An approximation delay between consecutive requests for congestion control in unicast CoAP-based group communication

This research presents a way to avoid network congestion during unicast CoAP-based group communication using increased delays between consecutive requests (DCR) in LoWPAN border routers to limit request send rates. It also provides a way to determine DCR values that are suitable for various network group sizes with differing node counts. The optimal DCR is obtained using the least squares approximation method and the relative minimum. Results from experimentation shows a positive relation, that is, an increase in group size necessitates an increase in DCR value. Experiments in various group sizes show favorable network performance and support the proposed congestion control method using DCR

The improvement of node Mobility in RPL to increase transmission efficiency

The Internet of Thing has gained interested to use for daily devices to industrial applications. Mission-critical applications such as connected car and healthcare services require real-time communications and mobility support. The 6LoWPAN protocol and IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) have become the standard for the IoT. However, the RPL protocol is unable to support the application requirement causing from the high network overhead, long message latency and high packet loss rate due to mobility. Thus, in this paper, we propose a new cost metric combining the number of hops, RSSI values, and the summation of delay to enhance RPL mobility. In addition, we define the movement notification for the mobile node to activate mobile detection and parent selection processes. Finally, we presented a comparative study of the improved RPL protocols in terms of packet delivery ratio, end-to-end delay and the number of control messages. The result shows that improved RPL protocol with the new cost metrics provides a high packet delivery ratio and offers a low message latency

Combining Space-Based and In-Situ Measurements to Track Flooding in Thailand

We describe efforts to integrate in-situ sensing, space-borne sensing, hydrological modeling, active control of sensing, and automatic data product generation to enhance monitoring and management of flooding. In our approach, broad coverage sensors and missions such as MODIS, TRMM, and weather satellite information and in-situ weather and river gauging information are all inputs to track flooding via river basin and sub-basin hydrological models. While these inputs can provide significant information as to the major flooding, targetable space measurements can provide better spatial resolution measurements of flooding extent. In order to leverage such assets we automatically task observations in response to automated analysis indications of major flooding. These new measurements are automatically processed and assimilated with the other flooding data. We describe our ongoing efforts to deploy this system to track major flooding events in Thailand

Using Multiple Space Assests with In-Situ Measurements to Track Flooding in Thailand

Increasing numbers of space assets can enable coordinated measurements of flooding phenomena to enhance tracking of extreme events. We describe the use of space and ground measurements to target further measurements as part of a flood monitoring system in Thailand. We utilize rapidly delivered MODIS data to detect major areas of flooding and the target the Earth Observing One Advanced Land Imager sensor to acquire higher spatial resolution data. Automatic surface water extent mapping products delivered to interested parties. We are also working to extend our network to include in-situ sensing networks and additional space assets