[Retracted] A Survey on Management Frameworks and Open Challenges in IoT

Kiani, Farzad

doi:10.1155/2018/9857026

Cited by 19 publications

(9 citation statements)

References 35 publications

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“…While, in the market, FC holds a tough competition, there are still several obstacles that need to be addressed to fit FC in an IoT ecosystem. The detailed FC challenges can be found from the study [10][11][12]. Therefore, FC needs some help to overcome its challenges and to fit into an IoT ecosystem.…”

Section: Fog Computing As a Solution Of CC For Iot Ecosystemmentioning

confidence: 99%

Software-Defined Dew, Roof, Fog and Cloud (SD-DRFC) Framework for IoT Ecosystem: The Journey, Novel Framework Architecture, Simulation, and Use Cases

2021

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The Internet of Things (IoT) has become one of the most known terms in present times, reaching new levels and setting a trend in the world. Evidently, it is the future of connectivity which has turned physical objects into intelligent objects. Therefore, there has been a growing curiosity in the IoT field and this leads to the concept of IoT ecosystem. But the contemporary fragmented ecosystem of regulations, technologies, and systems slows IoT deployments. Thus, we consider multi-tiered computational infrastructure which would be feasible to provide services from the nearest possible location of end devices. To mitigate multi-tier infrastructure issues, Software-Defined Networking (SDN) steps in. The journey behind SDN-supported multi-tier computational infrastructure can be understood from this paper's elaborate study. Next, a comparative analysis on dew, roof, fog and cloud is conducted and the impact of internet on these computing paradigms is briefly explained. Then a novel framework termed "SD-DRFC (Software-Defined Dew, Roof, Fog and Cloud computing)" is proposed for today's IoT ecosystem. The role and functionality of each tier of SD-DRFC framework are adequately explained. A use case focused on the SD-DRFC framework is then presented and simulated by utilizing iFogSim simulator. To evaluate the efficiency of the presented SD-DRFC framework, four QoS parameters (Latency, Network Usage, Cost, and Energy Consumption) are considered in this paper. When comparing the simulation results, the presented SD-DRFC framework performs much better than cloud-only implementation. The advantages and suitability of utilizing this proposed framework have been demonstrated by multiple use-cases which range from conceptual visions to existing running systems.

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Section: Fog Computing As a Solution Of CC For Iot Ecosystemmentioning

confidence: 99%

Software-Defined Dew, Roof, Fog and Cloud (SD-DRFC) Framework for IoT Ecosystem: The Journey, Novel Framework Architecture, Simulation, and Use Cases

2021

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“…The method to achieve load balance is clustering. In clustering, sensor nodes are connected to form a cluster, 19 where each cluster has a CH that connects another CH to form a network of clusters. CHs might have different initial energy requirements or the same initial energy requirement.…”

Section: Related Work/related Terminologiesmentioning

confidence: 99%

Intelligent energy optimization for advanced IoT analytics edge computing on wireless sensor networks

Agbehadji

Frimpong

Millham

et al. 2020

International Journal of Distributed Sensor Networks

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The current dispensation of big data analytics requires innovative ways of data capturing and transmission. One of the innovative approaches is the use of a sensor device. However, the challenge with a sensor network is how to balance the energy load of wireless sensor networks, which can be achieved by selecting sensor nodes with an adequate amount of energy from a cluster. The clustering technique is one of the approaches to solve this challenge because it optimizes energy in order to increase the lifetime of the sensor network. In this article, a novel bio-inspired clustering algorithm was proposed for a heterogeneous energy environment. The proposed algorithm (referred to as DEEC-KSA) was integrated with a distributed energy-efficient clustering algorithm to ensure efficient energy optimization and was evaluated through simulation and compared with benchmarked clustering algorithms. During the simulation, the dynamic nature of the proposed DEEC-KSA was observed using different parameters, which were expressed in percentages as 0.1%, 4.5%, 11.3%, and 34% while the percentage of the parameter for comparative algorithms was 10%. The simulation result showed that the performance of DEEC-KSA is efficient among the comparative clustering algorithms for energy optimization in terms of stability period, network lifetime, and network throughput. In addition, the proposed DEEC-KSA has the optimal time (in seconds) to send a higher number of packets to the base station successfully. The advantage of the proposed bio-inspired technique is that it utilizes random encircling and half-life period to quickly adapt to different rounds of iteration and jumps out of any local optimum that might not lead to an ideal cluster formation and better network performance.

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“…The WSN applications domain are increasing day by day especially in Internet of Things (IoT) based applications [12]. In general, the efficient resource management is essentially issue in these networks.…”

Section: Related Workmentioning

confidence: 99%

Efficient Resource Consumption by Dynamic Clustering and Optimized Routes in Wireless Sensor Networks

Kiani¹

2018

ijacsa

Self Cite

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Abstract-The energy issue is an important parameter in the wireless sensor networks and should be managed in the different applications. We propose a new routing algorithm that it is energy efficient and uses different approaches as dynamic clustering, spanning tree, self-configurable routing and controls energy consuming by data-driven and power management schemas. It has two main phases. The first is consisting of the steady cluster, cluster head election and creation-spanning tree in each cluster and the second phase is data transmission. The proposed protocol is compared with four other protocols in network lifetime, network balance, and average packet delay and packet delivery. Simulation results show the proposed protocol performance in the network lifetime is about 6 per cent higher than Improved-LEACH, 21.5 per cent higher than EESR and 5.8 per cent higher than DHCO. Its improvement in packet delivery parameter is about 3.5 per cent higher than Improved-LEACH, 6.5 per cent higher than EESR and 3 per cent higher than DHCO. In addition, the performance or in packet delay is about 17 per cent higher than EESR and 6 per cent higher than DHCO but Improved-LEACH protocol has a good performance than our protocol about 4 per cent.

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[Retracted] A Survey on Management Frameworks and Open Challenges in IoT

Cited by 19 publications

References 35 publications

Software-Defined Dew, Roof, Fog and Cloud (SD-DRFC) Framework for IoT Ecosystem: The Journey, Novel Framework Architecture, Simulation, and Use Cases

Software-Defined Dew, Roof, Fog and Cloud (SD-DRFC) Framework for IoT Ecosystem: The Journey, Novel Framework Architecture, Simulation, and Use Cases

Intelligent energy optimization for advanced IoT analytics edge computing on wireless sensor networks

Efficient Resource Consumption by Dynamic Clustering and Optimized Routes in Wireless Sensor Networks

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