The Hidden Costs of Land Degradation in US Maize Agriculture

The United States is a world leader in the production of maize and other crops and the agricultural success of the country is directly linked to the intensive use of fertilizers and irrigation. However, even in advanced agricultural systems, soils can become degraded over time due to factors such as soil organic matter (SOM) loss and erosion. Here, we use a series of scenario-based model analyses to show that about one-third of current annual US. N fertilizer use in maize agriculture is used to compensate for the long-term loss of soil fertility through erosion and organic matter loss. This leads to over a half billion dollars per year in extra fertilizer supply costs to US farmers. These results highlight the potential to reduce both the input costs and environmental impacts of agriculture through the restoration of SOM in agricultural soils

Securing the Wireless Emergency Alerts System

Modern cell phones are required to receive and display alerts via the Wireless Emergency Alert (WEA) program, under the mandate of the Warning, Alert, and Response Act of 2006. These alerts include AMBER alerts, severe weather alerts, and (unblockable) Presidential Alerts, intended to inform the public of imminent threats. Recently, a test Presidential Alert was sent to all capable phones in the U.S., prompting concerns about how the underlying WEA protocol could be misused or attacked. In this paper, we investigate the details of this system and develop and demonstrate the first practical spoofing attack on Presidential Alerts, using commercially available hardware and modified open source software. Our attack can be performed using a commercially available software-defined radio, and our modifications to the open source software libraries. We find that with only four malicious portable base stations of a single Watt of transmit power each, almost all of a 50,000-seat stadium can be attacked with a 90% success rate. The real impact of such an attack would, of course, depend on the density of cellphones in range; fake alerts in crowded cities or stadiums could potentially result in cascades of panic. Fixing this problem will require a large collaborative effort between carriers, government stakeholders, and cellphone manufacturers. To seed this effort, we also propose three mitigation solutions to address this threat

Enabling Delay-Guaranteed Congestion Control With One-Bit Feedback in Cellular Networks

Unexpected large packet delays are often observed in cellular networks due to huge network queuing caused by excessive traffic coming into the network. To deal with the large queue problem, many congestion control algorithms try to find out how much traffic the network can accommodate, either by measuring network performance or by directly providing explicit information. However, due to the nature of the control in which queue growth should be observed or the necessity to modify the overall network architecture, existing algorithms are experiencing difficulties in keeping queues within a strict bound. In this paper, we propose a novel congestion control algorithm based on simple feedback, ECLAT which can provide bounded queuing delay using only one-bit signaling already available in traditional network architecture. To do so, a base station or a router running ECLAT 1) calculates how many packets each flow should transmit and 2) analyzes when congestion feedback needs to be forwarded to adjust the flow's packet transmission to the desired rate. Our extensive experiments in our testbed demonstrate that ECLAT achieves strict queuing delay bounds, even in the dynamic cellular network environment

ECLAT: An ECN marking system for latency guarantee in cellular networks

As the importance of latency performance increases, a number of multi-bit feedback-based congestion control mechanisms have been proposed for explicit latency control in cellular networks. However, due to their reactive nature and limited access to the network queue, while latency reduction was possible, latency guarantee has not been achieved. Also, due to the need for end-host modifications, it was hard to commonly provide latency benefit to all connected devices. To this end, we propose a novel network-assisted congestion control, ECLAT, which can always bound the queuing delay within a delay-budget through ECN-based single-bit feedback while maintaining high link utilization for any device. To do so, ECLAT 1) calculates its target operating point for each flow, which is related to the maximum allowable cwnd to meet the delay-budget under time-varying cellular networks, and 2) determines its single-bit feedback policy to limit cwnd within the target operating point. Our extensive experiments in our testbed demonstrate that ECLAT is able to bound the queuing delays of multiple flows within their delay-budget and achieve high utilization even in the dynamic cellular network environment.N

Modeling MPTCP Performance

Multi-path TCP (MPTCP) has been standardized by IETF and being used in practice. However, the MPTCP performance analysis has been paid less attention than algorithm improvement, such as coupled congestion control between subflows. The existing analytical models lack consideration of both slow start and congestion avoidance phases. In this letter, we perform a full analysis to derive the MPTCP performance by considering both the phases in the network with shared bottleneck so that we can calculate data transfer latency as well as throughput for a given size of data. Via direct code execution on top of the NS-3 simulation, we show that the proposed analysis captures data transfer latency under packet losses due to buffer overflow

ECLAT: An ECN marking system for latency guarantee in cellular networks

As the importance of latency performance increases, a number of multi-bit feedback-based congestion control mechanisms have been proposed for explicit latency control in cellular networks. However, due to their reactive nature and limited access to the network queue, while latency reduction was possible, latency guarantee has not been achieved. Also, due to the need for end-host modifications, it was hard to commonly provide latency benefit to all connected devices. To this end, we propose a novel network-assisted congestion control, ECLAT, which can always bound the queuing delay within a delay-budget through ECN-based single-bit feedback while maintaining high link utilization for any device. To do so, ECLAT 1) calculates its target operating point for each flow, which is related to the maximum allowable cwnd to meet the delay-budget under time-varying cellular networks, and 2) determines its single-bit feedback policy to limit cwnd within the target operating point. Our extensive experiments in our testbed demonstrate that ECLAT is able to bound the queuing delays of multiple flows within their delay-budget and achieve high utilization even in the dynamic cellular network environment

Calibrating time-variant, device-specific phase noise for COTS WiFi devices

Current COTS WiFi based work on wireless motion sensing extracts human movements such as keystroking and hand motion mainly from amplitude training to classify different types of motions, as obtaining meaningful phase values is very challenging due to time-varying phase noises occurred with the movement. However, the methods based only on amplitude training are not very practical since their accuracy is not environment and location independent. This paper proposes an effective phase noise calibration technique which can be broadly applicable to COTS WiFi based motion sensing. We leverage the fact that multi-path for indoor environment contains certain static paths, such as reflections from wall or static furniture, as well as dynamic paths due to human hand and arm movements. When a hand moves, the phase value of the signal from the hand rotates as the path length changes and causes the superposition of signals over static and dynamic paths in antenna and frequency domain. To evaluate the effectiveness of the proposed technique, we experiment with a prototype system that can track hand gestures in a non-intrusive manner, i.e. users are not equipped with any device, using COTS WiFi devices. Our evaluation shows that calibrated phase values provide much rich, yet robust information on motion tracking ??? 80th percentile angle estimation error up to 14 degrees, 80th percentile tracking error up to 15 cm, and its robustness to the environment and the speed of movement

A Performance Analysis of Incentive Mechanisms for Cooperative Computing

As more devices gain Internet connectivity, more information needs to be exchanged between them. For instance, cloud servers might disseminate instructions to clients, or sensors in the Internet of Things might send measurements to each other. In such scenarios, information spreads faster when users have an incentive to contribute data to others. While many works have considered this problem in peer-to-peer scenarios, none have rigorously theorized the performance of different design choices for the incentive mechanisms. In particular, different designs have different ways of bootstrapping new users (distributing information to them) and preventing free-riding (receiving information without uploading any in return). We classify incentive mechanisms in terms of reciprocity-, altruism-, and reputation-based algorithms, and then analyze the performance of these three basic and three hybrid algorithms. We show that the algorithms lie along a tradeoff between fairness and efficiency, with altruism and reciprocity at the two extremes. The three hybrids all leverage their component algorithms to achieve similar efficiency. The reputation hybrids are the most fair and can nearly match altruism's bootstrapping speed, but only the reciprocity/reputation hybrid can match reciprocity's zero-tolerance for free-riding. It therefore yields better fairness and efficiency when free-riders are present. We validate these comparisons with extensive experimental results