Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks

Savaglio, Claudio; Pace, Pasquale; Aloi, Gianluca; Liotta, Antonio; Fortino, Giancarlo

doi:10.1109/access.2019.2902371

Cited by 95 publications

(55 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, we plan to verify the performance of the ODCR protocol in terms of latency, localization error and other performance metrics in the future. We also plan to include a reinforcement learning-based approach (i.e., machine learning and artificial intelligence [27,28]) in the MAC protocol and scheduling mechanism to achieve sensor energy efficiency as part of a future work.…”

Section: Discussionmentioning

confidence: 99%

Efficient Opportunistic Routing Protocol for Sensor Network in Emergency Applications

2020

View full text Add to dashboard Cite

Routing or forwarding information, such as the location of incidents and victims in a disaster, is significantly important for quick and accurate incident response. However, forwarding such information in disaster areas has been a challenging task for the Wireless Sensor Network as existing networks are affected (destroyed or overused) the disaster. Opportunistic information forwarding can play a vital role in such circumstances. Existing opportunistic routing protocols require huge message transmissions for cluster restoration, which is not energy efficient and results in packet loss. Hence, this paper introduces an energy efficient and reliable opportunistic density cluster-based routing protocol that opportunistically transmits data using a density-clustering protocol for emergency and disaster situations. Simulation results show that the proposed protocol outperforms some existing and well-known routing protocols in terms of network energy consumption, throughput and successful data transmissions.Electronics 2020, 9, 455 2 of 17 sensors can communicate properly and efficiently manage their energy consumption and forward information to the first responders. In this protocol, nodes carry stored messages while moving around and forward them whenever an opportunity arises. This opportunity is simply making a contact with a node that knows how to route the message closer to the desired receiver. Hence, a route is built dynamically from the sender to the receiver. Any node can possibly be the next hop in an opportunistic forwarding. Figure 1 demonstrates such an opportunistic network for disaster recovery.

show abstract

Section: Discussionmentioning

confidence: 99%

Efficient Opportunistic Routing Protocol for Sensor Network in Emergency Applications

2020

View full text Add to dashboard Cite

show abstract

“…Otherwise, it could negatively affect the wearable device's performance in terms of execution speed, responsiveness, and latency. Recently, some studies have also proposed using artificial intelligence-based techniques such as reinforcement learning to develop intelligent Medium Access Control (MAC) protocols for IoT devices to efficiently predict wakeup schedules and adaptive sleep cycle management to save energy [134].…”

Section: B Duty Cyclingmentioning

confidence: 99%

Towards Energy Efficiency in the Internet of Wearable Things: A Systematic Review

et al. 2020

View full text Add to dashboard Cite

Personal mobile devices such as smartwatches, smart jewelry, and smart clothes have launched a new trend in the Internet of Things (IoT) era, namely the Internet of Wearable Things (IoWT). These wearables are small IoT devices capable of sensing, storing, processing, and exchanging data to assist users by improving their everyday life tasks through various applications. However, the IoWT has also brought new challenges for the research community to address such as increasing demand for enhanced computational power, better communication capabilities, improved security and privacy features, reduced form factor, minimal weight, and better comfort. Most wearables are battery-powered devices that need to be recharged-therefore, the limited battery life remains the bottleneck leading to the need to enhance the energy efficiency of wearables, thus, becoming an active research area. This paper presents a survey of energy-efficient solutions proposed for diverse IoWT applications by following the systematic literature review method. The available techniques published from 2010 to 2020 are scrutinized, and the taxonomy of the available solutions is presented based on the targeted application area. Moreover, a comprehensive qualitative analysis compares the proposed studies in each application area in terms of their advantages, disadvantages, and main contributions. Furthermore, a list of the most significant performance parameters is provided. A more in-depth discussion of the main techniques to enhance wearables' energy efficiency is presented by highlighting the trade-offs involved. Finally, some potential future research directions are highlighted.

show abstract

“…The BS initiates the decision for further processes. Users received the crop growth information or other information related to the drip irrigation and take further initiatives to improve the microenvironment for their product [9]. In agriculture, for achieving the precision control, the sensor nodes monitored different parameters, analysis of monitored data for decision making and applying the control mechanism [10,11].…”

Section: Introductionmentioning

confidence: 99%

Optimized Cluster-Based Dynamic Energy-Aware Routing Protocol for Wireless Sensor Networks in Agriculture Precision

et al. 2020

View full text Add to dashboard Cite

Wireless sensor networks (WSNs) are becoming one of the demanding platforms, where sensor nodes are sensing and monitoring the physical or environmental conditions and transmit the data to the base station via multihop routing. Agriculture sector also adopted these networks to promote innovations for environmental friendly farming methods, lower the management cost, and achieve scientific cultivation. Due to limited capabilities, the sensor nodes have suffered with energy issues and complex routing processes and lead to data transmission failure and delay in the sensor-based agriculture fields. Due to these limitations, the sensor nodes near the base station are always relaying on it and cause extra burden on base station or going into useless state. To address these issues, this study proposes a Gateway Clustering Energy-Efficient Centroid-(GCEEC-) based routing protocol where cluster head is selected from the centroid position and gateway nodes are selected from each cluster. Gateway node reduces the data load from cluster head nodes and forwards the data towards the base station. Simulation has performed to evaluate the proposed protocol with state-of-the-art protocols. The experimental results indicated the better performance of proposed protocol and provide more feasible WSN-based monitoring for temperature, humidity, and illumination in agriculture sector.

show abstract

Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks

Cited by 95 publications

References 28 publications

Efficient Opportunistic Routing Protocol for Sensor Network in Emergency Applications

Efficient Opportunistic Routing Protocol for Sensor Network in Emergency Applications

Towards Energy Efficiency in the Internet of Wearable Things: A Systematic Review

Optimized Cluster-Based Dynamic Energy-Aware Routing Protocol for Wireless Sensor Networks in Agriculture Precision

Contact Info

Product

Resources

About