Adaptive directed evolved NSGA2 based node placement optimization for wireless sensor networks

Wireless sensor network (WSN) is a wireless network composed of a large number of static or mobile sensors in a self-organizing and multi-hop manner. In WSN research, node placement is one of the basic problems. In view of the coverage, energy consumption and the distance of node movement, an improved multi-objective optimization algorithm based on NSGA2 is proposed in this paper. The proposed algorithm is used to optimize the node placement of WSN. The proposed algorithm can optimize both the node coverage and lifetime of WSN while also considering the moving distance of nodes, so as to optimize the node placement of WSN. The experiments show that the improved NSGA2 has improvements in both searching performance and convergence speed when solving the node placement problem.

     

基于ERPMT改进启发式方法的WSN寿命最大化算法

针对传感器节点的电池容量限制导致无线传感网络寿命低的问题,基于容量最大化(CMAX)、线上最大化寿命(OML)两种启发式方法以及高效路由能量管理技术(ERPMT),提出了基于ERPMT改进启发式方法的无线传感网络寿命最大化算法。首先,通过启发式方法初始化每个传感器节点,将节点能量划分为传感器节点起源数据和其它节点数据延迟;然后利用加入的一种优先度量延迟一跳节点的能量消耗;最后,根据路径平均能量为每个路由分配一个优先级,并通过ERPMT实现最终的无线传感网络优化。针对不同分布类型网络寿命的实验验证了本文算法的有效性及可靠性,实验结果表明,相比较为先进的启发式方法CMAX及OML,本文算法明显增大了无线传感网络的覆盖范围,并且大大地延长了网络的寿命。     

A game theoretic approach to balancing energy consumption in heterogeneous wireless sensor networks

Energy balancing is an effective technique in enhancing the lifetime of a wireless sensor network (WSN). Specifically, balancing the energy consumption among sensors can prevent losing some critical sensors prematurely due to energy exhaustion so that the WSN's coverage can be maintained. However, the heterogeneous hostile operating conditions—different transmission distances, varying fading environments, and distinct residual energy levels—have made energy balancing a highly challenging task. A key issue in energy balancing is to maintain a certain level of energy fairness in the whole WSN. To achieve energy fairness, the transmission load should be allocated among sensors such that, regardless of a sensor's working conditions, no sensor node should be unfairly overburdened. In this paper, we model the transmission load assignment in WSN as a game. With our novel utility function that can capture realistic sensors’ behaviors, we have derived the Nash equilibrium (NE) of the energy balancing game. Most importantly, under the NE, while each sensor can maximize its own payoff, the global objective of energy balancing can also be achieved. Moreover, by incorporating a penalty mechanism, the delivery rate and delay constraints imposed by the WSN application can be satisfied. Through extensive simulations, our game theoretic approach is shown to be effective in that adequate energy balancing is achieved and, consequently, network lifetime is significantly enhanced. Copyright © 2012 John Wiley & Sons, Ltd.     

Optimized mobile sink based grid coverage-aware sensor deployment and link quality based routing in wireless sensor networks

Mobile sink (MS) has been used in wireless sensor networks (WSN) to increase the network lifetime by changing the location over time. The major quality of service given by WSN is coverage energy consumption (EC) and network lifetime. There are many methods implemented for enhance the coverage hole restoration and reduce the EC. We propose a novel MSCOLER (MS based Coverage Optimization and Link-stability Estimation Routing) protocol for Optimal Coverage restoration and Link stability Estimation. An optimization algorithm is used to optimize the coverage hole and move the redundant node besides the hole. During the routing process, link quality based routing is used to discover the relay nodes with the estimation of link stability to enhance the entire network lifetime and practically make the perfect transmission distance for energy saving. Experimental results demonstrate that proposed protocol can solve the coverage restoration problem, decrease the EC and reduce the network lifetime. The performance is evaluated regarding Average of residual energy (ARE), Receiving packets ratio (RPR), Moving energy consumption (MEC), Network lifetime (NL), Percentage of coverage (%C) and Average Energy Consumption (AEC).     

A Novel QoS Based Secure Unequal Clustering Protocol with Intrusion Detection System in Wireless Sensor Networks

Wireless sensor network (WSN) becomes a hot research topic owing to its application in different fields. Minimizing the energy dissipation, maximizing the network lifetime, and security are considered as the major quality of service (QoS) factors in the design of WSN. Clustering is a commonly employed energy-efficient technique; however, it results in a hot spot issue. This paper develops a novel secure unequal clustering protocol with intrusion detection technique to achieve QoS parameters like energy, lifetime, and security. Initially, the proposed model uses adaptive neuro fuzzy based clustering technique to select the tentative cluster heads (TCHs) using three input parameters such as residual energy, distance to base station (BS), and distance to neighbors. Then, the TCHs compete for final CHs and the optimal CHs are selected using the deer hunting optimization (DHO) algorithm. The DHO based clustering technique derives a fitness function using residual energy, distance to BS, node degree, node centrality, and link quality. To further improve the performance of the proposed method, the cluster maintenance phase is utilized for load balancing. Finally, to achieve security in cluster based WSN, an effective intrusion detection system using a deep belief network is executed on the CHs to identify the presence of intruders in the network. An extensive set of experiments were performed to ensure the superior performance of the proposed method interms of energy efficiency, network lifetime, packet delivery ratio, average delay, and intrusion detection rate.

     

A Novel Sensor Node Deployment using Low Discrepancy Sequences for WSN

The foremost challenge in designing Wireless Sensor Networks (WSNs) is careful node placement. Sensor Node placement is a one of the powerful optimization technique for accomplishing the anticipated goals. This paper focuses on categories of node deployment in WSN. The paper highlights various problems and identifies the different objectives in sensor node deployment. The paper proposes a novel node deployment strategy based on Quasi- random method of low-discrepancy sequences to increase the lifetime and the coverage of the network. The aim of the paper is to study how the node deployment affects the different QoS parameters such as packet delivery ratio, average energy consumption, delay, etc. with various multi-objective routing algorithms WSN. To validate the proposal simulation, results are presented in this paper. The paper concludes with the future outlook.     

Energy-Aware Healthcare System for Wireless Body Region Networks in IoT Environment Using the Whale Optimization Algorithm

Wireless Sensor Network (WSN) is one of the most significant technologies that typically involves of a large number of wireless sensor nodes with sensing, communications and computation capabilities. The sustained operation of WSN is achieved through the efficient consumption of node energy. The WSN is used to many applications especially military, science and medical. The WSN performance may be affect some issues such as load balancing, security and reduce energy consumption of the nodes. These issues must be reduced to enhance performance of the WSN structure in different applications. Henceforth, in this paper, Hybrid Emperor Penguin Optimization (EPO) is developed to solve load balancing, security enhancement and reduce energy consumption in WSN. The hybrid EPO is combined with Atom Search Optimization (ASO) algorithm, it is used to improve the updating function of the EPO algorithm. Three major objective functions can be considered towards improve the performance of WSN like load balancing, security enhancement in addition energy consumption reduction. The load balancing can be achieved by optimal clustering scheme which attained applying proposed hybrid EPO. The security also enhanced in WSN with the help of hybrid EPO by computing security measures. Similarly, energy consumption of WSN is achieved optimal routing scheme by hybrid EPO algorithm. The proposed methodology is developed to manage three objectives which is a major advantage. The projected technique can be implemented by NS2 simulator for validation process. The projected technology is contrasted with the conventional methods such as EPO and ASO respectively. The projected technique is evaluated in terms of delivery ratio, network lifetime, overhead, energy consumption, throughput, drop and delay.

     

Coverage and Lifetime Optimization of Wireless Sensor Networks with Gaussian Distribution

A wireless sensor network (WSN) has to maintain a desirable sensing coverage and periodically report sensed data to the administrative center (i.e., base station) and the reporting period may range from months to years. Coverage and lifetime are two paramount problems in a WSN due to constraint of associated battery power. All previous theoretical analysis on the coverage and lifetime is primarily focused on the random uniform distribution of sensors or some specific network scenarios (e.g., a controllable WSN). In this paper, we provide an analytical framework for the coverage and lifetime of a WSN that follows a two-dimensional Gaussian distribution. We also study the coverage and lifetime when the dimensions of Gaussian dispersion (i.e., x, y) admit different Gaussian parameters (i.e., standard deviation, $sigma_x neqsigma_y$). We identify intrinsic properties of coverage/lifetime in terms of Gaussian distribution parameters, which is a fundamental issue in designing a WSN. Following the results obtained, we further determine the sensor deployment strategies for a WSN that could satisfy a predefined coverage and lifetime. Two deployment algorithms are developed based on using our analytical models and are shown to effectively increase the WSN lifetime.     

Cluster-Head Restricted Energy Efficient Protocol (CREEP) for Routing in Heterogeneous Wireless Sensor Networks

A magnanimous number of collaborative sensor nodes make up a Wireless Sensor Network (WSN). These sensor nodes are outfitted with low-cost and low-power sensors. The routing protocols are responsible for ensuring communications while considering the energy constraints of the system. Achieving a higher network lifetime is the need of the hour in WSNs. Currently, many network layer protocols are considering a heterogeneous WSN, wherein a certain number of the sensors are rendered higher energy as compared to the rest of the nodes. In this paper, we have critically analysed the various stationary heterogeneous clustering algorithms and assessed their lifetime and throughput performance in mobile node settings also. Although many newer variants of Distributed Energy-Efficiency Clustering (DEEC) scheme execute proficiently in terms of energy efficiency, they suffer from high system complexity due to computation and selection of large number of Cluster Heads (CHs). A protocol in form of Cluster-head Restricted Energy Efficient Protocol (CREEP) has been proposed to overcome this limitation and to further improve the network lifetime by modifying the CH selection thresholds in a two-level heterogeneous WSN. Simulation results establish that proposed solution ameliorates in terms of network lifetime as compared to others in stationary as well as mobile WSN scenarios.     

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...     

Energy Efficient Energy Hole Repelling (EEEHR) Algorithm for Delay Tolerant Wireless Sensor Network

Reducing energy consumption and increasing network lifetime are the major concerns in Wireless Sensor Network (WSN). Increase in network lifetime reduces the frequency of recharging and replacing batteries of the sensor node. The key factors influencing energy consumption are distance and number of bits transmitted inside the network. The problem of energy hole and hotspot inside the network make neighbouring nodes unusable even if the node is efficient for data transmission. Energy Efficient Energy Hole Repelling (EEEHR) routing algorithm is developed to solve the problem. Smaller clusters are formed near the sink and clusters of larger size are made with nodes far from the sink. This methodology promotes equal sharing of load repelling energy hole and hotspot issues. The opportunity of being a Cluster Head (CH) is given to a node with high residual energy, very low intra cluster distance in case of nodes far away from the sink and very low CH to sink distance for the nodes one hop from the sink. The proposed algorithm is compared with LEACH, LEACH-C and SEP routing protocol to prove its novel working. The proposed EEEHR routing algorithm provides improved lifetime, throughput and less packet drop. The proposed algorithm also reduces energy hole and hotspot problem in the network.     

A Novel Heterogeneous Clustering Protocol for Lifetime Maximization of Wireless Sensor Network

The network lifetime of Wireless Sensor Network (WSN) is one of the most challenging issues for any network protocol. The nodes in the network are densely deployed and are provided with limited power supply. The routing strategy is treated as an effective solution to improve the lifetime of the network. The cluster based routing techniques are used in the WSN to enhance the network lifespan and to minimize the energy consumption of the network. In this paper, an energy efficient heterogeneous clustering protocol for the enhancement of the network lifetime is proposed. The proposed protocol uses the sensor energy for the clustering process in a well-organized manner to maximize the lifetime of network. The MATLAB simulator is used for implementing the clustering model of proposed protocol and for measuring the effectiveness of the proposed technique the comparison is performed with the various existing approaches such as Stability Election Protocol, Distributed Energy Efficient Clustering and Adaptive Threshold Energy Efficient cross layer based Routing.

     

无线传感器网络的覆盖优化机制研究

如何实现最优覆盖是无线传感器组网的一个基本问题.文章分析了传感器覆盖问题的背景,给出了节点调度方案的主要方法和技术原理,探讨了基于网络能量高效的覆盖优化与网络连通性之间的关系,重点阐述了实现区域覆盖和点覆盖的机制.对于覆盖薄弱地区,文章提出了采用分簇方式将覆盖地区划分成许多子区域或簇,用动态移动修复机制提供细粒度的网络监测与覆盖控制.文章认为调度传感器节点在休眠和活动模式之间进行切换,是一种重要节能方法;对于资源受限且拓扑动态变化的无线传感器网络,宜采用分布式和局部化的覆盖控制协议和算法.     

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.     

Research and Improvement of Wireless Sensor Network Secure Data Aggregation Protocol Based on SMART

The privacy-preserving of information is one of the most important problems to be solved in wireless sensor network (WSN). Privacy-preserving data aggregation is an effective way to protect security of data in WSNs. In order to deal with the problem of energy consumption of the SMART algorithm, we present a new dynamic slicing D-SMART algorithm which based on the importance degree of data. The proposed algorithm can decrease the communication overhead and energy consumption effectively while provide good performance in preserving privacy by the reasonable slicing based on the importance degree of the collected raw data. Simulation results show that the proposed D-SMART algorithm improve the aggregation accuracy, enhance the privacy-preserving, reduce the communication overhead to some extent, decrease the energy consumption of sensor node and prolong the network lifetime indirectly.     

Energy efficiency of virtual multi‐input,multi‐output based on sensor selection in wireless sensor networks

In this paper, a weighted node selection technique in wireless sensor networks is proposed. It is an energy‐efficient cooperative technique where a selected number of sensors at the transmitting end are connected with a selected number of sensors at the receiving end to form a virtual multi‐input multi‐output. The proposed technique is based on a weighted selection function that combines geographical location, inter‐sensor distance in a cluster, channel estimate energy, power circuit, channel loss, mobility factor, and residual energy of each sensor. The weight of each of these parameters in the selection function depends on the degree that this parameter affects the energy consumption. Then, the cluster head selects the sensors with better selection parameters that reduce the overall energy consumption. The numerical results show that the proposed weighted node selection technique achieves a significant improvement in the energy consumption, delay, and network lifetime than the conventional techniques with and without the selected number of sensors. Its improvement reaches 15% in the energy consumption that leads to an increase in the network lifetime by four times the network lifetime of other techniques. Copyright © 2012 John Wiley & Sons, Ltd.     

Adaptive energy aware cluster-based routing protocol for wireless sensor networks

Wireless sensor networks (WSNs) have grown excessively due to their various applications and low installation cost. In WSN, the main concern is to reduce energy consumption among nodes while maintaining timely and reliable data forwarding. However, most of the existing energy aware routing protocols incur unbalanced energy consumption, which results in inefficient load balancing and compromised network lifetime. Therefore, the main target of this research paper is to present adaptive energy aware cluster-based routing (AECR) protocol for improving energy conservation and data delivery performance. Our proposed AECR protocol differs from other energy efficient routing schemes in some aspects. Firstly, it generates balance sized clusters based on nodes distribution and avoids random clusters formation. Secondly, it optimizes both intra-cluster and inter-cluster routing paths for improving data delivery performance while balancing data traffic on constructed forwarding routes and at the end, in order to reduce the excessive energy consumption and improving load distribution, the role of Cluster Head (CH) is shifted dynamically among nodes by exploit of network conditions. Simulation results demonstrate that AECR protocol outperforms state of the art in terms of various performance metrics.

     

Fuzzy Tree Clustering Algorithm with Mobile Data Collectors in Wireless Sensor Networks

In recent years, the need to deploy Wireless Sensor Networks increases in different applications. Several studies have been proposed to demonstrate the importance to use Mobile Data Collectors (MDC) in Wireless sensor Networks. The main goal of this paper is to reduce the energy consumption of sensor nodes and to extend the network lifetime. In this paper, we propose to construct a Minimum Spanning tree, we design a fuzzy Cluster Head election system to elect the best sensor nodes as Cluster Heads, considering two input parameters, namely the weight of Sensor Nodes (WoSN) and the State of Sensor Node Locations (SoSNLoc). To extend the network lifetime, a subset of MDCs travels the area to gather the sensed data from nodes instead of sending them directly to the Base Station (BS) in a single hop or multi-hop manner. The BS is located at the center of the area which will be divided into sub-regions, one for each MDC. According to their positions, each CH will belong to a specific region, and then will be visited by the corresponding MDC. Simulation results show the effectiveness of our proposed algorithm in terms of energy consumption and network lifetime in comparison with other ones.

     

Research on WSN lifetime optimization game algorithm combined power and channel

Due to the problem of shortening the network lifetime which was caused by the big energy consumption for wireless sensor network (WSN) whose energy and computing power was limit,a lifetime optimization game algorithm combined power control and channel allocation (LOAPC) was proposed.The influence of node power and residual energy on the node interference was explored to construct an interference affection measurement model.Then,expected transmission times was introduced to establish a novel node lifetime model.Finally,LOAPC aimed at reducing interference and prolonging lifetime,and the node power was limited by an optional power set which ensured the network connectivity and economized energy consumption,so as to prolong the network lifetime effectively.At the same time,the simulation results show that the algorithm has the characteristics of low interference,low energy consumption and effectively prolonging the lifetime of the network.     

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.