Soft-WSN: Software-Defined WSN Management System for IoT Applications

Bera, Samaresh; Misra, Sudip; Roy, Sanku Kumar; Obaidat, Mohammad S.

doi:10.1109/jsyst.2016.2615761

Cited by 153 publications

(96 citation statements)

References 15 publications

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“…As a result, it makes it possible to figure out suspicious traffic. The authors of [32] offer a software-defined wireless sensor network framework (Soft-WSN) to support IoT service provisioning. Similarly, [33] introduces SDN-WISE that provides a flexible vendor-independent policy implementation in WSN for IoT application.…”

Section: Related Workmentioning

confidence: 99%

Load-Balanced and QoS-Aware Software-Defined Internet of Things

Montazerolghaem

Yaghmaee

2020

IEEE Internet Things J.

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Internet of Things (IoT) offers a variety of solutions to control industrial environments. The new generation of IoT consists of millions of machines generating huge traffic volumes; this challenges the network in achieving the Quality of Service (QoS) and avoiding overload. Diverse classes of applications in IoT are subject to specific QoS treatments. In addition, traffic should be distributed among IoT servers based on their available capacity. In this paper, we propose a novel framework based on Software-defined Networking (SDN) to fulfill the QoS requirements of various IoT services and to balance traffic between IoT servers simultaneously. At first, the problem is formulated as an Integer Linear Programming (ILP) model that is NP-hard. Then, a predictive and proactive heuristic mechanism based on time-series analysis and fuzzy logic is proposed. Afterwards, the proposed framework is implemented in a real testbed, which consists of the Open vSwitch, Floodlight controller, and Kaa servers. To evaluate the performance, various experiments are conducted under different scenarios. The results indicate the improved IoT QoS parameters, including throughput and delay, and illustrate the non-occurrence of overload on IoT servers in heavy traffic. Furthermore, the results show improved performance compared to similar methods.

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Section: Related Workmentioning

confidence: 99%

Load-Balanced and QoS-Aware Software-Defined Internet of Things

Montazerolghaem

Yaghmaee

2020

IEEE Internet Things J.

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“…Recently, several SD-WSN schemes have been proposed. Bera et al 14 proposed an SD-WSN architecture, named as Soft-WSN. Soft-WSN uses two management entities, that is, device manager and topology manager.…”

Section: Related Workmentioning

confidence: 99%

“…Recently, several softwaredefined wireless sensor network (SD-WSN) schemes have been proposed. [13][14][15] The SD-WSN has the capability of implementing global route orchestration. However, to our best knowledge, there has been no study that discusses global route orchestration for the purpose of energy saving in the SD-WSN environment.…”

Section: Introductionmentioning

confidence: 99%

Energy-saving route optimizationin a software-defined wireless sensor network

Huang

Tang

2018

International Journal of Distributed Sensor Networks

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Energy efficiency in wireless sensor networks is an important concern of 'green' Internet of Things. The existing energysaving routing protocols usually compute the route in isolation, which is disadvantageous to globally optimize the energy consumption. In this article, we propose a novel energy-saving route optimization solution based on the softwaredefined wireless sensor network. In our proposed solution, the controller obtains the overall information about the network topology and the existing routes. Based on the above information, this solution centrally optimizes the routes in a global manner. In contrast to the existing energy-saving routing protocols, the central route optimization better reduces the energy consumption from an overall perspective. The global route optimization tends to reduce the overall energy consumption using a small number of sensors, which can improve the effectiveness of the used sensors. However, using a small number of sensors leads to high energy consumption of related sensors. To solve the above problem, our proposed solution uses a routing evasion mechanism to balance the energy consumption between sensors.

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“…• Homogeneous Network: A Wireless sensor network composed of homogeneous devices that is node has same features [2].…”

Section: Characteristics Of Wireless Sensor Networkmentioning

confidence: 99%

Region Based Clustering for Data Collection in WSN

Kaur

Kumar

2017

IJCT

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The lower cost and easier installation of the WSNs than the wired counterpart pushes industry and academia to pay more attention to this promising technology. Large scale networks of small energy-constrained sensor nodes require techniques and protocols which are scalable, robust, and energy-efficient. The most efficient approach provided by clustering the nodes is hierarchy. The one node will send the data to another node and the another node will send to its neightbouring node. In smart cities, wireless sensor networks (WSNs) act as a type of core infrastructure that collects data from the city to implement smart services. Our thesis work included the region based clustering, cluster head selection and energy efficient communication using static base station and movable mobile nodes. Since it was earlier proposed that clustering improves the network lifetime. We modified the region based clustering by dividing the network area into n regions with cluster head chosen for each region and proposed a new method for cluster head selection having less computational complexity. It was also found that the modified approach has improved performance to that of the other clustering approaches. We have used the mobile nodes for each section with controlled trajectory path as a reference to compare the performance of each of the clustering methods.

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Soft-WSN: Software-Defined WSN Management System for IoT Applications

Cited by 153 publications

References 15 publications

Load-Balanced and QoS-Aware Software-Defined Internet of Things

Load-Balanced and QoS-Aware Software-Defined Internet of Things

Energy-saving route optimizationin a software-defined wireless sensor network

Region Based Clustering for Data Collection in WSN

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