Cluster-based Sensor Networks Research Articles

Novel Clustering Techniques in Wireless Sensor Networks – A Survey

A study of Wireless Sensor Networks has been growing tremendously these days. Wireless Sensor Networks play a major role in various fields ranging from smart homes to health care. WSN’s operate independently in remote places. Because of tiny size of the nodes in such type of networks, they have a limited number of resources in terms of energy and power. Basically, sensor networks can be classified into flat and cluster based Wireless Sensor Networks. But, Clustering based Sensor Networks play a major role in reducing the energy consumption in Wireless Sensor Networks. Clustering also focuses on solving the No.s that arise during transmission of data. Clustering will group nodes into clusters and elects Cluster Heads for all clusters in the network. Then the nodes sense data and send that data to cluster head where the aggregation of data will take place. This paper focuses on various novel clustering techniques that improve the network’s lifetime.

Simultaneous optimization of cluster head selection and inter-cluster routing in wireless sensor networks using a 2-level genetic algorithm

In cluster-based sensor networks, at each cluster, sensor nodes send the collected data to a cluster head which aggregates and forwards them to a sink node. Data transmission from a cluster head to the sink node can be done in a multi-hop fashion through other cluster heads. Hence, two problems need to be addressed in this regard: Selection of cluster heads, and optimal multi-hop routing. In previous studies, these two problems have been solved separately in two independent phases. This paper proposes a novel approach to solve them simultaneously in order to increase the network lifetime. In the proposed scheme, the cluster head’s role in transmitting the inter-cluster traffic is considered during the cluster head selection process. In other words, cluster heads are selected in a way which reduces the energy consumption for transmitting data from a cluster head to the sink node. To achieve this goal, the genetic algorithm is used in two levels. The first-level genetic algorithm selects the cluster heads while the second-level one considers multi-hop routing among them. Simulation of the proposed method and comparison of its results with three previously proposed schemes which solve the problems separately indicate the superiority of the proposed optimization scheme in improving the lifetime of the network.

Adaptive Energy Efficient Circular Spinning Protocol for Dynamic Cluster Based UWSNs

Under Water Sensor Network (UWSN) is a novel paradigm for exploring marine environments such as offshore and mineral exploration, underwater surveillance, and sea habitat monitoring. However, a good quality underwater communication is difficult to achieve due to different constraints such as limited bandwidth, acoustic propagation issues, delays, battery replacement hitches, etc. In recent works, efficient energy-based designing and overall performance evaluation of the UWSN has become a major consideration. Cluster-based sensor networks have proven to be a successful way to increase the network’s load congruency and scalability while lowering the system’s total energy consumption. Usually, clustering algorithms work in three phases; cluster setup, data collection, and transmission to sink. In these types of dynamic cluster-based networks, energy consumed in cluster setup has been considered insignificant. Since these network energy consumptions are not part of data communication, we consider it extra energy consumption. In this paper, a new Energy Efficient Circular Spinning (EECS) dynamic clustering algorithm has been proposed to provide an improved cluster setup system and to minimize energy usage in re-clustering or cluster setup. Our proposed EECS mechanism suggests that system performance can improve by reducing the Cluster Head (CH) selection phase or cluster setup phase and can ultimately minimize the energy consumption of networks. It is demonstrated that by reducing the transmission of superfluous control messages during the cluster arrangement stage, approximately 21.5% to28.4% of the total network energy expended can be saved. This paper also compares the extra energy consumption, total network energy consumption, and life of the network in our proposed EECS mechanism to two different mechanisms, (1) Adaptive LEACH for UW, (2) UMOD_LEACH. The optimum value of cluster head has been calculated from energy consumption of different protocols and results show that our proposed EECS can prolong network lifetime by 21.5% and 28.4%from the above-mentioned algorithms consequently. In future, we will extend outwork for multi-hop dynamic cluster base mechanism for UW.

A Survey on Attacks, Security Mechanisms and Secure Extensions of Hierarchical Clustering Based Sensor Networks

Wireless Sensor Networks (WSNs) consists of large number of sensors deployed in regions required by the applications to collect information about the surrounding environment. WSNs are highly vulnerable to security attacks at various levels due to their distributed nature, multi-hop data forwarding, and open wireless medium. A clustering-based routing protocol LEACH is a successful protocol for routing in WSNs as well as evenly utilizing energy of sensor nodes since all sensor nodes have limited source of energy. However, LEACH protocol also has some flaws which can attract attackers and they can cause serious damage either physically or it can also steal information from the network. Due to this reason security is the main problem of LEACH protocol and many secure versions of this protocol have been designed to make it resilient against insider as well as outsider attackers. In this paper, we discuss some of the threats in WSNs along with various kinds of attacks as well as mechanism to deal with such threats. Furthermore, we discuss LEACH protocol and its extensions, various techniques used to define secure LEACH which can protect network from entering intruders. Lastly, we compare some secure LEACH schemes like cryptographic-based or trust-based scheme.

An efficient secure key establishment method in cluster-based sensor network

The main issue for the security of wireless sensor networks (WSNs) is how to allow sensor nodes (SNs) to establish and share cryptographic keys in an energy-efficient, storage-efficient, and authentic manner for their secure data transmission. Furthermost recent studies carried out in this direction is concerned with homogeneous networks in which all sensor has identical characteristics and fundamental administration mechanisms. However, Cluster-based sensor networks have demonstrated better achievements and performance than homogeneous networks because of the several benefits of clustering. This inspired us to propose a secure key-establishment method for cluster-based sensor networks based on symmetric-key cryptography. Since symmetric key cryptography has small energy consumption, they are a great choice to prefer for securing the networks. Even though symmetric key cryptography has high storage needs, this deficiency can be reduced by using suitable methods—evaluating the proposed work that the storage needs are reduced along with reduced energy consumption. The work offers a favorable level of security against various intruders and possible security threats and is additionally scalable than the state-of-the-art techniques.

Modeling and Analysis of Data Prediction Technique Based on Linear Regression Model (DP-LRM) for Cluster-Based Sensor Networks

Recent developments in information gathering procedures and the collection of big data over a period of time as a result of introducing high computing devices pose new challenges in sensor networks. Data prediction has emerged as a key area of research to reduce transmission cost acting as principle analytic tool. The transformation of huge amount of data into an equivalent reduced dataset and maintaining data accuracy and integrity is the prerequisite of any sensor network application. To overcome these challenges, a data prediction technique is suggested to reduce transmission of redundant data by developing a regression model on linear descriptors on continuous sensed data values. The proposed model addresses the basic issues involved in data aggregation. It uses a buffer based linear filter algorithm which compares all incoming values and establishes a correlation between them. The cluster head is accountable for predicting data values in the same time slot, calculates the deviation of data values, and propagates the predicted values to the sink.

Energy-Efficient Data-Aggregation Technique for Correlated Spatial and Temporal Data in Cluster-Based Sensor Networks

Continuous-monitoring applications in sensor network applications require periodic data transmissions to the base-station (BS), which may lead to unnecessary energy depletion. The energy-efficient data aggregation solutions in sensor networks have evolved as one of the favorable fields for such applications. Former research works have recommended many spatial-temporal designs and prototypes for successfully minimizing the data-gathering overheads, but these are constrained to their relevance. This work has proposed a data aggregation technique for homogeneous application set-ups in sensor networks. For this, the authors have employed two ways of model generation for reducing correlated spatial-temporal data in cluster-based sensor networks: one at the Sensor nodes (SNs) and the other at the Cluster heads (CHs). Building on this idea, the authors propose two types of data filtration, first at the SNs for determining temporal redundancies (TRs) in data readings by both relative deviation (RD) and adaptive frame method (AFM) and second at the CHs for determining spatial redundancies (SRs) by both RD and AFM.

IMPROVE THE LIFE OF NETWORK IN WIRELESS SENSOR NETWORKS USING CLUSTER BASED EEEMR PROTOCOL

Ponte Academic JournalDec 2020, Volume 76, Issue 12 IMPROVE THE LIFE OF NETWORK IN WIRELESS SENSOR NETWORKS USING CLUSTER BASED EEEMR PROTOCOL Author(s): K. Hari Krishna ,Tapas Kumar, Y. Suresh BabuJ. Ponte - Dec 2020 - Volume 76 - Issue 12 doi: 10.21506/j.ponte.2020.12.11 Abstract:Energy efficient routing is a one of the major trusted area in Wireless Sensor Networks (WSNs). The wireless sensor network composed of a large number of sensor nodes which has limited energy resource. The sensor nodes are working through the battery, energy saving becomes more vital issue in WSNs. The routing algorithms assure that the concept of energy saving without affecting the Quality of Service (QoS). Parameters like Throughput, End to End Delay, Overhead and Packet Delivery Ratio in the existing algorithm in EEEMR Protocol. The development of cluster based sensor networks have recently shown to decrease the system delay, overhead and increase the system throughput and packet delivery ratio. Simulation is performed using NS2 and results shows that the proposed system is better than the system the Enhanced Energy Efficient Multipath Routing (EEEMR) Protocol is implemented. The EEEMR Protocol is modification of AOMDV Protocol. In this paper, we are implementing Clustering existing system. The proposed system energy consumption is decreased by 13% compared to the existing system. Download full text:Check if you have access through your login credentials or your institution Username Password

GWAS OF RESILIENCE TO COMBAT-RELATED PTSD IN THE MILLION VETERAN PROGRAM

In wireless sensor networks (WSNs), a large number of nodes are densely deployed in an open environment to gather some useful required information. These nodes are small in size, operating on limited processing capabilities with scarce working memory and battery life and not very powerful radio transceivers. They can only communicate with each other through wireless media. Radio waves are insecure in nature; therefore, by using such waves for communication there are always opportunities for different attacks on the network. Most wireless techniques are founded on the cluster-based sensor network. Forwarding cluster head's (CHs) data in a secure manner is very important because CHs collect data from the cluster members and send it to the sink node or base station. For securing CH's data, we propose a mechanism termed ICMDS (Inter-Cluster Multiple Key Distribution Scheme for Wireless Sensor Networks), which enables the securing of the entire network. In ICMDS, we use two phases of security implementations for the sensor node's authenticity while communicating with the CH. A recovery phenomena is also stated at the time when a CH ceases to function due to its high energy consumption.

A markov model for investigating the impact of IEEE802.15.4 MAC layer parameters and number of clusters on the performance of wireless sensor networks

In this paper, a new analytical model is presented for cluster-based sensor networks using the non-beacon-enabled mode of IEEE802.15.4 MAC protocol. To accurately investigate the impact of MAC parameters and the number of clusters in the cluster-based networks, a new discrete-time Markov chain model is proposed. To be more realistic and practical, these networks employ time-division multiple access and non-beacon-enabled IEEE 802.15.4 protocols for the intra-cluster and inter-cluster communications, respectively. The model parameters are derived from the characteristics of discrete-time Markov chain models. Three network parameters including packet delivery ratio, packet delay and energy consumption per successful packet transmission are derived from the model for performance evaluation. The results of the proposed model are validated with Monte Carlo simulation results.

Energy Efficient Evolutionary SEP Clustering Protocol for Wireless Sensor Network

Wireless Sensors Networks (WSN) have become vital in many areas and critical applications. Some applications require a reliable network and less maintenance, especially the power consumption. The standard helps the overall network to reduce worries about the sensors power dissipation. Therefore, the longevity of the network is the main concern of the WSN. In this paper an evolutionary SEP protocol is designed and implemented in order to reduce energy consumption of the cluster based sensor network. For this cluster head election process is performed using genetic algorithm. Analysis and simulation results indicate that the Evolutionary SEP protocol can reduce energy consumption between sensor nodes and increase network performance during data transmission. In this experiment, the MATLAB simulator is used here to evaluate the performance of the proposed Evolutionary SEP algorithm and its comparative analysis of simulation results using an existing cluster protocol named LEACH protocol.

A Spatial-Temporal Correlation Approach for Data Reduction in Cluster-Based Sensor Networks

In a resource-constrained Wireless Sensor Networks (WSNs), the optimization of the sampling and the transmission rates of each individual node is a crucial issue. A high volume of redundant data transmitted through the network will result in collisions, data loss, and energy dissipation. This paper proposes a novel data reduction scheme, that exploits the spatial-temporal correlation among sensor data in order to determine the optimal sampling strategy for the deployed sensor nodes. This strategy reduces the overall sampling/transmission rates while preserving the quality of the data. Moreover, a back-end reconstruction algorithm is deployed on the workstation (Sink). This algorithm can reproduce the data that have not been sampled by finding the spatial and temporal correlation among the reported data set, and filling the “nonsampled” parts with predictions. We have used real sensor data of a network that was deployed at the Grand-St-Bernard pass located between Switzerland and Italy. We tested our approach using the previously mentioned data-set and compared it to a recent adaptive sampling based data reduction approach. The obtained results show that our proposed method consumes up to 60% less energy and can handle nonstationary data more effectively.

A Novel Model of Sybil Attack in Cluster-Based Wireless Sensor Networks and Propose a Distributed Algorithm to Defend It

Today, Wireless Sensor Networks are widely employed in various applications including military, environment, medical and urban applications. Thus, security establishment in such networks is of great importance. One of the dangerous attacks against these networks is Sybil attack. In this attack, malicious node propagates multiple fake identities simultaneously which affects routing protocols and many other operations like voting, reputation evaluation, and data aggregation. In this paper, first, a novel model of Sybil attack in cluster-based sensor networks is proposed. In the proposed attack model, a malicious node uses each of its Sybil identity to join each cluster in the network. Thus, the malicious node joins many clusters of the network simultaneously. In this paper, also a distributed algorithm based on Received Signal Strength Indicator and positioning using three points to defend against the novel attack model is proposed. The proposed algorithm is implemented and its efficiency in terms of true detection rate, false detection rate, and communication overhead is evaluated through a series of experiments. Experiment results show that the proposed algorithm is able to detect 99.8% of Sybil nodes with 0.008% false detection rate (in average). Additionally, the proposed algorithm is compared with other algorithms in terms of true detection rate and false detection rate which shows that the proposed algorithm performs desirably.

Secure and Efficient Cluster-Based Range Query Processing in Wireless Sensor Networks

In wireless sensor networks, preserving privacy is more important and has attracted more attentions. Protecting data and sensor privacy while collecting and computing query results is a challenge. In cluster-based sensor networks, when a user queries a sensitive data, the adversaries can monitor original node or gain the data in cluster node. To deal with this problem, we propose a secure and efficient scheme for cluster-based query processing in wireless sensor networks. To preserve location privacy of sensors, we use anonymity method to confuse adversaries. To protect the sensitive data, we use prefix membership verification method to prevent adversaries from gaining sensitive messages collected by sensor nodes. And we analyze the security and communication cost. The results show that our scheme can efficiently protect privacy in query processing.

Target Tracking Based on Virtual Grid in Wireless Sensor Networks

One of the most important and typical application of wireless sensor networks (WSNs) is target tracking. Although target tracking, can provide benefits for large-scale WSNs and organize them into clusters but tracking a moving target in cluster-based WSNs suffers a boundary problem. The main goal of this paper was to introduce an efficient and novel mobility management protocol namely Target Tracking Based on Virtual Grid (TTBVG), which integrates on-demand dynamic clustering into a cluster- based WSN for target tracking. This protocol converts on-demand dynamic clusters to scalable cluster-based WSNs, by using boundary nodes and facilitates sensors’ collaboration around clusters. In this manner, each sensor node has the probability of becoming a cluster head and apperceives the tradeoff between energy consumption and local sensor collaboration in cluster-based sensor networks. The simulation results of this study demonstrated that the efficiency of the proposed protocol in both one-hop and multi-hop cluster-based sensor networks.

Energy-efficient scheduling strategies for minimizing big data collection in cluster-based sensor networks

Today, wireless sensor networks (WSNs) have been widely used in monitoring various applications, such as environment, military and health-care, etc. The explosive growth of the data volume generated in these applications has led to one of the most challenging research issues of the big data era. To deal with such amounts of data, exploring data correlation and scheduling strategies have received great attention in WSNs. In this paper, we propose an efficient mechanism based on the Euclidean distance for searching the spatial-temporal correlation between sensor nodes in periodic applications. Based on this correlation, we propose two sleep/active strategies for scheduling sensors in the network. The first one searches the minimum number of active sensors based on the set covering problem while the second one takes advantages from the correlation degree and the residual energy of the sensors for scheduling them in the network. Our mechanism with the proposed strategies were successfully tested on real sensor data. Compared to other existing techniques, the simulation results show that our mechanism significantly extends the lifetime of the network while conserving the quality of the collected data and the coverage of the monitored area.

Performance analysis of cluster based homogeneous sensor network using energy efficient N-policy (EENP) model

A wireless sensor network (WSN) consists of a large number of sensor nodes deployed over a geographical area and have broad applications like environment monitoring, target tracking and surveillance. The unique characteristics of WSNs such as limited bandwidth, computing capacity, data delivery delay and severe energy constraints make their design more challenging. A critical issue in WSN is the limited availability of energy and hence optimizing energy is very important. This paper proposes an energy minimization technique based on queue threshold using N-policy M / M / 1 queueing model of a sensor node in a cluster acting as cluster member (CM) and cluster head (CH). We develop an analytical model of a cluster based sensor network based on queue threshold using N-policy M / M / 1 queueing model. The performance of the proposed model is analysed in terms of average energy consumption and mean delay when the node acts as CM and CH. We also derive the expression for the optimal value of queue threshold (N*) for which the node consumes minimum energy. Results show that the average energy consumption savings is high when the node acts as CH when compared to node acting as CM and the trade-off exist between the average energy consumption and mean delay is explored. We perform simulations and the results obtained show that the simulation results match with the analytical results thus validating the accuracy of the approach.

Improving the Network Life Time of Wireless Sensor Network using EEEMR Protocol with Clustering Algorithm

Energy efficient routing is a one of the major trusted area in Wireless Sensor Networks (WSNs). The wireless sensor network composed of a large number of sensor nodes which has limited energy resource. The sensor nodes are working through the battery, energy saving becomes more vital issue in WSNs. The routing algorithms assure the concept of energy saving without affecting the Quality of Service (QoS) Parameters like Throughput, End to End Delay, Overhead and Packet Delivery Ratio. In the existing system the Enhanced Energy Efficient Multipath Routing (EEEMR) Protocol is implemented. The EEEMR Protocol is modification of AOMDV Protocol. In this paper, we are implementing Clustering algorithm in EEEMR Protocol. The development of cluster based sensor networks have recently shown to decrease the system delay, overhead and increase the system throughput and packet delivery ratio. Simulation is performed using NS2 and results shows that the proposed system is better than the existing system. The proposed system energy consumption is decreased by 13% compared to the existing system.

Reconstruction algorithm of chaotic signal based on generalized likelihood ratio threshold-decision

Blind signal reconstruction in sensor arrays is usually a highly nonlinear and non-Gaussian problem, and nonlinear filtering is an effective way to realize state estimation from available observations. Developing the processing problem of blind signal in wireless sensor networks (WSNs) will greatly extend the application scope. Meanwhile, it also meets great challenges such as energy and bandwidth constrained. For solving the constrained problem in WSNs, the observed signals must be quantified before sending to the fusion center, which makes the overall noise unable to be modeled accurately by simple probabilistic model. To study the reconstruction issue of chaotic signal with unknown statistics in WSNs, a reconstructed method of chaotic signal based on a cost reference particle filter (CRPF) is proposed in this paper. The cost recerence cubature particle filter (CRCPF) algorithm adopts cubature-point transformation to enhance the accuracy of prediction particles, and cost-risk functions are defined to complete particle propagation. The effectiveness of proposed CRCPF algorithm is verified in the sensor network with a fusion center. Moreover, a generalized likelihood ratio functionis obtained by the cost increment of local reconstructed signals in the cluster-based sensor network topology model, which is used to reduce the network energy consumption by selecting working nodes. Simulation results show that compared with CPF and CRPF, the proposed algorithm CRCPF attains good performance in a WSN with unknown noise statistics. Meanwhile, the CRCPF algorithm realizes the compromise between energy consumption and reconstruction accuracy simultaneously, which indicates that the proposed CRCPF algorithm has the potential to extend other application scope.

ICMDS: Secure inter-cluster multiple-key distribution scheme for wireless sensor networks

In wireless sensor networks (WSNs), a large number of nodes are densely deployed in an open environment to gather some useful required information. These nodes are small in size, operating on limited processing capabilities with scarce working memory and battery life and not very powerful radio transceivers. They can only communicate with each other through wireless media. Radio waves are insecure in nature; therefore, by using such waves for communication there are always opportunities for different attacks on the network. Most wireless techniques are founded on the cluster-based sensor network. Forwarding cluster head's (CHs) data in a secure manner is very important because CHs collect data from the cluster members and send it to the sink node or base station. For securing CH's data, we propose a mechanism termed ICMDS (Inter-Cluster Multiple Key Distribution Scheme for Wireless Sensor Networks), which enables the securing of the entire network. In ICMDS, we use two phases of security implementations for the sensor node's authenticity while communicating with the CH. A recovery phenomena is also stated at the time when a CH ceases to function due to its high energy consumption.