E2Net: Resource-Efficient Continual Learning with Elastic Expansion Network

Continual Learning methods are designed to learn new tasks without erasing previous knowledge. However, Continual Learning often requires massive computational power and storage capacity for satisfactory performance. In this paper, we propose a resource-efficient continual learning method called the Elastic Expansion Network (E2Net). Leveraging core subnet distillation and precise replay sample selection, E2Net achieves superior average accuracy and diminished forgetting within the same computational and storage constraints, all while minimizing processing time. In E2Net, we propose Representative Network Distillation to identify the representative core subnet by assessing parameter quantity and output similarity with the working network, distilling analogous subnets within the working network to mitigate reliance on rehearsal buffers and facilitating knowledge transfer across previous tasks. To enhance storage resource utilization, we then propose Subnet Constraint Experience Replay to optimize rehearsal efficiency through a sample storage strategy based on the structures of representative networks. Extensive experiments conducted predominantly on cloud environments with diverse datasets and also spanning the edge environment demonstrate that E2Net consistently outperforms state-of-the-art methods. In addition, our method outperforms competitors in terms of both storage and computational requirements

Improving Both Energy and Time Efficiency of Depth-Based Routing for Underwater Sensor Networks

Underwater Sensor Network (UWSN) is a representative three-dimensional wireless sensor network. Due to the unique characteristics of underwater acoustic communication, providing energy-efficient and low-latency routing protocols for UWSNs is challenging. Major challenges are water currents, limited resources, and long acoustic propagation delay. Network topology of UWSNs is dynamic and complex as sensors have always been moving with currents. Some proposed protocols adopt geographic routing to address this problem, but three-dimensional localization is hard to obtain in underwater environment. As depth-based routing protocol (DBR) uses depth information only which is much more easier to obtain, it is more practical for UWSNs. However, depth information is not enough to restrict packets to be forwarded within a particular area. Packets may be forwarded through multiple paths which might cause energy waste and increase end-to-end delay. In this paper, we introduce underwater time of arrival (ToA) ranging technique to address the problem above. To maintain all the original advantages of DBR, we make the following contributions: energy-efficient depth-based routing protocol that reduces redundancy energy cost in some blind zones; low-latency depth-based routing protocol that is able to deliver a packet through an optimal path. The proposed protocols are validated through extensive simulations

Effect of Ecological Factors on Nutritional Quality of Foxtail Millet (<i>Setaria italica</i> L.)

Foxtail millet (Setaria italica [L.] P. Beauv.) is a climate-change-ready crop, and it is crucial for predicting the impact of ecological factors on grain quality. In this study, multivariate statistical analysis was used to explore the relationship between ecological factors and the key nutritional quality of Jingu 21 from twelve production areas. The results showed that the crude fat and amylopectin content of foxtail millets showed a downward trend from south to north. The nutritional quality was significantly affected by geographical, climatic, and soil factors, and the foxtail millet produced in geographically close areas was extremely similar in nutritional quality. Most nutritional quality indicators of Jingu 21 had a strong correlation with the latitude and climatic factors such as average temperature, diurnal temperature range, and average precipitation, while the content of mineral elements was greatly affected by soil factors. Moreover, higher average precipitation in the jointing, booting–heading, and heading stages, a higher average temperature, and a lower diurnal temperature range in the heading and grain-filling stages are conducive to the establishment of nutritional quality. The findings could facilitate the rational distribution of high-quality foxtail millets under global climate change