A Distributed Application Placement and Migration Management Techniques for Edge and Fog Computing Environments

Goudarzi, Mohammad; Palaniswami, Marimuthu; Buyya, Rajkumar

doi:10.15439/2021f005

Cited by 23 publications

(36 citation statements)

References 37 publications

(79 reference statements)

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“…Several works in the literature such as [39,70,72,103] discuss modular applications. [24,25,38,137] have considered loosely-coupled applications.…”

Section: Modularmentioning

confidence: 99%

“…2. Although the microservice-based applications can significantly benefit the IoT scenarios, only a few works such as [38,137] have studied the scheduling and migration of microservices in Edge/Fog computing environments. So, further investigation is required to study the behavior of microservice-based applications with different resource management techniques.…”

Section: Research Gapsmentioning

confidence: 99%

“…Numerous techniques for scheduling IoT applications in Fog computing environments have been developed to address the above-mentioned challenges. Several works focused on the structure of IoT applications and how these parameters affect the scheduling [29,79,101] while some other techniques mainly focus on environmental parameters of Fog computing, such as the effect of hierarchical Fog layers on the scheduling of IoT applications [38,62]. Besides, several techniques focus on defining specific optimization models to formulate the effect of different parameters such as FSs' computing resources, networking protocols, and IoT devices characteristics, just to mention a few [68].…”

Section: Introductionmentioning

confidence: 99%

“…Besides, several techniques focus on defining specific optimization models to formulate the effect of different parameters such as FSs' computing resources, networking protocols, and IoT devices characteristics, just to mention a few [68]. Moreover, several works have proposed different placement techniques to find an acceptable solution for the optimization problem [5,51,78] while some other techniques consider mobility management [26,38,131] and failure recovery [8,40]. All these perspectives directly affect the scheduling problem, especially, when designing decision engines.…”

Section: Introductionmentioning

confidence: 99%

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Scheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions

Goudarzi¹,

Palaniswami²,

Buyya³

2022

Preprint

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Fog computing, as a distributed paradigm, offers cloud-like services at the edge of the network with low latency and high-access bandwidth to support a diverse range of IoT application scenarios. To fully utilize the potential of this computing paradigm, scalable, adaptive, and accurate scheduling mechanisms and algorithms are required to efficiently capture the dynamics and requirements of users, IoT applications, environmental properties, and optimization targets. This paper presents a taxonomy of recent literature on scheduling IoT applications in Fog computing. Based on our new classification schemes, current works in the literature are analyzed, research gaps of each category are identified, and respective future directions are described. CCS Concepts: • General and reference → General literature; • Computer systems organization → Distributed architectures.

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“…Several works in the literature such as [39,70,72,103] discuss modular applications. [24,25,38,137] have considered loosely-coupled applications.…”

Section: Modularmentioning

confidence: 99%

Section: Research Gapsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Scheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions

Goudarzi¹,

Palaniswami²,

Buyya³

2022

Preprint

Self Cite

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“…Moreover, the number of real-time IoT applications has been significantly increased. These applications require resources that support fast processing and low access latency to minimize the total response time [5]. Some examples of these applications are autonomous robots and disaster management applications (e.g., natural hazard management).…”

Section: Introductionmentioning

confidence: 99%

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

Wang¹,

Goudarzi²,

Aryal³

et al. 2022

Preprint

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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 heavy-weight 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.

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A cost‐efficient and QoS‐aware adaptive placement of applications in fog computing

Wang

et al. 2023

Concurrency and Computation

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SummaryWith the rapid development of the Internet of Things (IoT), fog computing has emerged as a complementary solution to address the issues faced in cloud computing. However, it is a challenging issue to ensure both of the high Quality of Service (QoS) and low cost for different requests when dealing with computing resources. In this article, we propose a new approach on adaptive cost‐efficient and QoS‐aware application placement for fog computing called DATSS. Specifically, this approach consists of a QoS state driven strategy and a credibility rating mechanism. The algorithm divides the QoS into three different states by calculating the QoS violation rate and adaptively selects the best scheduling strategy. Then evaluates the stability of the node based on the task history, and prioritize the task on the node with a higher rating. Performance results show that the cost, delay and energy consumption of the proposed algorithm can be reduced by 20.9%, 15.7%, and 12.6% respectively compared with other algorithms at most. The proposed algorithm can effectively improve cost efficiency and stability under QoS constraints in fog computing environments.

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A Distributed Application Placement and Migration Management Techniques for Edge and Fog Computing Environments

Cited by 23 publications

References 37 publications

Scheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions

Scheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions

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

A cost‐efficient and QoS‐aware adaptive placement of applications in fog computing

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