Fog Orchestration for Internet of Things Services (original) (raw)

Orchestration in Fog Computing: A Comprehensive Survey

ACM Computing Surveys, 2023

Fog computing is a paradigm that brings computational resources and services to the network edge in the vicinity of user devices, lowering latency and connecting with cloud computing resources. Unlike cloud computing, fog resources are based on constrained and heterogeneous nodes whose connectivity can be unstable. In this complex scenario, there is a need to define and implement orchestration processes to ensure that applications and services can be provided, considering the settled agreements. Although some publications have dealt with orchestration in fog computing, there are still some diverse definitions and functional intersection with other areas, such as resource management and monitoring. This article presents a systematic review of the literature with focus on orchestration in fog computing. A generic architecture of fog orchestration is presented, created from the consolidation of the analyzed proposals, bringing to light the essential functionalities addressed in the lit...

Container Orchestration in Edge and Fog Computing Environments for Real-Time IoT Applications

Lecture notes on data engineering and communications technologies, 2022

Resource management is the principal factor to fully utilize the potential of Edge/Fog computing to execute real-time and critical IoT applications. Although some resource management frameworks exist, the majority are not designed based on distributed containerized components. Hence, they are not suitable for highly distributed and heterogeneous computing environments. Containerized resource management frameworks such as FogBus2 enable efficient distribution of framework's components alongside IoT applications' components. However, the management, deployment, health-check, and scalability of a large number of containers are challenging issues. To orchestrate a multitude of containers, several orchestration tools are developed. But, many of these orchestration tools are heavyweight and have a high overhead, especially for resource-limited Edge/Fog nodes. Thus, for hybrid computing environments, consisting of heterogeneous Edge/Fog and/or Cloud nodes, lightweight container orchestration tools are required to support both resource-limited resources at the Edge/Fog and resource-rich resources at the Cloud. Thus, in this paper, we propose a feasible approach to build a hybrid and lightweight cluster based on K3s, for the FogBus2 framework that offers containerized resource management framework. This work addresses the challenge of creating lightweight computing clusters in hybrid computing environments. It also proposes three design patterns for the deployment of the FogBus2 framework in hybrid environments, including 1) Host Network, 2) Proxy Server, and 3) Environment Variable. The performance evaluation shows that the proposed approach improves the response time of real-time IoT applications up to 29% with acceptable and low overhead.

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

Journal of Internet Services and Applications

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.

A review on orchestration distributed systems for IoT smart services in fog computing

International Journal of Electrical and Computer Engineering (IJECE), 2021

This paper provides a review of orchestration distributed systems for IoT smart services in fog computing. The cloud infrastructure alone cannot handle the flow of information with the abundance of data, devices and interactions. Thus, fog computing becomes a new paradigm to overcome the problem. One of the first challenges was to build the orchestration systems to activate the clouds and to execute tasks throughout the whole system that has to be considered to the situation in the large scale of geographical distance, heterogeneity and low latency to support the limitation of cloud computing. Some problems exist for orchestration distributed in fog computing are to fulfil with high reliability and low-delay requirements in the IoT applications system and to form a larger computer network like a fog network, at different geographic sites. This paper reviewed approximately 68 articles on orchestration distributed system for fog computing. The result shows the orchestration distribute system and some of the evaluation criteria for fog computing that have been compared in terms of Borg, Kubernetes, Swarm, Mesos, Aurora, heterogeneity, QoS management, scalability, mobility, federation, and interoperability. The significance of this study is to support the researcher in developing orchestration distributed systems for IoT smart services in fog computing focus on IR4.0 national agenda.

Dynamic Orchestration of Security Services at Fog Nodes for 5G IoT

ICC 2020 - 2020 IEEE International Conference on Communications (ICC), 2020

Fog Computing is one of the edge computing paradigms that envisages being the proximate processing and storage infrastructure for a multitude of IoT appliances. With its dynamic deployability as a medium level cloud service, fog nodes are enabling heterogeneous service provisioning infrastructure that features scalability, interoperability, and adaptability. Out of the various 5G based services possible with the fog computing platforms, security services are imperative but minimally investigated direct live. Thus, in this research, we are focused on launching security services in a fog node with an architecture capable of provisioning on-demand service requests. As the fog nodes are constrained on resources, our intention is to integrate lightweight virtualization technology such as Docker for forming the service provisioning infrastructure. We managed to launch multiple security instances configured to be Intrusion Detection and Prevention Systems (IDPSs) on the fog infrastructure emulated via a Raspberry Pi-4 device. This environment was tested with multiple network flows to validate its feasibility. In our proposed architecture, orchestration strategies performed by the security orchestrator were stated as guidelines for achieving pragmatic, dynamic orchestration with fog in IoT deployments. The results of this research guarantee the possibility of developing an ambient security service model that facilitates IoT devices with enhanced security.

Orchestration in the Cloud-to-Things compute continuum: taxonomy, survey and future directions

Journal of Cloud Computing

IoT systems are becoming an essential part of our environment. Smart cities, smart manufacturing, augmented reality, and self-driving cars are just some examples of the wide range of domains, where the applicability of such systems have been increasing rapidly. These IoT use cases often require simultaneous access to geographically distributed arrays of sensors, heterogeneous remote, local as well as multi-cloud computational resources. This gives birth to the extended Cloud-to-Things computing paradigm. The emergence of this new paradigm raised the quintessential need to extend the orchestration requirements (i.e., the automated deployment and run-time management) of applications from the centralised cloud-only environment to the entire spectrum of resources in the Cloud-to-Things continuum. In order to cope with this requirement, in the last few years, there has been a lot of attention to the development of orchestration systems in both industry and academic environments. This pap...

Fog Function Virtualization: A flexible solution for IoT applications

2017 Second International Conference on Fog and Mobile Edge Computing (FMEC), 2017

The Internet of Things applications must carefully assess certain crucial factors such as the real-time and largely distributed nature of the "things". Fog Computing provides an architecture to satisfy those requirements through nodes located from near the "things" till the edge. The problem comes with the integration of the Fog nodes into current infrastructures. This process requires the development of complex software solutions and prevents Fog growth. In this paper we propose three innovations to enhance Fog: (i) a new orchestration policy, (ii) the creation of constellations of nodes, and (iii) Fog Function Virtualization (FFV). All together will complement Fog to reach its true potential as a generic scalable platform, running multiple IoT applications simultaneously. Deploying a new service is reduced to the development of the application code, fact that brings the democratization of the Fog Computing paradigm through ease of deployment and cost reduction.

Systematic Mapping on Orchestration of Container-based Applications in Fog Computing

2019 15th International Conference on Network and Service Management (CNSM), 2019

There is an increasing number of Internet of Things (IoT) devices in the border of computer networks, requiring local processing and lightweight virtualization to deal with issues such as heterogeneity, Quality of Service (QoS) management, scalability, mobility, federation, and interoperability. Fog computing can provide the computational resources required by IoT devices to process their data. Low energy consumption and total cost of ownership are among the desirable properties for auxiliar infrastructures such as those deployed for fog computing, which do not require large computational power though. There is a noteworthy trend of undergoing research efforts towards the definition of software and hardware architectures for fog computing in this context. In this sense, this paper presents a Systematic Literature Mapping with the purpose of understanding and identifying metrics and gaps in current literature about orchestration of container-based applications, especially those hosted in clusters of Single Board Computer (SBC) platforms, such as Raspberry Pi, which have been used for deploying fog computing environments.

Fog computing systems: State of the art, research issues and future trends, with a focus on resilience

Journal of Network and Computer Applications, 2020

Many future innovative computing services will use Fog Computing Systems (FCS), integrated with Internet of Things (IoT) resources. These new services, built on the convergence of several distinct technologies, need to fulfil time-sensitive functions, provide variable levels of integration with their environment, and incorporate data storage, computation, communications, sensing, and control. There are, however, significant problems to be solved before such systems can be considered fit for purpose. The high heterogeneity, complexity, and dynamics of these resourceconstrained systems bring new challenges to their robust and reliable operation, which implies the need for integral resilience management strategies. This paper surveys the state of the art in the relevant fields, and discusses the research issues and future trends that are emerging. We envisage future applications that have very stringent requirements, notably high-precision latency and synchronization between a large set of flows, where FCSs are key to supporting them. Thus, we hope to provide new insights into the design and management of resilient FCSs that are formed by IoT devices, edge computer servers and wireless sensor networks; these systems can be modelled using Game Theory, and flexibly programmed with the latest software and virtualization platforms.

Performance and Availability Trade-Offs in Fog–Cloud IoT Environments

Journal of Network and Systems Management, 2020

Internet of Things (IoT) is an emerging paradigm that transforms everyday devices (Things) into Internet-connected devices with sensing, processing, and actuation capabilities. These devices have limited storage and processing capacity, so they have been integrated with Cloud computing to overcome these limitations. Cloud computing offers various benefits such as offload data storage and processing burden at the Cloud side. Nevertheless, because Cloud is not an efficient solution for IoT latency-sensitive applications, Fog computing was introduced to address this limitation. Although Fog-Cloud IoT environments have begun to be adopted in the last few years, such environments have not been properly assessed in terms of their capacity to meet the growing demand of IoT devices. In this work, we present a Deterministic and Stochastic Petri Net (DSPN) approach for evaluating Fog-Cloud IoT environments composed of hundreds physical Things. Our approach allows evaluating the trade-offs of many performability metrics (e.g., utilization, response time, throughput, and availability) and, consequently, may help system designers to choose the most suitable Fog-Cloud IoT environment. We demonstrate the feasibility of our approach through a real-world case study. The results revealed that adopting a Fog device can improve availability. However, the performance is only improved in certain conditions like when the environment is not at full capacity.