Guang Tan

A Payment-based Incentive and Service Differentiation Mechanism for Peer-to-Peer Streaming Broadcast

We proposes a novel payment-based incentive mechanism for peer-to-peer (P2P) live media streaming. Using this approach, peers earn points by forwarding data to others; the data streaming is divided into fixed length periods, during each of which peers compete with each other for good parents (data suppliers) for the next period in a first-price auction like procedure using their points. We design a distributed algorithm to regulate peer competitions, and consider various individual strategies for parent selection from a game theoretic perspective. We then discuss possible strategies that can be used to maximize a peers expected media quality by planning different bids for its substreams. Finally, in order to encourage off-session users to keep staying online and continue contributing to the network, we develop an optimal data forwarding strategy that allows peers to accumulate points that can be used in future services. Simulations results show that proposed methods effectively differentiate the media qualities received by peers making different contributions (which originate from, for example, different forwarding band-widths or servicing times), and at the same time maintaining a high system-wide performance

A Payment-Based Incentive and Service Differentiation Scheme for Peer-to-Peer Streaming Broadcast

We propose a novel payment-based incentive scheme for peer-to-peer (P2P) live media streaming. Using this approach, peers earn points by forwarding data to others. The data streaming is divided into fixed-length periods; during each of these periods, peers compete with each other for good parents (data suppliers) for the next period in a first-price-auction-like procedure using their points. We design a distributed algorithm to regulate peer competitions and consider various individual strategies for parent selection from a game-theoretic perspective. We then discuss possible strategies that can be used to maximize a peers expected media quality by planning different bids for its substreams. Finally, in order to encourage off-session users to remain online and continue contributing to the network, we develop an optimal data forwarding strategy that allows peers to accumulate points that can be used in future services. Simulation results show that the proposed methods effectively differentiate the media qualities received by peers making different contributions (which originate from, for example, different forwarding bandwidths or servicing times) and at the same time maintain high overall system performance.

Improving the Fault Resilience of Overlay Multicast for Media Streaming

A key technical challenge for overlay multicast is that the highly dynamic multicast members can make data delivery unreliable. In this paper, we address this issue in the context of live media streaming by exploring 1) how to construct a stable multicast tree that minimizes the negative impact of frequent member departures on an existing overlay and 2) how to efficiently recover from packet errors caused by end-system or network failures. For the first problem, we identify two layout schemes for the tree nodes, namely, the bandwidth-ordered tree and the time-ordered tree, which represent two typical approaches to improving tree reliability, and conduct a stochastic analysis on their properties regarding reliability and tree depth. Based on the findings, we propose a distributed reliability-oriented switching tree (ROST) algorithm that minimizes the failure correlation among tree nodes. Compared with some commonly used distributed algorithms, the ROST algorithm significantly improves tree reliability and reduces average service delay, while incurring only a small protocol overhead; furthermore, it features a mechanism that prevents cheating or malicious behaviors in the exchange of bandwidth/time information. For the second problem, we develop a simple cooperative error recovery (CER) protocol that helps recover from packet errors efficiently. Recognizing that a single recovery source is usually incapable of providing the timely delivery of the lost data, the protocol recovers from data outages using the residual bandwidths from multiple sources, which are identified using a minimum-loss-correlation algorithm. Extensive simulations demonstrate the effectiveness of the proposed schemes

Convex Partition of Sensor Networks and Its Use in Virtual Coordinate Geographic Routing

Virtual coordinate geographic routing is an appeal- ing geographic routing approach for its ability to work without physical location information. We examine two representative such routing protocols, namely NoGeo and BVR, and show through experiments and theoretical analysis their limitation in adapting to complex field topologies, in particular fields with concave holes. Based on the new insights, we propose a distributed convex partition protocol that divides the field to subareas with convex shapes, using only connectivity information. A new geographic routing protocol, called CONVEX, that builds upon the partitioning protocol is then described. Simulations demonstrate significant performance improvement of the new routing protocol over NoGeo and BVR, in terms of transmission stretch and maintenance overheads. I. INTRODUCTION

Connectivity-Guaranteed and Obstacle-Adaptive Deployment Schemes for Mobile Sensor Networks

Mobile sensors can relocate and self-deploy into a network. While focusing on the problems of coverage, existing deployment schemes largely oversimplify the conditions for network connectivity: they either assume that the communication range is large enough for sensors in geometric neighborhoods to obtain location information through local communication, or they assume a dense network that remains connected. In addition, an obstacle-free field or full knowledge of the field layout is often assumed. We present new schemes that are not governed by these assumptions, and thus adapt to a wider range of application scenarios. The schemes are designed to maximize sensing coverage and also guarantee connectivity for a network with arbitrary sensor communication/sensing ranges or node densities, at the cost of a small moving distance. The schemes do not need any knowledge of the field layout, which can be irregular and have obstacles/holes of arbitrary shape. Our first scheme is an enhanced form of the traditional virtual-force-based method, which we term the connectivity-preserved virtual force (CPVF) scheme. We show that the localized communication, which is the very reason for its simplicity, results in poor coverage in certain cases. We then describe a floor-based scheme which overcomes the difficulties of CPVF and, as a result, significantly outperforms it and other state-of-the-art approaches. Throughout the paper our conclusions are corroborated by the results from extensive simulations.

Connectivity-based and anchor-free localization in large-scale 2d/3d sensor networks

This paper presents a Connectivity-based and Anchor-free Three-dimensional Localization (CATL) scheme for large-scale sensor networks with concave regions. It distinguishes itself from previous work with a combination of three features: (1) it works for networks in both 2D and 3D spaces, possibly containing holes or concave regions; (2) it is anchor-free, and uses only connectivity information to faithfully recover the original network topology, up to scaling and rotation; (3) it does not depend on the knowledge of network boundaries, which suits it well to situations where boundaries are difficult to identify. The key idea of CATL is to discover the notch nodes, where shortest paths bend and hop-count-based distance starts to significantly deviate from the true Euclidean distance. An iterative protocol is developed that uses a em notch-avoiding multilateration mechanism to localize the network. Simulations show that CATL achieves accurate localization results with a moderate per-node message cost.

Visibility-Graph-Based Shortest-Path Geographic Routing in Sensor Networks

We study the problem of shortest-path geographic routing in a static sensor network. Existing algorithms often make routing decisions based on node information in local neighborhoods. However, it is shown by Kuhn et al. that such a design constraint results in a highly undesirable lower bound for routing performance: if a best route has length c ,t hen in the worst case a route produced by any localized algorithm has length Ω(c 2 ), which can be arbitrarily worse than the optimal. We present VIGOR, a VIsibility-Graph-based rOuting pRotocol that produces routes of length Θ(c). Our design is based on the construction of a much reduced visibility graph, which guides nodes to find near-optimal paths. The per-node protocol overheads in terms of state information and message transmission depend only on the complexity of the fields large topological features, rather than on the network size. Simulation results show that our protocol dramatically outperforms localized protocols such as GPSR and GOAFR+ in both average and worst cases, with reasonable extra overheads.

CorLayer: a transparent link correlation layer for energy efficient broadcast

Wireless communication essentially occurs in a broadcast medium with concurrent receptions. Recent works [34, 41] have shown clear evidence that wireless links are not independent and that transmissions from a transmitter to multiple receivers are correlated, a phenomenon that has profound implications for the performance of network protocols such as broadcast, multi-cast, opportunistic forwarding and network coding. In this paper, we show how link correlation can significantly impact broadcast. We present the design and implementation of CorLayer, a general supporting layer for energy efficient reliable broadcast that carefully blacklists certain poorly correlated wireless links. This method uses only one-hop information, which makes it work in a fully distributed manner and introduces minimal communication overhead. The highlight of our work is CorLayers broad applicability and effectiveness. Our system effort is indeed significant. We integrate CorLayer transparently with sixteen state-of-the-art broadcast protocols specified in thirteen publications [1, 3, 18, 19, 23, 25--27, 32, 36, 38--40] on three physical testbeds running TelosB, MICAz, and GreenOrbs nodes, respectively. The experimental results show that CorLayer remarkably improves energy efficiency across a wide spectrum of broadcast protocols and that the total number of packet transmissions can be reduced consistently by 47% on average.

SpinLight: A High Accuracy and Robust Light Positioning System for Indoor Applications

This paper presents SpinLight, an indoor positioning system that uses infrared LED lamps as signal transmitters, and light sensors as receivers. The main idea is to divide the space into spatial beams originating from the light source, and identify each beam with a unique timed sequence of light signals. This sequence is created by a coded shade that covers and rotates around the LED, blocking the light or allowing it to pass through according to pre-defined patterns. The receiver, equipped with a light sensor, is able to determine its spatial beam by detecting the light signals, followed by optimization schemes to refine its location within that beam. We present both 2D and 3D localization designs, demonstrated by a prototype implementation. Experiments show that SpinLight produces a median location error of 3.8 cm, with a 95th percentile of 6.8 cm. The receiver design is very low power and thus can operate for months to years from a button coin battery.

Greedy geographic routing in large-scale sensor networks: a minimum network decomposition approach

In geographic (or geometric) routing, messages are by default routed in a greedy manner: The current node always forwards a message to its neighbor node that is closest to the destination. Despite its simplicity and general efficiency, this strategy alone does not guarantee delivery due to the existence of local minima (or dead ends). Overcoming local minima requires nodes to maintain extra nonlocal state or to use auxiliary mechanisms. We study how to facilitate greedy forwarding by using a minimum amount of such nonlocal states in topologically complex networks. Specifically, we investigate the problem of decomposing a given network into a minimum number of greedily routable components (GRCs), where greedy routing is guaranteed to work. We approach it by considering an approximate version of the problem in a continuous domain, with a central concept called the greedily routable region (GRR). A full characterization of GRR is given concerning its geometric properties and routing capability. We then develop simple approximate algorithms for the problem. These results lead to a practical routing protocol that has a routing stretch below 7 in a continuous domain, and close to 1 in several realistic network settings.