A Software-Defined Management System for IP-Enabled WSNs

Jurado-Lasso, F. Fernando; Clarke, Ken; Nirmalathas, Ampalavanapillai

doi:10.1109/jsyst.2019.2946781

Cited by 14 publications

(6 citation statements)

References 32 publications

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“…The difference lies in whether the forwarding of the control flow is independent of the data flow. At present, the in‐band mode in which the control flow and the data flow share the same wireless channel is generally adopted in the perception layer 14 . The truth behind this is that the sensor node is forced to sacrifice the reliability of network control under the constraints of low cost and resources.…”

Section: Related Workmentioning

confidence: 99%

HIC: A high‐reliable in‐band control network for perception layer of software‐defined IoT

Huang

Zhou

et al. 2023

Trans Emerging Tel Tech

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With the rapid development of the Internet of Things (IoT) and the popularity of the software‐defined idea, the software‐defined Internet of Things (SD‐IoT) came into being. However, the transmission conflict between control flow and data flow in the perception layer with poor channel resources has become an important constraint for SD‐IoT. Thus, this paper adopts the idea of isolated forwarding control flow based on an in‐band channel, that is, selecting some sensor nodes to be responsible for forwarding control flow, and proposes high‐reliable in‐band control network (HIC), a high‐reliability in‐band control network. In order to support real‐time tasks in the IoT environment, HIC adopts a divided control area to support parallel responses of multiple partially overlapping tasks. Further, in each control area, the graph theory is used to model the control node selection problem, and an algorithm for efficiently solving the model is designed based on the community detection method. Finally, we developed the HIC experimental platform composed of HIC‐topology and HIC‐simulation and carried out simulation experiments and analysis from topology generation, maintenance, and operation. The experimental results show that HIC could better adapt to the SD‐IoT under multi‐task deployment, and has great advantages in terms of the success rate and time of topology rapid maintenance compared with similar solutions.

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Section: Related Workmentioning

confidence: 99%

HIC: A high‐reliable in‐band control network for perception layer of software‐defined IoT

Huang

Zhou

et al. 2023

Trans Emerging Tel Tech

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“…The controller builds this table using the Depth First Search (DFS) Algorithm [22]. Lastly, the controller places the list of routes in an NC packet then it delivers the control packet as proposed in [17].…”

Section: A Energy Balancingmentioning

confidence: 99%

Energy-Aware Routing for Software-Defined Multihop Wireless Sensor Networks

et al. 2021

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In this paper, we propose an energy-aware routing algorithm and a control overhead reduction technique for prolonging the network lifetime of software-defined multihop wireless sensor networks (SDWSNs). This is an effort to optimize the energy consumption of WSNs that provide services to the Industrial Internet of Things (IIoT). A centralized controller grants a global view of the sensor network by introducing extra control overhead in the network, but this leads to extra energy costs. However, our new algorithm takes advantage of this global view and balances the network energy by selecting paths with the highest remaining energy level among multiple paths for each sensor node. We also identify key functions draining energy from the SDWSN and minimize their impact by implementing a data packet aggregation function, and minimizing the control overhead by keeping track of the sensor nodes' routing tables using a simple checksum function. We show that the proposed approach prolongs the network lifetime of the WSN by 6.5% on average compared to the standard shortest-path algorithm, and that the control overhead is reduced by approximately 12% while still maintaining a very high packet delivery ratio.

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“…The control plane consists of a logically centralised entity that process requirements from FIGURE 2. Simple representation of an SDWSN architecture [24].…”

Section: Introductionmentioning

confidence: 99%