Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things

Bagula, Antoine; Abidoye, Ademola P.; Zodi, Guy-Alain Lusilao

doi:10.3390/s16010009

“…In the case of visual sensor networks, they can be used to protect the services and applications running on some specific visual sensor motes. Using the service-aware routing paradigm in [36], MACO can be extended into a service aware multipath ant colony optimization (SAMACO) algorithm that routes the sensor readings according to the motes' service requirements. Differentiation of services can also be built around the path aware routing algorithms proposed in [37] where parallel paths are computed from the source nodes to the sink of the network, but constrained by specific QoS requirements for each path.…”

Section: Discussionmentioning

confidence: 99%

Modelling and QoS Implementation of Wireless Sensor Networks based on the Ant Colony Optimization Approach

Abidoye¹

2018

IJITCS

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A new form of wireless sensor networks is emerging as an important component of the Internet of Things (IoT) where camera devices are interconnected and endowed with an IP address to form visual sensor networks. The applications of these networks span from smart parking systems in smart cities, video surveillance for security systems to healthcare monitoring and many others which are emerging from niche areas. The management of such sensor networks will require meeting a higher quality of service (QoS) constraints than demanded from traditional sensor networks. While many works have focused only on energy efficiency as a way of providing QoS in sensor networks, we consider a novel modelling approach where local optimizations implemented on the sensor nodes are translated into pheromone distribution used in ant colony optimization for path computation. We propose a routing protocol called the multipath ant colony optimization (MACO) that finds QoS-aware routing paths for the sensor readings from source nodes to the sink by relying on four local parameters: the link cost, the remaining energy of neighboring nodes, sensor nodes location information and the amount of data a neighbor node is currently processing. Finally, we propose an architecture for integrating sensor data with the cloud computing. Simulation results reveal the relative efficiency of the newly proposed approach compared to selected related routing protocols in terms of several QoS metrics. These include the network energy efficiency, delay and throughput.

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“…Advanced nodes are included in the sensor networks to eliminate overheads that are usually involved in the selection of CHs, and unnecessary energy wastage during network operations. This differs from previous approaches reported in the literature, which are based on cluster formation and the selection of CHs [29][30][31]. In addition, the inclusion of fog computing ensures that not every sensed data is transmitted to the cloud for further processing and storage.…”

Section: Design Of the Studymentioning

confidence: 91%

Energy-efficient hierarchical routing in wireless sensor networks based on Fog Computing

Abidoye

¹

,

Kabaso

²

2020

Preprint

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4

0

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Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the 21st century. The applications of WSNs are rapidly increasing in almost every sector because they can be deployed in areas where cable and power supply are difficult to use. In the literature, different methods have been proposed to minimize energy consumption of sensor nodes so as to prolong WSNs utilization. In this article, we propose an efficient routing protocol for data transmission in WSNs; it is called Energy-Efficient Hierarchical routing protocol for wireless sensor networks based on Fog Computing (EEHFC). Fog computing is integrated into the proposed scheme due to its capability to optimize the limited power source of WSNs and its ability to scale up to the requirements of the Internet of Things applications. In addition, we propose an improved ant colony optimization (ACO) algorithm that can be used to construct optimal path for efficient data transmission for sensor nodes. The performance of the proposed scheme is evaluated in comparison with P-SEP, EDCF, and RABACO schemes. The results of the simulations show that the proposed approach can minimize sensor nodes’ energy consumption, data packet losses and extends the network lifetime.

show abstract

“…Advanced nodes are included in the sensor networks to eliminate overheads that are usually involved in the selection of CHs, and unnecessary energy wastage during network operations. This differs from previous approaches reported in the literature, which are based on cluster formation and the selection of CHs [29][30][31]. In addition, the inclusion of fog computing ensures that not every sensed data is transmitted to the cloud for further processing and storage.…”

Section: Design Of the Studymentioning

confidence: 91%

Energy-efficient hierarchical routing in wireless sensor networks based on Fog Computing

Abidoye

¹

,

Kabaso

²

2020

Preprint

Self Cite

0

View full text Add to dashboard Cite

Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the 21st century. The applications of WSNs are rapidly increasing in almost every sector because they can be deployed in areas where cable and power supply are difficult to use. In the literature, different methods have been proposed to minimize energy consumption of sensor nodes so as to prolong WSNs utilization. In this article, we propose an efficient routing protocol for data transmission in WSNs; it is called Energy-Efficient Hierarchical routing protocol for wireless sensor networks based on Fog Computing (EEHFC). Fog computing is integrated into the proposed scheme due to its capability to optimize the limited power source of WSNs and its ability to scale up to the requirements of the Internet of Things applications. In addition, we propose an improved ant colony optimization (ACO) algorithm that can be used to construct optimal path for efficient data transmission for sensor nodes. The performance of the proposed scheme is evaluated in comparison with P-SEP, EDCF, and RABACO schemes. The results of the simulations show that the proposed approach can minimize sensor nodes’ energy consumption, data packet losses and extends the network lifetime

show abstract

Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things

Cited by 32 publications

References 21 publications

Modelling and QoS Implementation of Wireless Sensor Networks based on the Ant Colony Optimization Approach

Modelling and QoS Implementation of Wireless Sensor Networks based on the Ant Colony Optimization Approach

Energy-efficient hierarchical routing in wireless sensor networks based on Fog Computing

Energy-efficient hierarchical routing in wireless sensor networks based on Fog Computing

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