Optimizing the Computational Offloading Decision in Cloud-Fog Environment

Bala, Mohammad Irfan; Chishti, Mohammad Ahsan

doi:10.1109/icitiit49094.2020.9071523

Cited by 5 publications

(4 citation statements)

References 19 publications

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“…The authors in [ 50 , 51 , 52 ] introduced a two-tier IoT model using the iFogSim simulator and analyzed the network parameters (including latency, power consumption, network usage, cost). Furthermore, in one of our previous works [ 47 ], we exploited the benefit of local tier processing, proposed a three-tier IoT edge model, and analyzed the performance of the network.…”

Section: The Evolution Of Cloud Iot Modelsmentioning

confidence: 99%

Health-BlockEdge: Blockchain-Edge Framework for Reliable Low-Latency Digital Healthcare Applications

Ejaz

Kumar

Kovacevic

et al. 2021

Sensors

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The rapid evolution of technology allows the healthcare sector to adopt intelligent, context-aware, secure, and ubiquitous healthcare services. Together with the global trend of an aging population, it has become highly important to propose value-creating, yet cost-efficient digital solutions for healthcare systems. These solutions should provide effective means of healthcare services in both the hospital and home care scenarios. In this paper, we focused on the latter case, where the goal was to provide easy-to-use, reliable, and secure remote monitoring and aid for elderly persons at their home. We proposed a framework to integrate the capabilities of edge computing and blockchain technology to address some of the key requirements of smart remote healthcare systems, such as long operating times, low cost, resilience to network problems, security, and trust in highly dynamic network conditions. In order to assess the feasibility of our approach, we evaluated the performance of our framework in terms of latency, power consumption, network utilization, and computational load, compared to a scenario where no blockchain was used.

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Section: The Evolution Of Cloud Iot Modelsmentioning

confidence: 99%

Health-BlockEdge: Blockchain-Edge Framework for Reliable Low-Latency Digital Healthcare Applications

Ejaz

Kumar

Kovacevic

et al. 2021

Sensors

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“…In cloud-only, processing services are transmitted to the cloud data center and in edge-ward services push towards fog devices when enough resources are available. Some research works for solving SPP employ optimization techniques [26,27], such as greedy, heuristics, ILP, and genetic algorithms. In Reference [21], the authors consider SPP for IoT applications over fog resources as an optimization problem and proposed a problem resolution heuristic using the genetic algorithm.…”

Section: Related Workmentioning

confidence: 99%

“…Some of the limitations of existing works are: (i) following the traditional hierarchical structure of fog-cloud, not making optimal use of the computing resources available in the fog layer and executing more services on cloud data centers, which increases the user response time [5,23,24,26,44], (ii) using hypothetical data instead of experimental data and, thus, uncertainty about the feasibility of implementing the algorithm in the real world [5,14,24,26,27,34,40,41,43,45], (iii) modeling the problem as an ILP and the complexity of problem solving when increasing the number of services and fog nodes on a large scale [21,22,32,44], (iv) ignoring priority for the applications and demands of services [5,14,18,[21][22][23][25][26][27]34,35,40,43], (v) ignoring mobility of fog nodes [3,14,18,[21][22][23]25,26,35,41,43,45], and (vi) improving only two or three QoS metrics…”

Section: Related Workmentioning

confidence: 99%

SCATTER: Service Placement in Real-Time Fog-Assisted IoT Networks

Khosroabadi

Fotouhi-Ghazvini

Fotouhi

2021

JSAN

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Internet of Things (IoT) networks dependent on cloud services usually fail in supporting real-time applications as there is no response time guarantees. The fog computing paradigm has been used to alleviate this problem by executing tasks at the edge of the network, where it is possible to provide time bounds. One of the challenging topics in a fog-assisted architecture is to task placement on edge devices in order to obtain a good performance. The process of task mapping into computational devices is known as Service Placement Problem (SPP). In this paper, we present a heuristic algorithm to solve SPP, dubbed as clustering of fog devices and requirement-sensitive service first (SCATTER). We provide simulations using iFogSim toolkit and experimental evaluations using real hardware to verify the feasibility of the SCATTER algorithm by considering a smart home application. We compared the SCATTER with two existing works: edge-ward and cloud-only approaches, in terms of Quality of Service (QoS) metrics. Our experimental results have demonstrated that SCATTER approach has better performance compared with the edge-ward and cloud-only, 42.1% and 60.2% less application response times, 22% and 27.8% less network usage, 45% and 65.7% less average application loop delays, and 2.33% and 3.2% less energy consumption.

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“…Several authors [73,74,75,76] have already proposed algorithms based on the mathematical analysis of two-layer middleware architectures (cloud and fog) for Smart Cities. Articles that are not focused on Smart Cities, such as Mahmoud et al [77] for health-care, were not considered here, although many had good proposals for algorithms and quantitative analysis.…”

Section: Multi-tier System Evaluationmentioning

confidence: 99%

Musanet: A Multitier Platform for Developing Smart-City Applications

MESLIN¹

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To my wife, Bianca, and my daughter, Amanda, who have always been close to me at best and also at worst times, always supporting me during this journey. To my friends for their psychological support and the rare pleasant moments of dinners and games. I would also like to dedicate to two special people who have always accompanied me and continue to accompany me, even though they are no longer with us, to my mother, Sônia, who always believed in me, and to Denise Cavalcante Meslin.

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Optimizing the Computational Offloading Decision in Cloud-Fog Environment

Cited by 5 publications

References 19 publications

Health-BlockEdge: Blockchain-Edge Framework for Reliable Low-Latency Digital Healthcare Applications

Health-BlockEdge: Blockchain-Edge Framework for Reliable Low-Latency Digital Healthcare Applications

SCATTER: Service Placement in Real-Time Fog-Assisted IoT Networks

Musanet: A Multitier Platform for Developing Smart-City Applications

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