环境能量驱动的无线传感器节点数据传输优化机制

将环境能量收集模块引入无线传感器网络,可以有效改善网络的使用寿命,但是能量的随时补充也给原有的能量管理策略带来了巨大挑战.针对单个环境能量驱动节点在数据序列已经到达的情况下,研究了优化的数据传输策略,采用内罚函数法优化传输过程,使得固定时间内节点传输的数据量最大.理论分析及仿真结果表明,当各个时刻节点的传输功率比较接近时会获得最大的数据传输量;当实际节点获得最大数据传输时节点的传输功率随时间呈增大趋势.     

一种太阳能传感器网络的自适应休眠调度算法

通过从外界获取太阳能,传感器网络节点的能量限制得到缓解。提出一种太阳能传感器网络的自适应休眠调度算法。当观测场景从区域观测到目标跟踪转变时,节点自适应地转换活跃和休眠状态,同时剩余能量低于能量阈值的休眠节点从外界获取太阳能。与不考虑太阳能获取的休眠调度算法相比,提出的算法延长了网络生命周期。     

A routing algorithm based on clusters and balanced use of energy for wireless sensor networks

In a sensor network,data collected by different sensors are often correlated because they are observations of related phenomena.Efficient sensor data fusion is one of the most important issues in building real sensor networks.To balance energy cost,how to select a cluster head is a key problem that must be addressed.In this paper,we use a compression-centric data collection algorithm for use in wireless sensor networks.Also,we propose a balanced cluster head selection algorithm in each cluster.Simulation re...     

无线传感器网络能量管理研究

传感器节点能量受限的特点使能量管理成为无线传感器网络(WSNs)设计的一个重要内容。对近年来无线传感器能量管理的研究进展进行了讨论和综述,指出了WSNs能量管理面临的问题与挑战。在分类阐述和比较当前具有代表性的各种休眠机制的同时,介绍了动态电压调节、动态功率管理、数据融合等能量管理策略。最后,指出了WSNs能量管理的未来发展方向。     

Optimizing in-network aggregate queries in wireless sensor networks for energy saving

This study proposes a method of in-network aggregate query processing to reduce the number of messages incurred in a wireless sensor network. When aggregate queries are issued to the resource-constrained wireless sensor network, it is important to efficiently perform these queries. Given a set of multiple aggregate queries, the proposed approach shares intermediate results among queries to reduce the number of messages. When the sink receives multiple queries, it should be propagated these queries to a wireless sensor network via existing routing protocols. The sink could obtain the corresponding topology of queries and views each query as a query tree. With a set of query trees collected at the sink, it is necessary to determine a set of backbones that share intermediate results with other query trees (called non-backbones). First, it is necessary to formulate the objective cost function for backbones and non-backbones. Using this objective cost function, it is possible to derive a reduction graph that reveals possible cases of sharing intermediate results among query trees. Using the reduction graph, this study first proposes a heuristic algorithm BM (standing for Backbone Mapping). This study also develops algorithm OOB (standing for Obtaining Optimal Backbones) that exploits a branch-and-bound strategy to obtain the optimal solution efficiently. This study tests the performance of these algorithms on both synthesis and real datasets. Experimental results show that by sharing the intermediate results, the BM and OOB algorithms significantly reduce the total number of messages incurred by multiple aggregate queries, thereby extending the lifetime of sensor networks.     

Dynamic sensor transmission power scheduling for remote state estimation

In this paper, we consider the problem of sensor transmission power scheduling for remote state estimation. We assume that the sensor has two transmission energy levels, where the high level corresponds to a high packet reception ratio. By exploiting the feedback information from the remote estimator, we aim to find an optimal transmission power schedule. We formulate the problem as a Markov decision process, and analytically develop a simple and optimal dynamic schedule which minimizes the average estimation error under the energy constraint. Furthermore, we derive the necessary and sufficient condition under which the remote state estimator is stable. It is shown that the estimation stability only depends on the high-energy packet reception ratio and the spectral radius of the system dynamic matrix.     

Real-time transaction scheduling in database systems

A database system supporting a real-time application, which can be called “a real-time database system (RTDBS)”, has to provide real-time information to the executing transactions. Each RTDB transaction is associated with a timing constraint, usually in the form of a deadline. Efficient resource scheduling algorithms and concurrency control protocols are required to schedule the transactions so as to satisfy both timing constraints and data consistency requirements. In this paper,^† we concentrate on the concurrency control problem in RTDBSs. Our work has two basic goals: real-time performance evaluation of existing concurrency control approaches in RTDBSs, and proposing new concurrency control protocols with improved performance. One of the new protocols is locking-based, and it prevents the priority inversion problem^{, †} by scheduling the data lock requests based on prioritizing data items. The second new protocol extends the basic timestamp-ordering method by involving real-time priorities of transactions in the timestamp assignment procedure. Performance of the protocols is evaluated through simulations by using a detailed model of a single-site RTDBS. The relative performance of the protocols is examined as a function of transaction load, data contention (which is determined by a number of system parameters) and resource contention. The protocols are also tested under various real-time transaction processing environments. The performance of the proposed protocols appears to be good, especially under conditions of high transaction load and high data contention.     

Wireless sensor node powered by aircraft specific thermoelectric energy harvesting

An energy autonomous wireless sensor system consisting of an energy harvesting power source, an energy management unit and a low power wireless sensor node is tested for aircraft applications. The autonomous power source combines aircraft specific outside temperature changes with a thermoelectric generator (TEG) and a heat storage unit. The temperature difference generated with the latter component artificially at the TEG is used to power the sensor node by thermoelectricity. Additionally, a high efficient low input voltage power management circuit is necessary to store the generated energy and to convert it to higher voltage levels needed to operate the sensor. The experimental data are compared with results from numerical simulation models to predict the energy conversion in the heat storage - TEG system. A new TEG prototype is tested and the energy output is improved by 14%. The power management storage capacitors are adapted to the available energy, thereby increasing storage voltage and conversion efficiency. Doing so, the efficiency of the complete system can be increased by around 50%.     

ADP-based optimal sensor scheduling for target tracking in energy harvesting wireless sensor networks

This paper proposes a novel sensor scheduling scheme based on adaptive dynamic programming, which makes the sensor energy consumption and tracking error optimal over the system operational horizon for wireless sensor networks with solar energy harvesting. Neural network is used to model the solar energy harvesting. Kalman filter estimation technology is employed to predict the target location. A performance index function is established based on the energy consumption and tracking error. Critic network is developed to approximate the performance index function. The presented method is proven to be convergent. Numerical example shows the effectiveness of the proposed approach.     

On a stochastic sensor selection algorithm with applications in sensor scheduling and sensor coverage

In this note we consider the following problem. Suppose a set of sensors is jointly trying to estimate a process. One sensor takes a measurement at every time step and the measurements are then exchanged among all the sensors. What is the sensor schedule that results in the minimum error covariance? We describe a stochastic sensor selection strategy that is easy to implement and is computationally tractable. The problem described above comes up in many domains out of which we discuss two. In the sensor selection problem, there are multiple sensors that cannot operate simultaneously (e.g., sonars in the same frequency band). Thus measurements need to be scheduled. In the sensor coverage problem, a geographical area needs to be covered by mobile sensors each with limited range. Thus from every position, the sensors obtain a different view-point of the area and the sensors need to optimize their trajectories. The algorithm is applied to these problems and illustrated through simple examples.     

无线传感器网络节点任务调度与功耗管理算法研究

针对有能量采集系统的无线传感器网络节点异质多核SoC平台,从提高能量利用效率的角度,提出了一种任务调度与功耗管理算法.该算法处理实时有截止时间并有相互依赖关系的任务,任务执行在多个电压可调的处理单元上.通过对节点系统能量采集行为和应用情况进行分析建立了问题模型,并运用运筹学软件LINGO对模型做了求解.利用多组随机输入的任务流图对模型与算法进行了验证,该算法在功耗与时间约束范围内确实能有效提高系统的能量利用效率.     

能量有效的无线传感器网络动态任务调度算法

为减少无线传感器网络任务调度的能量消耗,平衡网络负载,提出能量最小化的动态任务调度算法。在感知动态环境的基础上,将传感器网络节点的覆盖率、可调度性等作为该问题的约束条件。将改进后的蚁群算法应用于任务调度算法中,通过迭代得到最优分配方案,引入信息熵提升剩余能量充沛的节点执行任务的几率。仿真结果表明,该算法在降低任务分配的执行时间、能量消耗量及优化网络负载平衡方面取得了较好的效果。     

面向目标跟踪的传感器网络睡眠调度协议

移动目标跟踪是无线传感器网络中的一项重要应用,将睡眠调度机制引入到目标跟踪算法中可以大大降低能耗。针对目标跟踪的实际需求,提出一种面向目标跟踪的传感器网络睡眠调度协议。根据目标跟踪不同阶段,分别设计了目标跟踪前和跟踪过程中传感器节点的睡眠调度机制;另外给出了目标丢失时,如何唤醒节点继续跟踪目标的调度策略。结果表明:该算法能够在保证跟踪质量的同时,降低跟踪能耗。     

The problem of optimal robust sensor scheduling

This paper considers the sensor scheduling problem which consists of estimating the state of an uncertain process based on measurements obtained by switching a given set of noisy sensors. The noise and uncertainty models considered in this paper are assumed to be unknown deterministic functions which satisfy an energy type constraint known as an integral quadratic constraint. The problem of optimal robust sensor scheduling is formulated and solution to this problem is given in terms of the existence of suitable solutions to a Riccati differential equation of the game type and a dynamic programming equation. Furthermore, a real time implementable method for sensor scheduling is also presented.     

Sensor data scheduling for optimal state estimation with communication energy constraint

In this paper, we consider sensor data scheduling with communication energy constraint. A sensor has to decide whether to send its data to a remote estimator or not due to the limited available communication energy. We construct effective sensor data scheduling schemes that minimize the estimation error and satisfy the energy constraint. Two scenarios are studied: the sensor has sufficient computation capability and the sensor has limited computation capability. For the first scenario, we are able to construct the optimal scheduling scheme. For the second scenario, we are able to provide lower and upper bounds of the minimum error and construct a scheduling scheme whose estimation error falls within the bounds.     

TDMA scheduling for event-triggered data aggregation in irregular wireless sensor networks

Multi-hop wireless sensor networks often use a TDMA schedule to collect data periodically from multiple locations within a large area. If the measurements from neighboring sensors are cross-correlated, they can be aggregated and compressed as they travel to the data sink. In order for data aggregation to occur quickly, the TDMA schedule must arrange time slot assignments in a certain order. The existing scheduling protocols cannot quickly obtain a schedule with this order, high concurrency, and no collisions. We propose a distributed TDMA scheduling protocol for data aggregation called DATP. In DATP, the sensor nodes transmit dummy packets in order to determine whether they can tolerate the interference from the other nodes that are assigned the same time slot. In this way, time slot allocations are empirically verified to be collision-free. In contrast, the existing protocols obtain schedules with collisions because they use unrealistic interference models such as neglecting interference generated more than two hops away. Furthermore, our simulations reveal that DATP achieves similar concurrency and lower execution time than comparable protocols. These simulations are executed for different network sizes, node densities, and data compression models. In addition, we show that, in networks with fluctuating links, DATP’s main advantage is its execution speed.     

Real-time scheduling of divisible loads in cluster computing environments

Cluster computing has become an important paradigm for solving large-scale problems. To enhance the quality of service (QoS) and provide performance guarantees in a cluster computing environment, various real-time scheduling algorithms and workload models have been investigated. Computational loads that can be arbitrarily divided into independent tasks represent many real-world applications. However, the problem of providing performance guarantees to divisible load applications has only recently been studied systematically. In this work, three important and necessary design decisions, (1) workload partitioning, (2) node assignment, and (3) task execution order, are identified for real-time divisible load scheduling. A scheduling framework that can configure different policies for each of the three design decisions is proposed and used to generate various algorithms. This paper systematically studies these algorithms and identifies scenarios where the choices of design parameters have significant effects.     

一种无线多媒体传感器网络分区链路调度算法

链路干扰是无线多媒体传感器网络实现大容量、实时、可靠传输的主要困难。为提高多跳传输模式下无线网络性能,基于MAC层的调度算法得到了广泛关注。调度算法为每条链路分配合理的传输时槽,降低了冲突和重传次数,能显著提高网络传输性能。但随着网络规模的增大,无论是集中式还是分布式调度算法,都存在调度开销增大和性能降低的问题。针对这一问题,根据节点分布密度和承载网络流量大小,将网络划分为密集区域和稀疏区域。稀疏区域的节点传输冲突较小,直接采用CSMA的协议。密集区域的节点传输冲突大,采用基于队列长度的分布式调度。分区调度能够有效降低网络规模扩大导致的调度算法复杂性增大的问题。仿真实验表明,分区调度算法无论是在队列长度,还是在延时性能上,较传统算法有明显改善。     

Analyzing multi-hop routing feasibility for sensor data harvesting using mobile sinks

This paper presents a modeling framework for characterizing the feasibility and impacts of multi-hop packet routing in sensor networks with mobile sinks. Data collection in sensor networks using mobile sinks has recently been investigated to improve energy performance at the cost of collection delay. Although the data collection can be accomplished with varying degrees of multi-hop routing, for a given data generation rate, as the extent of multi-hop routing increases, the round traversal time of the sink decreases. At the same time, the interference experienced by the mobile sink-to-sensor links and the consequent upload time go up. This paper characterizes these competing effects and develops a methodology for determining the extent of multi-hop routing that is feasible for given network and application parameters such as sensor data generation rate, wireless link capacity between sensors and mobile sink, the speed of the mobile sink and node density.