessary tools and platforms. The SODALITE@RT open-source framework aims at addressing this scenario. In this paper, we present the main features of the SODALITE@RT: modeling of cloud-edge resources and applications using open standards and infrastructural code, and automated deployment, monitoring, and management of the applications in the target infrastructures based on such models. The capabilities of the SODALITE@RT are demonstrated through a relevant case study.

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“…The hardware platform, which is the infrastructure of the system, provides computing resource, storage resource, and network resource for services and users. The software framework is based on microservice architecture [18,34,35,36,37]. Using resource virtualization technology (virtual machine (VM), container, etc.…”

Section: System Frameworkmentioning

confidence: 99%

SatEC: A 5G Satellite Edge Computing Framework Based on Microservice Architecture

Lei

Cao

Gong

et al. 2019

Sensors

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As outlined in the 3Gpp Release 16, 5G satellite access is important for 5G network development in the future. A terrestrial-satellite network integrated with 5G has the characteristics of low delay, high bandwidth, and ubiquitous coverage. A few researchers have proposed integrated schemes for such a network; however, these schemes do not consider the possibility of achieving optimization of the delay characteristic by changing the computing mode of the 5G satellite network. We propose a 5G satellite edge computing framework (5GsatEC), which aims to reduce delay and expand network coverage. This framework consists of embedded hardware platforms and edge computing microservices in satellites. To increase the flexibility of the framework in complex scenarios, we unify the resource management of the central processing unit (CPU), graphics processing unit (GPU), and field-programmable gate array (FPGA); we divide the services into three types: system services, basic services, and user services. In order to verify the performance of the framework, we carried out a series of experiments. The results show that 5GsatEC has a broader coverage than the ground 5G network. The results also show that 5GsatEC has lower delay, a lower packet loss rate, and lower bandwidth consumption than the 5G satellite network.

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Deployment orchestration of microservices with geographical constraints for Edge computing

Cited by 23 publications

References 5 publications

MiCADO-Edge: Towards an Application-level Orchestrator for the Cloud-to-Edge Computing Continuum

MiCADO-Edge: Towards an Application-level Orchestrator for the Cloud-to-Edge Computing Continuum

SODALITE@RT: Orchestrating Applications on Cloud-Edge Infrastructures

SatEC: A 5G Satellite Edge Computing Framework Based on Microservice Architecture

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