Dezun Dong

Fine-grained boundary recognition in wireless ad hoc and sensor networks by topological methods

Location-free boundary recognition is crucial and critical for many fundamental network functionalities in wireless ad hoc and sensor networks. Previous designs, often coarse-grained, fail to accurately locate boundaries, especially when small holes exist. To address this issue, we propose a fine-grained boundary recognition approach using connectivity information only. This algorithm accurately discovers inner and outer boundary cycles without using location information. To the best of our knowledge, this is the first design being able to determinately locate all hole boundaries no matter how small the holes are. Also, this distributed algorithm does not rely on high node density. We formally prove the correctness of our design, and evaluate its effectiveness through extensive simulations.

Component-based localization in sparse wireless networks

Localization is crucial for wireless ad hoc and sensor networks. As the distance-measurement ranges are often less than the communication ranges for many ranging systems, most communication-dense wireless networks are localization-sparse. Consequently, existing algorithms fail to provide accurate localization supports. In order to address this issue, by introducing the concept of component, we group nodes into components so that nodes are able to better share ranging and anchor knowledge. Operating on the granularity of components, our design, CALL, relaxes two essential restrictions in localization: the node ordering and the anchor distribution. Compared to previous designs, CALL is proven to be able to locate the same number of nodes using the least information. We evaluate the effectiveness of CALL through extensive simulations. The results show that CALL locates 90% nodes in a network with average degree 7.5 and 5% anchors, which outperforms the state-of-the-art design Sweeps by about 40%.

Edge Self-Monitoring for Wireless Sensor Networks

Local monitoring is an effective mechanism for the security of wireless sensor networks (WSNs). Existing schemes assume the existence of sufficient number of active nodes to carry out monitoring operations. Such an assumption, however, is often difficult for a large-scale sensor network. In this work, we focus on designing an efficient scheme integrated with good self-monitoring capability as well as providing an infrastructure for various security protocols using local monitoring. To the best of our knowledge, we are the first to present the formal study on optimizing network topology for edge self-monitoring in WSNs. We show that the problem is NP-complete even under the unit disk graph (UDG) model and give the upper bound on the approximation ratio in various graph models. We provide polynomial-time approximation scheme (PTAS) algorithms for the problem in some specific graphs, for example, the monitoring-set-bounded graph. We further design two distributed polynomial algorithms with provable approximation ratio. Through comprehensive simulations, we evaluate the effectiveness of our design.

Self-monitoring for sensor networks

Local monitoring is an effective mechanism for the security of wireless sensor networks (WSNs). Existing schemes assume the existence of sufficient number of active nodes to carry out monitoring operations. Such an assumption, however, is often difficult for a large scale sensor network. In this work, we focus on designing an efficient scheme integrated with good self-monitoring capability as well as providing an infrastructure for various security protocols using local monitoring. To the best of our knowledge, we are the first to present the formal study on finding optimized self-monitoring topology for WSNs. We show the problem is NP-complete even under the unit disk graph (UDG) model, and give the upper bound on the approximation ratio. We further propose two distributed polynomial algorithms with provable approximation ratio to address this issue. Through comprehensive simulations, we evaluate the effectiveness of this design.

Component based localization in sparse wireless ad hoc and sensor networks

Localization is crucial for wireless ad hoc and sensor networks. As the distance-measurement ranges are often less than that of the communication range for many ranging systems, most communication-dense wireless networks are often localization-sparse. Consequently, most existing algorithms fail to provide accurate localization supports. In order to address this issue, by introducing a concept of component, we propose to group nodes into components, so that nodes are able to better share their ranging and anchor knowledge. This design, CALL, relaxes two essential restrictions in localization: node ordering and anchor distribution. We evaluate the effectiveness of CALL through extensive simulations. The results show that CALL locates 80% nodes in a network with average degree 7.5 and 5% percent anchors, which outperforms the state of the art design Sweeps about 20%.

PathZip: Packet path tracing in wireless sensor networks

In order to provide reliable data delivery and system management for large-scale wireless sensor networks (WSNs), tracing the route paths of packets in a lightweight manner is crucial and critical. Real-time path tracing technology enables us to observe every data transmission and analyze network dynamics in a fine-grained fashion. Due to resource constraints of WSNs, however, it is difficult, if not impossible, to integrate into each packet with its full path information. We attempt to capture such information with inserting a small and constant overhead into each packet. In this design, PathZip, each sensor node performs lightweight hash-based computations to passively label every packet forwarded. Meanwhile, the sink extracts the label information so as to leverage the pre-knowledge on the network to compute the full packet path. Both topology-aware and geometry-assistant techniques are utilized by PathZip in order to exploit different network knowledge and reduce the computation and storage overhead greatly. We conduct theoretical analysis and extensive simulations to evaluate the performance of our design. The results show that our method is effective to trace the full route path in large-scale WSNs, and outperforms the state-of-the-art methods.

Distributed Coverage in Wireless Ad Hoc and Sensor Networks by Topological Graph Approaches

Coverage problem is a fundamental issue in wireless ad hoc and sensor networks. Previous techniques for coverage scheduling often require accurate location information or range measurements, which cannot be easily obtained in resource-limited ad hoc and sensor networks. Recently, a method based on algebraic topology is proposed to achieve coverage verification using only connectivity information. The topological method sheds some light on the issue of location-free coverage. Unfortunately, the needs of centralized computation and rigorous restriction on sensing and communication ranges greatly limit the applicability in practical large-scale distributed sensor networks. In this work, we make the first attempt toward establishing a graph theoretical framework for connectivity-based coverage with configurable coverage granularity. We propose a novel coverage criterion and scheduling method based on cycle partition. Our method is able to construct a sparse coverage set in a distributed manner, using purely connectivity information. Compared with existing methods, our design has a particular advantage, which permits us to configure or adjust the quality of coverage by adequately exploiting diverse sensing ranges and specific requirements of different applications. We formally prove the correctness and evaluate the effectiveness of our approach through extensive simulations and comparisons with the state-of-the-art approaches.

Topological detection on wormholes in wireless ad hoc and sensor networks

Wormhole attack is a severe threat to wireless ad hoc and sensor networks. Most existing countermeasures either require specialized hardware devices or make strong assumptions on the network in order to capture the specific (partial) symptom induced by wormholes. Those requirements and assumptions limit the applicability of previous approaches. In this work, we present our attempt to understand the impact and inevitable symptom of wormholes and develop distributed detection methods by making as few restrictions and assumptions as possible. We fundamentally analyze the wormhole problem using a topology methodology, and propose an effective distributed approach, which relies solely on network connectivity information, without any requirements on special hardware devices or any rigorous assumptions on network properties. We rigorously prove the correctness of this design in continuous geometric domains and extend it into discrete domains. We evaluate its performance through extensive simulations.

High Performance Interconnect Network for Tianhe System

In this paper, we present the Tianhe-2 interconnect network and message passing services. We describe the architecture of the router and network interface chips, and highlight a set of hardware and software features effectively supporting high performance communications, ranging over remote direct memory access, collective optimization, hardware enable reliable end-to-end communication, user-level message passing services, etc. Measured hardware performance results are also presented.

WormCircle: Connectivity-Based Wormhole Detection in Wireless Ad Hoc and Sensor Networks

Wormhole attack is a severe threat against wireless ad hoc and sensor networks. It can be launched without compromising any legitimate node or cryptographic mechanisms, and often serves as a stepping stone for many serious attacks. Most existing countermeasures often make critical assumptions or require specialized hardware devices in the network. Those assumptions and requirements limit the applicability of previous approaches. In this work, we explore the impact of wormhole attacks on network connectivity topologies, and develop a simple distributed method to detect wormholes, called WormCircle. WormCircle relies solely on local connectivity information without any requirements on special hardware devices or making any rigorous assumptions on network properties. We establish the correctness of this design in continuous geometric domains and extend it into discrete networks. We evaluate the effectiveness in randomly deployed sensor networks through extensive simulations.