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.     

An open framework for translating portable applications into operating system‐specific wireless sensor networks applications

Wireless sensor networks (WSNs) are distributed systems integrated by tiny devices, called sensor nodes, with capabilities to monitor the environment and forward their measurements to a special node, the sink, where the results can be collected and further processed. The trend in WSN is moving towards heterogeneous networks that will contain different sensor nodes running different instances of custom operating systems. Given the growing demand of new hardware platforms and operating systems specifically designed for sensor nodes, the applications programming for sensor nodes is becoming a challenging process that needs to be alleviated. Currently, application programming for sensor nodes is a complex, ad hoc, and error‐prone process where the portability among different platforms has been sacrificed. In this paper, we propose an open framework aimed to achieve application portability in heterogeneous sensor networks. Our approach provides the programming abstractions needed to support the application development process for sensor nodes. We have implemented an open framework that provides a set of tools on top of the most popular WSN operating systems to translate portable applications to the native operating system in an automatic, simple, and transparent way for developers. We have also evaluated the applications thus generated in terms of productivity and overhead, by comparing their footprint to those originally developed in each specific operating system. The results show that the overhead is minimal—4% in the worst case—and in some cases, it was even possible to reduce the footprint by using code optimizations. Copyright © 2012 John Wiley & Sons, Ltd.     

CrimeSPOT: A language and runtime for developing active wireless sensor network applications

Advances in wireless sensing and actuation technology allow embedding significant amounts of application logic inside wireless sensor networks. Such active WSN applications are more autonomous, but are significantly more complex to implement. Event-based middleware lends itself to implementing these applications. It offers developers fine-grained control over how an individual node interacts with the other nodes of the network. However, this control comes at the cost of event handlers which lack composability and violate software engineering principles such as separation of concerns. In this paper, we present CrimeSPOT as a domain-specific language for programming WSN applications on top of event-driven middleware. Its node-centric features enable programming a node’s interactions through declarative rules rather than event handlers. Its network-centric features support reusing code within and among WSN applications. Unique to CrimeSPOT is its support for associating application-specific semantics with events that carry sensor readings. These preclude transposing existing approaches that address the shortcomings of event-based middleware to the domain of wireless sensor networks. We provide a comprehensive overview of the language and the implementation of its accompanying runtime. The latter comprises several extensions to the Rete forward chaining algorithm. We evaluate the expressiveness of the language and the overhead of its runtime using small, but representative active WSN applications.     

Energy-efficient distributed wireless sensor network scheme for cluster detection

Detection of an environmental phenomenon, e.g. air pollution and oil spills, occurs when a group of sensors continuously produces similar readings (i.e. data streams) over a period of time. Thus, detection of environmental phenomena is basically a process of clustering the sensors' data streams, which commonly involves the processing of hundreds and maybe thousands of data streams in real time. Since the sensor network environment is wireless, energy conservation of the sensors would be the main concern. Thus in this paper, we propose an efficient and energy friendly distributed scheme to detect phenomena in a wireless sensor network (WSN). To achieve fast response, the proposed algorithms reduce the dimensionality of the streams. Then, each stream is represented by a point in a multi-dimensional grid. The algorithm uses a grid-based clustering technique to detect clusters of similar stream values. The processing of the algorithm is distributed among different elements of the WSN in a hierarchical topology for more energy efficiency. The paper shows the feasibility of the proposed fully distributed scheme by comparing it with three other WSN schemes in terms of clustering accuracy and energy consumption.     

一种面向移动监控型网络的分簇路由协议

传统的无线传感器网络(wireless sensor network,WSN)中节点是基本保持静止的,使网络中的节点具有移动性可以改善WSN功能;针对移动监控型无线传感器网络中拓扑结构改变频繁,传统的路由协议不能适用的问题,提出了一种基于分簇的移动性路由协议(mobile cluster routing protocol,MCR);该协议包含一个分布式分簇算法(distributed cluster algorithm,DCB),此算法充分考虑了节点移动性和剩余能量,通信复杂度比较低,分簇效率很高;同时,针对节点移动,协议中提出了一种注册机制,通过这种机制可以实现在移动过程中的信息交互;实验表明,MCR协议能够有效提高在移动环境下的网络性能。     

传感器网络中能量最优化的聚类轮换算法

针对无线传感器网络节点能量难以补充,如何延长网络使用寿命的问题,将网络工作过程描述为不定阶段动态规划问题,结合总能量守恒关系推导出网络寿命上下界,提出能量优先的聚类轮换策略并证明了其最优性．在此基础上,设计了实用性好的最小切换聚类轮换算法（SSLL）,利用PowerTOSSIM仿真验证了SSLL取得接近最优的网络寿命．     

改进蚁群算法的无线传感器网络路径优化

研究无线传感器网络路径优化问题,针对无线传感器网络(WSN)路径优化问题,在分析了遗传算法和蚁群算法各自优缺点的基础上,通过把蚁群算法作为WSN路径优化的主框架,采用遗传算的选择、交叉和变异算子提高蚁群算法搜索速度,提出一种改进蚁群算法的WSN路径优化方法。仿真结果表明,改进蚁群算法有效地克服了基本蚁群算法的缺陷,提高了WSN路径优化效率和成功率,减少了能理消耗,有效延长了网络生存时间。     

基于Q学习和规划的传感器节点任务调度算法*

为了改善节点的学习策略,提高节点的应用性能,以数据收集为应用建立任务模型,提出基于Q学习和规划的传感器节点任务调度算法,包括定义状态空间、延迟回报、探索和利用策略等基本元素.根据无线传感器网络(WSN)特性,建立基于优先级机制和过期机制的规划过程,使节点可以有效利用经验知识,改善学习策略.实验表明,文中算法具备根据当前WSN环境进行动态任务调度的能力.相比其它任务调度算法,文中算法能量消耗合理且获得较好的应用性能.     

Energy optimal data propagation in wireless sensor networks

We propose an algorithm to compute the optimal parameters of a probabilistic data propagation algorithm for wireless sensor networks (WSN). The probabilistic data propagation algorithm we consider was introduced in previous work, and it is known that this algorithm, when used with adequate parameters, balances the energy consumption and increases the lifespan of the WSN. However, we show that in the general case achieving energy balance may not be possible. We propose a centralized algorithm to compute the optimal parameters of the probabilistic data propagation algorithm, and prove that these parameters maximize the lifespan of the network even when it is not possible to achieve energy balance. Compared to previous work, our contribution is the following: (a) we give a formal definition of an optimal data propagation algorithm: an algorithm maximizing the lifespan of the network. (b) We find a simple necessary and sufficient condition for the data propagation algorithm to be optimal. (c) We constructively prove that there exists a choice of parameters optimizing the probabilistic data propagation algorithm. (d) We provide a centralized algorithm to compute these optimal parameters, thus enabling their use in a WSN. (e) We extend previous work by considering the energy consumption per sensor, instead of the consumption per slice, and propose a spreading technique to balance the energy among sensors of a same slice. The technique is numerically validated by simulating a WSN accomplishing a data monitoring task and propagating data using the probabilistic data propagation algorithm with optimal parameters.     

Reliable distributed data stream management in mobile environments

The proliferation of sensor technology, especially in the context of embedded systems, has brought forward novel types of applications that make use of streams of continuously generated sensor data. Many applications like telemonitoring in healthcare or roadside traffic monitoring and control particularly require data stream management (DSM) to be provided in a distributed, yet reliable way. This is even more important when DSM applications are deployed in a failure-prone distributed setting including resource-limited mobile devices, for instance in applications which aim at remotely monitoring mobile patients. In this paper, we introduce a model for distributed and reliable DSM. The contribution of this paper is threefold. First, in analogy to the SQL isolation levels, we define levels of reliability and describe necessary consistency constraints for distributed DSM that specify the tolerated loss, delay, or re-ordering of data stream elements, respectively. Second, we use this model to design and analyze an algorithm for reliable distributed DSM, namely efficient coordinated operator checkpointing (ECOC). We show that ECOC provides lossless and delay-limited reliable data stream management and thus can be used in critical application domains such as healthcare, where the loss of data stream elements cannot be tolerated. Third, we present detailed performance evaluations of the ECOC algorithm running on mobile, resource-limited devices. In particular, we can show that ECOC provides a high level of reliability while, at the same time, featuring good performance characteristics with moderate resource consumption.     

MaD‐WiSe: a distributed stream management system for wireless sensor networks

Wireless sensor networks (WSN) are composed of several sensors having limited memory, processing power, communication bandwidth, and energy, which cooperate in performing a given task. The use of the database paradigm has emerged in the last few years as a viable solution to manage data in such a context. In this paper we present the MaD‐WiSe system, a distributed query processing framework that moves the processing of the query into the network. MaD‐WiSe reconsiders various aspects related to database system design and it reinterprets them according to the WSN constraints and requirements. In particular it considers the aspects related to the definition of a query language to formalize the queries, a stream model to manage data acquired by the sensors, a query algebra to define the operators that actually perform the query, and energy efficiency and query optimization strategies for saving energy. Copyright © 2010 John Wiley & Sons, Ltd.     

一种用于移动传感器网络的定位算法

无线传感器网络作为一种全新的信息获取和处理技术,可以在广泛的应用领域内实现复杂的大规模监测和追踪任务。在传感器网络中,定位问题已经是很多无线传感器网络应用的关键,以前的大多数定位算法只适用于静态网络。设计了一种适用于锚节点和普通节点都自由移动的移动传感器网络的定位算法,该算法结合Monte Carlo和RSSI方法,通过约束选取样点的样本空间,仿真结果显示同比提高了算法精度。     

Editorial

Wireless sensor network(WSN)is characterized by the dense deployment of sensor nodes that continuously observe physical phenomenon.The main advantages of WSN include its low cost,rapid deployment,self-organization,and fault tolerance.WSN has received tremendous interests of various research communities,and significant progresses have been made in various aspects including sensor platform development,wireless communication and networking,signal and information processing,as well as network performance eva...     

基于移动Agent的无线传感器网络拓扑发现机制

对监测区域中部署的传感器节点的拓扑发现是传感器网络应用的前提,它反映了传感器网络的监测能力。考虑目前拓扑发现算法中能量消耗过多、网络连通性不强等问题,文中结合移动Agent的特点,提出了一种基于移动Agent的无线传感器网络拓扑发现机制,通过建立数学模型,利用相关邻近图（relative neighborhood graph）理论生成网络拓扑。实验结果表明,基于移动Agent的拓扑发现机制相对于当前存在的拓扑发现算法具有很好的稳定性和良好的节能效果,该算法可以解决节点拓扑请求信息讨多导致过多能量消耗的问颢．     

一种及时恢复故障路由的无线传感器路由算法

无线传感器网络以其布网灵活,连接方便,功耗小,成本低,逐渐被应用于煤矿、消防、化工安全等民用领域.根据煤矿安全应用的特殊情况,提出一种无线传感器路由算法.该算法在定向扩散算法的基础上进行了改进,采用簇的方式,由簇首协调簇内节点的数据采集和整合,并且在每一煤层设置层首作为协调节点,通过层首之间建立的主干路由,有效地减少冗余数据的传播.该算法的特点就是能够及时恢复出现故障的路由.实验模拟结果也表明算法有效地减少了冗余数据和传输延时.     

Delay characterization and performance evaluation of cluster-based WSN with different deployment distributions

Provisioning of quality of service (QoS) is the ultimate goal for any wireless sensor network (WSN). Several factors can influence this requirement such as the adopted cluster formation algorithm. Almost all WSNs are structured based on grouping the sensors nodes into clusters. Not all contemporary cluster formation and routing algorithms (e.g. LEACH) were designed to provide/sustain certain QoS requirement such as delay constraint. Another fundamental design issue is that, these algorithms were built and tested under the assumption of uniformly distributed sensor nodes. However, this assumption is not always true. In some industrial applications and due to the scope of the ongoing monitoring process, sensors are installed and condensed in certain areas, while they are widely separated in other areas. Also unlike the random deployment distributions, there are many applications that need deterministic deployment of sensors like grid distribution. In this work, we investigated and characterized the impact of sensor node deployment distributions on the performance of different flavors of LEACH routing algorithm. In particular, we studied via extensive simulation experiments how LEACH cluster formation approach affects the delay (inter and intra-cluster delay) and energy efficiency expressed in terms of packet/joule for different base station locations and data loads. In this study, we consider four deployment distributions: grid, normal, exponential and uniform. The results showed the significant impact of nodes distribution on the network energy efficiency, throughput and delay performance measures. These findings would help the architects of real time application wireless sensor networks such as secure border sensor networks to design such networks to meet its specifications effectively and fulfill their critical mission.     

12 m跨超声速风洞运行监测系统研究

为改善风洞试验条件和提高试验效率,针对1.2m跨超声速风洞进行了运行监测系统研究.针对风洞环境复杂、监测对象分散的特点,引入无线传感器网络构建了基于多传感器的分布式风洞运行监测平台.重点研究了基于BP神经网络的无线传感器网络数据融合和基于D-S证据理论的多传感器信息融合在风洞运行监测中应用.在实际应用中取得了良好的效果.     

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。     

一种能耗均衡的WSN分布式拓扑博弈算法

无线传感器网络（wireless sensor network,WSN）中通常节点能量受限,节点间能耗不均衡会导致网络生命周期缩短.针对该问题,综合考虑节点的能量效率和能耗均衡,通过引入阿特金森指数设计了一种改进优化的综合效用函数;基于此,建立了一种能耗均衡的拓扑博弈模型,并证明了该拓扑博弈模型是序数势博弈且存在帕累托最优;提出了一种能耗均衡的WSN分布式拓扑博弈算法（DTCG）.通过仿真实验及对比分析表明,相较于其它基于博弈理论的拓扑控制算法,DTCG算法能在保证网络连通性和鲁棒性的前提下,降低节点发射功率,拥有更好的能量均衡性和能量效率,可以有效延长网络生命周期.     

WSNs clustering based on semantic neighborhood relationships

We propose a semantic clustering model based on a fuzzy inference system to find out the semantic neighborhood relationships in wireless sensor networks in order to both reduce energy consumption and improve the data accuracy. As a case study we describe a structural health monitoring application which was used to illustrate and assess the proposed model. We conduct experiments in order to evaluate the proposal in two different scenarios of damage with different data aggregation methods. We also compared our proposal, using the same data set, with a deterministic clustering method and with the LEACH algorithm. The results indicate that our approach is an energy-efficient clustering method for WSNs, outperforming both the deterministic clustering and LEACH algorithms in about 70% and 47% of energy savings respectively. The energy saving comes from the fact that we have a more efficient in-network data aggregation process since by exploiting the semantic relation between sensor nodes we can potentially aggregate more similar data and consequently, decrease the data redundancy (thus minimizing transmissions). Nodes that are semantically unrelated can operate in low-duty cycle, further reducing the energy consumption. Moreover, our proposal has the potential to improve the data accuracy provided for the application where accuracy is a QoS requirement in typical WSN applications.