Multi-hop Communication based optimal clustering in hexagon and voronoi cell structured WSNs

Energy saving is always an important issue as most of the Wireless Sensor Networks (WSNs) work in an unattended geographical environment where human access and monitoring are practically impossible. One of the existing ways of saving energy in WSNs is clustering of sensor nodes. Furthermore, the clustering process can be made more effective by optimizing the number of clusters. Cluster shape, Intra-cluster and Inter cluster topologies are some of the impacting factors for energy conservation in WSNs. In this paper, for the purpose of further saving the energy consumption, we considered a network with multi-hop communication. An analytical expression is developed for finding optimal clusters particularly, when the sensing field is split into hexagonal and voronoi clusters. Besides, the effect of data aggregation ratio, position of base station on the overall energy consumption is analysed through different case studies. The obtained results are compared with the single-hop counterparts. A significant reduction in the energy consumption can be observed from the results. Thus, multi-hop based optimal clustering results in a substantial reduction of energy consumption in WSN.     

Design strategy for optimizing power consumption of sensor node with Min(N,T) policy M/G/1 queuing models

Energy saving is an important issue in wireless sensor networks for majority of sensor nodes equipped with non‐rechargeable batteries. To prolong the lifetime of sensor nodes, most research works have focused on how to tune the duty cycling schemes among nodes to save the communication cost using multifarious wake‐up strategies. To this aim, we propose a novel design strategy for mitigating the average power consumption of sensor node using the Min(N,T) policy M/G/1 queuing theory. The basic point of our approach is that Min(N,T) dyadic policy would mitigate the total average times of medium contention by having both a counter (N) and a timer (T) for the control of triggering on a radio server to transmit queued packets, and then the power consumption of communication can be alleviated. A comprehensive mathematical analysis on the optimal control parameters had been made. Much data analysis and simulations had been conducted to validate the proposed model. In this article, we show how the improvement level on power consumption can be achieved through analytical and simulation results. With little or no extra management cost, the proposed add‐on power‐saving technique can provide a design strategy to optimize relevant system parameters including power consumption and latency delay. Copyright © 2011 John Wiley & Sons, Ltd.     

An energy‐efficient and balanced clustering approach for improving throughput of wireless sensor networks

Maximizing the lifespan of wireless sensor networks is currently drawing a lot of attention in the research community. In order to reduce energy consumption, sensor nodes that are far from the base station avoid sending data directly. As a result, several disjoint clusters are formed, and nodes within a cluster send their data through the cluster head to avoid long transmissions. However, several parameters related to transmission cost need to be considered when selecting a cluster head. While most of the existing research work considers energy and distance as the most stringent parameters to reduce energy consumption, these approaches fail to create a fair and balanced cluster. Consequently, unbalanced clusters are formed, resulting in the degradation of overall performance. In this research work, a cluster head selection algorithm is proposed that covers all parts of the sensing area in a balanced manner, saving a significant amount of energy. Furthermore, a capture effect–based intracluster communication mechanism is proposed that efficiently utilizes the time slot under various traffic conditions. A Näive Bayes classifier is used to adapt the window size dynamically according to the traffic pattern. Finally, a simulation model using OMNeT++ is developed to compare the proposed approach with the pioneer clustering approach, LEACH, and the contemporary LEACH‐MAC protocol in terms of performance. The results of the simulation indicate that the proposed approach improves the overall performance in terms of network lifetime, energy efficiency, and throughput.     

Delay-Constrained Optimal Data Aggregation in Hierarchical Wireless Sensor Networks

A lot of realistic applications with wireless sensor networks adopt hierarchical architecture in which sensor nodes are grouped into clusters, with each cluster relying on a gateway node for local data aggregation and long-distance radio transmission. Compared to normal sensor nodes, the gateway nodes, also called application nodes (ANs), are equipped with relatively powerful transceivers and have more energy. Nevertheless, since an AN is the main gateway for sensor nodes within its clusters, its energy may be depleted more quickly than normal sensor nodes. As such, it is important to find methods to save energy for ANs. This paper presents a Delay-Constrained Optimal Data Aggregation (DeCODA) framework that considers the unique feature of traffic patterns and information processing at ANs for energy saving. Mathematical models and analytical results are provided, and simulation studies are performed to verify the effectiveness of the DeCODA framework.     

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.     

Energy-Efficient Routing Algorithm Based on Unequal Clustering and Connected Graph in Wireless Sensor Networks

Clustering and multi-hop routing algorithms substantially prolong the lifetime of wireless sensor networks (WSNs). However, they also result in the energy hole and network partition problems. In order to balance the load between multiple cluster heads, save the energy consumption of the inter-cluster routing, in this paper, we propose an energy-efficient routing algorithm based on Unequal Clustering Theory and Connected Graph Theory for WSN. The new algorithm optimizes and innovates in two aspects: cluster head election and clusters routing. In cluster head election, we take into consideration the vote-based measure and the transmission power of sensor nodes when to sectionalize these nodes into different unequal clusters. Then we introduce the connected graph theory for inter-cluster data communication in clusters routing. Eventually, a connected graph is constituted by the based station and all cluster heads. Simulation results show that, this new algorithm balances the energy consumption among sensor nodes, relieves the influence of energy-hole problem, improve the link quality, achieves a substantial improvement on reliability and efficiency of data transmission, and significantly prolongs the network lifetime.     

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。     

DUCR: Distributed unequal cluster‐based routing algorithm for heterogeneous wireless sensor networks

Designing energy efficient communication protocols for wireless sensor networks (WSNs) to conserve the sensors' energy is one of the prime concerns. Clustering in WSNs significantly reduces the energy consumption in which the nodes are organized in clusters, each having a cluster head (CH). The CHs collect data from their cluster members and transmit it to the base station via a single or multihop communication. The main issue in such mechanism is how to associate the nodes to CHs and how to route the data of CHs so that the overall load on CHs are balanced. Since the sensor nodes operate autonomously, the methods designed for WSNs should be of distributed nature, i.e., each node should run it using its local information only. Considering these issues, we propose a distributed multiobjective‐based clustering method to assign a sensor node to appropriate CH so that the load is balanced. We also propose an energy‐efficient routing algorithm to balance the relay load among the CHs. In case any CH dies, we propose a recovery strategy for its cluster members. All our proposed methods are completely distributed in nature. Simulation results demonstrate the efficiency of the proposed algorithm in terms of energy consumption and hence prolonging the network lifetime. We compare the performance of the proposed algorithm with some existing algorithms in terms of number of alive nodes, network lifetime, energy efficiency, and energy population.     

Performance Analysis of IEEE 802.15.4 MAC Protocol with ACK Frame Transmission

A common way of achieving reliable data transmission in wireless sensor network applications is by using a retransmission mechanism with medium access control (MAC) level acknowledgements. The IEEE 802.15.4 standard, which is widely acknowledged as the state-of-the-art PHY/MAC standard for wireless sensor networks, supports MAC-level acknowledgements and retransmissions. In this paper, based on a three-dimensional discrete-time Markov chain, we propose a new analytical model to analyse the performance of the IEEE 802.15.4 MAC protocol with retransmission and MAC level acknowledgements under unsaturated traffic conditions. Further, we present a simplified version of the proposed analytical model with some approximations. Using the proposed analytical models, we evaluate the network performance in terms of the aggregate channel throughput, average power consumption of a node, frame discard ratio, and frame delivery ratio. The analytical results are substantiated through ns?2 simulations. The effects of the frame arrival rate, number of nodes, frame length and various MAC parameters, on the performance of the network are discussed. The results of both analytical models are compared and it is shown that the simplified model provides an acceptable accuracy with less computational complexity.     

A Green Clustering Protocol for Mobile Sensor Network Using Particle Swarm Optimization

Energy consumption of sensor nodes is one of the crucial issues in prolonging the lifetime of wireless sensor networks. One of the methods that can improve the utilization of sensor nodes batteries is the clustering method. In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. We define a new fitness function that can optimize the energy consumption of the whole network and minimize the relative distance between cluster heads and their respective member nodes. We also take into account the mobility factor when defining the cluster membership, so that the sensor nodes can join the cluster that has the similar mobility pattern. The performance of the proposed protocol is compared with well-known clustering protocols developed for wireless sensor networks such as LEACH (low-energy adaptive clustering hierarchy) and protocols designed for sensor networks with mobile nodes called CM-IR (clustering mobility-invalid round). In addition, we also modify the improved version of LEACH called MLEACH-C, so that it is applicable to the mobile sensor nodes environment. Simulation results demonstrate that the proposed protocol using PSO algorithm can improve the energy consumption of the network, achieve better network lifetime, and increase the data delivered at the base station.     

抵抗Sybil攻击的无线传感网中网络分布式密钥管理方案

Wireless sensor network nodes (WSN nodes) have limited computing power, storage capacity, communication capabilities and energy and WSN nodes are easy to be paralyzed by Sybil attack. In order to prevent Sybil attacks, a new key distribution scheme for wireless sensor networks is presented. In this scheme, the key information and node ID are associated, and then the attacker is difficult to forge identity ID and the key information corresponding to ID can not be forged. This scheme can use low-power to resist the Sybil attack and give full play to the resource advantages of the cluster head. The computing, storage and communication is mainly undertaken by the cluster head overhead to achieve the lowest energy consumption and resist against nodes capture attack. Theoretical analysis and experimental results show that compared with the traditional scheme presented in Ref. [14], the capture rate of general nodes of cluster reduces 40% , and the capture rate of cluster heads reduces 50% . So the scheme presented in this paper can improve resilience against nodes capture attack and reduce node power consumption.     

A new load balancing and data collection algorithm for energy saving in wireless sensor networks

Data gathering is a major function of many applications in wireless sensor networks. The most important issue in designing a data gathering algorithm is how to save energy of sensor nodes while meeting the requirements of special applications or users. Wireless sensor networks are characterized by centralized data gathering, multi-hop communication and many to one traffic pattern. These three characteristics can lead to severe packet collision, network congestion and packet loss, and even result in hot-spots of energy consumption thus causing premature death of sensor nodes and entire network. In this paper, we propose a load balance data gathering algorithm that classifies sensor nodes into different layers according to their distance to sink node and furthermore, divides the sense zone into several clusters. Routing trees are established between sensor node and sink depending on the energy metric and communication cost. For saving energy consumption, the target of data aggregation scheme is adopted as well. Analysis and simulation results show that the algorithm we proposed provides more uniform energy consumption among sensor nodes and can prolong the lifetime of sensor networks.     

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.     

Dynamic and adaptive detection method for flooding in wireless sensor networks

In recent years, wireless sensor networks (WSNs) have attracted an increasing attention in several fields. However, WSNs must be treated with significant challenges in their design due to their special characteristics such as limited energy, processing power, and data storage that make the energy consumption saving a real challenge. Also, regarding their distributed deployment in open radio frequency and lack of physical security, these networks are vulnerable and exposed to several attacks: passive eavesdropping, active attacks, and identity theft. In this paper, we propose a new method called accordion method to detect and apprehend denial of service attacks in WSNs. This approach is a dynamic and an adaptive method based on using clustering method which allows electing control nodes that analyze the traffic inside a cluster and send warnings to the cluster head whenever an abnormal behavior is suspected or detected. The proposed method relies on the analysis of the evolution of the threshold messages (alerts) sent in the cluster. The proposed method has been evaluated, and the obtained numerical results show its benefit compared with other detection methods.     

Relay characteristic impact on energy consumption in heterogeneous sensor network

Indoor heterogeneous wireless sensor networks are considered in this paper. We analyze the power consumption for multihop communications with non-regenerative relays. Since sensor nodes are battery operated, energy consumption is a crucial issue. We determine the optimal relay gains and transmitted power that minimize the dissipated power for a given quality of service in a narrow band fading channel. Our work includes two main contributions: firstly, we study the energy consumption taking into account hardware aspects, especially the relays’ efficiency. In an AWGN channel, carefully analyzing the energy gain as a function of the position, we show that relay characteristics have an important impact on the multihop link consumption budget. We then use a Rice channel model based on simulations and further study the hardware impact on energy saving.     

Time-variant balanced routing strategy for underwater wireless sensor networks

In the past decade, researchers’ interest in Underwater Wireless Sensors Networks has rapidly increased. There are several challenges facing the lifetime of UWSNs due to the harsh characteristics of the underwater environment. Energy efficiency is one of the major challenges in UWSNs due to the limited battery budget of the sensor nodes. In this paper, we aim at tackling the energy sink-hole problem that especially hits nodes close to the sink when they run out of battery power before other sensors in the network. We prove that we can evenly distribute the transmission load among mobile sensor nodes by letting sensor nodes adjust their transmission ranges. In this paper, we suppose that sensor nodes may adjust their transmission power up to three levels. Consequently, we strive for deriving the optimal load weight for each possible transmission power level that leads to fair energy consumption among all underwater sensors while taking into account the underwater sensors mobility. Performance results show that energy sink-hole problem is overcame and hence the network lifetime is maximized.

     

Increasing network lifetime by balancing node energy consumption in heterogeneous sensor networks

Sensor nodes are powered by battery and have severe energy constraints. The typical many‐to‐one traffic pattern causes uneven energy consumption among sensor nodes, that is, sensor nodes near the base station or a cluster head have much heavier traffic burden and run out of power much faster than other nodes. The uneven node energy dissipation dramatically reduces sensor network lifetime. In a previous work, we presented the chessboard clustering scheme to increase network lifetime by balancing node energy consumption. To achieve good performance and scalability, we propose to form a heterogeneous sensor network by deploying a few powerful high‐end sensors in addition to a large number of low‐end sensors. In this paper, we design an efficient routing protocol based on the chessboard clustering scheme, and we compute the minimum node density for satisfying a given lifetime constraint. Simulation experiments show that the chessboard clustering‐based routing protocol balances node energy consumption very well and dramatically increases network lifetime, and it performs much better than two other clustering‐based schemes. Copyright © 2006 John Wiley & Sons, Ltd.     

一种新的无线传感器节点的连续参数功耗模型

为了估计传感器节点的能量开销,需要对节点功耗进行合理、准确的建模。然而,现有的节点功耗模型都没有很好地满足准确性这一要求。该文提出了一种新的基于连续参数功耗状态机的节点功耗模型,可用于任意类型传感器节点的功耗建模。该模型能够根据电源电压和工作频率等参数的变化对节点功耗进行更为准确的预测。通过对传感器节点中常用的ATmega128(L)微处理器进行实际建模并与独立的实测结果进行比较,可以发现该模型对活动状态功耗的预测误差小于1%,对空闲状态功耗的预测误差小于9.7%。该模型可用于替换传感器网络仿真工具的现有模型,为传感器节点的能量开销提供更为准确的预测结果。     

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.     

Novel Data Fusion Algorithm Based on Event-Driven and Dempster–Shafer Evidence Theory

When a new event occurs, the nodes in the neighborhood of the event sense and then send many packets to the sink node. Such circumstances need their networks to be simultaneously reliable and event-driven. Moreover, it should be remove redundant packets in order to lower the average energy consumption. A data fusion algorithm based on event-driven and Dempster–Shafer evidence theory is proposed in this paper to reduce data packet quantities and reserve energy for wireless sensor networks upon detecting abnormal data. Sampling data is compared against the set threshold, and the nodes enter the relevant state only when there are abnormal datum; at this point, cluster formation begins. All cluster members incorporate a local forwarding history to decide whether to forward or to drop recent sampling data. Dempster–Shafer evidence theory is exploited to process the data. The basic belief assignment function, with which the output of each cluster member is characterized as a weighted-evidence, is constructed. Then, the synthetic rule is subsequently applied to each cluster head to fuse the evidences gathered from cluster member nodes to obtain the final fusion result. Simulation results demonstrate that the proposed algorithm can effectively ensure fusion result accuracy while saving energy.