Haiyun Luo

Zero-Configuration, Robust Indoor Localization: Theory and Experimentation

With the technical advances in ubiquitous comput- ing and wireless networking, there has been an increasing need to capture the context information (such as the location) and to figure it into applications. In this paper, we establish the theoreti- cal base and develop a localization algorithm for building a zero- configuration and robust indoor localization and tracking system to support location-based network services and management. The localization algorithm takes as input the on-line measurements of received signal strengths (RSSs) between 802.11 APs and between a client and its neighboring APs, and estimates the location of the client. The on-line RSS measurements among 802.11 APs are used to capture (in real-time) the effects of RF multi-path fading, temperature and humidity variations, opening and closing of doors, furniture relocation, and human mobility on the RSS measurements, and to create, based on the truncated singular value decomposition (SVD) technique, a mapping between the RSS measure and the actual geographical distance. The proposed system requires zero-configuration because the on-line calibration of the effect of wireless physical characteristics on RSS measurement is automated and no on-site survey or initial training is required to bootstrap the system. It is also quite responsive to environmental dynamics, as the impacts of physical characteristics changes have been explicitly figured in the mapping between the RSS measures and the actual geographical distances. We have implemented the proposed system with inexpensive off-the-shelf Wi-Fi hardware and sensory functions of IEEE 802.11, and carried out a detailed empirical study in our division building. The empirical results show the proposed system is quite robust and gives accurate localization results (i.e., with the localization error within 3 meters).

Flow Scheduling for End-Host Multihoming

Fueled by the competing DSL and Cable technologies, residential broadband access has seen a significant spread in availability to the point that many users have a choice from several ISPs. At the same time, 802.11 networks have spread rapidly in the residential area, and it is common for neighbors to be able to access each other’s wireless routers. End-users can leverage this diversity to improve their Internet connectivity at no additional cost by pooling all available Internet connections, both their own and their neighbors’ via wireless. In this paper we present our design and evaluation of flow scheduling algorithms in PERM, a framework for practical end-host multihoming. PERM scheduler employs automated on-line analysis of the endusers’ networking behaviors, and exploits the recognized patterns to achieve high-performance scheduling at flow level. We verify our models of end-user’s network traffic with large residential TCP traces. Based on these models we propose algorithms for scalable pre-probing and hybrid flow scheduling. Intensive experiments in our prototype testbed show that PERM scheduler reduces the latency by up to 50% for light-volume flows, and reduces the mean transmission time of heavy-volume flows by nearly 28% and 62% compared with a single Cable or DSL connection respectively. The PERM scheduler also out-performs algorithms for enterprise multihoming by up to 15% and 27% in mean transmission time for lightand heavy-volume flows

Rate-Adaptive Framing for Interfered Wireless Networks

The majority of existing wireless rate controls are based on the implicit assumption that frames are corrupted due to the random, arbitrary environmental and thermal noises. They generally reduce the channel rate on frame losses, trading lower efficiency in frequency band utilization for more robust modulation so that the current noise level may be tolerable. In highly interfered wireless networks where frames are lost mainly due to interference from other wireless transceivers, simply reducing the channel rate prolongs the frame transmission time and therefore aggravates frame loss ratio. This positive feedback in the rate control loop quickly diverges the interfered transceivers into a suboptimal channel rate and drives the network into a state with high interference. In the worst case, interfered transceivers can be starved. In this paper we present RAF, the rate-adaptive framing that jointly controls the channel rate and frame size according to the observed interference patterns and noise level at the receiver. Based on the inputs from physical layer carrier sense, the receiver derives the optimal channel rate and frame size that maximize throughput, and informs the transmitter of such optimal configuration in a few bits in the per-frame acknowledgement. Through intensive simulations we show that RAF consistently outperforms ARF, RBAR, and OAR in all simulated scenarios.

Self-Learning Collision Avoidance for Wireless Networks

The limited number of orthogonal channels and the autonomous installations of hotspots and home wireless networks often leave neighboring 802.11 basic service sets (BSS’s) operating on the same or overlapping channels, therefore interfering with each other. However, the 802.11 MAC does not work well in resolving inter-BSS interferences due to the well-known hidden/exposed receiver problem, which has been haunting in the research community for more than a decade. In this paper we propose SELECT, an effective and efficient self-learning collision avoidance strategy to address the open hidden/exposed receiver problem in wireless networks. SELECT is based on the observation that carrier sense with received signal strength (RSS) measurements at the sender and the receiver are strongly correlated. A SELECT-enabled sender exploits such correlation using automated on-line learning algorithm, and makes informed judgment of the channel availability at the intended receiver. SELECT achieves collision avoidance at packetlevel time granularity, involves zero communication overhead, requires no hardware support beyond what is available in offthe-shelf 802.11 devices, and easily integrates with the 802.11 DCF. Our evaluation in both analysis and simulations show that SELECT addresses the hidden/exposed receiver problem well. In typical hidden/exposed receiver scenarios SELECT improves the throughput by up to 140% and channel access success ratio by up to 302%, while almost completely eliminating contention-induced data packet drops.

SELECT: Self-Learning Collision Avoidance for Wireless Networks

The limited number of orthogonal channels and autonomous installations of hot spots and home wireless networks often leave neighboring 802.11 basic service sets (BSSs) operating on the same or overlapping channels, therefore interfering with each other. However, the 802.11 medium access control (MAC) does not work well in resolving inter-BSS interference due to the well-known hidden/exposed-receiver problem, which has been haunting the research community for more than a decade. In this paper, we propose SELECT, an effective and efficient self-learning collision avoidance strategy to address the hidden/exposed-receiver problem in 802.11 wireless networks. SELECT is based on the observation that carrier sense with received signal strength (RSS) measurements at the sender and the receiver can be strongly correlated. A SELECT-enabled sender exploits such correlation using an automated online learning algorithm and makes an informed judgment of the channel availability at the intended receiver. SELECT achieves collision avoidance at packet-level time granularity, involves zero communication overhead, and easily integrates with the 802.11 distributed coordination function (DCF). Our evaluation in analysis, simulations, and prototype experiments show that SELECT addresses the hidden/exposed-receiver problem well. In typical hidden/exposed-receiver scenarios, SELECT improves the throughput by up to 140 percent and the channel access success ratio by up to 302 percent while almost completely eliminating contention-induced data packet drops.

A Cross-Layer Architecture to Exploit Multi-Channel Diversity with a Single Transceiver

The design of multi-channel multi-hop wireless mesh networks is centered around the way nodes synchronize when they need to communicate. However, existing designs are confined to the MAC layer -they are based on either negotiation on a rendezvous control channel, or on optimistic synchronization. Both approaches scale poorly as the network grows in coverage and density. The rendezvous control channel may become the bottleneck, while optimistic synchronization may incur substantial overhead - especially amongst nodes close to a gateway, where the mesh traffic converges. In this paper, we describe Dominion - a cross-layer architecture that includes both medium access control and routing. At the MAC layer, a node switches channels in a deterministic manner to address the scalability issue. At the network layer, a Dominion node routes traffic along the shortest distance across both spatial and frequency domains, based on the deterministic channel-hopping schedule and network connectivity. Since the shortest distance path across the frequency domain is time variant, Dominion naturally spreads the packets of the same flow across multiple paths, relieving the intra-flow and inter-flow contention, and improving throughput. Through QualNet simulations we show that Dominion is able to achieve, on average, 1813% higher aggregate distance-normalized throughput than IEEE 802.11, while being 1730% fairer (using Jains fairness index) with 50 simultaneous random flows.

Routing in the frequency domain

The design of single transceiver based multi-channel multi-hop wireless mesh networks focuses on the trade-off between rapid neighbor synchronization and maximizing the usage of all available channels. Existing designs are confined to the MAC layer and scale poorly as the network grows in coverage and density. We recently proposed Dominion as a cross-layer architecture that includes both medium access control and routing. Dominion eliminates the need for neighbor synchronization at the MAC layer and pushes the intelligence up the network stack. At the MAC layer, a node switches channels according to a deterministic schedule which guarantees that a node converges with each of its neighbors periodically. At the network layer, the channel-hopping aware routing substrate routes traffic along the frequency domain, i.e., packets along a multi-hop route generally traverse via multiple channels. In this paper, we present the complete design, analysis and evaluation of Dominion and make four new contributions. Firstly, we extend Dominion to support goal-oriented routing: source nodes can locally choose to maximize throughput or minimize end-to-end latency without requiring any changes in the network. Secondly, we describe a technique that eliminates intra-flow interference. In absence of extrinsic interference, Dominion now allows network flows to maintain constant throughput and deterministic end-to-end latencies irrespective of distance. Thirdly, via theoretical modeling and analysis, we provide expected throughput and end-to-end latencies for network flows. Finally, via extensive QualNet simulations we show that Dominion achieves 1064% higher throughput than IEEE 802.11 while being 299% fairer.