Cluster Head Rotation Research Articles

Cross-Layer Energy Based Clustering Technique for Heterogeneous Wireless Sensor Networks

Increasing the lifetime of the network is one of the key research issues in Wireless Sensor Networks. Sensor nodes residing in hot spot locations get drained out of energy very quickly, which leads to disruption in operations of the network. Thus, a cluster-based algorithm for increasing energy efficiency is required to extend the lifetime of the network. In this research work, Cross-layer Energy based Clustering (CEC) technique is proposed to form clusters of sensor nodes in hexagonal shape. The cluster head has opted from the members of cluster itself on the basis of the ideal cluster head distance and the remaining energy of sensor nodes. In order to make a balance between the consumption of energy and the network traffic, the rotation of cluster heads is performed dynamically. The energy level of a node also gets affected due to collisions happening during the transmissions. These collisions can be prevented by applying protocols which are free of contention. In addition to this, slots are allocated by cluster head to all member nodes within a cluster on the basis of their remaining energy so that nodes can switch to sleep mode. Further, to reduce the consumption of energy, data aggregation is also used on the basis of the remaining energy of the cluster head. The performance of proposed CEC technique is evaluated and compared with existing techniques such as SOEECP, LCM and EEPCA. Experimental results show that CEC performs better than existing techniques in measures of the lifetime of the network, consumption of energy, the number of data packets received and accuracy of aggregated data along with the statistical analysis.

RETRACTED ARTICLE: Implementation of thermal aware wireless sensor network clustering algorithm based on fuzzy and spider optimized cluster head selection

In a modern approach, a smart grid requires an innovation on various fronts such as a wireless sensor network which is an important component of smart grid applicability. To fulfill the Quality of Service (QoS) needs in smart grid network, a structure of network and topology should be optimized especially in the urban areas. The clustering methodologies are useful technique for optimizing network topologies. In clustering, the clustering process consists of cluster head node selection and rotation which is based on Residual Energy, Distance of node from base station etc. However, the impact of temperature rise has not been considered so far. Based on the previous related works, this paper proposes a Thermal Aware solution based on combining Eigen Centrality Fuzzy Cluster size Control and Spider Optimization Algorithm. Furthermore, an influence of temperature can be realized through Received Signal Strength (RSS) and the number of packets received. The proposed algorithm is simulated in MATLAB and implemented in hardware test bed using Zigbee and PIC microcontroller. Consequently, the result confirms the impact of thermal heat on Cluster Head selection control and also the prediction of number of rounds.

Two-Hierarchy Communication/Computation Hybrid Optimization Protocol for Railway Wireless Monitoring Systems

Energy efficiency of wireless sensors is critical to maintaining the function of the monitoring system. Generally, the energy consumed in data transmission is much larger than in compression. Hence, decreasing data packet size with the aid of data compression before transmission can facilitate the reduction of energy consumption in communication. However, the energy consumed in data computation is also considerable, and improper computation ways may incur more energy consumption. To address this issue, in this article, two-hierarchy communication and computation hybrid optimization protocol is presented to minimize the total energy consumption. First, the cluster heads (CHs) rotation and clusters updating strategies are proposed in the communication layer, and the optimized adaptive compression ratios for the CHs are adopted in the computation layer. The hybrid optimization scheme is performed from the views of communication and computation synergistically to improve energy efficiency. The simulation results show the superiority of the proposed protocol compared with other outstanding protocols

An Improved Energy-Efficient Clustering Protocol to Prolong the Lifetime of the WSN-Based IoT

A wireless sensor network (WSN) is an important part of the Internet of Things (IoT). However, sensor nodes of a WSN-based IoT network are constraining with the energy resources. A clustering protocol provides an efficient solution to ensure energy saving of nodes and prolong the network lifetime by organizing nodes into clusters to reduce the transmission distance between the sensor nodes and base station (BS). However, existing clustering protocols suffer from issues concerning the clustering structure that adversely affects the performance of these protocols. In this study, we propose an improved energy-efficient clustering protocol (IEECP) to prolong the lifetime of the WSN-based IoT. The proposed IEECP consists of three sequential parts. First, an optimal number of clusters is determined for the overlapping balanced clusters. Then, the balanced-static clusters are formed on the basis of a modified fuzzy C-means algorithm by combining this algorithm with a mechanism to reduce and balance the energy consumption of the sensor nodes. Lastly, cluster heads (CHs) are selected in optimal locations with rotation of the CH function among members of the cluster based on a new CH selection-rotation algorithm by integrating a back-off timer mechanism for CH selection and rotation mechanism for CH rotation. In particular, the proposed protocol reduces and balances the energy consumption of nodes by improving the clustering structure, where IEECP is suitable for networks that require a long lifetime. The evaluation results prove that the IEECP performs better than existing protocols.

An Event-Aware Cluster-Head Rotation Algorithm for Extending Lifetime of Wireless Sensor Network with Smart Nodes.

Smart sensor nodes can process data collected from sensors, make decisions, and recognize relevant events based on the sensed information before sharing it with other nodes. In wireless sensor networks, the smart sensor nodes are usually grouped in clusters for effective cooperation. One sensor node in each cluster must act as a cluster head. The cluster head depletes its energy resources faster than the other nodes. Thus, the cluster-head role must be periodically reassigned (rotated) to different sensor nodes to achieve a long lifetime of wireless sensor network. This paper introduces a method for extending the lifetime of the wireless sensor networks with smart nodes. The proposed method combines a new algorithm for rotating the cluster-head role among sensor nodes with suppression of unnecessary data transmissions. It enables effective control of the cluster-head rotation based on expected energy consumption of sensor nodes. The energy consumption is estimated using a lightweight model, which takes into account transmission probabilities. This method was implemented in a prototype of wireless sensor network. During experimental evaluation of the new method, detailed measurements of lifetime and energy consumption were conducted for a real wireless sensor network. Results of these realistic experiments have revealed that the lifetime of the sensor network is extended when using the proposed method in comparison with state-of-the-art cluster-head rotation algorithms.

An energy-efficient unequal clustering routing protocol for wireless sensor networks

Wireless sensor networks have drawn tremendous attentions from all fields because of their wide application. Maximizing network lifetime is one of the main problems in wireless sensor networks. This article proposes an energy-efficient routing protocol which adopts unequal clustering technology to solve the hot spots problem and proposes double cluster head strategy to reduce the energy consumption of head nodes in the clusters. In addition, to balance the energy consumption between cluster heads and cluster members, a hybrid cluster head rotation strategy based on time-driven and energy-driven is proposed, which can make the timing of rotation more reasonable and the energy consumption more efficient. Finally, we compare the proposed protocol with LEACH, DEBUC, and UCNPD by simulation experiments. The simulation results prove that our proposed protocol can effectively improve the performance in terms of network lifetime, energy consumption, energy balance, stability, and throughput.

Influence of Received Signal Strength on Prediction of Cluster Head and Number of Rounds

Research studies reveal the fact that clustering improves energy efficiency and network lifetime in wireless sensor networks (WSNs). In clustering, cluster head (CH) selection and rotation are the key techniques that have been adopted over a decade. CH selection based on the residual energy of the node, the distance of the node from the base station (BS), the degree of neighboring nodes (DNNs), the rate of recurrent communication of sensor nodes (RCSNs), etc., has been dealt in many articles. However, the impact of an obstacle on CH selection and number of rounds prediction is not addressed. Furthermore, the influence of an obstacle can be realized through the received signal strength indicator (RSSI). Hence, this proposal incorporates the RSSI as one of the parameters in CH selection. Fuzzy logic is employed to predict the CH. Then, based on the energy consumption of the CH, the number of rounds for the node to continue as the CH is predicted using a threshold. The proposal is simulated in MATLAB and implemented in hardware using Zigbee and Atmega controller. The results confirm the impact of received signal strength on CH selection and the number of rounds prediction. Furthermore, to overcome the shortfall of the existing first-order radio model, a linear regression-based energy prediction model is proposed. The proposed energy prediction model exhibits closeness with actual energy consumption which demonstrates its efficacy.

Energy Efficient WSN with Cluster Head Rotation Algorithm for Underground Mine Supervising Environment

Energy Efficient WSN with Cluster Head Rotation Algorithm for Underground Mine Supervising Environment

A Novel Energy Harvesting: Cluster Head Rotation Scheme (EH-CHRS) for Green Wireless Sensor Network (GWSN)

Wireless Sensor Network (WSN) serves as a better solution for remote unmanned monitoring situations. The harvesting capabilities in Green Wireless Sensor Network (GWSN) do not satisfy the real energy demand and it greatly determines the lifetime of the GWSN. The (a) excess harvesting leads energy overflow and (b) meager energy harvesting leads unavailability in monitoring of the event. The energy management favoring continuous monitoring in WSN is the problem addressed in this article. This article concentrates in creating a solution for energy outage and energy overflow problem in GWSN. The residual energy of the buffer and current harvesting rate is considered to create an energy efficient routing algorithm for GWSN. The energy arrival is poisson in nature, the energy harvesting, storing and utilization in the battery is realized as a Double Chain Markov Model. The algorithm proves to be energy efficient and delivers high throughput when compared with Stable Election Protocol (SEP) algorithm. The proposed Energy Harvesting—Cluster Head Rotation Scheme (EH-CHRS) algorithm minimizes the energy overflow and energy outage in the network by optimal Cluster Head (CH) selection and CH rotation method. The algorithm is analyzed with different harvesting rate λ = 1 and 2. The EH-CHRS algorithm also promotes reduced drop packet when compared to the SEP protocol. The algorithm also resist energy hole problem and HOT SPOT problem in the network.

CER-CH: Combining Election and Routing Amongst Cluster Heads in Heterogeneous WSNs

Heterogeneous Wireless Sensor Networks (WSNs) are essential to the IoT vision. WSNs implement a virtual layer that can gather data about the real world. WSNs are composed of wireless battery powered devices that can have heterogeneous features related to computational power, memory, and communication capabilities. Because devices are battery powered, gathering data in an energy efficient way is crucial for the lifespan of the network. Clustering is a reasonable solution. This organises the devices into sets (clusters). Each cluster has a cluster head (CH) that gathers data from the nodes belonging to its cluster and communicates with other CHs in order to report data to a centralised base station (BS). This is usually achieved via a CH routing tree that is rooted at the BS. Beside clustering, the rotation in the role of CHs amongst the nodes of the network is a standard means to better distribute energy consumption. In this paper we propose a novel approach (CER-CH) where the CH routing tree definition and the CH rotation are combined together. More precisely, starting from any clustering criteria, we propose a novel rotation heuristic combined with a novel top-down CH routing tree definition in order to balance the node energy consumption and generate more energy efficient CH routing trees. Our experiments show that our rotation strategy enhances on average the network lifespan of 20% when compared to the state of art protocols.

An Energy-Efficient Clustering Algorithm Combined Game Theory and Dual-Cluster-Head Mechanism for WSNs

A novel energy-efficient clustering algorithm was proposed which aimed at improving the energy efficiency of WSNs via reducing and balancing energy consumption in this paper. The lemma concerning the dual-cluster-head mechanism which was designed to reduce the energy overhead during the process of rotation of Cluster Heads (CHs) was proposed and proven at first. In addition, a non-cooperative game model was presented with the purpose of balancing the energy consumption among the Cluster Heads. Besides, the Nash Equilibrium Point (NEP) of the game model was presented and the corresponding proof was provided. Subsequently, the Energy-efficient Clustering algorithm combined Game theory and Dual-cluster-head (ECGD) mechanism was detailed, which took the energy efficiency in both of the intra-cluster and inter-cluster communication into consideration. Finally, extensive experiments were conducted via simulation and the simulation results were compared with the existing Clustering strategies in terms of energy efficiency and network performance. The analyses of results have shown that the ECGD can improve energy efficiency and extend the network lifespan effectively.

Data Collection Through Mobile Vehicles in Edge Network of Smart City

With increasing technological facilities, billions of sensor devices are deployed in the smart city, which allows to sense and collect the status and information of all kinds of infrastructures in the city. Those large number of sensing nodes form many self-organized wireless sensor networks (WSNs). Although the single WSN has been widely studied by researchers. However, few studies have focused on how to effectively connect to Internet of Things (IoT) and collect data in many decentralized WSNs of smart city with a low cost. In this paper, a cluster head rotation joint mobile vehicle data collection (CHR) scheme is proposed to effectively collect data from many decentralized WSNs in smart city with a low cost. In CHR scheme, each WSN selects one or multiple nodes which can connect to mobile vehicles as the cluster heads. Then all the in-network sensor nodes send their data to cluster head through multi-hop communication, due to the cluster head can connect to mobile vehicles, so when mobile vehicles pass by cluster head, the data of cluster head can be sent to mobile vehicles and brought to the data center to process. We first propose a single cluster head rotation joint mobile vehicle data collection (SCHR) scheme to collect data by only using a single CH in a WSN in which the CH rotation and clustering algorithms are carefully designed to balance in-network energy consumption. Then multiple cluster head rotation joint mobile vehicle data collection (MCHR) scheme is proposed to further balance the energy consumption and prolong the network lifetime in which multiple cluster heads are selected to be jointly responsible for the data collection task. The extensive experiments show that the CHR scheme has good performance in the network energy, network lifetime and network transmit capacity.

An energy balance and mobility prediction clustering algrithm for large-scale UAV ad hoc networks

Creating a clustering structure is considered the performance of radio frequency (RF) stealth for data link in the battlefield environment and the dynamic topology characteristic for larger-scale unmanned aerial vehicle (UAV) ad hoc networks. This problem is of a great importance-to get low intercept probability of the data link and low randomness of clustering structure. An energy balance and mobility prediction (EBMP) clustering algorithm is proposed. In the initial clustering stage, the power management for information transmission is conducted in the network layer and the MAC layer. The Doppler shift is implemented to estimate the relative speeds stability degree between neighboring UAVs when they exchange Hello packets. It can be selected as cluster head (CH) where one UAV associateslower energy consumption with higher relative stability. In the cluster maintaining stage, a CH rotation process for the dynamic topology to improve resource utilization efficiency. The inter-cluster communication is enhanced by dynamic packet forwarding gateway. The simulations and analysis show that this scheme can provide better results for larger-scale UAV ad hoc networks compared to MPBC and MPCR in terms of improving CH lifetime and throughput, reducing average delay.

LAR-CH: A Cluster-Head Rotation Approach for Sensor Networks

In wireless sensor networks, sensors are expected to work autonomously for a long time with a finite source of energy. Therefore, the sensors must be energy efficient in their duties to prolong the network lifetime. Cluster-based protocols are widely used in the literature to prolong the network lifetime. Clustering protocols use cluster-head rotation (CH-rotation) and re-clustering methods to rotate the energy-intensive load of CH nodes among other nodes of the network. Re-clustering is a global method, so its overhead cost is higher compared with CH-rotation. Existing clustering protocols employ an energy threshold on the residual energy of the CH for CH-rotation. This energy threshold can be static or dynamic. The static threshold does not consider the current energy load of the CH for CH-rotation. Thus, it increases premature death of CH nodes. In this paper, a load-aware rotation of CH (LAR-CH) approach is proposed, which sets a dynamic threshold for CH-rotation to reduce the premature death of CH nodes. The LAR-CH uses the current energy load of the CH to determine the dynamic threshold for CH-rotation. The simulation results show that LAR-CH reduces the premature death of CH nodes by 40% compared with the low-energy adaptive clustering hierarchy protocol.

Energy aware cluster based routing protocol over distributed cognitive radio sensor network

Cognitive radio sensor network (CRSN) is a combination of wireless sensor network (WSN) and opportunistic spectrum access technology. It involves the issues related to energy and dynamic spectrum inherited by WSN and cognitive radio network (CRN) respectively. CRSN poses research challenges in designing an efficient topology control for communication in network. In this paper, we propose an Energy Aware Cluster based Routing Protocol (EACRP) for CRSN that jointly considers both the energy and dynamic spectrum challenges. Reported schemes for CRSN suffer from high frequency of re-clustering due to PU activities and are energy inefficient. The proposed scheme employs a self-organized distributed clustering to obtain less average node power by producing the optimal number of clusters. To mitigate the effect of PUs’ activities, our proposed scheme forms clusters having more number of common channels and employs the concept of cooperative sensing in selecting the data channels for intra-cluster communication. To enhance inter-cluster connectivity, EACRP selects gateway nodes having more energy, closer to sink node and more number of common channels with neighboring nodes. Furthermore, a cluster-head (CH) rotation mechanism is employed that picks the CH based on nodes’ residual energy values, available channels, neighbors and distance to the sink in order to have longer network lifetime. Upon detection of an event, the EACRP aims to route the event data through an energy efficient and stable path from source node to the sink node. On performance evaluation, we found that EACRP outperforms in terms of end-to-end packet delay, node energy consumption, packet delivery ratio and stability of selected gateway nodes than considered competitive approaches.

An Energy-Aware Clustering Protocol Based Grid For WSN

One of the most critical problems in Wireless Sensor Networks (WSNs) is to how to reduce energy consumption and prolong the network lifetime of WSNs. Clustering is of the solutions, which have been used to reduce energy consumption by partition the network into clusters. However; most of the clustering schemes select the cluster head (CH) either randomly or based on centralized manner. Both approaches lead to deficient utilization of WSN resources. Therefore, the purpose of this paper is to illustrate a new multi-hop clustering protocol called EACPG, which aimed to provide energy efficiency and maintain load balancing. In EACPG the network is divvied into multiple numbers of virtual square grids. Also, different parameters are considered for cluster head election based on distributed manner. In addition, a new mechanism for CH rotation is used in order to maintain load balancing between CHs. Finally, Results show that the proposed scheme has better performance in term of energy consumption and the number of alive sensor nodes and throughput.

Energy Threshold-based Cluster Head Rotation for Routing Protocol in Wireless Sensor Networks

Energy efficiency represents a fundamental issue in WSNs, since the network lifetime period entirely depends on the energy of sensor nodes, which are usually battery-operated. In this article, an unequal clustering-based routing protocol has been suggested, where parameters of energy, distance, and density are involved in the cluster head election. Besides, the sizes of clusters are unequal according to distance, energy, and density. Furthermore, the cluster heads are not changed every round unless the residual energy reaches a specific threshold of energy. The outcomes of the conducted simulation confirmed that the performance of the suggested protocol achieves improvement in energy efficiency.

Optimal Node Clustering and Scheduling in Wireless Sensor Networks

Selection and rotation of cluster head (CH) is a well known optimization problem in hierarchical Wireless sensor networks (WSNs), which affects its overall network performance. Population-based metaheuristic particularly Artificial bee colony (ABC) has shown to be competitive over other metaheuristics for solving optimization problems in WSNs. However, its search equation contributes to its insufficiency due to poor exploitation phase and low convergence rate. This paper, presents an improved artificial bee colony (iABC) metaheuristic with an improved search equation, which will be able to search an optimal solution to improve its exploitation capabilities moreover, in order to increase the global convergence of the proposed metaheuristic, an improved approach for population sampling is introduced through Student’s-t distribution. The proposed metaheuristic maintain a balance between exploration and exploitation search abilities with least memory requirements, with the use of first of its kind compact Student’s-t distribution, which is particularly suitable for WSNs limited hardware environment. Further utilising the capabilities of the proposed metaheuristic, an improved artificial bee colony based clustering and scheduling (iABC-CS) scheme is introduced, to obtain optimal cluster heads (CHs) along with optimal CH scheduling in WSNs. Simulation results manifest that iABC-CS outperform over other well known clustering algorithms on the basis of packet delivery ratio, energy consumption, network lifetime and end to end delay.

Load-Aware Cluster-Head Rotation in Wireless Sensor Network

In a wireless sensor network (WSN), few to thousands of sensors monitor information about nearby events and cooperatively transmit it to the base station for further processing. The sensors do their duty with a finite energy source, and in extreme conditions, the replacement or recharge of this energy is not possible always. Therefore, it is extremely important for every sensor to efficiently use its finite energy to make the network durable. Clustering based protocols are widely used in the literature as an energy saving scheme. In a cluster, the head node consumes more energy than regular member nodes. The head node not only senses the data from its surroundings but also receives the data from associated members, aggregates the received data with its own data, and transmits the aggregated data to the base station. The existing clustering protocols use cluster-head rotation and re-clustering approaches to evenly distribute the energy-intensive load of cluster-head among all the member nodes and all the nodes of the network, respectively. This paper proposes a mechanism that considers the current energy load of head node to determine the dynamic threshold for cluster-head rotation to minimize the premature death of cluster-heads. The proposed cluster-head rotation mechanism is compared with the other version of the proposed protocol where cluster-head is rotated based on a static threshold on residual energy of cluster-head. The results show that the proposed rotation mechanism outperforms its comparatives.

Wireless camera network with enhanced SIFT algorithm for human tracking mechanism

In order to deal with the wireless camera networks (WCNs), whose detecting power of conventional camera networks with elasticity, reconfigurability and with a simple deployment of wireless sensor networks (WSN) for efficiently addressing the significant responsibilities in the method of cluster based human (object) tracking, such as integrating the measurement, including or ruling out in the cluster and cluster head rotation. The WCN effectively uses division friendly representation and methods in which every node contributes to the estimation in each methodology without the requirement of any previous information of the remaining the nodes. These methods are integrated in two different schemas so that they can be deployed with the same mean time without considering the cluster size. Thus, the observation and practical evaluation shows that the proposed schemes and methodology drastically reduces the energy consumption and computational trouble in accordance to the existing methodology.