基于深度强化学习的协作通信中继选择

协作通信是无线传感器网络(Wireless Sensor Network,WSN)实现数据可靠传输的关键技术,而协作通信技术的关键在于中继方案的选择。为此,提出了一种基于深度强化学习的协作通信中继选择算法(Deep Q-Learning Based Relay Selection Scheme,DQ-RSS)。首先,将WSN中具有中继选择的协作通信过程建模为马尔科夫决策过程,并采用Q学习在未知网络模型的情况下获取最佳中继选择策略;其次,针对高维状态空间下Q学习收敛时间长的问题,采用DQN(Deep-Q-Net)算法来加速Q学习的收敛。对比仿真实验结果表明,DQ-RSS在中断概率、系统容量和能耗方面均优于现有的中继选择方案,且能够有效节省收敛时间。     

Optimal cooperative strategy based on quantum bat for cognitive radio of energy harvesting

In order to reduce energy consumption and improve spectral efficiency of the cognitive relay wireless communication system in 5G network,an optimal cooperative transmission strategy of information and energy was designed for cognitive relay radio with wireless energy harvesting.For the proposed optimal cooperative strategy,the maximal throughput formula and outage probability of secondary user were deduced.In order to resolve the derived maximum throughput equation,a quantum bat algorithm which was based on the optimization mechanism of quantum computing and bat algorithm was designed to solve the deduced equation,and the optimal cooperative transmission scheme for information and energy could be obtained.Simulation results show that the proposed optimal cooperative strategy not only can meet the information transfer demand of primary user,but also can realize the energy self-supply of the secondary user system and improve the communication quality of the secondary user.The proposed optimal cooperative strategy has a better performance than the cooperative strategy of existing cognitive relay radio for different simulation scenarios.     

Suppression model of energy sink-hole attack in WSN based on the unequal cluster radius and mobile cluster head

To overcome the problem that partial cluster heads were drastically exhausted by the energy sink-hole attack in wireless sensor network,a novel suppression model based on the optimal path of mobile cluster heads was proposed,which was shown to balance the energy consumption in each cluster head.With the adoption of unequal cluster radius and data traffic monitoring explicitly,the inhibition mechanism was modeled as multivariate linear equations.Furthermore,toroidal projection was adopted to calculate the Euclidean distance,based on which the initial energy of mobile cluster head was configured correspondingly.On this basis,an algorithm based on the minimum cluster lifetime and throughput threshold was provided to achieve the detection and suppression of energy sink-hole attack.The experimental results show that the developed algorithm can suppress energy sink-hole attack evidently and efficiently and is suitable to the resource constrained WSN.     

Extending the Lifetime of Wireless Sensor Networks Through Mobile Relays

We investigate the benefits of a heterogeneous architecture for wireless sensor networks (WSNs) composed of a few resource rich mobile relay nodes and a large number of simple static nodes. The mobile relays have more energy than the static sensors. They can dynamically move around the network and help relieve sensors that are heavily burdened by high network traffic, thus extending the latter's lifetime. We first study the performance of a large dense network with one mobile relay and show that network lifetime improves over that of a purely static network by up to a factor of four. Also, the mobile relay needs to stay only within a two-hop radius of the sink. We then construct a joint mobility and routing algorithm which can yield a network lifetime close to the upper bound. The advantage of this algorithm is that it only requires a limited number of nodes in the network to be aware of the location of the mobile relay. Our simulation results show that one mobile relay can at least double the network lifetime in a randomly deployed WSN. By comparing the mobile relay approach with various static energy-provisioning methods, we demonstrate the importance of node mobility for resource provisioning in a WSN.      

传感器网络簇间通信自适应节能路由优化算法

提出了一种用于无线传感器网络簇间通信的自适应节能路由优化算法。网络中以总体通信能耗最小为首要原则建立端到端之间的路由,并对簇间通信提出了一种优化算法,使得簇首之间相互通信时,可以在直接、中继以及协作3种不同方式中自适应地选择最节能的通信方式。所提出的路由算法可确保源节点与基站通信过程中选择到最优或次优的节能路由,并可降低由于通信覆盖盲区造成的通信中断的概率。仿真结果表明,与其他传感器网络路由算法相比,所提出的路由算法在相同吞吐量和误码率前提下每一轮都消耗更少的能量,并且在不同的节点密度下都可有效地延长网络的生命周期和工作时间。     

Using the node's experience from previous transmissions to improve the communication in an indoor localization system

Although originally the wireless sensor networks (WSN) were designed for transmitting environmental parameters with a low data rate, there is a growing need to use these networks for applications that require high throughput, such as real time localization systems (RTLS).     

Integrated Energy and Trust-Based Semi-Markov Prediction for Lifetime Maximization in Wireless Sensor Networks

Many of today’s computing and communication models are distributed systems that are composed of autonomous computational entities that communicate with each other, usually by passing messages. Distributed systems encompass a variety of applications and wireless sensor networks (WSN) is an important application of it. The tiny, multiple functionality and low power sensor nodes are considered to be interconnected in the WSN for efficient process of aggregating and transmitting the data to the base station. The clustering-based schemes of sensor networks are capable of organizing the network through the utilization of a specifically designated node termed as the cluster head for the objective of energy conservation and data aggregation. Further, the cluster head is responsible for conveying potential information collected by the cluster member nodes and aggregate them before transmitting it to the base station. In this paper, a Reliable Cluster Head Selection Technique using Integrated Energy and Trust-based Semi-Markov Prediction (RCHST-IETSMP) is proposed with the view to extend the lifetime of sensor networks. This proposed RCHST-IETSMP incorporated two significant parameters associated with energy and trust for effective selection of cluster head facilitated through the merits of Semi-Markoc prediction integrated with the Hyper Erlang distribution process. The simulation results of the proposed RCHST-IETSMP scheme is proving to be efficient in upholding the residual energy of the network and the throughput to a maximum level of 23% and 19% predominant to the trust and energy-based clustering schemes considered for investigation.

     

无线传感器网络中基于NDMA的跨层协作多包接收

本文研究了协作分集下的NDMA(网络辅助分集多址接入)机制,针对无线传感器网络特点和信道矩阵满秩性要求设计中继选择准则,提出了一个新的跨层协作多包接收机制.该机制在抗信道衰落的同时可有效限制数据包重传次数,从而大大提高多包接收的效率.对新机制的性能仿真以及该机制与NDMA、联合NDMA、时隙ALOHA之间的性能对比证实了新机制的有效性.     

一种基于WSN时变性与节点剩余能量均衡的机会路由算法

 为了解决数据报文在无线传感网络中动态路由以及网络内各节点剩余能量均衡问题,该文提出了一种机会路由算法。首先,利用热力学第2定律描述数据报文在无线传感器网络中动态路由的传输过程,其中,为了表征网络内各节点状态的时变性以及剩余能量,提出了机会熵模型;其次,以机会熵模型作为选择下一跳节点的理论依据,并结合蚁群优化(ACO)算法,设计并实现了考虑网络中各节点时变性与剩余能量均衡的机会路由算法(ACO for Time Dependent Opportunistic-routing Protocol, ATDOP),使得数据报文在转发过程时,能够有效地选择下一跳节点,从而使网络内各节点的通信资源和能量资源达到负载均衡。最后,通过实验证明,相对于已有的机会路由协议,ATDOP具有报文成功传输率高、网络有效吞吐量大以及网络工作寿命长等优点。     

A distributed,multi‐hop,adaptive, tree‐based energy‐balanced routing approach

To accomplish the primary objective of data sensing and collection of wireless sensor networks (WSN), the design of an energy efficient routing algorithm is very important. However, the energy constrained sensing nodes along with the intrinsic properties of the (WSN) environment makes the routing a challenging task. To overcome this routing dilemma, an improved distributed, multi‐hop, adaptive, tree‐based energy‐balanced (DMATEB) routing scheme is proposed in this paper. In this scheme, a relay node is selected in view of minimum distance and high energy from a current sensing node. Further, the parent node is chosen among the selected relay nodes on the basis of high residual energy and less power consumption with due consideration of its associated child nodes. As each sensing node itself selects its parent among the available alternatives, the proposed scheme offers a distributive and adaptive approach. Moreover, the proposed system does not overload any selected parent of a particular branch as it starts acting as a child whenever its energy lowers among the other available relay nodes. This leads to uniform energy utilization of nodes that offers a better energy balance mechanism and improves the network lifespan by 20% to 30% as compared with its predecessors.     

Relay algorithm based on network coding in wireless local network

The network coding is a new technology in the field of information in 21st century. It could enhance the network throughput and save the energy consumption, and is mainly based on the single transmission rate. However, with the development of wireless network and equipment, wireless local network MAC protocols have already supported the multi-rate transmission. This paper investigates the optimal relay selection problem based on network coding. Firstly, the problem is formulated as an optimization problem. Moreover, a relay algorithm based on network coding is proposed and the transmission time gain of our algorithm over the traditional relay algorithm is analyzed. Lastly, we compare total transmission time and the energy consumption of our proposed algorithm, Network Coding with Relay Assistance (NCRA), Transmission Request (TR), and the Direct Transmission (DT) without relay algorithm by adopting IEEE 802.11b. The simulation results demonstrate that our algorithm that improves the coding opportunity by the cooperation of the relay nodes leads to the transmission time decrease of up to 17% over the traditional relay algorithms.     

一种基于无交集节点分组的无线传感器网络覆盖算法

无线传感器网络是一种无线自组织网络,它由大量能量有限的传感器节点组成.能量消耗和网络覆盖是无线传感器网络的两个核心问题,网络覆盖决定了无线传感器网络对物理世界的监测能力,能量消耗则决定了无线传感器网络的生存时间.本文研究了一种改进的基于无交集节点分组算法,针对随机选取节点实现无交集节点分组方式获得的分组个数少且节点通信...     

A particle swarm optimization based energy efficient cluster head selection algorithm for wireless sensor networks

Clustering has been proven to be one of the most efficient techniques for saving energy of wireless sensor networks (WSNs). However, in a hierarchical cluster based WSN, cluster heads (CHs) consume more energy due to extra overload for receiving and aggregating the data from their member sensor nodes and transmitting the aggregated data to the base station. Therefore, the proper selection of CHs plays vital role to conserve the energy of sensor nodes for prolonging the lifetime of WSNs. In this paper, we propose an energy efficient cluster head selection algorithm which is based on particle swarm optimization (PSO) called PSO-ECHS. The algorithm is developed with an efficient scheme of particle encoding and fitness function. For the energy efficiency of the proposed PSO approach, we consider various parameters such as intra-cluster distance, sink distance and residual energy of sensor nodes. We also present cluster formation in which non-cluster head sensor nodes join their CHs based on derived weight function. The algorithm is tested extensively on various scenarios of WSNs, varying number of sensor nodes and the CHs. The results are compared with some existing algorithms to demonstrate the superiority of the proposed algorithm.     

A Centralized Balance Clustering Routing Protocol for Wireless Sensor Network

Routing protocol plays a role of great importance in the performance of wireless sensor networks (WSNs). A centralized balance clustering routing protocol based on location is proposed for WSN with random distribution in this paper. In order to keep clustering balanced through the whole lifetime of the network and adapt to the non-uniform distribution of sensor nodes, we design a systemic algorithm for clustering. First, the algorithm determines the cluster number according to condition of the network, and adjusts the hexagonal clustering results to balance the number of nodes of each cluster. Second, it selects cluster heads in each cluster base on the energy and distribution of nodes, and optimizes the clustering results to minimize energy consumption. Finally, it allocates suitable time slots for transmission to avoid collision. Simulation results demonstrate that the proposed protocol can balance the energy consumption and improve the network throughput and lifetime significantly.     

Weighted relay node placement for wireless sensor network connectivity

In wireless sensor networks (WSN), which are composed of unreliable sensor nodes, preserving the connectivity is a serious problem and one of the most effective solutions of this problem is to deploy powerful relay nodes (RN). The location of the RN is an important parameter for the network performance. In this paper, we investigate relay node placement (RNP) problem on a weighted terrain structure to satisfy WSN connectivity. Contrary to the existing studies, instead of minimizing the number of RN, the main objective of weighted RNP is to minimize the total weight of the points on which RN are deployed. In order to solve the weighted RNP problem, a mathematical formulation is proposed to find the optimal solution. However, because of the NP-complete nature of the problem, a polynomial time heuristic algorithm is also developed. Performance results show that the proposed heuristic algorithm can find near-optimal solutions in a reasonable time bound.     

Flower pollination algorithm‐based energy‐efficient stable clustering approach for WSNs

The advances in the size, cost of deployment, and user‐friendly interface of wireless sensor devices have given rise to many wireless sensor network (WSN) applications. WSNs need to use protocols for transmitting data samples from event regions to sink through minimum cost links. Clustering is a commonly used method of data aggregation in which nodes are organized into groups to reduce energy consumption. Nonetheless, cluster head (CH) has to bear an additional load in clustering protocols to organize different activities within the cluster. Proper CH selection and load balancing using efficient routing protocol is therefore a critical aspect for WSN's long‐term operation. In this paper, a threshold‐sensitive energy‐efficient cluster‐based routing protocol based on flower pollination algorithm (FPA) is proposed to extend the network's stability period. Using FPA, multihop communication between CHs and base station is used to achieve optimal link costs for load balancing distant CHs and energy minimization. Analysis and simulation results show that the proposed algorithm significantly outperforms competitive clustering algorithms in terms of energy consumption, stability period, and system lifetime.     

Adaptive quantized target tracking in wireless sensor networks

This paper addresses target tracking in wireless sensor networks (WSN) where the observed system is assumed to evolve according to a probabilistic state space model. We propose to improve the use of the variational filtering (VF) by optimally quantizing the data collected by the sensors. Recently, VF has been proved to be suitable to the communication constraints of WSN. Its efficiency relies on the fact that the online update of the filtering distribution and its compression are executed simultaneously. However, this problem has been used only for binary sensor networks neglecting the transmission energy consumption in a WSN and the information relevance of sensor measurements. Our proposed method is intended to jointly estimate the target position and optimize the quantization level under fixed and variable transmitting power. At each sampling instant, the adaptive method provides not only the estimate of the target position by using the VF but gives also the optimal number of quantization bits per observation. The adaptive quantization is achieved by minimizing the predicted Cramér–Rao bound if the transmitting power is constant for all sensors, and optimizing the power scheduling under distortion constraint if this power is variable. The computation of the predicted Cramér–Rao bound is based on the target position predictive distribution provided by the VF algorithm. The proposed adaptive quantization scheme suggests that the sensors with bad channels or poor observation qualities should decrease their quantization resolutions or simply become inactive in order to save energy.     

移动代理WSN网络中信道Sift MAC协议

介绍了一种采用移动代理的无线传感器(WSN)网络,该网络系统由移动代理节点负责复杂数据处理、接入处理、数据转发传输、路由维护等工作,与一般WSN网络相比具有节能优势。该网络系统MAC层采用S-ALOHA协议,不仅网络吞吐量低而且能耗大,依据网络结构特点提出了采用基于信噪比(SNR)的信道Sift协议。仿真验证该协议大大提高了网络吞吐量和降低了网络系统能耗。     

无线传感器网络模糊逻辑分簇路由协议

在无线传感器网络（Wireless Sensor Network,WSN）中,LEACH协议通过概率模型来选举簇头,由于没有考虑到传感器节点的分布情况和能量剩余等信息,可能会使得部分节点过早死亡.针对这一问题,提出基于模糊逻辑的分簇路由协议（DFLCP）.在预选簇头阶段,根据节点剩余能量等信息利用模糊逻辑计算出节点的竞争半径,使得簇头分布相对均匀;在簇头选举阶段,通过模糊逻辑确定节点成为簇头的概率.仿真结果表明：DFLCP协议可有效控制簇头节点的分布密度和簇的半径,均衡网络负载,延长节点平均生存时间.     

An energy efficient hole repair node scheduling algorithm for WSN

A sensor node in the wireless sensor network has limited energy and it normally cannot be replaced due to the random deployment, so how to prolong the network life time with limited energy while satisfying the coverage quality simultaneously becomes a crucial problem to solve for wireless sensor networks (WSN). In this work, we propose an energy efficient algorithm based on the sentinel scheme to reduce the sleeping node detection density by defining a new deep sleeping state for each sensor node. The average energy consumed by probing neighboring nodes is introduced as a factor to calculate the detection rate. In addition, after some theoretical analysis of the existence of coverage holes in WSN, a triangle coverage repair procedure is defined to repair coverage holes. Simulation results show that our proposed algorithm obtained better performance in terms of the coverage quality and network life time compared with some existing algorithms in the literature.