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.

     

Energy Efficient Cluster Based Routing Protocol Using Charged System Harmony Search Algorithm in WSN

In general, Wireless Sensor Networks (WSNs) is developed with a group of distributed and locative sensor nodes for sensing different environmental conditions. The primary challenges faced by WSN are: low network time and transmission data delay. In crucial applications like monitoring the ecosystem, military and disaster management, and data routing, the incorporation of WSN is very critical. Henceforth, a Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol was proposed but it was found to be uneconomical for energy management. Also, the optimization of Cluster Head (CH) is considered as NP hard problem. This research work deals the issues in optimal path selection in routing of wireless sensor networks to increase the network lifetime. Various techniques are available in metaheuristics, such as the Charged System Search (CSS), that effectively used to resolve the routing problem. Despite of this, most of the meta-heuristics suffer from local optima issues. A charged system search and harmony search algorithm based routing protocol is presented in this research work. Experimental results present the efficient performance of proposed HS model with increased cluster structures, improved network lifetime and reduced end-to-end delay and average packet loss rate.

     

Optimal Cluster Based Routing Technique for Wireless Sensor Networks using Hybrid Optimization Algorithm for Maximizing Life of Sensors

Wireless Sensor Network (WSN) has many sensor nodes that connect with sync nodes. The sensor node's power is a limitation. The expense and difficulty of battery charging and replacement affect sensor node life and network length. Clustering reduces the cost of internal cluster communication, thereby conserving energy. Generally, researchers seek for low energy usage via providing data to monitor the cluster's energy use. Many of them are tied to network length. The Ant Group (TAS) technique is the first notion for establishing a cluster using the OC algorithm that saves electricity. Next, we use improved myopia (IM) to find the cluster head (CH). This minimises the number of clusters and the expense of internal communications. The proposed OC-TAS-IM algorithm attempts to enhance energy efficiency. In the network. The route is also conducted using a special algorithm in the low energy adaptive cluster range (reach). It contains Network Simulator implementation and simulation experiments to test specific OC-TAS-IM algorithms (NS2). Because of optimum clustering, the OC-TAS-IM method is stable in terms of energy clustering and grid lifespan.

     

Energy Efficient Clustering Scheme (EECS) for Wireless Sensor Network with Mobile Sink

The participants in the Wireless Sensor Network (WSN) are highly resource constraint in nature. The clustering approach in the WSN supports a large-scale monitoring with ease to the user. The node near the sink depletes the energy, forming energy holes in the network. The mobility of the sink creates a major challenge in reliable and energy efficient data communication towards the sink. Hence, a new energy efficient routing protocol is needed to serve the use of networks with a mobile sink. The primary objective of the proposed work is to enhance the lifetime of the network and to increase the packet delivered to mobile sink in the network. The residual energy of the node, distance, and the data overhead are taken into account for selection of cluster head in this proposed Energy Efficient Clustering Scheme (EECS). The waiting time of the mobile sink is estimated. Based on the mobility model, the role of the sensor node is realized as finite state machine and the state transition is realized through Markov model. The proposed EECS algorithm is also been compared with Modified-Low Energy Adaptive Clustering Hierarchy (MOD-LEACH) and Gateway-based Energy-Aware multi-hop Routing protocol algorithms (M-GEAR). The proposed EECS algorithm outperforms the MOD-LEACH algorithm by 1.78 times in terms of lifetime and 1.103 times in terms of throughput. The EECS algorithm promotes unequal clustering by avoiding the energy hole and the HOT SPOT issues.     

Clustering Based Two Dimensional Motion of Sink Node in Wireless Sensor Networks

The wireless sensor network (WSN) is always known for its limited-energy issues and finding a good solution for energy minimization in WSNs is still a concern for researchers. Implementing mobility to the sink node is used widely for energy conservation or minimization in WSNs which reduces the distance between sink and communicating nodes. In this paper, with the intention to conserve energy from the sensor nodes, we designed a clustering based routing protocol implementing a mobile sink called ‘two dimensional motion of sink node (TDMS)’. In TDMS, each normal sensor node collects data and send it to their respective leader node called cluster head (CH). The sink moves in the two dimensional direction to collect final data from all CH nodes, particularly it moves in the direction to that CH which has the minimum remaining energy. The proposed protocol is validated through rigorous simulation using MATLAB and comparisons have been made with WSN’s existing static sink and mobile sink routing protocols over two different geographical square dimensions of the network. Here, we found that TDMS model gives the optimal result on energy dissipation per round and increased network lifetime.

     

Zone-based routing protocol with mobility consideration for wireless sensor networks

Hierarchical routing and clustering mechanisms in Wireless Sensor Networks (WSN) help to reduce the energy consumptions and the overhead created when all the sensor nodes in the network are sending information to the central data collection point. Most of the routing and clustering protocols proposed for WSN assume that the nodes are stationary. However, in applications like habitat monitoring or search and rescue, that assumption makes those clustering mechanisms invalid, since the static nature of sensors is not real. In this paper, we propose Zone-based Routing Protocol for Mobile Sensor Networks (ZoroMSN) that considers the design aspects such as mobility of sensors, zones and routes maintenance, information update and communication between sensor nodes. Simulation results show the effectiveness and strengths of the ZoroMSN protocol such as a low routing and mobility overhead, while achieving a good performance in WSN using small zone sizes and sensors with low speed. Simulation results also show that ZoroMSN outperforms existing LEACH-ME and LEACH-M protocols in terms of network lifetime and energy consumptions.     

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.     

Intrusion Detection in Mobile Sensor Networks: A Case Study for Different Intrusion Paths

Optimization of energy consumption in the batteries of a sensor node plays an essential role in wireless Sensor networks (WSNs). The longevity of sensor nodes depends on efficiency of energy utilization in batteries. Energy is consumed by sensor nodes in WSNs to perform three significant functions namely data sensing, transmitting and relaying. The battery energy in WSNs depletes mainly due to sampling rate and transmission rate. In the present work, the most important parameters affecting the longevity of network are indentified by modeling the energy consumption. The parameters are expressed as a fuzzy membership function of variables affecting the life time of network. Fuzzy logic is used at multiple levels to optimize the parameters. Network simulator-2 is used for experimentation purpose. The proposed work is also compared with the existing routing protocols like Enhanced Low Duty Cycle, Threshold Sensitive Energy Efficient Sensor Network and Distributed Energy Efficient Adaptive Clustering Protocol with Data Gathering. The proposed solution is found to be more energy efficient and hence ensures longer network lifetime.

     

Unequal Clustering Protocols for Wireless Sensor Networks—Taxonomy,Comparison and Simulation

Wireless Sensor Network (WSN) consists of randomly distributed sensor nodes which can collect, process, route and transmit data from their respective environment. Most of the research on WSN is oriented towards optimizing utilization of finite resources of Sensor Nodes to increase the overall network operative time. Recent literature on WSNs reveals that hierarchical routing unequal clustering methodologies are gaining popularity due to energy efficiency, load balancing and scalability. In literature, numerous surveys on clustering methodologies are available which address different equal clustering methods. The unequal clustering protocols, which have their own attributes viz. balance load distribution, hot spot mitigation and energy efficiency, are comparatively less explored. This motivated us to undertake the present study on the taxonomy, comparison and simulation analysis of different methodologies pertaining to less explored unequal clustering protocols. Our base metrics for comparison of different unequal clustering protocols are scalability, energy efficiency & load balancing capability of the resulting network. A comprehensive discussion has also been presented to highlight the various advantages and disadvantages of different unequal clustering protocols. Further, we have summarized the study of unequal clustering protocols in the tabular form.

     

一种基于K-means的WSN移动汇聚路由算法

无线传感网络(Wireless Sensor Network,WSN)作为一种资源受限的网络,网络中节点的能耗直接影响了网络的性能。因此,均衡网络中的能耗,延长网络的生命周期,成为设计WSN路由算法的重要目标。于是,在LEACH-C协议的基础上提出了一种移动汇聚路由算法。分簇阶段由Sink节点计算最优簇首个数,通过K-means聚类将网络中的节点划分至不同的集群,选择通信成本最低的节点作为各集群的簇首。稳定传输阶段通过移动Sink进行数据采集,针对不同的延迟分别规划Sink节点的移动轨迹。MATLAB仿真结果表明,与LEACH和LEAHC-C算法相比簇首的分布更合理,结合Sink节点的移动策略能有效均衡网络能耗,延长网络的寿命。     

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.

     

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.

     

Outage Probability Analysis of Multi-relay Cooperative Decode-and-Forward System Over Generalized η–μ and κ–μ Fading Channels

In present scenario of wireless sensor networks and communications, efficient sensed data transmission among nodes is being a great confrontation because of the impulsive and volatile nature of sensors in the network. For providing that and enhancing network lifetime, there are several approaches are developed, specifically using clustering techniques. Still, there are requirements for energy based efficient routing in WSN. With that note, this paper develops anEnergy Aware Efficient Data Aggregation (EAEDAR) and Data Re-Schedulingwith the incorporation of clustering techniques. Moreover, the model used energy based cluster formation and cluster head selection for increasing the network stability and data delivery rate. The model comprises four main phases, namely, Energy factor based cluster formation, Aggregator_SN (Sensor Node) Selection, Efficient Data Aggregation (EDA) and Data Re-Scheduling based on delay and processing time. Furthermore, the model is updated with respect to the status of the nodes and links, for providing consistent network with improved reliable data transmissions. The simulation results portrays the effectiveness of the proposed model over other compared works in terms of the performance factors such as, throughput, packet delivery ratio, network lifetime, transmission delay and packet drop.

     

Dynamic clustering approach based on wireless sensor networks genetic algorithm for IoT applications

Energy is vital parameter for communication in Internet of Things (IoT) applications via Wireless Sensor Networks (WSN). Genetic algorithms with dynamic clustering approach are supposed to be very effective technique in conserving energy during the process of network planning and designing for IoT. Dynamic clustering recognizes the cluster head (CH) with higher energy for the data transmission in the network. In this paper, various applications, like smart transportation, smart grid, and smart cities, are discussed to establish that implementation of dynamic clustering computing-based IoT can support real-world applications in an efficient way. In the proposed approach, the dynamic clustering-based methodology and frame relay nodes (RN) are improved to elect the most preferred sensor node (SN) amidst the nodes in cluster. For this purpose, a Genetic Analysis approach is used. The simulations demonstrate that the proposed technique overcomes the dynamic clustering relay node (DCRN) clustering algorithm in terms of slot utilization, throughput and standard deviation in data transmission.

     

安全高效的无线传感器网络远程身份验证协议

针对无线传感器网络节点资源受限及通信链路易出错的问题,给出一种安全高效的无线传感器网络远程身份验证协议。该协议采用集中式基于簇的分层无线传感器网络选出最优百分比的簇头,并对其与相邻节点的通信进行授权,再最小化节点能耗实现网络负载平衡,然后每个簇头作为服务器在每个传递消息的有效负载内保证数据认证与交换,对相邻节点进行身份验证后即可构成簇。由仿真分析结果可知：该协议的安全性、抗攻击鲁棒性、握手持续时间、平均能耗和网络平均吞吐量指标都优于已有改进的低功耗自适应集簇分层协议(imp-LEACH)与安全LEACH协议(sec-LEACH)。     

Energy Efficient Target Tracking with Collision Avoidance in WSNs

Wireless sensor network (WSN) is one of the most evolving technologies. WSN involves collecting, processing, transferring and storing information about objects with the help of sensor nodes. Tracking and detection of targets is one of the most attractive applications of WSN in surveillance systems. To resolve the problem of target tracking, it is essential to deploy a system model. It has been observed that clustering algorithms play an important role in cluster head selection, but they consume significant amount of energy. In this paper an energy efficient system model is deployed with a novel target tracking algorithm to track the target around the vicinity of the WSN. As there is more possibility of collision proximate to the base station, a new collision avoidance method is introduced. The lifetime of the network on the basis of congestion around the sink node, packet density and path loss are also measured efficiently.

     

容错能量均衡WSN拓扑控制方案研究

针对WSN（Wireless Sensor Net）结构中存在大量的网络覆盖冗余与节点唤醒时间的延长,耗费了资源同样也增加了节点的工作能耗的特点。设计了一个拓扑控制方案,减少网络冗余的同时,兼顾了网络的鲁棒性。并且保证生成拓扑具有最小的能量消耗。该方案根据节点的位置信息。建立各监测节点到簇节点的能量消耗最小并且可以保证...     

Recursive‐clustering‐based approach for denial of service (DoS) attacks in wireless sensors networks

This paper presents a novel approach for detecting denial of service attacks. In particular, the concern is on the sleeping deprivation attacks such as the malicious nodes that use flooding technique. Our approach is based on wireless sensor network (WSN) clustering. It consists in recursively clustering sensors until a required granularity (chosen by the expert) is achieved. We apply our approach with two different clustering algorithms. Indeed, we use the common clustering WSN algorithm Low Energy Algorithm Adaptive Clustering Hierarchy and the general clustering method Fast and Flexible Unsupervised Clustering Algorithm (FFUCA) based on ultrametric properties. We discuss the behavior of the approach with the two algorithms. Also, we present numerical results that show the efficiency of recursive clustering using the FFUCA algorithm. Copyright © 2013 John Wiley & Sons, Ltd.     

Dynamic clustering approach with ACO-based mobile sink for data collection in WSNs

Enhancing the network lifetime of wireless sensor networks is an essential task. It involves sensor deployment, cluster formation, routing, and effective utilization of battery units. Clustering and routing are important techniques for adequate enhancement of the network lifetime. Since the existing clustering and routing approaches have high message overhead due to forwarding collected data to sinks or the base station, it creates premature death of sensors and hot-spot issues. The objective of this study is to design a dynamic clustering and optimal routing mechanism for data collection in order to enhance the network lifetime. A new dynamic clustering approach is proposed to prevent premature sensor death and avoid the hot spot problem. In addition, an Ant Colony Optimization (ACO) technique is adopted for effective path selection of mobile sinks. The proposed algorithm is compared with existing routing methodologies, such as LEACH, GA, and PSO. The simulation results show that the proposed cluster head selection algorithm with ACO-based MDC enhances the sensor network lifetime significantly.