An efficient placement of sinks and SDN controller nodes for optimizing the design cost of industrial IoT systems

Faragardi, Hamid Reza; Vahabi, Maryam; Fotouhi, Hossein; Nolte, Thomas; Fahringer, Thomas

doi:10.1002/spe.2593

Cited by 15 publications

(11 citation statements)

References 51 publications

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“…An optimization model for the deployment of controllers and sinks for wireless sensor networks (WSN) is proposed in [ 21 ]. The prime focus of the proposed model is to determine the optimal location of the controllers and sinks to maintain reliability and performance in a delay sensitive Internet of Things (IoT) system.…”

Section: Related Workmentioning

confidence: 99%

“…The prime focus of the work is to find the optimal placement of the controllers to reduce operational latency by locally distributing the top layer of the controllers while the bottom layer of the controllers is placed near the road side unit (RSU). Nevertheless, the studies in [ 21 , 22 , 23 ] do not consider the optimal number of controllers in their proposed models and scenarios.…”

Section: Related Workmentioning

confidence: 99%

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Control Plane Optimisation for an SDN-Based WBAN Framework to Support Healthcare Applications

Hasan

Ahmed

Biswas

et al. 2020

Sensors

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Software-Defined Networking (SDN) offers an abstract view of the network and assists network operators to control the network traffic and the associated network resources more effectively. For the past few years, SDN has shown a lot of merits in diverse fields of applications, an important one being the Wireless Body Area Network (WBAN) for healthcare services. With the amalgamation of SDN with WBAN (SDWBAN), the patient monitoring and management system has gained much more flexibility and scalability compared to the conventional WBAN. However, the performance of the SDWBAN framework largely depends on the controller which is a core element of the control plane. The reason is that an optimal number of controllers assures the satisfactory level of performance and control of the network traffic originating from the underlying data plane devices. This paper proposes a mathematical model to determine the optimal number of controllers for the SDWBAN framework in healthcare applications. To achieve this goal, the proposed mathematical model adopts the convex optimization method and incorporates three critical SDWBAN factors in the design process: number of controllers, latency and number of SDN-enabled switches (SDESW). The proposed analytical model is validated by means of simulations in Castalia 3.2 and the outcomes indicate that the network achieves high level of Packet Delivery Ratio (PDR) and low latency for optimal number of controllers as derived in the mathematical model.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Control Plane Optimisation for an SDN-Based WBAN Framework to Support Healthcare Applications

Hasan

Ahmed

Biswas

et al. 2020

Sensors

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“…The final article of the special issue, entitled “An efficient placement of sinks and SDN controller nodes for optimizing the design cost of industrial IoT systems”, is presented by Faragardi et al For satisfying performance requirements in time‐critical IoT systems while reducing deployment costs in underlying software‐defined networks, it is important to select a proper number of controllers and sink nodes and locate them in a way that they facilitate an efficient coverage. The article addressed the multiple‐sink/controller problem (MSCP), supporting decisions regarding the type and location of controllers and sinks while satisfying reliability and timeliness requirements of a sensor network.…”

Section: Summary Of the Contributionsmentioning

confidence: 99%

“…The subsequent two articles focus on composite software‐as‐a‐service (SaaS) placement optimization and web service composition . Finally, the last article of this special issue addresses an industrial IoT application by proposing metaheuristic‐based methods for optimizing the placement of software‐defined networking controllers and sink nodes in cloud environments . In the remainder of this editorial, we summarize the scope and contribution of the articles included in this special issue.…”

Section: Introductionmentioning

confidence: 99%

Metaheuristics in cloud computing

et al. 2018

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The cloud computing paradigm is increasingly becoming mainstream and a growing number of companies and research organizations seek to gain value from its unique characteristics, service models, and deployment forms. According to recent estimates of Gartner 1 and IDC, 2 the public cloud services market is projected to grow at a compound annual growth rate of 16.5% and 21.5%, respectively, from 2015-2020. Gartner expects the highest growth rates in spendings on public cloud infrastructure services. This implies not only a high relevance of approaches supporting the management of cloud infrastructures, but also the need for approaches facilitating and improving the use of cloud infrastructures from the consumer's point of view. The realization of the computing utility vision, commoditized and delivered in a manner similar to traditional utilities like water and electricity, 3 however, currently fails because of the huge complexity in cloud environments where many complex decisions have to be made, as recently reported in one of the largest global IT leadership surveys. 4 In addition, due to the environmental impact of cloud computing and the relation between energy consumption and costs, a sustainable use of resources is of considerable importance and requires the development of new policies and techniques. As a result, the success of cloud computing adoption and provision is highly dependent on efficient and intelligent decision making.This gives rise to many complex combinatorial optimization problems both from the consumers' and providers' perspective. 5 The implications of decisions need to be quantifiable in terms of different dimensions (eg, economics, sustainability, performance) to allow a comparison of alternatives and to decide on the right course of action. Cloud service providers aim to reduce operational expenses and improve economies of scale to maximize profits and provide competitive prices in a highly competitive market. Therefore, cloud service providers are particularly concerned with a cost-effective, energy-efficient, fault-tolerant utilization and management of physical and virtual computing resources, whereby the quality-of-service (QoS) requirements of consumers have to be satisfied. From the consumers' point of view, particularly an efficient selection and utilization of cloud providers and cloud services, as well as the management thereof, is of interest. Several requirements in terms of costs, service quality, and legal constraints need to be taken into account when placing applications into the cloud (for extensive overviews, the interested reader is referred to Heilig et al 6,7 ). This also involves specific characteristics of cloud computing, such as the options of scalability, load balancing, and replication. Moreover, cloud-related application areas and research directions have been expanded to novel paradigms in recent years including fog computing, serverless computing, and internet of things (IoT), leading to new open issues and optimization challenges regarding resource management...

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“…A promising solution to implement the SDN controller is to integrate additional node(s) within WSNs, which are supposed to be responsible for executing the SDN controller software. Although the notion behind the control plane in software-defined networks is based on a centralized fashion, the SDN controller must be physically distributed among multiple nodes to achieve higher performance, scalability, and fault tolerance [7,8].…”

Section: Introductionmentioning

confidence: 99%

Cuckoo-PC: An Evolutionary Synchronization-Aware Placement of SDN Controllers for Optimizing the Network Performance in WSNs

Tahmasebi

Safi

Zolfi

et al. 2020

Sensors

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Due to reliability and performance considerations, employing multiple software-defined networking (SDN) controllers is known as a promising technique in Wireless Sensor Networks (WSNs). Nevertheless, employing multiple controllers increases the inter-controller synchronization overhead. Therefore, optimal placement of SDN controllers to optimize the performance of a WSN, subject to the maximum number of controllers, determined based on the synchronization overhead, is a challenging research problem. In this paper, we first formulate this research problem as an optimization problem, then to address the optimization problem, we propose the Cuckoo Placement of Controllers (Cuckoo-PC) algorithm. Cuckoo-PC works based on the Cuckoo optimization algorithm which is a meta-heuristic algorithm inspired by nature. This algorithm seeks to find the global optimum by imitating brood parasitism of some cuckoo species. To evaluate the performance of Cuckoo-PC, we compare it against a couple of state-of-the-art methods, namely Simulated Annealing (SA) and Quantum Annealing (QA). The experiments demonstrate that Cuckoo-PC outperforms both SA and QA in terms of the network performance by lowering the average distance between sensors and controllers up to 13% and 9%, respectively. Comparing our method against Integer Linear Programming (ILP) reveals that Cuckoo-PC achieves approximately similar results (less than 1% deviation) in a noticeably shorter time.

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An efficient placement of sinks and SDN controller nodes for optimizing the design cost of industrial IoT systems

Cited by 15 publications

References 51 publications

Control Plane Optimisation for an SDN-Based WBAN Framework to Support Healthcare Applications

Control Plane Optimisation for an SDN-Based WBAN Framework to Support Healthcare Applications

Metaheuristics in cloud computing

Cuckoo-PC: An Evolutionary Synchronization-Aware Placement of SDN Controllers for Optimizing the Network Performance in WSNs

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