Cluster-based Wireless Sensor Networks Research Articles

Improvement of cluster-based WSN protocol using fuzzy logic

<span>A wireless sensor network is a collection of wireless nodes with sensor devices that can collect data from the real world. This is because sensor nodes usually use limited-powered batteries. Therefore, if the battery on the sensor node is exhausted, the node will no longer be available. If the battery on some nodes is discharged, the sensor network will not work properly. To maintain sensor network system, there are many wireless sensor network protocols to increase energy efficiency of nodes. One of the energy-efficient methods is cluster-based protocols. These protocols divide the sensor fields into clusters and send and receive data between nodes. Thus, depending on how the cluster is constructed, the network's lifetime may be reduced or increased. Cluster-based protocols cannot always be optimal cluster configurations. These problems have been improved using fuzzy logic. In general, fuzzy logic is used to elect cluster heads based on node residual energy, node concentration and node centrality. However, it is possible that nodes close to each other at a high density area are elected as cluster heads. In this paper, we propose a method to consider the number of adjacent cluster heads instead of Node Concentration to improve the problem.</span>

ACHIEVING ENHANCED HIGH THROUGHPUT ON CLUSTER BASED WIRELESS SENSOR NETWORK WITH MULTIPLE MOBILE SINK

Wireless sensor networks (WSNs) with multiple mobile sink are expected to increase the flexibility for gathering information in large-scale sensing environment. Energy harvesting becomes one of the most important features of the sensor nodes to extend their lifetime of networks. In order to increase the life time, many energy harvesting scheme has been devoted. Despite of many advantageous on those schemes, it still faces several challenges due to heavy involvement of network periphery nodes in data retrieval, processing, buffering, and delivering tasks. In this paper, a new energy efficient technique has been employed to increase the throughput of the data transmission in cluster based wireless sensor network along multiple mobile sink. The model constructs the cluster consisting of the member nodes which route the routing information to the high density node in the cluster which is referred as cluster head. Cluster head provides the routing data to the multiple sinks propagating for data collection and packet header to establish the data transferring path in either single hop or multihop on available mobile sink trajectories. Enhanced high throughput strategies and constrainst employed on the cluster head to filter the redundant data and forward the appropriate data to end nodes with sufficient residual energy whereas to eliminate the packet loss due link destruction. Simulation results confirm the effectiveness and efficiency of the proposed approach on the performance metric such as throughput, traffic, packet losses, bandwidth utilization and packet delivery ratio.

Multi-QoS constraint multipath routing in cluster-based wireless sensor network

Achieving the best quality as per user requirement is one of the important challenges in Wireless Sensor Network (WSN) containing numerous sensor nodes with limited battery power. The time-critical applications in WSN demand energy-efficient and reliable transmission of data with limited resource availability. To resolve these issues, our proposed optimal cluster head selection method choose node as CH subjected to minimal end-to-end delay and congestion index. The nodes with maximum remaining energy, not being subjected to delay and heavy traffic have been selected as a cluster head (CH) for the next round. The Inter-cluster routing path constructed based on energy, delay, and congestion index cost function to achieve aggregated bandwidth through the establishment of multipath. MQoScMR supports adaptive CH and path selection, tuning QoS parameter according to application requirement. The technique proposed outperforms when compared with the existing protocol in terms of minimized energy consumption, delay, packet drop ratio, and high throughput.

Adaptive and Dynamic Mechanism for Round Length Determination in Cluster Based Wireless Sensor Networks

The resource-constrained nature of WSNs require efficient use of resources, especially energy, to prolong their lifetime. Clustering is one of the popular approaches to allocate the resources efficiently among the WSN nodes. In this work, we analyze the problem of round length determination in cluster based WSN which has severe impact on the energy efficiency. This problem is very important since round length determines how often the cluster head (CH) rotates or re-clustering process occurs. A longer round length will cause the CH nodes to operate for a long time and drain their energies faster than other nodes resulting in uneven energy consumption in the network, while a shorter round length results in considerable wastage of energy due to frequent running of the setup phase. Hence, we propose an adaptive and dynamic mechanism for round length determination in cluster based WSNs by adapting Behavior Curve Function modeled by quadratic Bezier curves, where we associate the remaining energy level of the cluster to its round operation length and to its assigned criticality which is defined based on network energy level. This helps to determine the number of frames in a round or how many times the data collection occurs in a cluster in a round and the criticality of the energy in the WSN. Simulation results reveal that the proposed mechanism has effectively reduced the energy consumption and improved the WSN lifetime in both homogeneous and heterogeneous network settings.

A New Intra-Cluster Scheduling Scheme for Real-Time Flows in Wireless Sensor Networks

Real-time flows using time division multiple access (TDMA) scheduling in cluster-based wireless sensor networks try to schedule more flows per time frame to minimize the schedule length to meet the deadline. The problem with the previously used cluster-based scheduling algorithm is that intra-cluster scheduling does not consider that the clusters may have internal or outgoing flows. Thus, intra-cluster scheduling algorithms do not utilize their empty time-slots and thus increase schedule length. In this paper, we propose a new intra-cluster scheduling algorithm by considering that clusters may have having internal or outgoing flows. Thus, intra-cluster scheduling algorithms do not differentiate the intra-cluster time slots and utilize their empty time slots. The objective is to schedule more flows per time frame, to reduce schedule length and improve the acceptance rate of flows. Simulation results show that the acceptance rate of the proposed scheme has a higher performance than the previous scheme.

Energy Performance of a Combined Horizontal and Vertical Compression Approach in Cluster-based WSNS

Energy Performance of a Combined Horizontal and Vertical Compression Approach in Cluster-based WSNS

Cluster based wireless sensor network for forests environmental monitoring

Cluster based wireless sensor network for forests environmental monitoring

Energy EC: An artificial bee colony optimization based energy efficient cluster leader selection for wireless sensor networks

In recent times, the applications of cluster-based Wireless Sensor Networks (WSNs) have shown rapid growth. Many researchers are working on approaches for an efficient way of cluster formation and selecting a cluster leader in a way to improve the energy efficiency of the WSN. One of the biggest challenges for the selection of a suitable cluster leader is that which criteria should be given priority over others. This paper consists of such an approach that deals with the cluster leader selection in the cluster based on the fitness function. At first, the cluster of sensor nodes is created using the k-means clustering algorithm and then the optimization of the fitness function is done with nature-inspired optimization technique is known as Artificial Bees Colony (ABC) optimization. The objective function considered for the optimization is based on; sensor’s energy; sink distance from cluster leader; and the cluster members distance. The benefit of the chosen objective function is that it yields the optimal cluster leaders. After simulating it is observed that the results obtained are better than that of other similar works.

Stability Analysis of Relay Access Protocol (RAP) using Fuzzy Logic in Wireless Sensor Networks

Cluster Head (CHs) determination is critical whereas the combination of input parameters is expected to play an important role. However, each WSN’s protocol uses a different combination of input parameters based on residual energy and several other input parameters, which produce different amount of energy consumption. Besides, most of the previous works on cluster heads selection do not take received signal strength indication (RSSI) into consideration. As a result, the sensor nodes with bad RSSI can be elected as CHs which lead to an increase in energy consumption. Moreover, the CHs use single-hop communication to forward their sensed data to the Base Station (BS). This results in high energy consumption and consequently, decrease the network lifetime. In this case, the inter-node distances may degrade the performance of the network due to long distance. Thus, this paper proposed a Relay Access Protocol (RAP) in order to reduce energy consumption in cluster-based wireless sensor networks (WSNs). The RAP protocol is a 2-tier protocol used for energy efficiency by selecting Cluster Heads (CHs) based on Fuzzy Logic (FL). The performance of the proposed protocol was evaluated under two different scenarios and compared with existing protocols through simulations. The experimental results show that the proposed scheme outperformed the existing protocols in terms of First Node Dead (FND) and Last Node Dead (LND) in all of the scenarios.

A lifetime-enhancing cooperative data gathering and relaying algorithm for cluster-based wireless sensor networks

Despite unique energy-saving dispositions of cluster-based routing protocols, clustered wireless sensor networks with static sinks typically have problems of unbalanced energy consumptions, as the cluster head nodes around the sink are typically loaded with traffic from upper levels of clusters. This results in reduced lifetimes of the nodes and deterioration of other crucial performances. Meanwhile, it has been inferred from current literature that dedicated relay cooperation in cluster-based wireless sensor networks guarantees longer lifetime of the nodes and more improved performance. Therefore, to attain further enhanced performance among the current schemes, a lifetime-enhancing cooperative data gathering and relaying algorithm for cluster-based wireless sensor networks is proposed in this article. The proposed lifetime-enhancing cooperative data gathering and relaying algorithm shares the nodes into clusters using a hybrid K-means clustering algorithm that combines K-means clustering and Huffman coding algorithms. It makes full use of dedicated relay cooperative multi-hop communication with network coding mechanisms to achieve reduced data propagation cost from the various cluster sections to the central base station. The relay node selection is framed as a NP-hard problem, with regard to communication distances and residual energy metrics. Furthermore, to resolve the problem, a gradient descent algorithm is proposed. Simulation results endorse the proposed scheme to outperform related schemes in terms of latency, lifetime, and energy consumption and delivery rates.

Performance of Quasi Oppositional Butterfly Optimization Algorithm for Cluster Head Selection in WSNs

Abstract Wireless sensor networks (WSNs) technology is attracting the most of researchers and industry due to its application in wide contexts that include the military, surveillance, monitoring of habitat, health care, public safety and environmental monitoring. The consumption of energy is a crucial challenge faced in the WSN research. Clustering is an efficient technique for limiting the energy consumption of WSNs. But considering the hierarchical and cluster-based WSNs, the cluster heads utilize a high-level of energy because of data aggregation from various sensor nodes and transmit the same to the sink node. So, proper cluster head (CH) selection is required for sensor nodes’ energy conservation to prolong the network’s lifespan of the WSNs. In this paper, a CH selection protocol is proposed that is based on the quasi oppositional butterfly optimization algorithm (QOBOA). The proposed method is compared with original butterfly optimization along with certain existing algorithms with respect to the networks’ lifetime and efficiency of energy. Simulation results show that the QOBOA based CH selection scheme outperforms the existing ones.

Dynamic coefficient-based cluster head election in wireless sensor networks

Owing to the fact that the selection of cluster heads has a significant effect on the lifetime of the network, many researches have proposed various cluster head election methodologies for cluster-based WSNs. Although recent studies have focused on adaptive approaches, in which different parameters are assembled under a function, the effect of these parameters on cluster head election is not investigated in detail. In this paper, initially, a small-scale dataset is constructed by evaluating the death of the first, the half and the last node in a cluster-based WSN using three popular cluster head parameters, including the remaining energy of the nodes, the intra-cluster communication cost and the number of neighbours. In consideration of the results, a dynamically changeable coefficient based adaptive cluster head election, DCoCH, is proposed. The coefficients of the cluster head election parameters show alteration within three different periods of the lifetime of the network. DCoCH is compared with two recent adaptive based cluster head election methodologies for various WSN parameters and the results show that DCoCH outperforms equivalent approaches for different values of the location of the base station, the size of the network, the number of the nodes, the initial batteries of the nodes and the distribution of the nodes.

Security and Privacy in Medical Internet of Things and Cluster-Based Wireless Sensor Networks for Health Care

Security and Privacy in Medical Internet of Things and Cluster-Based Wireless Sensor Networks for Health Care

A Data Clustering Algorithm for Detecting Selective Forwarding Attack in Cluster-Based Wireless Sensor Networks.

In cluster-based wireless sensor networks, cluster heads (CHs) gather and fuse data packets from sensor nodes; then, they forward fused packets to the sink node (SN). This helps wireless sensor networks balance energy effectively and efficiently to prolong their lifetime. However, cluster-based WSNs are vulnerable to selective forwarding attacks. Compromised CHs would become malicious and launch selective forwarding attacks in which they drop part of or all the packets from other nodes. In this paper, a data clustering algorithm (DCA) for detecting a selective forwarding attack (DCA-SF) is proposed. It can capture and isolate malicious CHs that have launched selective forwarding attacks by clustering their cumulative forwarding rates (CFRs). The DCA-SF algorithm has been strengthened by changing the DCA parameters (Eps, Minpts) adaptively. The simulation results show that the DCA-SF has a low missed detection rate of 1.04% and a false detection rate of 0.42% respectively with low energy consumption.

Reliable data transmission method based on 6LoWPAN for building energy systems

The building energy internet of things is based on radio frequency technology and a wireless sensor network that can collect building energy consumption data in real time. However, with the increasing complexity of wireless sensor network topology, there is a problem of insufficient IP address space relying on IPv4 protocol. In this paper, a design scheme of a building energy system based on 6LoWPAN network is proposed. IPv4/IPv6 address conversion is used to realise the access of IP addresses to each other, so as to monitor building energy consumption information anytime and anywhere. In view of the shortcomings of existing wireless network data transmission methods in low energy consumption and high reliability in building energy monitoring applications, a reliable data transmission method based on multipath routing coding algorithm is proposed. This strategy improves the transmission reliability of the network by increasing the number of redundant packets, and reduces the energy consumption of the network by reducing the number of transmission paths. The simulation results show that the proposed method can effectively improve the success rate of data packet transmission, reduce the standard energy consumption of sensor networks, and provide an effective method for the application of wireless sensor networks in building energy monitoring systems. Practical application: This paper studies how to improve transmission reliability and energy efficiency in cluster-based WSN and proposes a multi-path transmission strategy for selective coding of intermediate cluster head nodes. The strategy improves the transmission reliability of the network by increasing the number of transmissions of redundant packets and reduces the network energy consumption by reducing the number of transmission paths. It has good use value for the actual development and application of the building energy consumption monitoring system.

Structural Compressed Network Coding for Data Collection in Cluster-Based Wireless Sensor Networks

Structural Compressed Network Coding for Data Collection in Cluster-Based Wireless Sensor Networks

E-SATS: An Efficient and Simple Time Synchronization Protocol for Cluster- Based Wireless Sensor Networks

Over the past decade, the Internet of Things (IoT) has attracted enormous interest from the research community and industry. IoT requires a synergy of various technologies, and wireless sensor networks (WSNs) are poised to play a critical role in many IoT applications like weather monitoring, smart-grids, smart-city and so on. The synchronization of local clocks of the WSN nodes is essential in many network functionalities, and thus a time synchronization protocol is required in WSNs. Although several synchronization protocols have been proposed for WSNs, most of them are simulation-based works. They make many assumptions at a high-abstraction level and do not consider the conditions of the line-of-sight (LOS) in the network. These factors significantly affect the performance of these protocols. Thus, conclusive experimental proof of the effectiveness of these protocols for different LOS conditions is required. In this direction, this paper proposes a time synchronization protocol called efficient and simple algorithm for time synchronization (E-SATS) for a cluster-based WSN. In this paper, E-SATS has been tested on a large-sized WSN testbed in different LOS scenarios and compared with the existing state-of-the-art protocols. E-SATS outperformed existing protocols by achieving up to six times better accuracy as compared to existing protocols with significantly lesser computations and energy consumption.

A Fuzzy Based Techniques For Energy Efficient Cluster Head Selection For Wireless Sensor Network

WSN is split into various clustering nodes in order to obtain proper arrangement and network stability and thus drags the system's lifetime. Each detector node transmits the necessary data to cluster head of each cluster in each cluster-based WSN. Cluster head is liable for collecting the data gathered and forwarding it to sink of network deployed. This manuscript suggests an enhanced Fuzzy-based CH selection algorithm that observes the leftover energy, node compactness and sink distance as input to the Fuzzy inference system. For each node, the eligibility index is calculated to select the head of the cluster. By taking in account the probability assigned to , this algorithm chooses the best candidate for place of the cluster advisor. To each sensor node and helps to increase the energy efficient of network.

A robust uncertainty-aware cluster-based deployment approach for WSNs: Coverage, connectivity, and lifespan

Predicting the expected performance of Wireless Sensor Networks (WSNs) is the key to their successful deployment. This paper investigates the following fundamental problem: how to judiciously plan the physical and the logical topologies of a WSN so that performance demands including network connectivity, sensing coverage quality, reliability, and lifetime are all satisfied with the least possible cost. To handle the uncertainty related to sensor connectivity and coverage, we devise a probabilistic-based communication cost model, and we exploit the belief functions theory to define a generic evidence fusion scheme that captures several characteristics of real-world applications. The uncertainty-aware cluster-based WSNs deployment problem is formulated as a multi-objective binary nonlinear and non-convex optimization problem, and an efficient heuristic using genetic algorithms is investigated. Using both simulations and testbed-based experiments, we show that the proposed deployment approach can fulfill the user performance needs, which confirms that the deployment of real-world fusion-based WSNs with predictable performance is possible.

MCRO-ECP: Mutation Chemical Reaction Optimization based Energy Efficient Clustering Protocol for Wireless Sensor Networks

Wireless sensor networks encounter energy saving as a major issue as the sensor nodes having no rechargeable batteries and also the resources are limited. Clustering of sensors play a pivotal role in energy saving of the deployed sensor nodes. However, in the cluster based wireless sensor network, the cluster heads tend to consume more energy for additional functions such as reception of data, aggregation and transmission of the received data to the base station. So, careful selection of cluster head and formation of cluster plays vital role in energy conservation and enhancement of lifetime of the wireless sensor networks. This study proposes a new mutation chemical reaction optimization (MCRO) which is an algorithm based energy efficient clustering protocol termed as MCRO-ECP, for wireless sensor networks. The proposed protocol is extensively developed with effective methods such as potential energy function and molecular structure encoding for cluster head selection and cluster formation. While developing potential functions for energy conservation, the following parameters are taken into account: neighbor node distance, base station distance, ratio of energy, intra-cluster distance, and CH node degree to make the MCRO-ECP protocol to be potential energy conserver. The proposed protocol is studied extensively and tested elaborately on NS2.35 Simulator under various senarios like varying the number of sensor nodes and CHs. A comparative study between the simulation results derived from the proposed MCRO-ECP protocol and the results of the already existing protocol, shows that MCRO-ECP protocol produces significantly better results in energy conservation, increase network life time, packets received by the BS and the convergence rate.