In-network wireless sensor network query processors: State of the art,challenges and future directions

In wireless sensor networks (WSNs), energy is valuable because it is scarce. This causes their life time to be determined by their ability to use the available energy in an effective and frugal manner. In most of the earlier sensor network applications, the main requirement consisted mainly of data collection but transmitting all of the raw data out of the network may be prohibitively expensive (in terms of communication) or impossible at given data collection rates.In the last decade, the use of the database paradigm has emerged as a feasible solution to manage data in a WSN context. There are various sensor network query processors (SNQPs) (implementing in-network declarative query processing) that provide data reduction, aggregation, logging, and auditing facilities. These SNQPs view the wireless sensor network as a distributed database over which declarative query processor can be used to program a WSN application with much less effort. They allow users to pose declarative queries that provide an effective and efficient means to obtain data about the physical environment, as users would not need to be concerned with how sensors are to acquire the data, or how nodes transform and/or transmit the data.This paper surveys novel approaches of handling query processing by the current SNQP literature, the expressiveness of their query language, the support provided by their compiler/optimizer to generate efficient query plans and the kind of queries supported. We introduce the challenges and opportunities of research in the field of in-network sensor network query processing as well as illustrate the current status of research and future research scopes in this field.     

Information discovery in mission-critical wireless sensor networks

Wireless sensor networks (WSN) are attractive for information gathering in large-scale data rich environments and can add value to mission-critical applications such as battlefield surveillance and reconnaissance. However, in order to fully exploit these networks for such applications, energy-efficient and scalable solutions for data storage and information discovery are essential. In this paper, we propose a novel method of information management in wireless sensor networks that can significantly increase network lifetime and minimize query processing delay resulting in quality of service (QoS) improvements that are of significant benefit to mission-critical applications. We propose novel methods for data dissemination, information storage and discovery that are totally distributed and also take into account the energy limitations of individual sensors. We present analytical and simulations results that prove the proposed methods of information management to offer significant improvements in the resolution of global ALL-type as well as individual ANY-type queries in comparison to current approaches. In addition, the results prove that the QoS improvements come with significant network-wide energy savings that will result in an increase of the network lifetime.     

On query processing in wireless sensor networks using classes of quality of queries

This paper introduces the concept of quality of queries (QoQs) towards a more adaptive query processing in wireless sensor networks (WSNs). This approach aims at the intelligent consumption of the limited resources (energy and memory) available in these networks while still delivering a reasonable level of data quality as expected by client applications. In a nutshell, the concept of QoQ stipulates that the results of different queries injected into the same WSN can be tailored according to different criteria, in particular the levels of query result accuracy and energy consumption. For this purpose, four classes of QoQ (CoQoQ) are specified having in mind distinct requirements in terms of these criteria. To allow the implementation of these classes in a real WSN setting, a new novelty-detection based algorithm, referred to as AdaQuali (which stands for “ADAptive QUALIty control for query processing in WSN”), is also proposed in a manner as to control the sensor node activities through the dynamic adjustment of their rates of data collection and transmission. In order to validate the novel approach, simulations with a prototype implemented in Sinalgo have been conducted over real temperature data. The results achieved evidence the suitability of the proposal and point to gains of up to 66.76%, for different CoQoQ, in terms of reduction in energy consumption.     

EQOWSN: Evolutionary-based query optimization over self-organized wireless sensor networks

In this paper, a new approach has been introduced that integrates an evolutionary-based mechanism with a distributed query sensor cover algorithm for optimal query execution in self-organized wireless sensor networks (WSN). An algorithm based on an evolutionary technique is proposed, with problem-specific genetic operators to improve computing efficiency. Redundancy within a sensor network can be exploited to reduce the communication cost incurred in execution of spatial queries. Any reduction in communication cost would result in an efficient use of battery energy, which is very limited in sensors. Our objective is to self-organize the network, in response to a query, into a topology that involves an optimal subset of sensors that is sufficient to process the query subject to connectivity, coverage, energy consumption, cover size and communication overhead constraints. Query processing must incorporate energy awareness into the system by reducing the total energy consumption and hence increasing the lifetime of the sensor cover, which is beneficial for large long running queries. Experiments have been carried out on networks with different sensors Transmission radius, different query sizes, and different network configurations. Through extensive simulations, we have shown that our designed technique result in substantial energy savings in a sensor network. Compared with other techniques, the results demonstrated a significant improvement of the proposed technique in terms of energy-efficient query cover with lower communication cost and lower size.     

Effective query aggregation for data services in sensor networks

Providing efficient data services has been required by many sensor network applications. While most existing work in this area focuses on data aggregation, not much attention has been paid to query aggregation. For many applications, especially ones with high query rates, query aggregation is very important. In this paper, we study a query aggregation-based approach to provide efficient data services. In particular: (1) we propose a multi-layer overlay-based framework consisting of a query manager and access points (nodes), where the former provides the query aggregation plan and the latter executes the plan; (2) we design an effective query aggregation algorithm to reduce the number of duplicate/overlapping queries and save overall energy consumption in the sensor network. We also design protocols to effectively deliver aggregated queries and query results in the sensor network. Our performance evaluations show that by applying our query aggregation algorithm, the overall energy consumption can be significantly reduced and the sensor network lifetime can be prolonged correspondingly.     

Broadcast routing in wireless sensor networks with dynamic power management and multi-coverage backbones

In a wireless sensor network (WSN), nodes are power constrained. As a consequence, protocols must be energy efficient to prolong the network lifetime while keeping some quality-of-service (QoS) requirements. In WSNs, most protocols resort to the broadcast of control messages like, for example, for the topology control (TC) of the network. On its turn, TC itself can be applied to improve the broadcast of data packets in the network, and because only a subset of nodes need to be active at any time, it is possible to extend the network lifetime. We investigate some alternatives to improve broadcasting in WSN for an extended network lifetime. This is accomplished in two ways. First, we adapt the dynamic power management with scheduled switching modes (DPM-SSM) technique to a blind flooding protocol (i.e., FLOOD). To capture the battery capacity recovery effect as a result of applying DPM, we consider a more realistic battery model (i.e., Rakhmatov-Vrudhula battery model). Second, we implement a multi-coverage TC solution for computing an energy efficient broadcast backbone. Extensive simulation results using the NS2 network simulator show that it is possible to extend the network lifetime while keeping good broadcasting performance.     

传感器网络中一种基于分层的功率控制算法

无线传感器网络的能耗决定了网络的生存时间,如何设计有效的算法来延长网络的生存时间是一个重要的研究课题。针对矩形传感器网络,提出一种基于分层的功率控制算法,通过分析节点的能耗来计算层的宽度和节点的通信半径,以达到网络能耗的均衡分布。仿真实验表明,算法能有效延长网络的生存时间。     

一种新的能量有效性无线传感网节点设计

当无线传感网运用于恶劣、时变的环境中,如何使网络的生命周期最大化,并满足一定QoS要求,成为无线传感网在这些应用领域广泛应用的关键问题。主要提出了一种基于直扩通信体制的双内核节点架构,不仅能满足复杂环境中的通信性能要求,并且功耗较低。该节点的设计主要采用了软硬件相结合的动态能量管理策略以及参数可调的软件无线电设计,通过底层的灵活设计为无线传感网各层协议的设计提供了一个良好的测试和实践平台,从而研究、设计新的物理层及上层协议来减少非理想硬件平台的功耗,提高整个网络的生存时间和通信性能。     

限制链路数量对无线传感器网络寿命的影响

由于传感器节点能量受限,如何优化无线传感器网络(WSN)寿命是一项重要任务。借助混合二元线性规划(MBLP)框架,对限制传入/传出链路数量的WSN寿命影响进行了研究。利用MBLP最大化WSN寿命,并给出对应约束条件;通过线性网络拓扑结构,分析了节点数量、节点面积对WSN寿命的影响。性能分析表明,如果传入/传出链路数量至少为3时,网络寿命降低小于1.0%,从而进一步证明了分割流量为三部分足以平衡传感器节点间的能耗。     

无线传感器网络QoS仿真与研究

无线传感器网络在军事和民用领域均具有广阔的应用前景,但由于传感器节点资源的限制,网络能否满足在实际应用中的QoS要求是一个重要问题。本文对无线传感器网络的主要QoS指标进行了介绍,并分别从能量效率、丢包率、吞吐量和传输时延等主要QoS指标对三种典型拓扑结构的无线传感器网络进行了分析;实现了基于NS2的无线传感器网络通用仿真平台,借助此平台对典型拓扑结构的传感器网络主要QoS指标进行了仿真验证和分析,得到了不同拓扑结构对无线传感器网络QoS指标的影响程度。     

A simple, least-time, and energy-efficient routing protocol with one-level data aggregation for wireless sensor networks

The area of wireless sensor networks (WSN) is currently attractive in the research community area due to its applications in diverse fields such as defense security, civilian applications and medical research. Routing is a serious issue in WSN due to the use of computationally-constrained and resource-constrained micro-sensors. These constraints prohibit the deployment of traditional routing protocols designed for other ad hoc wireless networks. Any routing protocol designed for use in WSN should be reliable, energy-efficient and should increase the lifetime of the network. We propose a simple, least-time, energy-efficient routing protocol with one-level data aggregation that ensures increased life time for the network. The proposed protocol was compared with popular ad hoc and sensor network routing protocols, viz., AODV ( [35] and [12]), DSR (Johnson et al., 2001), DSDV (Perkins and Bhagwat, 1994), DD (Intanagonwiwat et al., 2000) and MCF (Ye et al., 2001). It was observed that the proposed protocol outperformed them in throughput, latency, average energy consumption and average network lifetime. The proposed protocol uses absolute time and node energy as the criteria for routing, this ensures reliability and congestion avoidance.     

Improving the QoS for information discovery in autonomic wireless sensor networks

Wireless sensor networks (WSN) are attractive for information gathering in large-scale data rich environments. In order to fully exploit the data gathering and dissemination capabilities of these networks, energy-efficient and scalable solutions for data storage and information discovery are essential. Traditionally, the communication pattern in WSNs has been assumed to be many-to-one; i.e., numerous sensors gather information which is routed to a central point commonly referred to as the sink. However, many emerging applications for WSNs require dissemination of information to interested clients within the network requiring support for differing traffic patterns. Further, in-network query processing capabilities are required for autonomic information discovery.In this paper, we formulate the information discovery problem as a load-balancing problem, with the combined aim being to maximize network lifetime and minimize query processing delay resulting in quality of service (QoS) improvements. We propose novel methods for data dissemination, information discovery and data aggregation that are designed to provide significant QoS benefits. We make use of affinity propagation to group “similar” sensors and have developed efficient mechanisms that can resolve both ALL-type and ANY-type queries in-network with improved energy-efficiency and query resolution time.Simulation and Analytical results prove the proposed method(s) of information discovery offer significant QoS benefits for ALL-type and ANY-type queries in comparison to previous approaches.     

Cost Minimization of Wireless Sensor Networks with Unlimited-lifetime Energy for Monitoring Oil Pipelines

Cyber-physical-system (CPS) has been widely used in both civil and military applications. Wireless sensor network (WSN) as the part and parcel of CPS faces energy problem because sensors are battery powered, which results in limited lifetime of the network. To address this energy problem, we take advantage of energy harvesting device (EHD) and study how to indefinitely prolong oil pipeline monitoring network lifetime by reasonable selecting EHD. Firstly, we propose a general strategy worst case-energy balance strategy (WC-EBS), which defines worst case energy consumption (WCEC) as the maximum energy sensor node could expend for oil pipeline monitoring WSN. When the energy collected by EHD is equal or greater than WCEC, network can have an unlimited lifetime. However, energy harvesting rate is proportional to the price of EHD, WC-EBS will cause high network cost. To reduce network cost, we present two optimization strategies, optimization workloadenergy balance strategy (OW-EBS) and optimization first nodeenergy balance strategy (OF-EBS). The main idea of OW-EBS is to cut down WCEC by reducing critical node transmission workload; OF-EBS confirms critical node by optimizing each sensor node transmission range, then we get the optimal energy harvesting rate in OF-EBS. The experimental results demonstrate that OF-EBS can indefinitely extend network lifetime with lower cost than WC-EBS and OW-EBS, and energy harvesting rate P in each strategy satisfies POF-EBS ≤ POW-EBS ≤ PWC-EBS.      

基于分层小生境蚁群算法的WSN中QoS组播路由研究

针对无线传感网络(WSN)的动态网络环境和能量约束的问题,在优化网络动态结构的基础上,提出用分层小生境蚁群算法求解WSN的QoS组播路由的方法.首先依据能耗将网络结构进行分簇分层优化并建立小生境,然后再结合蚁群算法优化QoS组播路由,最后进行能耗分析.该策略在保证能量最优的前提下,降低了路由的时间复杂度和空间复杂度,仿真结果表明了其有效性.     

HDEEC：面向异构网络的一种基于簇路由协议

有效地使用传感节点的能量进而延长网络寿命成为设计无线传感网路由协议的一项挑战性的工作.为了延长网络,现存的多数簇方案是面向同构网络.为此,面向异构网络,提出基于簇的分布式能量有效路由HDEEC(heterogeneous WSN distributed energy-efficient clustering)协议.HDEEC协议首先提出异构网络模型,考虑了普通节点、特优节点和超特优节点三级能量节点;然后,提出能量消耗模型;最后依据这两个模型,提出了簇头选择方案.HDEEC协议以平衡、有效方式动态改变节点被选为簇头的概率.仿真结果表明,提出的HDEEC协议能够有效延长网络寿命,比DEEC、DDEEC的网络寿命分别提高了72％、68％.     

WSN in cyber physical systems: Enhanced energy management routing approach using software agents

Recently, the cyber physical system has emerged as a promising direction to enrich the interactions between physical and virtual worlds. Meanwhile, a lot of research is dedicated to wireless sensor networks as an integral part of cyber physical systems. A wireless sensor network (WSN) is a wireless network consisting of spatially distributed autonomous devices that use sensors to monitor physical or environmental conditions. These autonomous devices, or nodes, combine with routers and a gateway to create a typical WSN system. Shrinking size and increasing deployment density of wireless sensor nodes implies the smaller equipped battery size. This means emerging wireless sensor nodes must compete for efficient energy utilization to increase the WSN lifetime. The network lifetime is defined as the time duration until the first sensor node in a network fails due to battery depletion. One solution for enhancing the lifetime of WSN is to utilize mobile agents. In this paper, we propose an agent-based approach that performs data processing and data aggregation decisions locally i.e., at nodes rather than bringing data back to a central processor (sink). Our proposed approach increases the network lifetime by generating an optimal routing path for mobile agents to transverse the network. The proposed approach consists of two phases. In the first phase, Dijkstra’s algorithm is used to generate a complete graph to connect all source nodes in a WSN. In the second phase, a genetic algorithm is used to generate the best-approximated route for mobile agents in a radio harsh environment to route the sensory data to the base-station. To demonstrate the feasibility of our approach, a formal analysis and experimental results are presented.     

无线传感器网络能量优化与建模技术综述

由于无线传感器网络的能量受限,如何优化网络能量消耗和评估网络生存周期是当前无线传感器网络研究的首要挑战。在分析无线传感器网络能量消耗特征的基础上,调研传感器网络节点和网络系统的能量优化策略;并针对能量优化存在的不足,分析近几年兴起的无线传感器网络能耗建模工作;从基于无线通信、状态转换、协议栈等方面归纳总结无线传感器网络能耗模型的建模方法;指出跨层能量优化以及软硬件综合的能耗建模技术是无线传感器网络能量研究的重点。     

Energy‐efficient task allocation with quality of service provisioning for concurrent applications in multi‐functional wireless sensor network systems

Multi‐functional wireless sensor network (WSN) system is a new design trend of WSNs, which are evolving from dedicated application‐specific systems to an integrated infrastructure that supports the execution of multiple concurrent applications. Such system offers inherent advantages in terms of cost and flexibility because it allows the effective utilization of available sensors and resource sharing among multiple applications. However, sensor nodes are very constrained in resources, mainly regarding their energy. Therefore, the usage of such resources needs to be carefully managed, and the sharing with several applications imposes new challenges in achieving energy efficiency in these networks. In order to exploit the full potential of multi‐functional WSN systems, it is crucial to design mechanisms that effectively allocate tasks onto sensors so that the entire system lifetime is maximized while meeting various application requirements. However, it is likely that the requirements of different applications cannot be simultaneously met. In this paper, we present the Multi‐Application Requirements Aware and Energy Efficiency algorithm as a new resource allocation heuristic for multi‐functional WSN system to maximize system lifetime subject to various application requirements. The heuristic effectively deals with different quality of service parameters (possibly conflicting) trading those parameters and exploiting heterogeneity of multiple WSNs. Copyright © 2013 John Wiley & Sons, Ltd.     

无线传感器网络动态节点选择优化策略

无线传感器网络的能耗和有效覆盖率是衡量其性能的两个重要指标.无线传感器网络动态节点选择优化策略通过合理配置各无线传感器节点状态,平衡网络能耗和有效覆盖率,提高网络能效性,延长网络寿命.提出一种结合了Hopfield网络与遗传算法的动态节点选择优化策略,简称为HN-GA.该策略通过遗传算法实现全局搜索,采用Hopfield网络缩小遗传算法的搜索范围,保证遗传算法中每个基因对应待选解的有效性,并针对动态节点选择优化提出一种基于无线传感器网络能耗、寿命和有效覆盖率的综合指标.仿真实验表明,HN-GA算法能有效完成无线传感器网络动态节点选择优化,并在确保网络有效覆盖率的前提下,通过动态配置各无线传感器节点状态,降低网络能耗,延长网络寿命.与遗传算法和Hopfield网络相比,HN-GA算法不仅全局搜索能力强,且收敛速度快、耗时少.     

数据集成技术在树型WSN中的应用与研究

针对无线传感器网络中节点能量有限这一特点,如何提高能量利用率、延长网络寿命是每个WSN研究者所必须面临的问题,同样也是WSN发展过程中必须被解决的难题。为此,本文将一种数据集成算法引入无线传感器网络,通过去除节点间的冗余信息来降低网络中的数据流量,从而降低网络能耗,达到提高网络能量利用率和延长网络寿命的目的。文章以树型无线传感器网络为例,分别对采用数据集成算法前后的网络能量消耗进行分析研究,并给出了相应的能量消耗模型。随后又通过计算机仿真和实验数据监测的方法,验证了此数据集成算法在降低树型WSN能耗中是有效的,而且具有一定的实用价值。