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.     

基于线性规划的WSN最大工作寿命之节点调度

由于传感器节点能量受限,如何延长WSN的工作寿命是一重大挑战.提出了一种最大化WSN工作寿命的节点调度策略.首先使用线性规划方法计算网络的最大工作寿命,然后通过求负载矩阵、分解负载矩阵成调度矩阵序列和求传感器监控树,得到从活跃传感器节点到基站的优化节点调度.提出的策略从全局角度综合考虑传感器到基站的通信代价,优化了WSN中的节点调度,获得了WSN的最大工作寿命.仿真结果表明提出方法能有效延长WSN的工作寿命.     

Energy-Efficient Routing Using Novel Optimization with Tabu Techniques for Wireless Sensor Network

Wireless Sensor Network (WSN) consists of a group of limited energy source sensors that are installed in a particular region to collect data from the environment. Designing the energy-efficient data collection methods in large-scale wireless sensor networks is considered to be a difficult area in the research. Sensor node clustering is a popular approach for WSN. Moreover, the sensor nodes are grouped to form clusters in a cluster-based WSN environment. The battery performance of the sensor nodes is likewise constrained. As a result, the energy efficiency of WSNs is critical. In specific, the energy usage is influenced by the loads on the sensor node as well as it ranges from the Base Station (BS). Therefore, energy efficiency and load balancing are very essential in WSN. In the proposed method, a novel Grey Wolf Improved Particle Swarm Optimization with Tabu Search Techniques (GW-IPSO-TS) was used. The selection of Cluster Heads (CHs) and routing path of every CH from the base station is enhanced by the proposed method. It provides the best routing path and increases the lifetime and energy efficiency of the network. End-to-end delay and packet loss rate have also been improved. The proposed GW-IPSO-TS method enhances the evaluation of alive nodes, dead nodes, network survival index, convergence rate, and standard deviation of sensor nodes. Compared to the existing algorithms, the proposed method outperforms better and improves the lifetime of the network.     

Energy-aware node placement,topology control and MAC scheduling for wireless sensor networks

In the WSNs, the nodes closer to the sink node have heavier traffic load for packet forwarding because they do not only collect data within their sensing range but also relay data for nodes further away. The unbalanced power consumption among sensor nodes may cause network partition. This paper proposes efficient node placement, topology control, and MAC scheduling protocols to prolong the sensor network lifetime, balance the power consumption of sensor nodes, and avoid collision. Firstly, a virtual tree topology is constructed based on Grid-based WSNs. Then two node-placement techniques, namely Distance-based and Density-based deployment schemes, are proposed to balance the power consumption of sensor nodes. Finally, a collision-free MAC scheduling protocol is proposed to prevent the packet transmissions from collision. In addition, extension of the proposed protocols are made from a Grid-based WSN to a randomly deployed WSN, enabling the developed energy-balanced schemes to be generally applied to randomly deployed WSNs. Simulation results reveal that the developed protocols can efficiently balance each sensor node’s power consumption and prolong the network lifetime in both Grid-based and randomly deployed WSNs.     

无线传感器网络媒质接入控制协议的研究进展

媒质接入控制（Medium Access Control）是无线传感器网络设计的关键问题之一。由于无线通信模块是传感器节点能量消耗的主要来源，而媒质接入控制协议则直接控制着节点无线通信模块的活动，因此MAC协议节能效率的好坏将严重影响网络的性能。本文首先介绍了MAC层能量消耗的主要来源，阐述了无线传感器网络中MAC协议的研究内容和设计目标，并讨论了影响MAC协议性能的若干参数指标，随后介绍了几类典型的MAC协议，最后对MAC协议的发展方向进行了总结和展望。     

一种能量有效的无线传感器网络轮询接入控制协议

周期性休眠的PCF机制虽然较好地解决了无线传感器网络的能耗问题,但没有考虑节点的负载状态,降低了系统性能,也增加了系统的查询能耗.以限定(K=1)服务为基础,提出了一种改进的PCF轮询控制协议,即具有混合服务策略的无线传感器网络轮询接入控制协议PCF-SS.该协议在保障公平性的前提下,能够根据节点状态动态调整优先级并改变服务K值,中心服务器AP则根据各节点的服务K值在每轮服务时对节点的下一轮服务时间进行预估计,并采用统一的服务时间表唤醒节点,达到节能的效果.仿真实验表明系统的平均等待时间、平均排队队长等性能指标比周期性休眠的PCF机制要好,能量的有效利用率更高,具有更长的生命周期,适合作为无线传感器网络的MAC控制协议.     

一种由接收端发起的无线传感器网络MAC协议

在无线传感器网络(Wireless sensor networks,WSN)中,现有的基于接收节点发起的异步MAC层协议,在计算接收节点唤醒时刻时,多采用维持邻居节点的伪随机唤醒时间表的方法。在网络动态负载条件下,此方法不能动态地改变节点唤醒间隔,从而带来较高的数据传输冲突率及较大的数据传输延时。为了解决此问题,本文提出一种新协议HELD-MAC(High energy efficiency and　low delay MAC),保证节点之间具有不同的唤醒时间,同时能够准确预测接收端唤醒时刻,而且接收端可以根据网络负载情况动态改变唤醒间隔。同时为了减轻能量黑洞问题,协议根据节点的剩余能量,自适应地改变节点的最小唤醒间隔。通过仿真对HELD-MAC进行评估,与RI-MAC,PW-MAC等对比,在数据传输延时、能量消耗、网络吞吐量和传输碰撞方面具有较大优势。     

无线传感器网络随机密钥预分配改进方案

由于无线传感器网络节点能量、存储能力和计算能力的有限性,使传统的网络安全方案受到挑战。针对无线传感器网络的特点,在预共享密钥和随机密钥分发方案的基础上,提出了一种密钥分配方案。该方案采用只保存密钥池中密钥ID号的方法,节省了节点的存储空间。同时,考虑到传感器节点自身资源有限的特点,在满足加密需要的前提下,通过减少会话步骤、简化计算方法来降低传感器节点的工作负荷,从而使得传感器节点存储空间和通信开销都非常小,大大提高了传感器网络的工作效率。     

An asynchronous scheduled MAC protocol for wireless sensor networks

Wireless sensor networks (WSNs) comprise a number of autonomous sensors and one or more sinks to cooperatively monitor physical or environmental conditions. Energy efficiency is a key design factor of a MAC protocol for WSNs. Due to the importance of the problem, a number of energy efficient MAC protocols have been developed for WSNs. Preamble-sampling based MAC protocols (e.g., B-MAC and X-MAC) have overheads due to their preambles, and are inefficient at large wakeup intervals. SCP-MAC, a synchronous scheduled energy-efficient scheduling MAC protocol, minimizes the preamble by combining preamble sampling and scheduling techniques; however, it does not prevent energy loss due to overhearing; in addition, due to its synchronization procedure, it results in increased contention and delay. In this paper, we present an energy efficient MAC protocol for WSNs that avoids overhearing and reduces contention and delay by asynchronously scheduling the wakeup time of neighboring nodes. We provide an energy consumption analysis for multi-hop networks. To validate our design and analysis, we implement the proposed scheme in TinyOS. Experimental results show that AS-MAC considerably reduces energy consumption, packet loss and delay when compared with existing energy efficient MAC protocols.     

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％.     

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．     

基于空间分辨率的无线传感网节点调度策略

节点调度策略是解决无线传感器网络(WSN)能量受限和覆盖高度冗余的一种有效方法,但在节能的同时又必须满足覆盖率的需求。针对随机调度中的能量消耗不均衡且使用不合理等问题,提出一种基于空间分辨率的节点调度策略。该策略通过控制区域中的活动节点数来保障网络的覆盖率要求,并利用剩余能量来均衡化各节点的能耗。同时借助邻居节点保障机制,一方面关闭休眠节点的实时监听,减少不合理的能耗;另一方面缓解节点轮休时可能出现的覆盖漏洞问题,有效保障网络覆盖率。仿真结果表明,该策略在网络覆盖率、生存期以及节点间的能耗均衡度等方面的性能表现优于Gur Game等调度算法。     

Energy and delay optimized contention for wireless sensor networks

In wireless sensor network (WSN) studies, the main objective is minimizing the energy consumption so that the lifetime is maximized under the limited battery capacity constraints. Additionally, in most event-driven WSN applications, the end-to-end delay, and hence, the medium access delay should be minimized. Majority of the WSN MAC protocols are contention-based wherein contention window size setting involves an important trade-off between the collision probability and idle listening durations in contentions where both are aimed to be lowered for efficient network operation. In this paper, the energy optimizing and the delay optimizing contention window sizes are derived as a function of the number of contending nodes. For this purpose, we present separate analyses for the contention delay and for the energy consumed which are verified with detailed simulations. In order to obtain close to optimal performance values in a distributed manner, we propose a method for estimating the number of contending nodes since the individual wireless sensor nodes do not have this information readily. Simulations of an event-driven WSN application verify that the proposed method successfully improve both delay and energy efficiency of the contention-based medium access. The end-to-end network performance is also investigated by employing a geographical routing protocol. Results show that using the heuristic method proposed that use the optimum contention window size analyses presented, the overall network performance can be improved without incurring any overhead to the system.     

基于网络效用最大化与冲突避免的无线传感器网络MAC协议

针对周期汇报型无线传感器网络(WSN)中的无线信号冲突和能量利用效率问题,提出了一种基于网络效用最大化与冲突避免的媒体访问控制(UM-MAC)协议。该协议基于时分多路复用(TDMA)调度机制,将效用模型引入无冲突的节点工作时隙分配过程中,把链路可靠性、网络能耗归纳到一个统一的效用优化框架中;进而提出了一个启发式算法,使网络能够快速找到一个基于网络效用最大化与冲突避免的节点工作时隙调度方案。将UM-MAC协议与S-MAC协议和冲突避免MAC(CA-MAC)协议进行比较,在不同节点数量的网络环境中,UM-MAC获得的网络效用较大,平均数据包成功发送率较高,生命周期介于S-MAC与CA-MAC之间,在不同的网络负载下所有节点发数据包到汇聚节点的平均时延有所增加。仿真实验结果表明:UM-MAC协议较好地解决了冲突干扰问题,提高了网络的数据包成功发送率和能量利用效率等性能;在低网络负载时,TDMA类协议的性能并不比竞争类协议好。     

一种适用于无线传感器网络的功率控制MAC协议

功率控制技术通过减少节点的发射功率来降低能耗,但节点间不对称的发射功率会增加网络的冲突概率并降低吞吐量.根据实际环境中的节点部署情况,引入了基于Pareto分布的系统模型.研究了传感器网络中功率控制技术在节省能量方面的性能,提出了一种基于SMAC(sensor-MAC)可适用于无线传感器网络的功率控制MAC(media access control)协议.此协议使用功率控制调度算法选择最优相邻节点,使网络中节点的拓扑连接得到优化,在保证网络连通性的同时,降低通信的冲突率,扩大网络的吞吐量.信息的传递以最优功率发射,并使通信节点具有反作用冲突节点的能力,从而在降低网络能耗的同时保证了节点间通信的公平性.实验仿真结果显示,与现有的几种重要方案相比,新的功率控制MAC协议使网络具有了更大的有效吞吐量及更长的生存时间.     

一种基于学习自动机的WSN区域覆盖算法

基于连通支配集(Connected dominating set,CDS)的区域覆盖算法大都采用休眠节点数量的最大化机制来实现节能,这将给无线传感器网络中的活动节点带来沉重的负担。活动节点电能的迅速耗尽将导致CDS失效,产生覆盖盲区。不断激活其他休眠节点,会出现频繁的网络拓扑变化,导致网络收敛性出现问题。提出了一种基于学习自动机的WSN区域覆盖算法。采用受度限制的连通支配集d-CDS来构造WSN骨干网络,利用学习自动机选择当前节点的最优邻居节点,以此实现对所构造CDS的优化,实现活动节点的负载均衡,改善区域覆盖性能。通过仿真实验对比Gossip、ST-MSN和TMPO等算法,表明本文提出的算法在网络覆盖比率、活动节点的剩余电量等方面均存在优势。     

Performance evaluation of MAC transmission power control in wireless sensor networks

In this paper we provide a method to analytically compute the energy saving provided by the use of transmission power control (TPC) at the MAC layer in wireless sensor networks (WSN). We consider a classical TPC mechanism: data packets are transmitted with the minimum power required to achieve a given packet error probability, whereas the additional MAC control packets are transmitted with the nominal (maximum) power. This scheme has been chosen because it does not modify the network topology, since control packet transmission range does not change. This property also allows us to analytically compute the expected energy savings. Besides, this type of TPC can be implemented in the current sensor hardware, and it can be directly applied to several MAC protocols already proposed for WSN. The foundation of our analysis is the evaluation of L ratio, defined as the total energy consumed by the network using the original MAC protocol divided by the total energy consumed if the TPC mechanism is employed. In the L computation we emphasize the basic properties of sensor networks. Namely, the savings are calculated for a network that is active for a very long time, and where the number of sensors is supposed to be very large. The nodes position is assumed to be random – a normal bivariate distribution is assumed in the paper – and no node mobility is considered. In the analysis we stress the radio propagation and the distribution of the nodes in the network, which will ultimately determine the performance of the TPC. Under these conditions we compute the mean value of L. Finally, we have applied the method to evaluate the benefits of TPC for TDMA and CSMA with two representative protocols, L-MAC and S-MAC using their implementation reference parameters. The conclusion is that, while S-MAC does not achieve a significant improvement, L-MAC may reach energy savings up to 10–20%.     

基于RFID的无线传感器网络节能MAC技术

将无线射频识别(RFID)技术与无线传感器网络相融合，设计具有RFID读取功能的传感器节点。针对基于RFID的无线传感器网络，提出基于簇族结构的节能MAC协议——CSMAC协议。该协议具有节能和广播导向等特征，采用冲突减少机制来提高信道利用率，同时采用减少发送时间、减少监听时间、减少开关转换时间等功率优化机制，以提高网络能量效率。仿真试验表明，与传统MAC协议相比，CSMAC协议更能提高信道利用率和能量效率。     

Approximation schemes for load balanced clustering in wireless sensor networks

Clustering sensor nodes is an efficient technique to improve scalability and life time of a wireless sensor network (WSN). However, in a cluster based WSN, the leaders (cluster heads) consume more energy due to some extra load for various activities such as data collection, data aggregation, and communication of the aggregated data to the base station. Therefore, balancing the load of the cluster heads is a crucial issue for the long run operation of the WSNs. In this paper, we first present a load balanced clustering scheme for wireless sensor networks. We show that the algorithm runs in O(nlogn) time for n sensor nodes. We prove that the algorithm is optimal for the case in which the sensor nodes have equal load. We also show that it is a polynomial time 2-approximation algorithm for the general case, i.e., when the sensor nodes have variable load. We finally improve this algorithm and propose a 1.5-approximation algorithm for the general case. The experimental results show the efficiency of the proposed algorithm in terms of the load balancing of the cluster heads, execution time, and the network life.     

基于马尔可夫链的无线传感器网络分布式调度方法

能量效率是无线传感器网络(Wireless sensor network, WSN)研究中的核心问题之一. 当节点采用电池供电时, 有限的能量限制了网络的生存周期, 从而对无线传感器网络的大规模应用提出了挑战. 本文基于马尔可夫链, 提出了一种实用的、协作分布式的调度方法, 并从理论上证明了该方法的收敛性. 该方法不仅可对节点的休眠/唤醒进行调度, 还可以对节点数据发送进行调度以减少数据冲突的发生. 仿真实验结果表明, 该方法能够有效地减少节点能量的消耗, 且对其他网络性能的影响较小.