Adaptive Storage Policy Switching for Wireless Sensor Networks

In wireless sensor networks, storage policies can be categorized into external storage, local storage and data centric storage. Each storage police has its suitable network environments. If a correct storage policy is chosen for a given network condition, unnecessary control messages can be significantly reduced. Then the network lifetime can be increased. In this paper, adaptive data storage (ADS) policy which can dynamically choose suitable storage policy for wireless sensor network according to the frequencies of user queries and events happening is proposed. Through collection and computation of user query and event rates, the proposed algorithm switches between local storage and data centric storage policies adaptively. Simulations are given to justify that the proposed adaptive storage policy indeed reduces the traffic in network and increases network lifetime.

An unequal cluster-based routing protocol in wireless sensor networks

Clustering provides an effective method for prolonging the lifetime of a wireless sensor network. Current clustering algorithms usually utilize two techniques; selecting cluster heads with more residual energy, and rotating cluster heads periodically to distribute the energy consumption among nodes in each cluster and extend the network lifetime. However, they rarely consider the hot spot problem in multihop sensor networks. When cluster heads cooperate with each other to forward their data to the base station, the cluster heads closer to the base station are burdened with heavier relay traffic and tend to die much faster, leaving areas of the network uncovered and causing network partitions. To mitigate the hot spot problem, we propose an Unequal Cluster-based Routing (UCR) protocol. It groups the nodes into clusters of unequal sizes. Cluster heads closer to the base station have smaller cluster sizes than those farther from the base station, thus they can preserve some energy for the inter-cluster data forwarding. A greedy geographic and energy-aware routing protocol is designed for the inter-cluster communication, which considers the tradeoff between the energy cost of relay paths and the residual energy of relay nodes. Simulation results show that UCR mitigates the hot spot problem and achieves an obvious improvement on the network lifetime. Guihai Chen obtained his B.S. degree from Nanjing University, M. Engineering from Southeast University, and PhD from University of Hong Kong. He visited Kyushu Institute of Technology, Japan in 1998 as a research fellow, and University of Queensland, Australia in 2000 as a visiting professor. During September 2001 to August 2003, he was a visiting professor at Wayne State University. He is now a full professor and deputy chair of Department of Computer Science, Nanjing University. Prof. Chen has published more than 100 papers in peer-reviewed journals and refereed conference proceedings in the areas of wireless sensor networks, high-performance computer architecture, peer-to-peer computing and performance evaluation. He has also served on technical program committees of numerous international conferences. He is a member of the IEEE Computer Society. Chengfa Li was born 1981 and obtained his Bachelor’s Degree in mathematics in 2003 and his Masters Degree in computer science in 2006, both from Nanjing University, China. He is now a system programmer at Lucent Technologies Nanjing Telecommunication Corporation. His research interests include wireless ad hoc and sensor networks. Mao Ye was born in 1981 and obtained his Bachelor’s Degree in computer science from Nanjing University, China, in 2004. He served as a research assistant At City University of Hong Kong from September 2005 to August 2006. He is now a PhD candidate with research interests in wireless networks, mobile computing, and distributed systems. Jie Wu is a professor in the Department of Computer Science and Engineering at Florida Atlantic University. He has published more than 300 papers in various journal and conference proceedings. His research interests are in the areas of mobile computing, routing protocols, fault-tolerant computing, and interconnection networks. Dr. Wu serves as an associate editor for the IEEE Transactions on Parallel and Distributed Systems and several other international journals. He served as an IEEE Computer Society Distinguished Visitor and is currently the chair of the IEEE Technical Committee on Distributed Processing (TCDP). He is a member of the ACM, a senior member of the IEEE, and a member of the IEEE Computer Society.     

基于网格的移动无线传感网生存时间优化算法

为克服陆地静态无线传感网和水下无线传感网因节点能耗分布不均衡而出现的能量空穴问题,和具有单一移动Sink节点的无线传感网数据收集时延过长问题,该文提出基于网格的移动无线传感网生存时间优化算法(Grid-based Lifetime Optimization Algorithm,GLOA)。GLOA算法考虑多个Sink节点的移动,将监测区域分成多个大小相同的网格。根据网格潜能值确定Sink节点移动的锚点,将锚点分配给不同的Sink节点,建立路径选择优化模型并获得Sink节点的最短移动路径,采用移动收集方法或静态收集方法循环收集数据。仿真结果表明:与Ratio_w或TPGF算法相比,GLOA算法能延长网络生存时间,降低和均衡节点能耗。与LOA_SMSN算法相比,GLOA算法能降低数据收集时延。在一定的条件下,比Ratio_w,TPGF和LOA_SMSN算法更优。     

Network configuration for optimal utilization efficiency of wireless sensor networks

This paper addresses the problem of configuring wireless sensor networks (WSNs). Specifically, we seek answers to the following questions: how many sensors should be deployed, what is the optimal sensor placement, and which transmission structure should be employed. The design objective is utilization efficiency defined as network lifetime per unit deployment cost. We propose an optimal approach and an approximation approach with reduced complexity to network configuration. Numerical and simulation results demonstrate the near optimal performance of the approximation approach. We also study the impact of sensing range, channel path loss exponent, sensing power consumption, and event arrival rate on the optimal network configuration.     

一种基于多权值优化的无线传感网分簇算法的研究

在无线传感网(WSN)中,网络的拓扑结构影响传感器节点的负载平衡,关系网络的容量与生存周期,而分簇结构是一种有效的拓扑控制方式。该文着眼于无线传感网络的拓扑结构,提出基于多权值的分簇算法MWBC(Multi-WeightBasedClustering),在初期通过节点间的信息交互,获得较多的局部网络信息,如:节点的度、当前能量值、发射功率、链路质量、相对位置等,在此基础上根据不同的网络应用背景作出不同的分簇决策,并预设簇的最大规模以利于接入协议的资源管理与分配。仿真结果表明,与具有代表性的分簇算法LEACH与HEED相比,在分簇的合理性上有较大的优势。     

A cognitive mobile sensor network for environment observation

Nowadays, with the development of industrialization and urbanization, air pollution has been a serious problem all of the word. Air pollutant is harmful to human and ecological environment, for example, SO₂ and NO₂ produced by industry are vital to living organisms, greenhouse air such as CO₂ causes global warming. As a result, environmental monitoring is of great importance for human beings.This paper proposes a scheme to implement environmental monitoring. In particular, wireless sensor network collect data from surrounding environment and mobile communication system receive and process these data. To avoid network congestion, a cognitive protocol is proposed for wireless sensors accessing to mobile network. Besides that, a dynamic working scheme is also proposed for sensors so that data collection rate can be adapted to the situation of network.     

无线传感网自适应能量驱动簇头轮换算法研究

分簇结构是大规模无线传感网(WSN)的一种有效的拓扑管理方法。在这种结构下,由于簇头(Cluster Head,CH)节点的能耗速率远高于簇成员节点(Cluster Member,CM),需要做簇头轮换以平衡网络能耗。该文分析了基于能量驱动的簇头轮换策略,并提供一种基于簇头节点实时负载来估计其启动轮换的能量阈值的自适应簇头轮换算法(Adaptive Cluster Rotation Algorithm,ACRA)。仿真结果表明,与现有算法如LEACH,EDAC等比较,ACRA算法最少化簇头轮换次数,延长了网络生存时间。     

Energy-efficiency clustering protocol in wireless sensor networks

The conventional clustering method has the unique potential to be the framework for power-conserving ad hoc networks. In this environment, studies on energy-efficient strategies such as sleeping mode and redirection have been reported, and recently some have even been adopted by some standards like Bluetooth and IEEE 802.11. However, consider wireless sensor networks. The devices employed are power-limited in nature, introducing the conventional clustering approach to the sensor networks provides a unique challenge due to the fact that cluster-heads, which are communication centers by default, tend to be heavily utilized and thus drained of their battery power rapidly. In this paper, we introduce a re-clustering strategy and a redirection scheme for cluster-based wireless sensor networks in order to address the power-conserving issues in such networks, while maintaining the merits of a clustering approach. Based on a practical energy model, simulation results show that the improved clustering method can obtain a longer lifetime when compared with the conventional clustering method.     

无线传感器网络安全研究与分析

本文简要介绍了无线传感器网络的技术，分析了无线传感器网络的安全机制，分析了物理层，链路层和网络层的攻击和防御等问题，并对解决这些安全问题的关键技术进行了讨论。     

无线传感器网络中基于刚性的移动锚节点路径规划

在移动锚节点辅助定位中,锚节点通常沿着预设轨迹扫描或采用随机方式移动,当节点分布不均匀、待定位区域形状复杂时,存在锚节点冗余移动、位置冗余广播及定位性能难以确保等问题。该文提出了利用网络拓扑信息进行移动路径规划的新思路,首先利用刚性理论将网络划分为多个唯一可定位的单元,之后寻找一条遍历各单元的最短路径作为锚节点的移动轨迹,锚节点沿着该轨迹移动、依次定位各单元。大规模仿真结果表明,该策略可以有效避免锚节点的冗余移动和位置广播,灵巧适应各种布设情形,与经典的扫描式路径相比,大大降低了路径长度和位置数目。     

一种基于树的无线传感器网络数据收集方法

该文提出一种基于树的无线传感器网络数据收集方法,它将查询请求的传递与数据回传结构的建立有机结合起来,通过使用一种洪泛避免的方法传递查询请求,建立起一棵以sink节点为根的、包含最少中间节点的查询转发树,作为数据回传结构。理论分析和仿真试验表明,该方法不会降低无线传感器网络的连通性,可以有效节省能量。     

基于等概率路由模型的传感器网络负载均衡研究

无线传感器网络的能耗效率与流量负载分布密切相关。论文从微观角度研究了无线传感器网络的负载均衡问题。基于等概率路由模型,分析了拓扑传输结构对于感知数据流量的分流作用。根据分析结果,提出了多对一传输模式下任意节点负载密度的定义和算法。分析了节点的负载密度与传感器网络生命期的关系,进一步论证了在多对一的多跳传感器网络中不能实现完全的负载均衡,但是通过设计合理的拓扑结构可以实现准负载均衡。仿真结果说明,从微观角度得到的节点负载密度可以准确描述无线传感器网络的流量负载分布,由此得到的准负载均衡条件也能实现绝大多数节点的负载均衡。     

测量和分析CDMA导频污染的利器——中兴XPOS CNA1软件

介绍了利用中兴通讯自主开发的无线网络规划优化系列软件 Ｎ ｅｔＳｃｏｐｅ 中的分析软件 Ｚ Ｘ ＰＯ Ｓ Ｃ Ｎ Ａ １来测试和 分析Ｃ Ｄ Ｍ Ａ 网络优化中的导频污染问题 并通过实际案例归纳总结 ，出解决导频污染的常用方案 。     

基于交叉流网络编码的节能路由

节能路由是无线自组织网络的一个重要研究课题,对延长网络生存时间极为重要。在传统路由下,多对节点之间通信使用的多条数据传递路径会出现交叉存在公共节点,这些公共节点因需要转发来自多条交叉路径的数据包而比其它节点消耗更多的能量,从而过早因能量耗竭而失效。为了克服这一能耗不均衡问题,该文提出基于网络编码的节能路由NCBEER (Network Coding Based Energy Efficient Routing),它可捕捉多条路径交叉的机会,让公共节点对所转发的数据包进行编码,然后把编码数据包多播(Multicast)邻居节点,以减少公共节点转发数据包次数从而降低能耗;推导了编码节点使全部接收节点接收到编码数据包所需要的平均多播次数,定义了无线链路的传输代价,并将之作为信源将流量分配给不同路径的依据。仿真试验表明,NCBEER可降低和均衡节点的能耗,且能够延长网络生存时间。     

Multiconstrained QoS multipath routing in wireless sensor networks

Sensor nodes are densely deployed to accomplish various applications because of the inexpensive cost and small size. Depending on different applications, the traffic in the wireless sensor networks may be mixed with time-sensitive packets and reliability-demanding packets. Therefore, QoS routing is an important issue in wireless sensor networks. Our goal is to provide soft-QoS to different packets as path information is not readily available in wireless networks. In this paper, we utilize the multiple paths between the source and sink pairs for QoS provisioning. Unlike E2E QoS schemes, soft-QoS mapped into links on a path is provided based on local link state information. By the estimation and approximation of path quality, traditional NP-complete QoS problem can be transformed to a modest problem. The idea is to formulate the optimization problem as a probabilistic programming, then based on some approximation technique, we convert it into a deterministic linear programming, which is much easier and convenient to solve. More importantly, the resulting solution is also one to the original probabilistic programming. Simulation results demonstrate the effectiveness of our approach. This work was supported in part by the U.S. National Science Foundation under grant DBI-0529012, the National Science Foundation Faculty Early Career Development Award under grant ANI-0093241 and the Office of Naval Research under Young Investigator Award N000140210464. Xiaoxia Huang received her BS and MS in the Electrical Engineering from Huazhong University of Science and Technology in 2000 and 2002, respectively. She is completing her Ph.D. degree in the Department of Electrical and Computer Engineering at the University of Florida. Her research interests include mobile computing, QoS and routing in wireless ad hoc networks and wireless sensor networks. Yuguang Fang received a Ph.D. degree in Systems Engineering from Case Western Reserve University in January 1994 and a Ph.D degree in Electrical Engineering from Boston University in May 1997. He was an assistant professor in the Department of Electrical and Computer Engineering at New Jersey Institute of Technology from July 1998 to May 2000. He then joined the Department of Electrical and Computer Engineering at University of Florida in May 2000 as an assistant professor, got an early promotion to an associate professor with tenure in August 2003 and to a full professor in August 2005. He holds a University of Florida Research Foundation (UFRF) Professorship from 2006 to 2009. He has published over 200 papers in refereed professional journals and conferences. He received the National Science Foundation Faculty Early Career Award in 2001 and the Office of Naval Research Young Investigator Award in 2002. He has served on several editorial boards of technical journals including IEEE Transactions on Communications, IEEE Transactions on Wireless Communications, IEEE Transactions on Mobile Computing and ACM Wireless Networks. He have also been activitely participating in professional conference organizations such as serving as The Steering Committee Co-Chair for QShine, the Technical Program Vice-Chair for IEEE INFOCOM’2005, Technical Program Symposium Co-Chair for IEEE Globecom’2004, and a member of Technical Program Committee for IEEE INFOCOM (1998, 2000, 2003–2007).     

无线传感器网络中基于概率的能量平衡算法

各传感器节点的能耗不平衡严重地影响了无线传感器网络的生命周期。该文提出了基于传输概率的能量平衡算法。首先把圆形区域网络模型划分成若干圆环,每一圆环中的传感器节点以混合传输的方式传输数据。其次,为使每个传感器节点能耗均衡,提出了一种混合传输概率求解算法,获得一组传输概率决定节点传输数据的方式,从而更好地平衡网络能耗。然后对圆环宽度进行了分析和优化。仿真结果证明这些算法可以有效地降低网络能耗,延长网络生命周期。     

无线网格网关键技术及其应用

无线网格网(WirelessMeshNetwork,WMN)是一种新型的无线宽带接入网络,它融合了无线局域网(WirelessLAN,WLAN)和AdHoc网络的优势,是一种大容量、高速率、覆盖范围广的网络,成为宽带接入的一种有效手段。本文主要介绍了无线网格网的研究现状、结构、关键技术以及与其他通信网络的区别,最后介绍了两种无线网格网的技术方案以及应用前景。