scholarly journals A Security Framework for Cluster-Based Wireless Sensor Networks against the Selfishness Problem

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Zeba Ishaq ◽  
Seongjin Park ◽  
Younghwan Yoo
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Limited Resources ◽  
Security Framework ◽  
Insider Attack ◽  
Head Node ◽  
Special Working

Over the last few decades, Cluster-Based Wireless Sensor Networks (CBWSNs) have played a crucial role in handling various challenges (load balancing, routing, network lifetime, etc.) of large scale Wireless Sensor Networks (WSNs). However, the security becomes a big problem for CBWSNs, especially when nodes in the cluster selfishly behave, e.g., not forwarding other nodes’ data, to save their limited resources. This may make the cluster obsolete, even destroying the network. Thus, a way to guarantee the secure and consistent clusters is needed for proper working of CBWSNs. We showed that the selfishness attack, i.e., passive attack or insider attack, in CBWSNs can cause severe performance disaster, when particularly a cluster head node becomes selfish. In order to prevent this situation, this paper proposes a security framework that involves a novel clustering technique as well as a reputation system at nodes for controlling selfishness, making them cooperative and honest. The novelty of the clustering comes from the existence of inspector node (IN) to monitor the cluster head (CH) and its special working style. The experimental results showed that the proposed security framework can control the selfishness and improve the security of the clusters.

scholarly journals Security Issues of Wireless Sensor Networks Based on Target Tracking

2016 ◽  
Vol 12 (10) ◽  
pp. 97
Author(s):  
Jun Ma
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Target Tracking ◽  
Large Scale ◽  
Target Location ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Security Issues ◽  
Head Node

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; -ms-layout-grid-mode: line; mso-fareast-font-family: SimSun; mso-fareast-theme-font: minor-fareast; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">In this paper the dynamic point target tracking is studied, and a message driven target tracking algorithm based on non-ranging is proposed by combining the actual sensor node characteristics. By tissue tracking around the target sensor nodes collaborate to establish a tracking cluster and the cluster head node for data fusion to accurately locate the target and thus formed a kind of efficient and precise distributed dynamic tracking cluster algorithm of DTC. The tracking cluster can follow the target as a shadow, and it can realize the management of the cluster itself and constantly report to the sink node to the target location. The protocol is especially suitable for the use of large scale wireless sensor networks with low node cost.</span>

scholarly journals Energy Balance Routing Algorithm Based on Virtual MIMO Scheme for Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Jianpo Li ◽  
Xue Jiang ◽  
I-Tai Lu
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Balance ◽  
Network Lifetime ◽  
Routing Algorithm ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Virtual Mimo ◽  
Head Node

Wireless sensor networks are usually energy limited and therefore an energy-efficient routing algorithm is desired for prolonging the network lifetime. In this paper, we propose a new energy balance routing algorithm which has the following three improvements over the conventional LEACH algorithm. Firstly, we propose a new cluster head selection scheme by taking into consideration the remaining energy and the most recent energy consumption of the nodes and the entire network. In this way, the sensor nodes with smaller remaining energy or larger energy consumption will be much less likely to be chosen as cluster heads. Secondly, according to the ratio of remaining energy to distance, cooperative nodes are selected to form virtual MIMO structures. It mitigates the uneven distribution of clusters and the unbalanced energy consumption of the whole network. Thirdly, we construct a comprehensive energy consumption model, which can reflect more realistically the practical energy consumption. Numerical simulations analyze the influences of cooperative node numbers and cluster head node numbers on the network lifetime. It is shown that the energy consumption of the proposed routing algorithm is lower than the conventional LEACH algorithm and for the simulation example the network lifetime is prolonged about 25%.

Cluster-to-Cluster Relay Schemes in Wireless Sensor Network

2011 ◽  
Vol 179-180 ◽  
pp. 728-733
Author(s):  
Xue Fen Zhang ◽  
Fang Zhen Li
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Cooperative Communications ◽  
Cluster Head ◽  
Cooperative Transmission ◽  
Wireless Sensor ◽  
Transmission Scheme ◽  
Numerical Examples ◽  
Data Packets ◽  
Head Node

Cooperative communications is a promising technology to improve the performance of wireless sensor networks. To ensure scalability sensor networks are often partitioned into clusters, each managed by a cluster head. most of the previous research focused on the optimal communication of sensors in one cluster, very little attention has been paid to the efficiency of cooperation among the clusters .In this paper, we consider cluster-to-cluster cooperative communications where cluster head node relay data packets to nearby cluster head nodes using cooperative communications, and propose two cooperative transmission scheme and analysis on the throughput and outage probability. Finally, we demonstrate the applicability of our results through numerical examples.

A Cluster Algorithm for Wireless Sensor Networks Based on Energy Efficiency

2015 ◽  
Vol 785 ◽  
pp. 744-750
Author(s):  
Lei Gao ◽  
Qun Chen
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Selection Criterion ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Head Node

In order to solve the energy limited problem of sensor nodes in the wireless sensor networks (WSN), a fast clustering algorithm based on energy efficiency for wire1ess sensor networks is presented in this paper. In the system initialization phase, the deployment region is divided into several clusters rapidly. The energy consumption ratio and degree of the node are chosen as the selection criterion for the cluster head. Re-election of the cluster head node at this time became a local trigger behavior. Because of the range of the re-election is within the cluster, which greatly reduces the complexity and computational load to re-elect the cluster head node. Theoretical analysis indicates that the timing complexity of the clustering algorithm is O(1), which shows that the algorithm overhead is small and has nothing to do with the network size n. Simulation results show that clustering algorithm based on energy efficiency can provide better load balancing of cluster heads and less protocol overhead. Clustering algorithm based on energy efficiency can reduce energy consumption and prolong the network lifetime compared with LEACH protocol.

scholarly journals Energy-Efficient QoS-Aware Intelligent Hybrid Clustered Routing Protocol for Wireless Sensor Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Parvinder Singh ◽  
Rajeshwar Singh
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Large Scale ◽  
Fitness Function ◽  
Geographical Area ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor

A wireless sensor network consists of numerous low-power microsensor devices that can be deployed in a geographical area for remote sensing, surveillance, control, and monitoring applications. The advancements of wireless devices in terms of user-friendly interface, size, and deployment cost have given rise to many smart applications of wireless sensor networks (WSNs). However, certain issues like energy efficiency, long lifetime, and communication reliability restrict their large scale utilization. In WSNs, the cluster-based routing protocols assist nodes to collect, aggregate, and forward sensed data from event regions towards the sink node through minimum cost links. A clustering method helps to improve data transmission efficiency by dividing the sensor nodes into small groups. However, improper cluster head (CH) selection may affect the network lifetime, average network energy, and other quality of service (QoS) parameters. In this paper, a multiobjective clustering strategy is proposed to optimize the energy consumption, network lifetime, network throughput, and network delay. A fitness function has been formulated for heterogenous and homogenous wireless sensor networks. This fitness function is utilized to select an optimum CH for energy minimization and load balancing of cluster heads. A new hybrid clustered routing protocol is proposed based on fitness function. The simulation results conclude that the proposed protocol achieves better efficiency in increasing the network lifetime by 63%, 26%, and 10% compared with three well-known heterogeneous protocols: DEEC, EDDEEC, and ATEER, respectively. The proposed strategy also attains better network stability than a homogenous LEACH protocol.

Minimizing Energy Consumption Based on Neural Network in Clustered Wireless Sensor Networks

2019 ◽  
Vol 16 (2) ◽  
pp. 496-502
Author(s):  
N. Vadivelan ◽  
A. Ramamurthy ◽  
P. Padmaja
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Physical Phenomenon ◽  
Geographical Area ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Head Node ◽  
Large Geographical Area

Wireless sensor networks were organized with the collections of sensor nodes for the purpose of monitoring physical phenomenon such as temperature, humidity and seismic events, etc., in the real world environments where the manual human access is not possible. The major tasks of this type of networks are to route the information to sink systems in the sensor network from sensor nodes. Sensors are deployed in a large geographical area where human cannot enter such as volcanic eruption or under the deep sea. Hence sensors are not rechargeable and limited with battery backup; it is very complicated to provide the continuous service of sending information to sink systems from sensor nodes. To overcome the drawback of limited battery power, this paper proposes the concept of minimizing energy consumption with the help of neural networks. The modified form of HRP protocol called energy efficient HRP protocol has been implemented in this paper. Based on this concept, the workload of cluster head is shared by the cluster isolation node in order to increase the lifetime of the cluster head node. Also cluster monitoring node is introduced to reduce the re-clustering process. The implementation procedure, algorithm, results and conclusions were proved that the proposed concept is better than the existing protocols.

An Improved LEACH Protocol in Wireless Sensor Networks

2015 ◽  
Vol 743 ◽  
pp. 748-752 ◽  
Author(s):  
L.F. Liu ◽  
P. Guo ◽  
J. Zhao ◽  
N. Li
Keyword(s):  
Wireless Sensor Networks ◽  
Life Cycle ◽  
Sensor Networks ◽  
Cluster Head ◽  
Network Routing ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Head Node ◽  
Leach Protocol

Wireless sensor network routing protocol is to prolong the survival time of wireless sensor networks by using the sensor nodes energy efficiently. Traditional LEACH protocol is random in the election of the cluster head, if a less energy node is first elected as a cluster head node, then the node might die soon, it will greatly reducing the lifetime of the network. In order to collect data more efficiently and prolong the network life cycle,we need better clustering protocol. Aim at the traditional LEACH protocol have some weakness,this paper improve the protocol based on traditional LEACH protocol, two influence factors which the residual energy and the number of elected cluster head of the nodes had been introduced to make the clustering more ideal. Simulation results show that compared to the traditional Leach algorithm ,the improved LEACH protocol can prolong the network life cycle more effective and reduce the energy consumption of the whole network.

A Clustering Protocol for Maximum Coverage in Large-Scale Wireless Sensor Networks

2015 ◽  
Vol 11 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Wassim Jerbi ◽  
Abderrahmen Guermazi ◽  
Hafedh Trabelsi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Large Scale ◽  
Cluster Head ◽  
Low Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Basic Algorithm ◽  
Adaptive Clustering

The optimum use of coverage in wireless sensor networks (WSNs) is very important. The hierarchical routing protocol LEACH (Low Energy Adaptive Clustering Hierarchy) is referred to as the basic algorithm of distributed clustering protocols. LEACH allows clusters formation. Each cluster has a leader called Cluster Head (CH). The selection of CHs is made with a probabilistic calculation. It is supposed that each non-CH node join a cluster and becomes a cluster member. Nevertheless, some CHs can be concentrated in a specific part of the network. Thus several sensor nodes cannot reach any CH. As a result, the remaining part of the controlled field will not be covered; some sensor nodes will be outside the network. To solve this problem, the authors propose O-LEACH (Orphan Low Energy Adaptive Clustering Hierarchy), a routing protocol that takes into account the orphan nodes. O-LEACH presents two scenarios, a gateway and sub cluster that allow the joining of orphan nodes.

scholarly journals A Data Collecting Strategy for Farmland WSNs using a Mobile Sink

2020 ◽  
Vol 15 (6) ◽  
Author(s):  
Yaqiong Zhang ◽  
Jiyan Lin ◽  
Hui Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Time Allocation ◽  
Large Scale ◽  
Cluster Head ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Allocation Mechanism

To the characteristics of large number of sensor nodes, wide area and unbalanced energy consumption in farmland Wireless Sensor Networks, an efficient data collection strategy (GCMS) based on grid clustering and a mobile sink is proposed. Firstly, cluster is divided based on virtual grid, and the cluster head is selected by considering node position and residual energy. Then, an optimal mobile path and residence time allocation mechanism for mobile sink are proposed. Finally, GCMS is simulated and compared with LEACH and GRDG. Simulation results show that GCMS can significantly prolong the network lifetime and increase the amount of data collection, especially suitable for large-scale farmland Wireless Sensor Networks.

scholarly journals Optimization-Based Artificial Bee Colony Algorithm for Data Collection in Large-Scale Mobile Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Yinggao Yue ◽  
Jianqing Li ◽  
Hehong Fan ◽  
Qin Qin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Large Scale ◽  
Cluster Head ◽  
Mobile Sink ◽  
Wireless Sensor ◽  
Mobile Wireless ◽  
Mobile Wireless Sensor Networks ◽  
Mobile Wireless Sensor

Data collection is a fundamental operation in various mobile wireless sensor networks (MWSN) applications. The energy of nodes around the Sink can be untimely depleted owing to the fact that sensor nodes must transmit vast amounts of data, readily forming a bottleneck in energy consumption; mobile wireless sensor networks have been designed to address this issue. In this study, we focused on a large-scale and intensive MWSN which allows a certain amount of data latency by investigating mobile Sink balance from three aspects: data collection maximization, mobile path length minimization, and network reliability optimization. We also derived a corresponding formula to represent the MWSN and proved that it represents an NP-hard problem. Traditional data collection methods only focus on increasing the amount data collection or reducing the overall network energy consumption, which is why we designed the proposed heuristic algorithm to jointly consider cluster head selection, the routing path from ordinary nodes to the cluster head node, and mobile Sink path planning optimization. The proposed data collection algorithm for mobile Sinks is, in effect, based on artificial bee colony. Simulation results show that, in comparison with other algorithms, the proposed algorithm can effectively reduce data transmission, save energy, improve network data collection efficiency and reliability, and extend the network lifetime.

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