mePaaS: Mobile-Embedded Platform as a Service for Distributing Fog Computing to Edge Nodes

Liyanage, Mohan; Chang, Chii; Srirama, Satish Narayana

doi:10.1109/pdcat.2016.030

Cited by 29 publications

(16 citation statements)

References 26 publications

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“…In contrast to Yangui et al [4] and Pahl et al [10], the PaaS architecture proposed by Liyanage et al [5] enables generating the best deployment plan by proposing a component distribution scheme. In addition, they incorporate a publication/discovery mechanism for the underlying node's specifications using Service Description Metadata (SDM).…”

Section: The State-of-the-art and Its Shortcomingsmentioning

confidence: 99%

“…Application providers use PaaS to provision (i.e., develop, deploy, manage, and orchestrate) applications in the cloud. However, existing PaaS solutions (including IoT PaaS solutions) usually focus on cloud computing and do not enable the provisioning of applications with components spanning both cloud and fog, e.g., references [4]- [5]. Provisioning applications that span the cloud and fogs requires novel functions such as application graph generation, which are absent from existing cloud PaaS solutions.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An IoT Platform-as-a-Service for NFV-Based Hybrid Cloud/Fog Systems

Mouradian

Ebrahimnezhad

Jebbar

et al. 2020

IEEE Internet Things J.

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Cloud computing, despite its inherent advantages (e.g., resource efficiency) still faces several challenges. The wide area network used to connect the cloud to end-users could cause high latency, which may not be tolerable for some applications, especially Internet of Things (IoT) applications. Fog computing can reduce this latency by extending the traditional cloud architecture to the edge of the network and by enabling the deployment of some application components on fog nodes. Application providers use Platform-as-a-Service (PaaS) to provision (i.e., develop, deploy, manage, and orchestrate) applications in cloud. However, existing PaaS solutions (including IoT PaaS) usually focus on cloud and do not enable provisioning of applications with components spanning cloud and fog. Provisioning such applications requires novel functions, such as application graph generation, that are absent from existing PaaS. Furthermore, several functions offered by existing PaaS (e.g., publication/discovery) need to be significantly extended in order to fit in a hybrid cloud/fog environment. In this paper, we propose a novel architecture for PaaS for hybrid cloud/fog system. It is IoT use case-driven, and its applications' components are implemented as Virtual Network Functions (VNFs) with execution sequences modeled as graphs with sub-structures such as selection and loops. It automates the provisioning of applications with components spanning cloud and fog. In addition, it enables the discovery of existing cloud and fog nodes and generates application graphs. A proof of concept is built based on Cloudify open source. Feasibility is demonstrated by evaluating its performance when PaaS modules and application components are placed in clouds and fogs in different geographical locations.

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Section: The State-of-the-art and Its Shortcomingsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An IoT Platform-as-a-Service for NFV-Based Hybrid Cloud/Fog Systems

Mouradian

Ebrahimnezhad

Jebbar

et al. 2020

IEEE Internet Things J.

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“…Dynamic deployment is achieved by integrating continuous deployment technology on the edge of the network while coping with IoT's intrinsic heterogeneity [170,99]. As IoT devices may be offline for quite some time, an orchestrator needs to gracefully cope with loss of connectivity [133] and increased likelihood of failing devices [166].…”

Section: Dynamismmentioning

confidence: 99%

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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“…Distributed computing on the device layer focuses on collaboration and partitioning of application execution load across the IoT architecture layers. Mist computing [43,55] involves sensor and actuator devices in the application-specific data processing. The goal is to introduce proactivity with self-and contextawareness for edge application execution.…”

Section: Device Layer Distributed Computingmentioning

confidence: 99%

“…The goal is to introduce proactivity with self-and contextawareness for edge application execution. However, the presented platforms are centrally controlled and based on the service-oriented architecture paradigm [43]. Other proposed solutions include mobile edge clouds [14], MCC [15,20], femtoclouds [22] and mobile fog [25].…”

Section: Device Layer Distributed Computingmentioning

confidence: 99%

Energy efficient opportunistic edge computing for the Internet of Things

Leppänen

Riekki

2019

WEB

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Edge computing in Internet of Things enhances application execution by retrieving cloud resources to the close proximity of resource-constrained end devices at the edge and by enabling task offloading from end devices to the edge. In this paper, edge computing platforms are extended into the data producing end devices, including wireless sensor network nodes and smartphones, with mobile agents. Mobile agents operate as a multi-agent system on the opportunistic network of heterogeneous end devices, where the benefits include autonomous, asynchronous and the adaptive execution and relocation of application-specific tasks, while taking into account local resource availability. In addition to the vertical edge connectivity, mobile agents enable horizontal sharing of the information between end devices. Use cases are presented, where mobile agents address challenges in current edge computing platforms. An edge application is evaluated, where mobile agents as a multi-agent system process sensor data in a heterogeneous set of end devices, control the operation of the devices and share their results with system components. Mobile agents operate atop a REST-based mobile agent software framework that relies on embedded Web services for interoperability. A real-world evaluation and large-scale simulations show that energy consumption is reduced significantly in the edge application execution.

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mePaaS: Mobile-Embedded Platform as a Service for Distributing Fog Computing to Edge Nodes

Cited by 29 publications

References 26 publications

An IoT Platform-as-a-Service for NFV-Based Hybrid Cloud/Fog Systems

An IoT Platform-as-a-Service for NFV-Based Hybrid Cloud/Fog Systems

Research challenges in nextgen service orchestration

Energy efficient opportunistic edge computing for the Internet of Things

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