An efficient cluster-based communication protocol for wireless sensor networks

A wireless sensor network is a network of large numbers of sensor nodes, where each sensor node is a tiny device that is equipped with a processing, sensing subsystem and a communication subsystem. The critical issue in wireless sensor networks is how to gather sensed data in an energy-efficient way, so that the network lifetime can be extended. The design of protocols for such wireless sensor networks has to be energy-aware in order to extend the lifetime of the network because it is difficult to recharge sensor node batteries. We propose a protocol to form clusters, select cluster heads, select cluster senders and determine appropriate routings in order to reduce overall energy consumption and enhance the network lifetime. Our clustering protocol is called an Efficient Cluster-Based Communication Protocol (ECOMP) for Wireless Sensor Networks. In ECOMP, each sensor node consumes a small amount of transmitting energy in order to reach the neighbour sensor node in the bidirectional ring, and the cluster heads do not need to receive any sensed data from member nodes. The simulation results show that ECOMP significantly minimises energy consumption of sensor nodes and extends the network lifetime, compared with existing clustering protocol.     

多簇无线传感网的优化生存时间近邻功率控制算法

针对非均匀分布的无线传感网的生存时间问题,提出多簇无线传感网的优化生存时间近邻功率控制(NPCAOL_MC)算法。该算法采用K-means算法确定网络的簇个数和对应每个簇的节点,利用近邻算法评估每个簇的节点密度,确定簇的最优通信距离。结合Friss自由空间模型计算当前簇的最优发送功率。Sink节点广播通知其他节点,如果是同一簇内的节点相互通信,则采用簇最优功率发送数据,否则采用默认最大发送功率发送数据。仿真结果表明,利用NPCAOL_MC算法可以分析整个网络节点的位置信息,采用簇最优发送功率发送数据,从而提高生存时间,并使能耗经济有效。在密度分布不均的无线传感网中,NPCAOL_MC比采用固定发送功率的Ratio_w算法更优。     

基于移动Agent和WSN的突发事件场景数据收集算法研究

该文针对无线传感器网络应用于突发事件监测场景的能量消耗和网络延迟问题,提出了基于移动Agent的无线传感器网络簇式数据收集算法.动态成簇过程基于事件严重程度,并由其决定簇的生命周期和覆盖范围.Sink和簇头之间形成以Sink节点为簇头的虚拟簇.移动Agent迁移路径规划过程中下一跳节点的选取基于节点剩余能量、路径损耗及受刺激强度.移动Agent通过节点遍历的方式完成对所有簇内成员节点信息的收集.仿真结果表明,相对于C/S数据收集模型,基于移动Agent的模型具有更好的节能效果,并能一定程度地减少网络延迟,尤其适用于大规模无线传感器网络应用.     

A new algorithm for cluster head selection in LEACH protocol for wireless sensor networks

In wireless sensor network, a large number of sensor nodes are distributed to cover a certain area. Sensor node is little in size with restricted processing power, memory, and limited battery life. Because of restricted battery power, wireless sensor network needs to broaden the system lifetime by reducing the energy consumption. A clustering‐based protocols adapt the use of energy by giving a balance to all nodes to become a cluster head. In this paper, we concentrate on a recent hierarchical routing protocols, which are depending on LEACH protocol to enhance its performance and increase the lifetime of wireless sensor network. So our enhanced protocol called Node Ranked–LEACH is proposed. Our proposed protocol improves the total network lifetime based on node rank algorithm. Node rank algorithm depends on both path cost and number of links between nodes to select the cluster head of each cluster. This enhancement reflects the real weight of specific node to success and can be represented as a cluster head. The proposed algorithm overcomes the random process selection, which leads to unexpected fail for some cluster heads in other LEACH versions, and it gives a good performance in the network lifetime and energy consumption comparing with previous version of LEACH protocols.     

自适应多传感器网络覆盖节点部署技术研究

基于多传感器节点圆形数据采集区域相切形成一系列相似三角形在几何原理上的有效性和可行性,提出了一种基于相似三角形的网络节点协同控制节点部署技术.首先把数据采集区域分割为多个几何相似的三角形,保证对监测区域无缝覆盖的同时聚集最少的传感器节点;其次在簇首节点与分簇区域内的传感器节点之间构建高效拓扑;然后建立一种自适应节点失效重建网络拓扑控制机制.仿真实验表明,该节点部署算法可以对监测区域实现完全无缝覆盖,保持网络整体性能高效以及数据传输的可靠性..     

Low-Energy Adaptive Unequal Clustering Protocol Using Fuzzy c-Means in Wireless Sensor Networks

Clustering technique in wireless sensor networks incorporate proper utilization of the limited energy resources of the deployed sensor nodes with the highest residual energy that can be used to gather data and send the information. However, the problem of unbalanced energy consumption exists in a particular cluster node in the network. Some more powerful nodes act as cluster head to control sensor network operation when the network is organized into heterogeneous clusters. It is important to assume that energy consumption of these cluster head nodes is balanced. Often the network is organized into clusters of equal size where cluster head nodes bear unequal loads. Instead in this paper, we proposed a new protocol low-energy adaptive unequal clustering protocol using Fuzzy c-means in wireless sensor networks (LAUCF), an unequal clustering size model for the organization of network based on Fuzzy c-means (FCM) clustering algorithm, which can lead to more uniform energy dissipation among the cluster head nodes, thus increasing network lifetime. A heuristic comparison between our proposed protocol LAUCF and other different energy-aware protocol including low energy adaptive clustering hierarchy (LEACH) has been carried out. Simulation result shows that our proposed heterogeneous clustering approach using FCM protocol is more effective in prolonging the network lifetime compared with LEACH and other protocol for long run.     

基于无线信号不规则性的无线传感网层次型拓扑控制算法

构建层次型拓扑结构是延长网络生存时间的有效方法。该文将拓扑构建过程分为由簇成员组成的感知层和由簇头组成的平面数据转发层,建立了基于无线信号不规则性的网络能耗模型以及节点成簇稳定性模型,提出了基于无线信号不规则性的层次型拓扑控制(WSIBTC)算法。WSIBTC算法根据节点平均有效传输距离将监测区域划分为多个子区域,由成簇稳定性和节点在簇中的位置决定最终簇头,簇头间形成平面拓扑结构,延长网络生存时间。分析和仿真结果表明由WSIBTC算法得到的网络拓扑大幅度地提升了网络生存时间。     

Two-phase data traffic optimization of wireless sensor networks for prolonging network lifetime

Wireless network sensing and control systems are becoming increasingly important in many application domains due to advent of nanotechnology. The size of a wireless sensor network can easily reach hundreds or even thousands of sensor nodes. Since these types of networks usually have limited battery resources, power consumption optimization for prolonging system lifetime of such networks have received a great attention by the researchers in this field in recent years. In this paper, a centralized approach for clustering and data transmission mechanism is proposed that optimizes the power consumption and hence lifetime of the network. The mechanism is comprised of two phases. In the first phase, a mechanism based on a centralized cluster head selection that utilizes information such as nodes residual energies and their locations in the network is proposed in order to select the most appropriate candidates as cluster heads. In the second phase, the concept of a “window size” is introduced where minimization of the number of cluster head changes of a node and consequently maximization of the network lifetime is considered. Simulation results validate that the proposed mechanism does effectively reduce data traffic and therefore increases network lifetime.     

Sleep scheduling with expected common coverage in wireless sensor networks

Sleep scheduling, which is putting some sensor nodes into sleep mode without harming network functionality, is a common method to reduce energy consumption in dense wireless sensor networks. This paper proposes a distributed and energy efficient sleep scheduling and routing scheme that can be used to extend the lifetime of a sensor network while maintaining a user defined coverage and connectivity. The scheme can activate and deactivate the three basic units of a sensor node (sensing, processing, and communication units) independently. The paper also provides a probabilistic method to estimate how much the sensing area of a node is covered by other active nodes in its neighborhood. The method is utilized by the proposed scheduling and routing scheme to reduce the control message overhead while deciding the next modes (full-active, semi-active, inactive/sleeping) of sensor nodes. We evaluated our estimation method and scheduling scheme via simulation experiments and compared our scheme also with another scheme. The results validate our probabilistic method for coverage estimation and show that our sleep scheduling and routing scheme can significantly increase the network lifetime while keeping the message complexity low and preserving both connectivity and coverage.     

Hybrid Chameleon Search and Remora Optimization Algorithm-based Dynamic Heterogeneous load balancing clustering protocol for extending the lifetime of wireless sensor networks

Clustering is an indispensable strategy that helps towards the extension of lifetime of each sensor nodes with energy stability in wireless sensor networks (WSNs). This clustering process aids in sustaining energy efficiency and extended network lifetime in sensitive and critical real-life applications that include landslide monitoring and military applications. The dynamic characteristics of WSNs and several cluster configurations introduce challenge in the process of searching an ideal network structure, a herculean challenge. In this paper, Hybrid Chameleon Search and Remora Optimization Algorithm-based Dynamic Clustering Method (HCSROA) is proposed for dynamic optimization of wireless sensor node clusters. It utilized the global searching process of Chameleon Search Algorithm for selecting potential cluster head (CH) selection with balanced trade-off between intensification and extensification. It determines an ideal dynamic network structure based on factors that include quantity of nodes in the neighborhood, distance to sink, predictable energy utilization rate, and residual energy into account during the formulation of fitness function. It specifically achieved sink node mobility through the integration of the local searching capability of Improved Remora Optimization Algorithm for determining the optimal points of deployment over which the packets can be forwarded from the CH of the cluster to the sink node. This proposed HCSROA scheme compared in contrast to standard methods is identified to greatly prolong network lifetime by 29.21% and maintain energy stability by 25.64% in contrast to baseline protocols taken for investigation.     

无线传感网络中基于蚁群的路由算法

In the wireless sensor networks, high efficient data routing for the limited energy resource networks is an important issue. By introducing Ant-colony algorithm, this paper proposes the wireless sensor network routing algorithm based on LEACH. During the construction of sensor network clusters, to avoid the node premature death because of the energy consumption, only the nodes whose residual energy is higher than the average energy can be chosen as the cluster heads. The method of repeated division is used to divide the clusters in sensor networks so that the numbers of the nodes in each cluster are balanced. The basic thought of ant-colony algorithm is adopted to realize the data routing between the cluster heads and sink nodes, and the maintenance of routing. The analysis and simulation showed that the proposed routing protocol not only can reduce the energy consumption, balance the energy consumption between nodes, but also prolong the network lifetime.     

一种基于冗余度的无线传感器网络节能策略

在无线传感器网络中,传感节点由于采用电池供电,因此寿命有限。如何有效节省传感器节点的能量,延长网络的使用寿命,一直是广泛研究的焦点。文章提出一种适用于高冗余度布置的无线传感器网络结构中,节省传感器节点能量消耗的方法-接续调度法。该方法通过协调点对小区域内节点的调度,使区域内节点依次分时段工作。通过这种接续调度,避免了节点间的冲突和串扰,达到延长整体网络寿命的效果。     

运动检测与定位的热释电红外传感新方法

针对人体目标运动检测与定位,提出了一种新型的热释电红外感知方法,采用递阶的体系结构对菲涅尔透镜的视场(FoV)进行空间调制。首先,对单个传感器节点上的多个热释电红外(PIR)传感器及其菲涅尔透镜的FoV进行环形调制编码,实现单自由度的FoV细分;然后,利用相邻的3个传感器节点相互协作定位。实验表明,该方法具有计算简单、鲁棒性好等优点。     

有效降低无线网络节点能量的LEACH新算法

LEACH是一种低功耗自适应按簇分层路由算法.为了降低节点能耗,在LEACH协议的基础上提出了在选举簇头时,改变阈值T(n)的大小以降低节点成为簇头的概率,从而节省网络因分簇而消耗的能量.同时又提出了一种基于节点剩余能量的二层簇头的算法,该算法能使节点减少将冗余信息传输到基站,从而达到降低节点消耗能量的目的.通过实验仿真,表明这些方法能使网络节点能量的消耗减少,达到了延长网络生命周期的目的.     

A New Method to Find a High Reliable Route in IoT by Using Reinforcement Learning and Fuzzy Logic

Recently, Internet is moving quickly toward the interaction of objects, computing devices, sensors, and which are usually indicated as the Internet of things (IoT). The main monitoring infrastructure of IoT systems main monitoring infrastructure of IoT systems is wireless sensor networks. A wireless sensor network is composed of a large number of sensor nodes. Each sensor node has sensing, computing, and wireless communication capability. The sensor nodes send the data to a sink or a base station by using wireless transmission techniques However, sensor network systems require suitable routing structure to optimizing the lifetime. For providing reasonable energy consumption and optimizing the lifetime of WSNs, novel, efficient and economical schemes should be developed. In this paper, for enhancing network lifetime, a novel energy-efficient mechanism is proposed based on fuzzy logic and reinforcement learning. The fuzzy logic system and reinforcement learning is based on the remained energies of the nodes on the routes, the available bandwidth and the distance to the sink. This study also compares the performance of the proposed method with the fuzzy logic method and IEEE 802.15.4 protocol. The simulations of the proposed method which were carried out by OPNET (Optimum Network performance) indicated that the proposed method performed better than other protocols such as fuzzy logic and IEEE802.15.4 in terms of power consumption and network lifetime.

     

Mobile Malicious Node Detection Using Mobile Agent in Cluster-Based Wireless Sensor Networks

Many application domains require that sensor node to be deployed in harsh or hostile environments, such as active volcano area tracking endangered species, etc. making these nodes more prone to failures. The most challenging problem is monitoring the illegal movement within the sensor networks. Attacker prefers mobile malicious node because by making the diversity of path intruder maximize his impact. The emerging technology of sensor network expected Intrusion detection technique for a dynamic environment. In this paper, a defective mechanism based on three-step negotiation is performed for identifying the mobile malicious node using the mobile agent. In many approaches, the multi-mobile agents are used to collect the data from all the sensor nodes after verification. But it is inefficient to verify all the sensor nodes (SNs) in the network, because of mobility, energy consumption, and high delay. In the proposed system this can be solved by grouping sensor nodes into clusters and a single mobile agent performs verification only with all the cluster heads instead of verifying all the SNs. The simulation result shows the proposed system shows a better result than the existing system.

     

Fuzzy-based unequal clustering protocol for underwater wireless sensor networks

Underwater wireless sensor network (UWSN) is a network made up of underwater sensor nodes, anchor nodes, surface sink nodes or surface stations, and the offshore sink node. Energy consumption, limited bandwidth, propagation delay, high bit error rate, stability, scalability, and network lifetime are the key challenges related to underwater wireless sensor networks. Clustering is used to mitigate these issues. In this work, fuzzy-based unequal clustering protocol (FBUCP) is proposed that does cluster head selection using fuzzy logic as it can deal with the uncertainties of the harsh atmosphere in the water. Cluster heads are selected using linguistic input variables like distance to the surface sink node, residual energy, and node density and linguistic output variables like cluster head advertisement radius and rank of underwater sensor nodes. Unequal clustering is used to have an unequal size of the cluster which deals with the problem of excess energy usage of the underwater sensor nodes near the surface sink node, called the hot spot problem. Data gathered by the cluster heads are transmitted to the surface sink node using neighboring cluster heads in the direction of the surface sink node. Dijkstra's shortest path algorithm is used for multi-hop and inter-cluster routing. The FBUCP is compared with the LEACH-UWSN, CDBR, and FBCA protocols for underwater wireless sensor networks. A comparative analysis shows that in first node dies, the FBUCP is up to 80% better, has 64.86% more network lifetime, has 91% more number of packets transmitted to the surface sink node, and is up to 58.81% more energy efficient than LEACH-UWSN, CDBR, and FBCA.     

Joint Routing and Resource Allocation for Cluster Based Isolated Nodes in Cognitive Radio Wireless Sensor Networks

Clustering is an effective way to increase network lifetime but it leads to formation of isolated nodes in the wireless sensor network. These isolated sensor nodes forward data directly to sink and consume more energy which significantly reduces the network lifetime. In this article, we present how to maximize the network lifetime through joint routing and resource allocation with isolated nodes technique (JR-IN) between cluster head and isolated nodes in a cognitive based wireless sensor networks. In JR-IN technique the network area is divided into different layers and cluster size is formulated in each layer such that the size of the cluster remains unequal when it moves towards sink. Hence the cluster size is lager in the outermost layer compared to the cluster size in the inner most layer. To avoid inter cluster collision, we proposed different fixed channel to all the cluster heads in the network. For the intra cluster communication, the cluster member (sensor nodes) will lease the spectrum from the cluster head and forward data to their respective cluster head using TDMA technique. The periodical data gathering of cluster heads and forwarding the data to one hop cluster head may tend to lose energy faster and dies out quickly. We also propose in the JR-IN technique, the isolated nodes in the layer will take charge as a cluster head node and utilizes the resource allocated to the respective cluster head and forward the data to next hop cluster head. Simulation result shows that JR-IN outperforms the existing techniques, maximizes network lifetime and throughput and reduces the end to end delay.

     

An unequal cluster-based routing scheme for multi-level heterogeneous wireless sensor networks

In wireless sensor networks (WSNs), clustering can significantly reduce energy dissipation of nodes, and also increase communication load of cluster heads. When multi-hop communication model is adopted in clustering, “energy hole” problem may occur due to unbalanced energy consumption among cluster heads. Recently, many multi-hop clustering protocols have been proposed to solve this problem. And the main way is using unequal clustering to control the size of clusters. However, many of these protocols are about homogeneous networks and few are about heterogeneous networks. In this paper, we present an unequal cluster-based routing scheme for WSNs with multi-level energy heterogeneity called UCR-H. The sensor field is partitioned into a number of equal-size rectangular units. We first calculate the number of clusters in each unit by balancing energy consumption among the cluster heads in different units. And then we find the optimal number of units by minimizing the total energy consumption of inter-cluster forwarding. Finally, the size of clusters in each unit is elaborately designed based on node’s energy level and the number of clusters in this unit. And a threshold is also designed to avoid excessive punishment to the nodes with higher energy level. Simulation results show that our scheme effectively mitigates the “energy hole” problem and achieves an obvious improvement on the network lifetime.     

Energy-aware redundancy-aware clustering in wireless sensor networks using Spined Loach Searching Optimization

Wireless sensor networks play dominant role in data communication in many engineering applications and faces lot of challenges in its implementation. Energy conservation is also significantly required in these systems as the sensor nodes are battery operated. Hence, the energy efficient-based technique needs to be implemented in data transmission. The most widely used methods are clustering-based data transmission and energy efficient routing detection. In clustering, the proper selection of cluster head (CH) node is important to ensure energy balancing. The CH node should have more residual energy as it does many transmissions in the network. Moreover, the location of CH node should be nearer to all member nodes in the cluster. The clustering process must also perform the job of avoiding unnecessary transmissions. By considering these factors, the CH node can be optimally selected using Spined Loach Searching Optimization algorithm. The food searching behavior and environmental suitability for spiny loach fish living are deliberated to develop this bio-inspired algorithm. In addition, the redundant transmissions inside the clusters can be reduced by employing a new technique called Least Difference Threshold Based Similarity Grouping. This work improves energy efficiency comparing with the conventional low energy adaptive clustering hierarchy protocol, and it is evaluated by setting the network in simulation environment. The network lifetime is increased; energy consumption, delay of transmission and the message cost are reduced.