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Wireless sensor network: Energy efficiency, security, and, fault tolerance.

机译:无线传感器网络:能源效率,安全性和容错能力。

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摘要

Wireless sensor network (WSN) is an emerging networking paradigm that promises a wide range of potential applications in both civilian and military areas. WSN runs different kinds of applications in a variety of physical environments, which offers many challenges. The main design constraints include energy efficiency, fault tolerence, and security. In this thesis, we investigate the research problems involved in three types of sensor networks including the UnderWater Sensor Network (UWSN), the Wireless Terrestrial Sensor Network (WTSN), and the Wireless Multimedia Sensor Network (WMSN).;We first formulate the node clustering problem into a cluster-centric cost-based optimization problem with an objective to improve the energy efficiency and prolong the network lifetime in UWSN. A novel distributed clustering protocol called minimum-cost clustering protocol (MCCP) is proposed, which selects a set of non-overlapping clusters from all potential clusters based on the cost metric assigned to each potential cluster and attempts to minimize the overall cost of the selected clusters. To provide a robust clustered architecture against cluster-head failures in UWSNs, a dependable clustering protocol is proposed in which two mechanisms are employed: fault prevention clustering and cluster head replication. Fault prevention clustering attempts to select those healthy nodes as cluster heads to prevent cluster head failures, and cluster head replication attempts to select a primary cluster head and a backup cluster head for each cluster member so that the constructed cluster hierarchy can tolerate cluster-head failures.;The successful working of any fault recovery schemes heavily depends on a proper and efficient fault detection mechanism. Therefore, we propose a cooperative fault detection mechanism, which can accurately and quickly detect the failure of a cluster head through the independent fault status detection from each cluster member and a distributed agreement process for final decision. It runs concurrently with normal network operation at each cluster member and makes use of the data periodically sent by a cluster head as the heartbeats for fault detection. An agreement can be efficiently achieved within two TDM frames in each detection process.;To address the energy efficiency problem in WTSN, Slepian-Wolf coding is employed to remove the redundancy caused by the data correlation. We first consider the clustered Slepian-Wolf coding problem, which aims at selecting a set of disjoint potential clusters to cover the whole network such that the global compression gain of Slepian-Wolf coding is maximized, and then propose a distributed optimal-compression clustering protocol to solve the problem. Based on the resulting cluster hierarchy constructed, we study the optimal intra-cluster rate allocation problem to minimize the intra-cluster communication cost and further combine with the explicit entropy coding to minimize the inter-cluster communication cost.;Furthermore, based on inherent characteristic of Slepian-Wolf coding, we propose a combined data aggregation and encryption scheme, called spatially selective encryption, for efficient and secure data transmission in WTSNs. Using this mechanism, as long as the data of the cluster head (a.k.a. the visual key) is properly protected, the data from all cluster members are secure. This novel approach can significantly reduce the energy consumption for data encryption. An energy-efficient key establishment protocol is also proposed to securely and efficiently establish the key used for encrypting the visual key.;Finally, we propose a clustered on-demand multi-channel MAC protocol (COMMAC) to support energy-efficient, high-throughput, and reliable data transmission in WMSNs. A scheduled multi-channel medium access is used within each cluster so that cluster members can operate in a contention-free manner in both time and frequency domains to avoid collision, idle listening and overhearing. A traffic-adaptive and QoS-aware scheduling algorithm is executed to maximize the network throughput. A spectrum-aware ARQ is further incorporated to better exploit the unused spectrum for a balance between reliability and retransmission.
机译:无线传感器网络(WSN)是一种新兴的网络范例,有望在民用和军事领域中广泛应用。 WSN在各种物理环境中运行各种应用程序,这带来了许多挑战。主要设计限制包括能效,容错性和安全性。本文主要研究水下传感器网络(UWSN),无线地面传感器网络(WTSN)和无线多媒体传感器网络(WMSN)三种类型的传感器网络所涉及的研究问题。将问题聚类为以簇为中心的基于成本的优化问题,目的是提高能效并延长UWSN中的网络寿命。提出了一种新颖的分布式集群协议,称为最小成本集群协议(MCCP),该协议根据分配给每个潜在集群的成本指标从所有潜在集群中选择一组不重叠的集群,并尝试将所选总体成本最小化集群。为了提供针对UWSN中簇头故障的健壮的簇体系结构,提出了一种可靠的簇协议,其中采用了两种机制:故障预防簇和簇头复制。故障预防群集尝试选择那些健康的节点作为群集头,以防止群集头故障,并且群集头复制尝试为每个群集成员选择一个主群集头和一个备用群集头,以便构造的群集层次结构可以容忍群集头故障。;任何故障恢复方案的成功工作,在很大程度上取决于适当而有效的故障检测机制。因此,我们提出了一种协作式故障检测机制,该机制可以通过从每个集群成员进行独立的故障状态检测以及通过分布式协议过程进行最终决策,来准确,快速地检测集群头的故障。它与每个群集成员的正常网络运行同时运行,并利用群集头定期发送的数据作为检测故障的心跳。在每个检测过程中,可以在两个TDM帧内有效地达成协议。为了解决WTSN中的能效问题,采用了Slepian-Wolf编码来消除数据相关性引起的冗余。我们首先考虑聚类的Slepian-Wolf编码问题,该问题旨在选择一组不相交的潜在聚类来覆盖整个网络,以使Slepian-Wolf编码的全局压缩增益最大化,然后提出一种分布式最优压缩聚类协议解决问题。基于构造的集群层次结构,我们研究了最优集群内速率分配问题,以最小化集群内通信成本,并进一步与显式熵编码相结合,以最小化集群间通信成本。在Slepian-Wolf编码的基础上,我们提出了一种组合的数据聚合和加密方案,称为空间选择性加密,以在WTSN中高效且安全地传输数据。使用此机制,只要正确保护了簇头(也就是可视键)的数据,所有簇成员的数据都是安全的。这种新颖的方法可以大大减少数据加密的能耗。还提出了一种节能密钥建立协议,以安全有效地建立用于加密可视密钥的密钥。最后,我们提出了一种集群式按需多通道MAC协议(COMMAC),以支持节能,高安全性的WMSN中的吞吐量和可靠的数据传输。在每个群集中使用调度的多通道媒体访问,以便群集成员可以在时域和频域中以无竞争的方式运行,以避免冲突,空闲监听和偷听。执行流量自适应和QoS感知调度算法以最大化网络吞吐量。进一步集成了频谱感知型ARQ,以更好地利用未使用的频谱,从而在可靠性和重传之间取得平衡。

著录项

  • 作者

    Wang, Pu.;

  • 作者单位

    Memorial University of Newfoundland (Canada).;

  • 授予单位 Memorial University of Newfoundland (Canada).;
  • 学科 Engineering Electronics and Electrical.
  • 学位 M.Eng.
  • 年度 2008
  • 页码 164 p.
  • 总页数 164
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

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