Recent advances in unmanned aerial vehicle (UAV) technologies have made it possible to deploy an aerial video surveillance system to provide an unprecedented aerial perspective for ground monitoring in real time. Multiple UAVs would be required to cover a large target area, and it is difficult for users to visualize the overall situation if they were to receive multiple disjoint video streams. To address this problem, we designed and implemented SkyStitch, a multiple-UAV video surveillance system that provides a single and panoramic video stream to its users by stitching together multiple aerial video streams. SkyStitch addresses two key design challenges: (i) the high computational cost of stitching and (ii) the difficulty of ensuring good stitching quality under dynamic conditions. To improve the speed and quality of video stitching, we incorporate several practical techniques like distributed feature extraction to reduce workload at the ground station, the use of hints from the flight controller to improve stitching efficiency and a Kalman filter-based state estimation model to mitigate jerkiness. Our results show that SkyStitch can achieve a stitching rate that is 4 times faster than existing state-of-the-art methods and also improve perceptual stitching quality. We also show that SkyStitch can be easily implemented using commercial off-the-shelf hardware.

In this paper, we describeFairMesh, which is the first attempt at mitigating the unfairnessarising from physical layer capture (PLC)in 802.11 mesh networks. In the presence of PLC, which is surprisingly common in practical mesh networks, existing state-of-art solutions either fail to correctly identify the sender that needs to be throttled or are too aggressive in reducing the sending rate. FairMesh is able to accurately detect unfairness quickly and employs a simple$CW_{min}$adjustment algorithm to achieve approximate max-min fairness. Our key insight is that the nodes that cause an unfair situation to arise and can act to remedy it are often distinct from the ones that can accurately assess the degree of unfairness. To the best of our knowledge, we are the first to decouple the detection and assessment of unfairness from the remedial action. A key strength of our approach is itssimplicity, which makes it amenable for deployment in practical 802.11 mesh networks to allow an arbitrary number of flows to operate concurrently without modifications to the 802.11 MAC. We show via simulation and with experiments on a 20-node outdoor 802.11 wireless mesh testbed that FairMesh has many desirable properties. First, it is fully distributed and has negligible control overhead. Second, it achieves approximate max-min fairness, and can be modified to support a different notion of fairness (e.g., proportional fairness). Third, it can handle multiple (more than two) competing links and can scale up to mesh networks with tens of nodes. Fourth, it remains efficient under high data rates and high loss rates. Finally, FairMesh interacts well with TCP and maintains good fairness when a multi-hop flow competes with a single-hop flow.

Previous work on 802.1 1x (Wi-Fi) power control have focused almost exclusively on the mitigation of interference from data frames. Since Wi-Fi wireless access points are increasingly ubiquitous, it is now common for an 802.1 1x client to be able to receive signals from more than 10 APs simultaneously in a modern urban operating environment. At such high densities, we found that the interference from the MAC acknowledgment (ACK) frames can potentially reduce throughput by several fold. We show that by dynamically adjusting the transmission power of the ACK frames, a simple ACK power control algorithm, which we call MinPACK, can significantly mitigate interference and increase throughput by a median of 31%, while simultaneously improving fairness. MinPACK is complementary to existing data frames power control algorithms, and adapts rapidly to dynamic environments.

We design and evaluate a new type of wireless mesh nodes called Dyntenna nodes that are equipped with steerable omnidirectional antenna. Designed for 3D wireless mesh networks, these nodes adaptively adjust the antenna orientation to increase throughput by improving the Received Signal Strength Indicator (RSSI) reading between nodes. We demonstrate the importance of being able to programmatically orient the antenna, by presenting the measurement results from our 3D urban mesh testbed. We propose a simple antenna adjustment algorithm that can improve the throughput for 26% of one-hop paths and 35% of multi-hop paths by a median value of 31% and 46%, respectively. Our algorithm converges quickly and typically probes less than 10% of all possible antenna orientations on average.

It is well known that the pervasive IEEE 802.11 MAC is intrinsically unfair. In particular, in the topology shown in Fig. 1(a), when links AB and CD both carry backlogged transmissions, the packets from sender A experience persistent collisions at node B while sender C enjoys collision-free transmission to D. Node A can transmit successfully only if it is able to "insert" its packets into the small inter-packet gaps of C's packets. Thus, we refer to the topology in Fig. 1(a) as the unfair topology and to C and A as the superior and inferior nodes respectively.