Xicheng Lu

Underwater Localization in Sparse 3D Acoustic Sensor Networks

We study the localization problem in sparse 3D underwater sensor networks. Considering the fact that depth information is typically available for underwater sensors, we transform the 3D underwater positioning problem into its two- dimensional counterpart via a projection technique and prove that a non-degenerative projection preserves network localizability. We further prove that given a network and a constant k, all of the geometric k-lateration localization methods are equivalent. Based on these results, we design a purely distributed localization framework termed USP. This framework can be applied with any ranging method proposed for 2D terrestrial sensor networks. Through theoretical analysis and extensive simulation, we show that USP preserves the localizability of the original 3D network via a simple projection and improves localization capabilities when bilateration is employed. USP has low storage and computation requirements, and predictable and balanced communication overhead.

3D Underwater Sensor Network Localization

We transform the 3D underwater sensor network (USN) localization problem into its 2D counterpart by employing sensor depth information and a simple projection technique. We first prove that a nondegenerative projection preserves network localizability. We then prove that given a network and a constant k, all of the geometric k-lateration localization methods are equivalent. Based on these results, we design a purely distributed bilateration localization scheme for 3D USNs termed as underwater sensor positioning (USP). Through extensive simulations, we show that USP has the following nice features: (1) improved localization capabilities over existing 3D methods, (2) low storage and computation requirements, (3) predictable and balanced communication overhead, and (4) robustness to errors from the underwater environment.

FISSIONE: a scalable constant degree and low congestion DHT scheme based on Kautz graphs

The distributed hash table (DHT) scheme has become the core component of many large-scale peer-to-peer networks. Degree, diameter, and congestion are important measures of DHT schemes. Many proposed DHT schemes are based on traditional interconnection topologies, one being the Kautz graph, which is a static topology with many good properties such as optimal diameter, optimal fault-tolerance, and low congestion. In this paper, we propose FISSIONE: the first effective DHT scheme based on Kautz graphs. FISSIONE is constant degree, O(log N) diameter, and (1 + o(1))-congestion-free. FISSIONE shows that a DHT scheme with constant degree and constant congestion can still achieve O(log N) diameter, which is better than the lower bound /spl Omega/(N/sup 1/d/) conjectured before. The average degree of FISSIONE is 4, the diameter is less than 2 log N, and the maintenance message cost is less than 3 log N. The average routing path length is about log N and is shorter than CAN or Koorde with the same degree when the peer-to-peer network is large-scale. FISSIONE can achieve good load balance, high performance, and low congestion and these properties are carefully evaluated by formal proofs or simulations in the paper.

Time-Synchronization Free Localization in Large Scale Underwater Acoustic Sensor Networks

We introduce and study the localization problem in large scale underwater acoustic sensor networks. Considering that depth information is typically available for underwater sensors, we transform the 3D underwater positioning problem into its two-dimensional counterpart via a projection technique. We then introduce a localization scheme specifically designed for large scale acoustic underwater sensor networks. The proposed localization scheme does not require time-synchronization in the network. This scheme relies on time-differences of arrival (TDoA) measured locally at a sensor to detect range differences from the sensor to three anchors that can mutually hear each other. We consider variations in the speed of sound and analyze the performance of the proposed scheme in terms of the number of localized nodes, location errors, and the number of reference nodes.

Efficient Range Query Processing in Peer-to-Peer Systems

With the increasing popularity of the peer-to-peer (P2P) computing paradigm, many general range query schemes for distributed hash table (DHT)-based P2P systems have been proposed. Although those schemes can provide range query capability without modifying the underlying DHTs, they have the query delay depending on both the scale of the system and the size of the query space or the specific query, and thus cannot guarantee to return the query results in a bounded delay. In this paper, we propose Armada, an efficient range query processing scheme to support delay-bounded single-attribute and multiple-attribute range queries. It is the first delay-bounded general range query scheme on constant-degree DHTs, and can return the results for any range query within 2logN hops in a P2P system with N peers. Results of analysis and simulations show that the average delay in Armada is less than logN, and the average message cost of single-attribute range queries is about logN+2n 2 (n is the number of peers that intersect with the query). These results are very close to the lower bounds on delay and message cost of range queries over constant-degree DHTs.

A distributed paging RAM grid system for wide-area memory sharing

Memory-intensive applications often suffer from the poor performance of disk swapping when memory is inadequate. Remote memory sharing schemes, which provide a remote memory that is faster than the local hard disk, are able to improve the performance of such applications. Due to the limitation of being applicable within single clusters only, however, most of the previous remote memory mechanisms, such as the network memory scheme, fail to be extendable into a large scale, distributed, heterogeneous, and dynamic environment. In this work, we propose a service-oriented grid memory sharing scheme, distributed paging RAM grid (DPRG). We study the properties and criteria of large scale memory sharing, and then design major operations and optimizations to fit the usage of grid systems. We collect trace from our grid environment, and evaluate DPRG through comprehensive trace-driven simulations. Results show that DPRG significantly outperforms existing remote memory sharing schemes and supports grid computing applications effectively

The Complexity of Channel Scheduling in Multi-Radio Multi-Channel Wireless Networks

The complexity of channel scheduling in Multi- Radio Multi-Channel (MR-MC) wireless networks is an open research topic. This problem asks for the set of edges that can support maximum amount of simultaneous traffic over orthogonal channels under a certain interference model. There exist two major interference models for channel scheduling, with one under the physical distance constraint, and one under the hop distance constraint. The complexity of channel scheduling under these two interference models serves as the foundation for many problems related to network throughput maximization. However, channel scheduling was proved to be NP-Hard only under the hop distance constraint for SR-SC wireless networks. In this paper, we fill the void by proving that channel scheduling is NP-Hard under both models in MR-MC wireless networks. In addition, we propose a polynomial-time approximation scheme (PTAS) framework that is applicable to channel scheduling under both interference models in MR-MC wireless networks. Furthermore, we conduct a comparison study on the two interference models and identify conditions under which these two models are equivalent for channel scheduling.

Delay-Bounded Range Queries in DHT-based Peer-to-Peer Systems

Many general range query schemes for DHT-based peer-to-peer (P2P) systems have been proposed, which do not need to modify the underlying DHTs. However, most existing works have the query delay depending on both the scale of the system and the size of the query space or the specific query, and thus cannot guarantee to return the query results in a bounded delay. In this paper, we propose Armada, an efficient general range query scheme to support single-attribute and multipleattribute range queries. Armada is the first delaybounded range query scheme over constant-degree DHTs, and can return the results for any range query within 2logN hops in a P2P system with N peers. Results of analysis and simulations show that the average delay of Armada is less than logN, and the average message cost of single-attribute range queries is about logN+2n..2 (n is the number of peers that intersect with the query). These results are very close to the lower bounds on delay and message cost of range queries over constant-degree DHTs.

Route recovery in vertex-disjoint multipath routing for many-to-one sensor networks

Multipath routing is attractive for load-balancing, fault-tolerance, and security enhancement. However, constructing and maintaining a set of node-disjoint paths between the data source and sink is non-trivial in a dynamic environment. In this paper, we study the problem of route recovery in vertex-disjoint multipath routing for sensor networks with many-to-one traffic patterns. We identify the sufficient conditions for multipaths to be recovered when the existing node-disjoint paths are broken, and provide a simple framework for multipath maintenance. This framework is very efficient in time when multipath source routing is employed. Our findings can help to conserve network resource by not launching any route discovery when the data source realizes that a new route may not exist, to guide mobile data sources to relocate themselves in order to reconstruct the new multipaths, and to help newly-deployed data sources quickly determine whether the required number of multipaths exist for sure or not and then compute them. The technique proposed in this paper is a good complement to the classic max-flow algorithm when node-disjoint multipaths are needed.

Graph-theoretic analysis of Kautz topology and DHT schemes

Many proposed distributed hash table (DHT) schemes for peer-to-peer network are based on some traditional parallel interconnection topologies. In this paper, we show that the Kautz graph is a very good static topology to construct DHT schemes. We demonstrate the optimal diameter and optimal fault tolerance properties of the Kautz graph and prove that the Kautz graph is (1+o(1))-congestion-free when using the long path routing algorithm. Then we propose FissionE, a novel DHT scheme based on Kautz graph. FissionE is a constant degree, O(log N) diameter and (1+o(1))-congestion-free. FissionE shows that the DHT scheme with constant degree and constant congestion can achieve O(log N) diameter, which is better than the lower bound Ω(N 1/d) conjectured before.