An Application of Throughput Request Satisfaction Method for Maximizing Concurrent Throughput in WLAN for IoT Application System.

With the wide applications of the Internet of Things (IoT) in smart home systems, IEEE 802.11n Wireless Local Area Networks (WLANs) have become a frequently chosen communication technology due to their adaptability and affordability. In a high-density network of devices such as the smart home scenerio, a host often meets interferences from other devices and unequal Received Signal Strength (RSS) from Access Points (APs). This results in throughput unfairness/insufficiency problems between hosts communicating concurrently in WLAN. Previously, we have studied the throughput request satisfaction method to address this problem. It calculates the target throughput from measured single and concurrent throughputs of hosts and controls the actual throughput at this target one by applying traffic shaping at the AP. However, the insufficiency problem of maximizing the throughput is not solved due to interferences from other hosts. In this paper, we present an extension of the throughput request satisfaction method to maximize the throughput of a high-priority host under concurrent communications. It recalculates the target throughput to increase the actual throughput as much as possible while the other hosts satisfy the least throughput. For evaluations, we conduct experiments using the test-bed system with Raspberry Pi as the AP devices in several topologies in indoor environments. The results confirm the effectiveness of our proposal.

Spirodalesol analog 8A inhibits NLRP3 inflammasome activation and attenuates inflammatory disease by directly targeting adaptor protein ASC.

Pharmacological inhibition of the Nod-like receptor family protein 3 (NLRP3) inflammasome contributes to the treatment of numerous inflammation-related diseases, making it a desirable drug target. Spirodalesol, derived from the ascomycete fungus Daldinia eschscholzii, has been reported to inhibit NLRP3 inflammasome activation. Based on the structure of spirodalesol, we synthesized and screened a series of analogs to find a more potent inhibitor. Analog compound 8A was identified as the most potent selective inhibitor for NLRP3 inflammasome assembly, but 8A did not inhibit the priming phase of the inflammasome. Specifically, while 8A did not reduce NLRP3 oligomerization, we found that it inhibited the oligomerization of adaptor protein apoptosis-associated speck-like protein containing a caspase activation and recruitment domain (ASC), as ASC speck formation was significantly reduced. Also, 8A interrupted the assembly of the NLRP3 inflammasome complex and inhibited the activation of caspase-1. Subsequently, we used a cellular thermal shift assay and microscale thermophoresis assay to demonstrate that 8A interacts directly with ASC, both in vitro and ex vivo. Further, 8A alleviated lipopolysaccharide-induced endotoxemia, as well as monosodium urate-induced peritonitis and gouty arthritis in mice by suppressing NLRP3 inflammasome activation. Thus, 8A was identified as a promising ASC inhibitor to treat inflammasome-driven diseases.

An Interface Setup Optimization Method Using a Throughput Estimation Model for Concurrently Communicating Access Points in a Wireless Local Area Network.

The IEEE 802.11 wireless local-area network (WLAN) has been deployed around the globe as a major Internet access medium due to its low cost and high flexibility and capacity. Unfortunately, dense wireless networks can suffer from poor performance due to high levels of radio interference resulting from adjoining access points (APs). To address this problem, we studied the AP transmission power optimization method, which selects the maximum or minimum power supplied to each AP so that the average signal-to-interference ratio (SIR) among the concurrently communicating APs is maximized.However, this method requires measurements of receiving signal strength (RSS) under all the possible combinations of powers. It may need intolerable loads and time as the number of APs increases. It also only considers the use of channel bonding (CB), although non-CB sometimes achieves higher performance under high levels of interference. In this paper, we present an AP interface setup optimization method using the throughput estimation model for concurrently communicating APs. The proposed method selects CB or non-CB in addition to the maximum or minimum power for each AP. This model approach avoids expensive costs of RSS measurements under a number of combinations. To estimate the RSS at an AP from another AP or a host, the model needs the distance and the obstacles between them, such as walls. Then, by calculating the estimated RSS with the model and calculating the SIR from them, the AP interface setups for a lot of APs in a large-scale wireless network can be optimized on a computer in a very short time. For evaluation, we conducted extensive experiments using Raspberry Pi for APs and Linux PCs for hosts under 12 network topologies in three buildings at Okayama University, Japan, and Jatiya Kabi Kazi Nazrul Islam University, Bangladesh. The results confirm that the proposed method selects the best AP interface setup with the highest total throughput in any topology.