Li Lao

VBF: vector-based forwarding protocol for underwater sensor networks

In this paper, we tackle one fundamental problem in Underwater Sensor Networks (UWSNs): robust, scalable and energy efficient routing. UWSNs are significantly different from terrestrial sensor networks in the following aspects: low bandwidth, high latency, node float mobility (resulting in high network dynamics), high error probability, and 3-dimensional space. These new features bring many challenges to the network protocol design of UWSNs. In this paper, we propose a novel routing protocol, called vector-based forwarding (VBF), to provide robust, scalable and energy efficient routing. VBF is essentially a position-based routing approach: nodes close to the “vector” from the source to the destination will forward the message. In this way, only a small fraction of the nodes are involved in routing. VBF also adopts a localized and distributed self-adaptation algorithm which allows nodes to weigh the benefit of forwarding packets and thus reduce energy consumption by discarding the low benefit packets. Through simulation experiments, we show the promising performance of VBF.

CapProbe: a simple and accurate capacity estimation technique

We present a new capacity estimation technique, called CapProbe. CapProbe combines delay as well as dispersion measurements of packet pairs to filter out samples distorted by cross-traffic. CapProbe algorithms include convergence tests and convergence speed-up techniques by varying probing parameters. Our study of CapProbe includes a probability analysis to determine the time it takes CapProbe to converge on the average. Through simulations and measurements, we found CapProbe to be quick and accurate across a wide range of traffic scenarios. We also compared CapProbe with two previous well-known techniques, pathchar and pathrate. We found CapProbe to be much more accurate than pathchar and similar in accuracy to pathrate, while providing faster estimation than both. Another advantage of CapProbe is its lower computation cost, since no statistical post processing of probing data is required.

A Scalable Overlay Multicast Architecture for Large-Scale Applications

In this paper, we propose a two-tier overlay multicast architecture (TOMA) to provide scalable and efficient multicast support for various group communication applications. In TOMA, multicast service overlay network (MSON) is advocated as the backbone service domain, while end users in access domains form a number of small clusters, in which an application-layer multicast protocol is used for the communication between the clustered end users. TOMA is able to provide efficient resource utilization with less control overhead, especially for large-scale applications. It also alleviates the state scalability problem and simplifies multicast tree construction and maintenance when there are large numbers of groups in the network. To help MSON providers efficiently plan backbone service overlay, we suggest several provisioning algorithms to locate proxies, select overlay links, and allocate link bandwidth. Extensive simulation studies demonstrate the promising performance of TOMA

Reducing large internet topologies for faster simulations

In this paper, we develop methods to “sample” a small realistic graph from a large real network. Despite recent activity, the modeling and generation of realistic graphs is still not a resolved issue. All previous work has attempted to grow a graph from scratch. We address the complementary problem of shrinking a graph. In more detail, this work has three parts. First, we propose a number of reduction methods that can be categorized into three classes: (a) deletion methods, (b) contraction methods, and (c) exploration methods. We prove that some of them maintain key properties of the initial graph. We implement our methods and show that we can effectively reduce the nodes of a graph by as much as 70% while maintaining its important properties. In addition, we show that our reduced graphs compare favourably against construction-based generators. Apart from its use in simulations, the problem of graph sampling is of independent interest.

TOMA: a viable solution for large-scale multicast service support

In this paper, we propose a Two-tier Overlay Multicast Architecture (TOMA) to provide scalable and efficient multicast support for various group communication applications. In TOMA, Multicast Service Overlay Network (MSON) is advocated as the backbone service domain, while end users in the access domains form a number of small clusters, in which an application-layer multicast protocol is used for the communication between the clustered end users. TOMA is able to provide efficient resource utilization with less control overhead, especially for large-scale applications. It also alleviates the state scalability problem and simplifies multicast tree construction and maintenance when there are large numbers of groups in the networks. Simulation studies are conducted and the results demonstrate the promising performance of TOMA.

BEAM: a distributed aggregated multicast protocol using bi-directional trees

IP multicast confronts a severe scalability problem when there are large numbers of multicast groups in the network due to state explosion and control explosion. In backbone networks, this state scalability problem is exacerbated, since there are potentially enormous multicast groups crossing backbone domains, in this paper, we propose a scalable protocol, called BEAM (bi-directional aggregate multicast), which uses the concept of aggregated multicast. BEAM is a distributed protocol using bi-directional trees. It is simple and easy to implement. Through simulations, we show that BEAM can greatly improve state scalability with very low overhead: up to 98% state and tree setup and maintenance overhead reduction with less than 0.14 bandwidth waste in our experiments.

Reducing multicast traffic load for cellular networks using ad hoc networks

There has been recent extensive research on integrating cellular networks and ad hoc networks to overcome the limitations of cellular networks. Although several schemes have been proposed to use such hybrid networks to improve the performance of individual multicast groups, they do not address quality of service (QoS) issues when multiple groups are present. This paper, on the other hand, considers an interesting scenario of hybrid networks when an ad hoc network cannot accommodate all the groups and a base station has to select a subset of groups to optimize its bandwidth savings and maximize the utilization of the ad hoc network while providing QoS support for multicast users. In this paper, a network model for multicast admission control that takes wireless interference into account is developed, the group selection problem is formulated as a multidimensional knapsack problem, and an integer linear programming (ILP) formulation and a polynomial-time dynamic algorithm are proposed. A distributed implementation of the dynamic algorithm in real systems is also examined. Simulation studies demonstrate that the dynamic algorithm is able to achieve very competitive performance under various conditions, in comparison with the optimal solution computed by the ILP approach

Tackling group-to-tree matching in large scale group communications

As a mechanism to support group communications, multicasting faces a serious state scalability problem when there are large numbers of groups in the network: lots of resources (e.g., memory to maintain group state information) and control overhead (e.g., multicast tree setup and maintenance) are required to manage the groups. Recently, an efficient solution called aggregated multicast is proposed [8]. In this approach, groups are assigned to proper trees and multiple groups can share one delivery tree. A key problem in aggregated multicast is group-tree matching (i.e., matching groups to trees). In this paper, we investigate this group-tree matching problem. We first formally define the problem, and formulate two versions of the problem: static and dynamic. We analyze the static version of the problem and prove that it is NP-complete. To tackle this hard problem, we propose three algorithms: one optimal (using Linear Integer Programming, or ILP), one nearoptimal (using Greedy method), and one pseudo-dynamic algorithm. For the dynamic version, we present a general heuristic on-line group-tree matching algorithm. Simulation studies are conducted to compare the three algorithms for the static version. Our results show that Greedy algorithm is a feasible solution to the static problem and its performance is very close the ILP optimal solution, while pseudo-dynamic algorithm is a good heuristic for many cases where Greedy does not work well. We also evaluate the performance of the heuristic online algorithm, and show that it is a practical solution to the dynamic on-line group-tree matching problem.

SDC: a distributed clustering protocol for peer-to-peer networks

Network clustering can facilitate data discovery and peer-lookup in peer-to-peer systems. In this paper, we design a distributed network clustering protocol, called SCM-based Distributed Clustering (SDC), for peer-to-peer networks. In this protocol, clustering is dynamically adjusted based on Scaled Coverage Measure (SCM), a practical clustering accuracy measure. By exchanging messages with neighbors, peers can dynamically join or leave a cluster so that the clustering accuracy of the whole network is improved. SDC is a fully distributed protocol which requires only neighbor information, and it can handle node dynamics locally with very small message overhead while keeping good quality of clustering. Through extensive simulations, we demonstrate that SDC can discover good quality clusters very efficiently.

Distributed qos routing for backbone overlay networks

In recent years, overlay networks have emerged as an attractive alternative for supporting value-added services. Due to the difficulty of supporting end-to-end QoS purely in end-user overlays, backbone overlays for QoS support have been proposed. In this paper, we describe a backbone QoS overlay network architecture for scalable, efficient and practical QoS support. In this architecture, we advocate the notion of QoS overlay network (referred to as QSON) as the backbone service domain. The design of QSON relies on well-defined business relationships between the QSON provider, network service providers and end users. A key challenge in making QSON a reality consists of efficiently determining routes for end user QoS flows based on the service level agreements between the QSON provider and network service providers. In this paper, we propose and present a scalable and distributed QoS routing scheme that can be used to efficiently route end user QoS flows through QSON. We demonstrate the effectiveness of our solution through simulations.