Energy-efficient skyline query optimization in wireless sensor networks

With the deployment of wireless sensor networks (WSNs) for environmental monitoring and event surveillance, WSNs can be treated as virtual databases to respond to user queries. It thus becomes more urgent that such databases are able to support complicated queries like skyline queries. Skyline query which is one of popular queries for multi-criteria decision making has received much attention in the past several years. In this paper we study skyline query optimization and maintenance in WSNs. Specifically, we first consider skyline query evaluation on a snapshot dataset, by devising two algorithms for finding skyline points progressively without examining the entire dataset. Two key strategies are adopted: One is to partition the dataset into several disjoint subsets and produce the skyline points in each subset progressively. Another is to employ a global filter that consists of some skyline points in the processed subsets to filter out unlikely skyline points from the rest of unexamined subsets. We then consider the query maintenance issue by proposing an algorithm for incremental maintenance of the skyline in a streaming dataset. A novel maintenance mechanism is proposed, which is able to identify which skyline points from past skylines to be the global filter and determine when the global filter is broadcast. We finally conduct extensive experiments by simulations to evaluate the performance of the proposed algorithms on both synthetic and real sensing datasets, and the experimental results demonstrate that the proposed algorithms significantly outperform existing algorithms in terms of network lifetime prolongation.     

Energy-efficient top-k query evaluation and maintenance in wireless sensor networks

Top-k query in a wireless sensor network is to identify k sensors with the highest sensor readings. Since sensors usually are powered by energy-limited batteries, a fundamental problem associated with top-k query evaluation in such a network is to maximize network lifetime, which poses great challenges due to the unique characteristics of sensor networks. In this paper, we first propose a novel filter-based algorithm for top-k query evaluation, which is able to filter out a fractional amount of data from network-wide transmission. We then develop an online algorithm for answering time-dependent top-k queries with different values of k through the dynamic maintenance of a materialized view that consists of historical top-k results. We finally conduct extensive experiments by simulations to evaluate the performance of the proposed algorithms using real sensing data sets. Experimental results show that the proposed algorithms outperform a well known existing algorithm significantly, and the network lifetime delivered by the proposed optimal quantile algorithm is at least 142 % times longer than that by an existing algorithm.     

面向WSN的安全范围查询协议研究

针对两层无线传感器网络中范围查询所要求的低能耗和高隐私保护,提出了一种具有隐私和完整性保护的安全范围查询协议:SPQ。SPQ是由数据加密、前缀成员验证、概率邻居验证、查询传输过程分离等技术组成,能够在保证不泄露隐私的情况下完成范围查询。分析和仿真结果表明,相对于其他安全协议,SPQ在保证范围查询安全性的同时具有更低能耗。     

顽健的无线传感器网络K近邻查询处理算法

提出了一种顽健的K近邻查询处理算法ROC-KNN,根据网络拓扑动态地将查询区域划分成若干子区域.每个子区域中选择一个簇头节点收集其他节点的感知数据,并将其发送至下一个子区域的簇头节点,直至遍历所有子区域.给出了2种分布式的启发式算法,用于设置子区域大小和选择簇头节点,以减少能量消耗.设计了一种利用子区域中非簇头节点恢复查询处理过程的算法,降低了查询处理因簇头节点失效而中断的概率.实验结果表明,ROC-KNN在能量消耗、查询成功率方面均优于现有的算法.     

Multi‐regional query scheduling in wireless sensor networks with minimum latency

Query scheduling as one of the most important technologies used in query processing has been widely studied recently. In this paper, we investigate the Minimum Latency Multi‐Regional Query Scheduling (ML‐MRQS) problem in wireless Sensor Networks (WSNs), which aims to generate a scheduling plan with minimum latency under a more practical query model called Multi‐Regional Query (MRQ). An MRQ targets at interested data from multiple regions of a WSN, where each region is a subarea. Because the ML‐MRQS problem is NP‐hard, we propose a heuristic scheduling algorithm Multi‐Regional Query Scheduling Algorithm (MRQSA) to solve this problem. Theoretical analysis shows that the latency of MRQSA is upper bounded by 23A + B + C for an MRQ with m query regions , where is the maximum latency for non‐overlapped regions, is the maximum latency for overlapped regions, and is the accumulated latency for data transmission from the accessing nodes to the sink. Simulation results show that MRQSA reduces latency by 42.7% to 51.63% with respect to different number of query regions, network density, region size, and interference/transmission range compared with C‐DCQS, while guaranteeing energy efficiency. Copyright © 2012 John Wiley & Sons, Ltd.     

Active query forwarding in sensor networks

While sensor networks are going to be deployed in diverse application specific contexts, one unifying view is to treat them essentially as distributed databases. The simplest mechanism to obtain information from this kind of a database is to flood queries for named data within the network and obtain the relevant responses from sources. However, if the queries are (a) complex, (b) one-shot, and (c) for replicated data, this simple approach can be highly inefficient. In the context of energy-starved sensor networks, alternative strategies need to be examined for such queries.We propose a novel and efficient mechanism for obtaining information in sensor networks which we refer to as ACtive QUery forwarding In sensoR nEtworks (ACQUIRE). The basic principle behind ACQUIRE is to consider the query as an active entity that is forwarded through the network (either randomly or in some directed manner) in search of the solution. ACQUIRE also incorporates a look-ahead parameter d in the following manner: intermediate nodes that handle the active query use information from all nodes within d hops in order to partially resolve the query. When the active query is fully resolved, a completed response is sent directly back to the querying node.We take a mathematical modelling approach in this paper to calculate the energy costs associated with ACQUIRE. The models permit us to characterize analytically the impact of critical parameters, and compare the performance of ACQUIRE with respect to other schemes such as flooding-based querying (FBQ) and expanding ring search (ERS), in terms of energy usage, response latency and storage requirements. We show that with optimal parameter settings, depending on the update frequency, ACQUIRE obtains order of magnitude reduction over FBQ and potentially over 60–75% reduction over ERS (in highly dynamic environments and high query rates) in consumed energy. We show that these energy savings are provided in trade for increased response latency. The mathematical analysis is validated through extensive simulations.     

无线传感器网络中一种实时高效的数据存储和查询方法

集中研究了非结构化的数据存储和查询.为了在保证查询成功率的同时最小化总的能耗,分别在存储受限和不受限两种情况下,建立了MESQ(minimizing energy on successful query)优化问题模型,给出并证明了最优的复本和查询个数.在此基础上,还设计了一个实用的分布式数据分发算法:BubbleGeocast,其主要包含精确自适应快速分发和基于拒绝的均匀分发两个部分,其中前者用自适应分支的方法加速数据扩散,并精确控制总的复本个数;后者根据每个节点Voronoi单元面积,决定是否接受或拒绝这个报文.从而保证了复本和查询分发的精确性、实时性、均匀性、顽健性.最后,详细的理论分析和模拟实验进一步验证了其性能.分析和实验表明,同已有工作相比,在相同查询成功率时,BubbleGeocast能量有效性平均提高了约30%,复本分发的延迟平均缩短了约30%,成功查询的延迟平均缩短了约50%.     

容忍节点失效的传感器网络空间范围查询算法

提出了一种容忍节点失效的空间范围查询处理算法GSA.给出了理论上最节省能量的网格大小设置.提出了一种基于网格的查询结果收集调度策略,以避免查询结果收集过程中的消息碰撞问题.系统地分析了算法在不同节点密度、节点失效概率和查询区域大小条件下的查询成功率,以及不同节点密度、查询消息大小、感知数据大小、查询区域大小、节点失效概率条件下的能量消耗.理论和实验表明,在多数情况下,GSA算法优于现有的IWQE算法.     

Distributed data storage solution under sink failures in wireless sensor networks

In challenging environment, sensory data must be stored inside the network in case of sink failures, we need to redistribute overflowing data items from the depleted storage source nodes to sensor nodes with available storage space and residual energy. We design a distributed energy efficient data storage algorithm named distributed data preservation with priority (D²P²). This algorithm takes both data redistribution costs and data retrieval costs into account and combines these two problems into a single problem. D²P² can effectively realize data redistribution by using cooperative communication among sensor nodes. In order to solve the redistribution contention problem, we introduce the concept of data priority, which can avoid contention consultations between source nodes and reduce energy consumption. Finally, we verify the performance of the proposed algorithm by both theory and simulations. We demonstrate that D²P²'s performance is close to the optimal centralized algorithm in terms of energy consumption and shows superiority in terms of data preservation time.     

Query similarity index based query preprocessing mechanism for multiapplication sharing wireless sensor networks

In multiapplication sharing wireless sensor networks, various application queries exhibit similarity in their spatial, temporal, and sensing attribute requirements, thus result in redundant sensing tasks. The dissemination and execution of such redundant sensing tasks cause network traffic overhead and quick energy drop of the sensor nodes. Existing task scheduling and allocation mechanisms focus on reducing upstream traffic by maximizing data sharing among sensing tasks. However, downstream traffic due to sensing tasks dissemination plays a crucial role in large-scale WSNs and required to be addressed. This paper proposes a query similarity index based query preprocessing mechanism that prevents the generation of redundant sensing tasks by creating a common query corresponding to the overlapping functional requirements of the queries and reduces the downstream as well as upstream traffic significantly. The performance evaluation reveals approximately 60% reduction in downstream traffic, 20–40% reduction in upstream traffic, and 40% reduction in energy consumption when compared with state-of-the-art mechanisms.

     

A trajectory-based selective broadcast query protocol for large-scale,high-density wireless sensor networks

We present a small-footprint search protocol designed to facilitate any-type queries for data content and services in large population, high-density wireless sensor networks. Our protocol, termed Trajectory-based Selective Broadcast Query (TSBQ), works in conjunction with time division multiple access- or schedule-based medium access control protocols to reduce per-query energy expenditure. We compare the performance of TSBQ to unicast- and local broadcast-based search algorithms and also determine a critical node density based on the energy expended by nodes to transmit and receive. Minimal energy expenditure is achieved by determining the optimal number of data/service replicates and the number of nodes designated to receive each query transmission. Numerical results indicate that TSBQ significantly reduces the total energy expenditure of a network as compared to unicast and local broadcast-based search protocols.     

Relay sensor placement in wireless sensor networks

This paper addresses the following relay sensor placement problem: given the set of duty sensors in the plane and the upper bound of the transmission range, compute the minimum number of relay sensors such that the induced topology by all sensors is globally connected. This problem is motivated by practically considering the tradeoff among performance, lifetime, and cost when designing sensor networks. In our study, this problem is modelled by a NP-hard network optimization problem named Steiner Minimum Tree with Minimum number of Steiner Points and bounded edge length (SMT-MSP). In this paper, we propose two approximate algorithms, and conduct detailed performance analysis. The first algorithm has a performance ratio of 3 and the second has a performance ratio of 2.5. Xiuzhen Cheng is an Assistant Professor in the Department of Computer Science at the George Washington University. She received her MS and PhD degrees in Computer Science from the University of Minnesota - Twin Cities in 2000 and 2002, respectively. Her current research interests include Wireless and Mobile Computing, Sensor Networks, Wireless Security, Statistical Pattern Recognition, Approximation Algorithm Design and Analysis, and Computational Medicine. She is an editor for the International Journal on Ad Hoc and Ubiquitous Computing and the International Journal of Sensor Networks. Dr. Cheng is a member of IEEE and ACM. She received the National Science Foundation CAREER Award in 2004. Ding-Zhu Du received his M.S. degree in 1982 from Institute of Applied Mathematics, Chinese Academy of Sciences, and his Ph.D. degree in 1985 from the University of California at Santa Barbara. He worked at Mathematical Sciences Research Institutea, Berkeley in 1985-86, at MIT in 1986-87, and at Princeton University in 1990-91. He was an associate-professor/professor at Department of Computer Science and Engineering, University of Minnesota in 1991-2005, a professor at City University of Hong Kong in 1998-1999, a research professor at Institute of Applied Mathematics, Chinese Academy of Sciences in 1987-2002, and a Program Director at National Science Foundation of USA in 2002-2005. Currently, he is a professor at Department of Computer Science, University of Texas at Dallas and the Dean of Science at Xi’an Jiaotong University. His research interests include design and analysis of algorithms for combinatorial optimization problems in communication networks and bioinformatics. He has published more than 140 journal papers and 10 written books. He is the editor-in-chief of Journal of Combinatorial Optimization and book series on Network Theory and Applications. He is also in editorial boards of more than 15 journals. Lusheng Wang received his PhD degree from McMaster University in 1995. He is an associate professor at City University of Hong Kong. His research interests include networks, algorithms and Bioinformatics. He is a member of IEEE and IEEE Computer Society. Baogang Xu received his PhD degree from Shandong University in 1997. He is a professor at Nanjing Normal University. His research interests include graph theory and algorithms on graphs.     

Security in wireless sensor networks

With sensor networks on the verge of deployment, security issues pertaining to the sensor networks are in the limelight. Though the security in sensor networks share many characteristics with wireless ad hoc networks, the two fields are rapidly diverging due to the fundamental differences between the make‐up and goals of the two types of networks. Perhaps the greatest dividing difference is the energy and computational abilities. Sensor nodes are typically smaller, less powerful, and more prone to failure than nodes in an ad hoc network. These differences indicate that protocols that are valid in the context of ad‐hoc networks may not be directly applicable for sensor networks. In this paper, we survey the state of art in securing wireless sensor networks. We review several protocols that provide security in sensor networks, with an emphasis on authentication, key management and distribution, secure routing, and methods for intrusion detection. Copyright © 2006 John Wiley & Sons, Ltd.     

Security in wireless sensor networks

Recent advances in electronics and wireless communication technologies have enabled the development of large-scale wireless sensor networks that consist of many low-power, low-cost, and small-size sensor nodes. Sensor networks hold the promise of facilitating large-scale and real-time data processing in complex environments. Security is critical for many sensor network applications, such as military target tracking and security monitoring. To provide security and privacy to small sensor nodes is challenging, due to the limited capabilities of sensor nodes in terms of computation, communication, memory/storage, and energy supply. In this article we survey the state of the art in research on sensor network security.     

G-skyline query over data stream in wireless sensor network

Wireless Networks - There are much data sampled continuously by sensors in the wireless sensor network. Storing and mining these data can find more potential information and provide help for...     

Multimedia communication in wireless sensor networks

The technological advances in Micro ElectroMechanical Systems (Mems) and wireless communications have enabled the realization of wireless sensor networks (Wsn) comprised of large number of low-cost, low-power, multifunctional sensor nodes. These tiny sensor nodes communicate in short distances and collaboratively work toward fulfilling the application specific objectives ofWsn. However, realization of wide range of envisionedWsn applications necessitates effective communication protocols which can address the unique challenges posed by theWsn paradigm. Since many of these envisioned applications may also involve in collecting information in the form of multimedia such as audio, image, and video; additional challenges due to the unique requirements of multimedia delivery overWsn, e.g., diverse reliability requirements, time constraints, high bandwidth demands, must be addressed as well. Thus far, vast majority of the research efforts has been focused on addressing the problems of conventional data communication inWsn. Therefore, there exists an urgent need for research on the problems of multimedia communication inWsn. In this paper, a survey of the research challenges and the current status of the literature on the multimedia communication inWsn is presented. More specifically, the multimediaWsn applications, factors influencing multimedia delivery overWsn, currently proposed solutions in application, transport, and network layers, are pointed out along with their shortcomings and open research issues.     

Non-intrusive aggregation in wireless sensor networks

Since energy is scarce in sensor nodes, wireless sensor networks aim to transmit as few packets as possible. To achieve this goal, sensor protocols often aggregate measured data from multiple sensor nodes into a single packet. In this paper, a survey of aggregation techniques and methods is given. Based on this survey, it is concluded that there are currently several dependencies between the aggregation method and the behavior of the other network layers. As a result, existing aggregation methods can often not be combined with different routing protocols. To remedy this shortcoming, the paper introduces a new ‘non-intrusive’ aggregation approach which is independent of the routing protocol. The proposed aggregation method is evaluated and compared to traditional aggregation approaches using a large-scale sensor testbed of 200 TMoteSky sensor nodes. Our experimental results indicate that existing aggregation approaches are only suited for a limited set of network scenarios. In addition, it is shown both mathematically and experimentally that our approach outperforms existing non-intrusive techniques in a wide range of scenarios.     

Fault management in wireless sensor networks

Wireless sensor networks (WSNs) have gradually emerged as one of the key growth areas for pervasive computing in the twenty-first century. Recent advances in WSN technologies have made possible the development of new wireless monitoring and environmental control applications. However, the nature of these applications and harsh environments also created significant challenges for sensor networks to maintain a high quality of service in potentially harsh environments. Therefore, efficient fault management and robust management architectures have become essential for WSNs. In this article, we address these challenges by surveying existing fault management approaches for WSNs. We divide the fault management process into three phases: fault detection, diagnosis, and recovery and classify existing approaches according to these phases. Finally, we outline future challenges for fault management in WSNs.     

Anomaly detection in wireless sensor networks

Anomaly detection in wireless sensor networks is an important challenge for tasks such as fault diagnosis, intrusion detection, and monitoring applications. The algorithms developed for anomaly detection have to consider the inherent limitations of sensor networks in their design so that the energy consumption in sensor nodes is minimized and the lifetime of the network is maximized. In this survey article we analyze the state of the art in anomaly detection techniques for wireless sensor networks and discuss some open issues for research.