Joint routing, scheduling, and power control for multichannel wireless sensor networks with physical interference

Reliability and real-time requirements bring new challenges to the energy-constrained wireless sensor networks, especially to the industrial wireless sensor networks. Meanwhile, the capacity of wireless sensor networks can be substantially increased by operating on multiple nonoverlapping channels. In this context, new routing, scheduling, and power control algorithms are required to achieve reliable and real-time communications and to fully utilize the increased bandwidth in multichannel wireless sensor networks. In this paper, we develop a distributed and online algorithm that jointly solves multipath routing, link scheduling, and power control problem, which can adapt automatically to the changes in the network topology and offered load. We particularly focus on finding the resource allocation that realizes trade-off among energy consumption, end-to-end delay, and network throughput for multichannel networks with physical interference model. Our algorithm jointly considers 1) delay and energy-aware power control for optimal transmission radius and rate with physical interference model, 2) throughput efficient multipath routing based on the given optimal transmission rate between the given source-destination pairs, and 3) reliable-aware and throughput efficient multichannel maximal link scheduling for time slots and channels based on the designated paths, and the new physical interference model that is updated by the optimal transmission radius. By proving and simulation, we show that our algorithm is provably efficient compared with the optimal centralized and offline algorithm and other comparable algorithms.     

Target tracking based on the extended H-infinity filter in wireless sensor networks

In this paper, we propose a new target tracking approach for wireless sensor networks (WSNs) by using the extended H-infinity filter. First, the extended H-infinity filter for nonlinear discrete-time systems is deduced through the Krein space analysis scheme. Then, the proposed extended H-infinity filtering algorithm is applied to target tracking in wireless sensor networks. Finally, experiments are conducted through a small wireless sensor network test-bed. Both experimental and simulation results illustrate that the extended H-infinity filtering algorithm is more accurate to track a moving target in wireless sensor networks than using the extended Kalman filter in the case of having no knowledge of the statistics of the environment and the target to be tracked.     

Novel sensor scheduling and energy-efficient quantization for tracking target in wireless sensor networks

This paper focuses on sensor scheduling and information quantization issues for target tracking in wireless sensor networks (WSNs). To reduce the energy consumption of WSNs, it is essential and effective to select the next tasking sensor and quantize the WSNs data. In existing works, sensor scheduling’ goals include maximizing tracking accuracy and minimizing energy cost. In this paper, the integration of sensor scheduling and quantization technology is used to balance the tradeoff between tracking accuracy and energy consumption. The main characteristic of the proposed schemes includes a novel filtering process of scheduling scheme, and a compressed quantized algorithm for extended Kalman filter (EKF). To make the algorithms more efficient, the proposed platform employs a method of decreasing the threshold of sampling intervals to reduce the execution time of all operations. A real tracking system platform for testing the novel sensor scheduling and the quantization scheme is developed. Energy consumption and tracking accuracy of the platform under different schemes are compared finally.     

A topology-transparent MAC scheduling algorithm with guaranteed QoS for multihop wireless network

Due to its character of topology independency, topology-transparent medium access control (MAC) scheduling algorithm is very suitable for large-scale mobile ad hoc wireless networks. In this paper, we propose a new topologytransparent MAC scheduling algorithm, with parameters of the node number and the maximal nodal degree known, our scheduling algorithm is based on a special balanced incomplete block design whose block size is optimized by maximizing the guaranteed throughput. Its superiority over typical other scheduling algorithms is proven mathematically with respect to the guaranteed throughput, the maximal transmission delay, and also the minimal transmission delay. The effect of inaccuracy in the estimation of the maximal nodal degree on the guaranteed throughput is deduced mathematically, showing that the guaranteed throughput decreases almost linearly as the actual nodal degree increases. Further techniques for improving the feasibility of the algorithm, such as collision avoidance, time synchronization, etc., are also discussed.     

A QoS-aware routing algorithm based on ant-cluster in wireless multimedia sensor networks

QoS-aware routing algorithm is important in wireless multimedia sensor networks. This paper formulates a generalized QoS-aware routing model on the basis of multiple routing metrics and priorities of packets. We first introduce a 2D plain-based routing algorithm IPACR which improves the standard ant colony algorithm by optimizing the initial distribution of artificial pheromone in order to accelerate the algorithm convergence rate. Then a clustering-based routing algorithm ICACR is presented which can be well applied in a large scale network. ICACR is a variation of IPACR because it can be suitable for clustering cases to satisfy the larger scale situations. Both the numerical algorithm performance analysis and simulation of IPACR and ICACR are given. The results show that ICACR outperforms IPACR in terms of both network lifetime and QoS-aware routing metrics in large scale wireless multimedia sensor networks. Moreover, the simulation based on the real video traces shows that by extending the multi-path to ICACR for different priorities of video frames better performance can be achieved.     

Energy-aware routing for delay-sensitive underwater wireless sensor networks

The energy reduction is a challenging problem in the applications of underwater wireless sensor networks （UWSNs）. The embedded battery is difficult to be replaced and it has an upper bound on its lifetime. Multihop relay is a popular method to reduce energy consumption in data transmission. The energy minimum path from source to destination in the sensor networks can be obtained through the shortest path algorithm. However, because of the node mobility, the global path planning approach is not suitable for the routing in UWSNs. It calls for an energy-efficient routing protocol for the high dynamic UWSNs. In this paper, we propose the modified energy weight routing （MEWR） protocol to deal with the energy-efficient routing of delay- sensitive UWSNs. MEWR is a low flooding routing protocol. It can tolerate the node mobility in UWSNs and achieve a low end-to-end packet delay. MEWR can provide lower energy consumption than the existing low delay routing protocols through the dynamic sending power adjustment. The simulation results demonstrate the effectiveness of MEWR.     

Energy saving in wireless sensor networks

With the development of low-cost processor, memory, and radio technologies, it becomes possible to build inexpensive wireless micro-sensor nodes. However, energy is the biggest constraint to wireless sensor capabilities and such constraint combined with a typical deployment of large numbers of sensor nodes have posed many challenges to the design and management of sensor networks. Due to their ad-hoc deployment in hazardous environment, once sensor nodes are deployed in a sensor network, they cannot be easily replaced or recharged. Thus, energy saving acts as one of the hottest topics in wireless sensor networks （WSNs） and hence several energy conservation schemes have been proposed in the literature. In this work, we will make a short survey on the main techniques used for energy conservation in sensor networks. Specifically, we will focus primarily on duty cycling schemes which represent the most suitable technique for energy saving. Moreover, we will also survey in-network processing and network coding techniques which can guarantee a significant amount of energy saving in packet transmission. Finally, we will make a review on some communication protocols proposed for sensor networks.     

A Monte Carlo Enhanced PSO Algorithm for Optimal QoM in Multi-Channel Wireless Networks

In wireless monitoring networks, wireless sniffers are distributed in a region to monitor the activities of users. It can be used for fault diagnosis, resource management and critical path analysis. Due to hardware limitations, wireless sniffers typically can only collect information on one channel at a time. Therefore, it is a key topic to optimize the channel selection for sniffers to maximize the information collected, so as to maximize the quality of monitoring (QoM) of the network. In this paper, a particle swarm optimization (PSO)-based solution is proposed to achieve the optimal channel selection. A2D mapping particle coding and its moving scheme are devised. Monte Carlo method is incorporated to revise the solution and significantly improve the convergence of the algorithm. The extensive simulations demonstrate that the Monte Carlo enhanced PSO (MC-PSO) algorithm outperforms the related algorithms evidently with higher monitoring quality, lower computation complexity, and faster convergence. The practical experiment also shows the feasibility of this algorithm.     

Achieving high throughput and TCP Reno fairness in delay-based TCP over large networks

The transport control protocol （TCP） has been widely used in wired and wireless Intemet applications such as FTP, email and HTTP. Numerous congestion avoidance algorithms have been proposed to improve the performance of TCP in various scenarios, especially for high speed and wireless networks. Although different algorithms may achieve different performance improvements under different network conditions, designing a congestion algorithm that can perform well across a wide spectrum of network conditions remains a great challenge. Delay-based TCP has a potential to overcome above challenges. However, the unfairness problem of delay-based TCP with TCP Reno blocks widely the deployment of delay-based TCP over wide area networks. In this paper, we proposed a novel delay-based congestion control algorithm, named FAST-FIT, which could perform gracefully in both ultra high speed networks and wide area networks, as well as keep graceful faimess with widely deployed TCP Reno hosts. FAST-FIT uses queuing delay as a primary input for controlling TCP congestion window. Packet loss is used as a secondary signal to adaptively adjust parameters of primary control process. Theoretical analysis and experimental results show that the performance of the algorithm is significantly improved as compared to other state-of-the-art algorithms, while maintaining good faimess.     

A Hyper-Heuristic Framework for Lifetime Maximization in Wireless Sensor Networks With A Mobile Sink

Maximizing the lifetime of wireless sensor networks(WSNs) is an important and challenging research problem. Properly scheduling the movements of mobile sinks to balance the energy consumption of wireless sensor network is one of the most effective approaches to prolong the lifetime of wireless sensor networks. However, the existing mobile sink scheduling methods either require a great amount of computational time or lack effectiveness in finding high-quality scheduling solutions. To address the above issues, this paper proposes a novel hyperheuristic framework, which can automatically construct high-level heuristics to schedule the sink movements and prolong the network lifetime. In the proposed framework, a set of low-level heuristics are defined as building blocks to construct high-level heuristics and a set of random networks with different features are designed for training. Further, a genetic programming algorithm is adopted to automatically evolve promising high-level heuristics based on the building blocks and the training networks. By using the genetic programming to evolve more effective heuristics and applying these heuristics in a greedy scheme, our proposed hyper-heuristic framework can prolong the network lifetime competitively with other methods, with small time consumption. A series of comprehensive experiments, including both static and dynamic networks,are designed. The simulation results have demonstrated that the proposed method can offer a very promising performance in terms of network lifetime and response time.     

Pair-Wise Collision-Based Underwater Time Synchronization

Time synchronization is a critical issue for Underwater Wireless Sensor Networks (UWSN). Although numerous time synchronization algorithms have been proposed for terrestrial wireless sensor networks, none of them could be applied to UWSN directly. This is because underwater time synchronization offers two fundamental challenges compared with terrestrial wireless sensor networks, i.e., (1) long propagation delay and (2) sensor node mobility. We propose a novel time synchronization approach called Coll-Sync to address the above challenging problems, which is a pair-wise collision-based time synchronization scheme for mobile underwater acoustic sensor networks. Coll-Sync adopts collision and packet meetings in a long propagation process to eliminate the effect of node mobility. In this paper, we indicate that collision and packet meetings contain highly useful information that can be leveraged to improve time synchronization. Through comprehensive experiments, we show that our proposed Coll-Sync greatly outperforms existing time synchronization schemes in both precision and energy saving.     

无线传感器网络时间同步技术研究

时间同步技术是无线传感器网络的一项重要技术,它对无线传感器网络中许多技术的实现具有重大意义.有限的电池能量,存储以及带宽限制等传感器固有特性的存在,导致传统的时间同步算法不适合无线传感器网络.具体介绍了现有的无线传感器中的一些时间同步问题和时间同步算法,并对其具体特性进行了深入的分析比较.     

无线传感器网络按需时间同步算法研究

节点的时间同步是无线传感器网络的一项支撑技术。鉴于目前对低能耗的多跳时间同步算法的研究相对缺乏,本文在分析了TPSN时间同步算法的基础上,提出了一种适合低流量无线传感器网络的低能耗多跳按需时间同步算法。具体阐述了单点同步和多点同步算法,分析了算法的精度与复杂度。仿真实验表明本文提出的算法与TPSN算法相比,在相同精度的前提下,具有复杂度低、节能等优点。     

一种低功耗无线传感器网络时间同步算法

间同步对无线传感器网络的应用至关重要,为提高同步精度,多数算法都以较多的消息交换或复杂的计算为代价来达到这一目的,因而能耗较大.为减少时间同步的消息交换开销,节约节点能量,提出了一种简单低功耗时间同步算法,该算法结合了单向广播同步机制和双向成对同步机制,有效利用网络中节点的广播信息,使网络中节点单跳广播域内只有一个下层节点与之进行双向成对同步,从而达到了减少消息开销和节约能量的目的.最后通过仿真验证了该算法的性能.     

无线传感器网络的广播时间同步算法

基于包交换机制，利用无线信道的广播特性和捎带技术减少同步报文个数；对包时间信息进行缓存并采用最小方差线性拟合方法平滑同步误差抖动．模拟结果表明，在Mica2上单跳平均同步精度达到约57μs．最后与类似算法进行了性能比较．     

一种基于多普勒效应的水下无线传感器网络时间同步机制

时间同步是无线传感器网络的基础问题。电磁波在水下环境的传输衰损极大,为此水下无线传感器网络通常采用超声波实现信息传输。由于超声波较低的传输速率和传感器节点在水中的运动,必将导致严重的信号传输延迟。构建了一种基于多普勒效应的水下无线传感器网络时间同步机制,通过检测接收到的超声波频率变化来实现时间同步校正。基于MATLAB实现了该同步算法的仿真。实验结果显示,传感器的采样时间间隔越短,移动速度越快,在水中所处的深度越小,整个系统的同步性越高。     

基于分簇的无线传感器网络时间同步算法

时间同步是无线传感器网络中一个重要支撑技术,为了提高时间同步精度,提出了一种基于分簇的无线传感器网络时间同步算法;在部署无线传感器网络的初期阶段,建立簇状拓扑结构,首先是基站与簇首节点实现同步,然后簇内实现同步,最终建立一个全网统一的时钟,在同步过程中,采用了成对节点间的同步算法,很好利用了多信道广播方式;该算法能很好地满足无线传感器网络低能耗的要求;性能分析和实验结果表明,该算法减少了同步层次,提高了同步精度。     

无线生理传感器网络TPSN算法的改进与分析

通过对无线生理传感器网络TPSN算法的研究,针对采用TPSN算法进行时间同步时产生的同步误差,采用最小二乘法对其进行改进,并在NS-2仿真环境下进行仿真分析。仿真结果表明改进后算法的时间同步误差更小,同步精度更高,更适用于无线生理传感器网络。     

考虑干扰的无线传感器网络拓扑控制问题研究

无线传感器网络的拓扑控制是一个十分重要的技术问题。干扰对传感器网络应用产生了重要的影响,较大的传输干扰将导致信号的碰撞,增大网络延时间。但是,目前的大多数文献没有把干扰作为传感器网络拓扑控制的设计目标和考虑因素之一。本文研究考虑干扰的拓扑控制机制问题,根据传感器网络通信特点,设计了最优的集中式算法和适合合实际应用的次优分布式算法解决该问题。模拟实验结果表明,提出的算法与传统算法相比能有效减少网络干扰、节省能量消耗和减少网络延时,因此是一种新的高效的拓扑控制机制。     

无线传感器网络中带延时的一致性时间同步

针对无线传感器网络(WSNs)中节点间通信存在传输延迟,影响同步精度的情况,将加权平均应用于相对时钟斜率的计算,提出了一种带延时的一致性时间同步算法.该算法中每个传感器节点通过与邻居节点通信交换时钟信息,根据一致性理论更新时钟参数,从而到达时间同步的目的.研究了在假定传输延时服从正态分布的情况下对一致性时间同步算法的影响,提出的算法降低了延时对同步精度的影响,Matlab仿真验证了该算法的有效性.