Edge Computing-Based Joint Client Selection and Networking Scheme for Federated Learning in Vehicular IoT

In order to support advanced vehicular Internet-of-Things(IoT)applications,information exchanges among different vehicles are required to find efficient solutions for catering to different application requirements in complex and dynamic vehicular environments.Federated learning(FL),which is a type of distributed learning technology,has been attracting great interest in recent years as it performs knowledge exchange among different network entities without a violation of user privacy.However,client selection and networking scheme for enabling FL in dynamic vehicular environments,which determines the communication delay between FL clients and the central server that aggregates the models received from the clients,is still under-explored.In this paper,we propose an edge computing-based joint client selection and networking scheme for vehicular IoT.The proposed scheme assigns some vehicles as edge vehicles by employing a distributed approach,and uses the edge vehicles as FL clients to conduct the training of local models,which learns optimal behaviors based on the interaction with environments.The clients also work as forwarder nodes in information sharing among network entities.The client selection takes into account the vehicle velocity,vehicle distribution,and the wireless link connectivity between vehicles using a fuzzy logic algorithm,resulting in an efficient learning and networking architecture.We use computer simulations to evaluate the proposed scheme in terms of the communication overhead and the information covered in learning.

NEW ERA SOFTWARE DEFINED NETWORK

Software-Defined Networking(SDN)is now considered as one of the promising future networking technologies,and this trend can be clearly verified by observing activities of both industry and academia.In industry,we can easily notice that many major

Flux Growth and Properties of KNPBN Crystal

Potasium sodium lead barium niobate KNPBN crystals have been grown successfully by flux method.The dielectric constant along the polar axis was measured at 50 kHz as a function of temperature in the range of 0 to 400℃.The flux system,diffuse phase transition and optical absorption were also discussed.

Hypoxia-Responsive Root Hydraulic Conductivity Influences Soybean Cultivar-Specific Waterlogging Tolerance

Excess soil moisture induces hypoxic conditions and causes waterlogging injury in soybean [Glycine max (L.) Merr.]. This study investigated the mechanism underlying the development of waterlogging injury. Nine Japanese soybean cultivars with varying degrees of waterlogging tolerance were grown in a hydroponic system for 14 days under hypoxic conditions. Shoot and root biomasses and root hydraulic conductivity were measured at an early vegetative stage for plants under control and hypoxic conditions. Root morphological traits and intramembrane aquaporin proteins were also analyzed. The tolerance of each cultivar to field waterlogging was based on biomass changes induced by the hypoxia treatment. Root hydraulic conductivity responses to hypoxia were associated with changes in total dry weight, leaf dry weight, and leaf area. The effects of hypoxic conditions on root hydraulic conductivity were also represented by the changes in root morphology, such as total root length, thick-root length, and number of root tips. Additionally, a 32.3 kDa aquaporin-like protein seemed to regulate root hydraulic conductivity. Our results from a hydroponic culture suggest that the soybean cultivar-specific responses to hypoxic conditions in the rhizosphere reflect fluctuations in hydraulic conductivity related to root morphological or qualitative changes.

Structural performance of flexible freeform panelssubjected to wind loads

An increased number of hurricanes and tornadoes have been recorded worldwide in the last decade,while research efforts to reduce wind-related damage to structures become essential.Freeform architecture,which focuses on generating complex curved shapes including streamlined shapes,has recently gained interest.This study focuses on investigating the potential of kerf panels,which have unique flexibility depending on the cut patterns and densities,to generate complex shapes for facades and their performance under wind loads.To investigate the kerf panel's potential capacity against wind loads,static and dynamic analyses were conducted for two kerf panel types with different cut densities and pre-deformed shapes.It was observed that although solid panels result in smaller displacement amplitudes,stresses,and strains in some cases,the kerf panels allow for global and local cell deformations resulting in stress reduction in various locations with the potential to reduce damage due to overstress in structures.For the predeformed kerf panels,it was observed that both the overall stress and strain responses in kerf cut arrangements were lower than those of the flat-shaped panels.This study shows the promise of the use of kerf panels in achieving both design flexibility and performance demands when exposed to service loadings.Considering that this newly proposed architectural configuration(design paradigm)for facades could revolutionize structural engineering by pushing complex freeform shapes to a standard practice that intertwines aesthetic arguments,building performance requirements,and material design considerations has the potential for significant practical applications.