A software defined wireless sensor network

Miyazaki, Toshiaki; Shoichi, Yamaguchi; Kobayashi, Katsuhei; Kitamichi, Junji; Guo, Song; Tsukahara, Takehiko; Hayashi, Takafumi

doi:10.1109/iccnc.2014.6785448

Cited by 50 publications

(30 citation statements)

References 8 publications

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“…Due to the application-specific nature of WSNs, it remains a challenge to manipulate its sensor nodes after a full system deployment as these sensors are built for their specific applications. In this regard, a work by Miyazaki et al [50] proposes an SDWSN approach to curb this challenge by means of sensor node (reconfigurable sensor nodes composed of an ultra-low power Field Programmable Gate Array (FPGA) and a Microcontroller Unit (MCU) role assignment. In their proposition, a wireless communication was used to inject roles on certain sensor nodes, thereby allowing the possibility to manipulate or even update the functionality of these sensor nodes depending the system's application requirement.…”

Section: Existing Work On Sdwsnmentioning

confidence: 99%

Software defined wireless sensor networks application opportunities for efficient network management: A survey

Modieginyane

Letswamotse

Malekian

et al. 2018

Computers & Electrical Engineering

179

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Wireless Sensor Networks (WSNs) are one the most widely adopted information technologies of modern networking and computing platforms. Today's network computing applications are faced with a high demand of powerful network functionalities. Functional network reach is central to customer satisfaction such as in mobile networks and cloud computing environments. However, efficient management of WSNs remains a challenge, due to problems supplemental to them. Recent technology shift proposes Software Defined Networking (SDN) for improving computing networks. This review paper highlights application challenges faced by WSNs for monitored environments and those faced by the proposed approaches, as well as opportunities that can be realized on applications of WSNs using SDN. We also highlight Implementation considerations by focusing on critical aspects that should not be disregarded when attempting to improve network functionalities. We then propose a strategy for Software Defined Wireless Sensor Network (SDWSN) as an effort for application improvement in monitored environments.

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Section: Existing Work On Sdwsnmentioning

confidence: 99%

Software defined wireless sensor networks application opportunities for efficient network management: A survey

Modieginyane

Letswamotse

Malekian

et al. 2018

Computers & Electrical Engineering

179

View full text Add to dashboard Cite

show abstract

“…In [22], the authors deployed multiple controllers to build a more flexible control channel, which greatly reduced the average network control delay. The dynamic redefinition function of the node function [23] could effectively extend the network lifetime. In [24], the authors proposed a general architecture for implementing the controller on the WSN base station to enhance the intelligent management of the network.…”

Section: Related Workmentioning

confidence: 99%

Deep Learning Based Proactive Caching for Effective WSN‐Enabled Vision Applications

et al. 2019

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Wireless Sensor Networks (WSNs) have a wide range of applications scenarios in computer vision, from pedestrian detection to robotic visual navigation. In response to the growing visual data services in WSNs, we propose a proactive caching strategy based on Stacked Sparse Autoencoder (SSAE) to predict content popularity (PCDS2AW). Firstly, based on Software Defined Network (SDN) and Network Function Virtualization (NFV) technologies, a distributed deep learning network SSAE is constructed in the sink nodes and control nodes of the WSN network. Then, the SSAE network structure parameters and network model parameters are optimized through training. The proactive cache strategy implementation procedure is divided into four steps. (1) The SDN controller is responsible for dynamically collecting user request data package information in the WSNs network. (2) The SSAEs predicts the packet popularity based on the SDN controller obtaining user request data. (3) The SDN controller generates a corresponding proactive cache strategy according to the popularity prediction result. (4) Implement the proactive caching strategy at the WSNs cache node. In the simulation, we compare the influence of spatiotemporal data on the SSAE network structure. Compared with the classic caching strategy Hash + LRU, Betw + LRU, and classic prediction algorithms SVM and BPNN, the proposed PCDS2AW proactive caching strategy can significantly improve WSN performance.

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“…There have been attempts for actual deployment of proposed management mechanisms such as the case of SDN-WISE, the attempt by Miyazaki et al [136] to build a reprogrammable WSN based on SDN and more recently Soft-WSN but there is still room for many such implementations. Areas such as distributed management based on distributed controllers, low power and long range SDN-based management of WSNs need investigation.…”

Section: Open Challengesmentioning

confidence: 99%

Software Defined Networking for Improved Wireless Sensor Network Management: A Survey

Ndiaye

Hancke

Abu‐Mahfouz³

2017

Sensors

183

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Wireless sensor networks (WSNs) are becoming increasingly popular with the advent of the Internet of things (IoT). Various real-world applications of WSNs such as in smart grids, smart farming and smart health would require a potential deployment of thousands or maybe hundreds of thousands of sensor nodes/actuators. To ensure proper working order and network efficiency of such a network of sensor nodes, an effective WSN management system has to be integrated. However, the inherent challenges of WSNs such as sensor/actuator heterogeneity, application dependency and resource constraints have led to challenges in implementing effective traditional WSN management. This difficulty in management increases as the WSN becomes larger. Software Defined Networking (SDN) provides a promising solution in flexible management WSNs by allowing the separation of the control logic from the sensor nodes/actuators. The advantage with this SDN-based management in WSNs is that it enables centralized control of the entire WSN making it simpler to deploy network-wide management protocols and applications on demand. This paper highlights some of the recent work on traditional WSN management in brief and reviews SDN-based management techniques for WSNs in greater detail while drawing attention to the advantages that SDN brings to traditional WSN management. This paper also investigates open research challenges in coming up with mechanisms for flexible and easier SDN-based WSN configuration and management.

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A software defined wireless sensor network

Cited by 50 publications

References 8 publications

Software defined wireless sensor networks application opportunities for efficient network management: A survey

Software defined wireless sensor networks application opportunities for efficient network management: A survey

Deep Learning Based Proactive Caching for Effective WSN‐Enabled Vision Applications

Software Defined Networking for Improved Wireless Sensor Network Management: A Survey

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