High Residual Energy Research Articles

Enhanced three Layer Energy Efficient Clustering (ETLEEC) Algorithm for Wireless Sensor Networks

Providing route stability isconsidered to be crucial task in Wireless Sensor Networks (WSNs). Hierarchical topologyis considered to preserve the energy of the sensor networks in which the nodes with the higher residual energy is used to gather the data. However, most of the existingmethods on clustering have adopted a two-layer hierarchy. This paper proposes an Enhanced Three Layer Energy Efficient Clustering (ETLEEC) algorithm for WSNs. The proposed method uses an extra layer called the lattice head where the cluster head collects the information form sensor nodes and sends it to the lattice head which in turn send to the base station. Simulations are performed in network simulator and the results show that the proposed system is more efficient in terms of energy and quality of service compared to all other existing distributed algorithms.

Optimized Energy Harvesting, Cluster-Head Selection and Channel Allocation for IoTs in Smart Cities.

This paper highlights three critical aspects of the internet of things (IoTs), namely (1) energy efficiency, (2) energy balancing and (3) quality of service (QoS) and presents three novel schemes for addressing these aspects. For energy efficiency, a novel radio frequency (RF) energy-harvesting scheme is presented in which each IoT device is associated with the best possible RF source in order to maximize the overall energy that the IoT devices harvest. For energy balancing, the IoT devices in close proximity are clustered together and then an IoT device with the highest residual energy is selected as a cluster head (CH) on a rotational basis. Once the CH is selected, it assigns channels to the IoT devices to report their data using a novel integer linear program (ILP)-based channel allocation scheme by satisfying their desired QoS. To evaluate the presented schemes, exhaustive simulations are carried out by varying different parameters, including the number of IoT devices, the number of harvesting sources, the distance between RF sources and IoT devices and the primary user (PU) activity of different channels. The simulation results demonstrate that our proposed schemes perform better than the existing ones.

An Improved Three-Layer Low-Energy Adaptive Clustering Hierarchy for Wireless Sensor Networks

Topology control in wireless sensor networks (WSNs) balances the communication load on sensor devices and increases the network lifetime and scalability. Hierarchical or cluster-based design is one of the approaches to conserve the energy of the sensor networks in which the nodes with the higher residual energy could be used to gather data and route the information. However, most of the previous work on clustering has adopted a two-layer hierarchy, and only few methods studied a three-layer scheme instead. Based on a three-layer hierarchy, this paper has proposed a semi-distributed clustering approach by considering a hybrid of centralized gridding for the upper level head selection and distributed clustering for the lower level head selection. The simulation results show that the proposed approach is more efficient than other distributed algorithms. Therefore, the technique presented in this paper could be further applied to large-scale WSNs.

Multi-constraint multi-objective QoS aware routing heuristics for query driven sensor networks using fuzzy soft sets

In this paper, a fuzzy based distributed power aware routing scheme considering both energy and bandwidth constraints, especially for query driven applications in the asynchronous duty-cycled wireless sensor networks are devised. The proposed multi-constraint, multi-objective routing optimization approach under strict resource constraints guarantees reliability and fast data delivery along with efficient power management in spite of unreliable wireless links and limited power supply. In query driven applications, the request from the sink to the individual sensor node will be a broadcast message, whereas the individual sensor nodes replies back to sink as unicast messages. In the proposed work, the fuzzy approach and “A Star” algorithm are utilized for satisfying energy and bandwidth constraints to route the broadcast messages of the sink while querying all the sensor nodes in the network. Every node will be provided with a guidance list, which is used to decide the next best neighbor node with good route quality for forwarding the received multi-hop broadcast messages. The route quality of the every node is estimated with fuzzy rules based on the network parameters such as maximum remaining energy, minimum traffic load and better link quality to increase the network lifetime. The provision of overhearing the broadcast messages and acknowledgements within the transmission range minimizes the effort to search for the active time of nodes while routing the broadcast messages with asynchronous scheduling. Further, in the proposed work only the time slot of its nearest neighbor relay node (to which packets are to be forwarded) is learnt to reduce the number of message transmissions in the network. For the unicast message replies, the fuzzy membership function is modified and devised based on the routing metrics such as higher residual energy, minimum traffic loads and minimum hop count under energy and bandwidth constraints. Also, the multi-hop heuristic routing algorithm called Nearest Neighbor Tree is effectively used to reduce the number of neighbors in the guidance list that are elected for forwarding. This helps to increase the individual sensor node’s lifetime, thereby maximizes the network lifetime and guarantees increased network throughput. The simulation results show that the proposed technique reduces repeated transmissions, decreases the number of transmissions, shortens the active time of the sensor nodes and increases the network lifetime for query driven sensor network applications invariant to total the number of sensor nodes and sinks in the network. The proposed algorithm is tested in a small test bed of sensor network with ten nodes that monitors the room temperature.

Application of Data Fusion and Sensor Head Algorithm for Data Extraction from Wireless Sensor Networks

Objectives: The primary objective of the paper is to propose an optimized data extraction technique to obtain data from the Wireless Sensor Networks (WSNs)using ‘Sensor Head Algorithm’ and Data Fusion. Methods/Statistical Analysis: The proposed idea works in a three-layered architecture which includes the deployed sensors, the selected Sensor Head and the Static Data Sink. The Sensor Head Algorithm is used to select a sensor head that collects data from all sensors. The Data Fusion algorithm results in generation of unified data which is used to derive the output. Finally, the fused data is transmitted from the Sensor Head to the Static Data sink. Findings: A sample data was used to verify the working of the model using simulations. On the application of Sensor Head Algorithm, the sensors are assigned priorities on the basis of their residual energies. The sensor with highest residual energy becomes the Sensor Head. All the sensors transmit their data to the Sensor Head where the Data Fusion takes place later. Data Fusion initially removes redundancy in from the collected data making the processing simpler and saving the energy. The resultant data is then used to generate fused inference using Fuzzy Logic Controller (FLC). These inferences are recorded and later used to generate final output. The proposed idea ensures reduction of load on the system, simplifies the previously proposed methods, reduces latency in data collection and improves network lifetime. This data, finally transmitted to the static data sink, can be used for finding inferences or reaching a conclusion about the target area in the desired way. Application/Improvements: In the current paper, we have proposed an idea which we shall use to develop a fully functional model. Since, the proposed technique is concerned with data extraction, it can be applied to every situation where the Wireless Sensor Network is deployed.

Design of Energy Efficient Cluster Head Routing Algorithm for Heterogeneous Wireless Sensor Networks

The cluster based technique is one of the good approaches to reduce energy consumption in Wireless Sensor Networks (WSNs). A new Energy Efficient Cluster Head Routing protocol for heterogeneous WSN, which is called EECHR is proposed and evaluated which works on sleep-awake policy that help in prolonging lifetime of the network. In EECHR, the cluster head is elected if its residual energy is more than system average energy of the network. The nodes with high initial and residual energy will have more chances to become cluster head. Finally the simulation results show that EECHR enhances lifetime of heterogeneous sensor network as compared to other protocols i.e., Distributed Energy Efficient Clustering (DEEC) and Threshold Sensitive Stable Electron Protocol (TSEP).

Energy Efficient, Lifetime Improving and Secure Periodic Data Collection Protocol for Wireless Sensor Networks

The most emerging prominent sensor network applications collect data from sensor nodes and monitors periodically. Resource constraint Sensor motes sense the environment and transit data to the remote sink via multiple hops. Minimum energy dissipation and secure data transmission are crucial to such applications. This paper delivers an energy efficient, lifetime improving, secure periodic Data Gathering scheme that is a hybrid of heuristic path establishment and secure data transmission. This protocol uses artificial intelligence (AI) based A* heuristic search algorithm to establish energy efficient admissible optimal path to sink in terms of high residual energy, minimum hop counts and high link quality. This scheme also adopts block encryption Rivest Cipher (RC6) Algorithm to secure the transmission of packets. This code and speed optimized block encryption provides confidentiality against critical data and consumes less energy for encryption. This proposed method increases the network lifetime there by reducing the total traffic load. Evaluation of performance analysis of this algorithm using Network Simulator (NS2) shows the superiority of the proposed scheme.

Performance Analysis of Hybrid TB-LEACH Enegy based Multihop Protocol

An energy efficient routing protocol named Hybrid TBLEACH Energy Based Multihop Protocol is proposed. The proposed protocol selects sensor nodes having higher residual energy as Cluster Heads which communicate with the base station by the means of minimum spanning tree. It has reduced energy consumed by sensor nodes. In this paper, performance of proposed protocol is analyzed with the effect of change in position of base station. The performance of proposed protocol is compared with the previous proposed protocols LEACH, TB-LEACH and CTPEDCA protocol.

A Novel Energy Efficient Clustering Mechanism in Wireless Sensor Network

The area of wireless sensor networks (WSNs) is one of the emerging and fast growing fields in the scientific world. This has brought about developing low cost, low-power and multi-function sensor nodes. However, the major fact that sensor nodes run out of energy quickly has been an issue and many energy efficient routing protocols have been proposed to solve this problem and preserve the longevity of the network. This is the reason why routing techniques in wireless sensor network focus mainly on the accomplishment of power conservation. Most of the recent publications have shown so many protocols mainly designed to minimize energy consumption in sensor networks. This paper proposes a hierarchical routing technique which shows energy efficiency. Our technique selects cluster head with highest residual energy in each communication round of transmission and also takes into account, the shortest distance to the base station from the cluster heads. Simulation results show that hierarchical routing technique with different level of hierarchy prolongs the lifetime of the network compared to other clustering scheme and the energy residual mean value after some communication rounds of simulation increases significantly.

Steadfast Energy Proficient Sensor Node Activation System in Wireless Networks Lifetime Enhancement

The wireless sensor network (WSN) is one of the budding exploring areas and fast rising fields in wireless communications. The sensor nodes in the network are generally small-size, low-cost, low-power and multi-function capabilities. Wireless sensor networks (WSNs) are used for various applications; since numerous sensor nodes are usually deployed on remote and inaccessible places, the employment and preservation should be easy and scalable. Sensor nodes in the field being run out of energy quickly has been an issue and many energy efficient routing protocols have been proposed to solve this problem and preserve the long life of the network. This paper work proposes a hierarchical based node activation routing technique which shows energy efficiency. This technique selects cluster head with highest residual energy in each communication round of transmission to the base station from the cluster heads. Hierarchical based node activation routing technique with different levels of hierarchy simulation results prolongs the lifetime of the network compared to other clustering schemes and communication rounds of simulation increase significantly.

SAC-TA: A Secure Area Based Clustering for Data Aggregation Using Traffic Analysis in WSN

Clustering is the most significant task characterized in Wireless Sensor Networks (WSN) by data aggregation through each Cluster Head (CH). This leads to the reduction in the traffic cost. Due to the deployment of the WSN in the remote and hostile environments for the transmission of the sensitive information, the sensor nodes are more prone to the false data injection attacks. To overcome these existing issues and enhance the network security, this paper proposes a Secure Area based Clustering approach for data aggregation using Traffic Analysis (SAC-TA) in WSN. Here, the sensor network is clustered into small clusters, such that each cluster has a CH to manage and gather the information from the normal sensor nodes. The CH is selected based on the predefined time slot, cluster center, and highest residual energy. The gathered data are validated based on the traffic analysis and One-time Key Generation procedures to identify the malicious nodes on the route. It helps to provide a secure data gathering process with improved energy efficiency. The performance of the proposed approach is compared with the existing Secure Data Aggregation Technique (SDAT). The proposed SAC-TA yields lower average energy consumption rate, lower end-to-end delay, higher average residual energy, higher data aggregation accuracy and false data detection rate than the existing technique.

Enhancement of network lifetime in wireless sensor networks using residual energy

Wireless sensor networks (WSNs) are partitioned into clusters to gather sensitive information more efficiently and provide efficient way to extend the life time of the WSNs. Clustering protocol provides two methods of selecting cluster heads with more residual energy and rotating cluster heads periodically to distribute the energy consumption amongst nodes in each cluster and extend the network lifetime. Resource limitations were considered in the proposed work to determine an effective routing path from the source to the destination by choosing the highest residual energy, minimum hops (shortest path) and minimum traffic loads. Life time is the major challenge in WSNs. In this proposed work, life time can be increased by selecting appropriate cluster heads with the help of fuzzy inference system which helps to increase the network life time. Energy consumption is the major challenge in WSNs. When the node energy consumption is more, life time can be decreased. Simulation results reveal that the proposed approach enhanced low energy adaptive clustering hierarchy protocol enhances network life time when compared with low energy adaptive clustering hierarchy protocol.

Research of energy efficient clustering algorithm for multilayer wireless heterogeneous sensor networks prediction research

In designing wireless sensor networks of image transmitting, it is important to reduce energy dissipation and prolong network lifetime. This paper presents the research on existing clustering algorithm applied in heterogeneous sensor networks and then puts forward an energy-efficient prediction clustering algorithm, which is adaptive to sensor networks with energy and objects heterogeneous. This algorithm enables the nodes to select the cluster head according to factors such as energy and communication cost, thus the nodes with higher residual energy have higher probability to become a cluster head than those with lower residual energy, so that the network energy can be dissipated uniformly. In order to reduce energy consumption when broadcasting in clustering phase and prolong network lifetime, an energy consumption prediction model is established for regular data acquisition nodes. Simulation results and the application in image clustering show that compared with current clustering algorithms, this algorithm can achieve longer sensor network lifetime, higher energy efficien- cy, and superior network monitoring quality.

Load Balancing Technique Based on Broadcasting and Residual Energy Using Adaptive Clustering Hierarchy Protocol (LBEACH)

One of the important factors of Wireless Sensor Networks (WSNs) is sensors lifetime. Elongating sensors lifetime increases the benefits from the network capabilities as much as possible. To elongate WSNs lifetime, power consumption should be reduced. To do so, load balance technique is applied to distribute the energy consumption among cluster’s nodes in the WSN. In each cluster, the node that acts as Cluster Head (CH) is the one that significantly suffers from power consumption problem. To elongate the WSNs lifetime, different sensor node is elected to act as CH for a period of time (round). Choosing the proper CH per round greatly affects the energy efficiency in the network. In this study, a new protocol for clustered heterogeneous WSNs (called LBEACH) is suggested to reduce power consumption and prolong the network lifetime. Distributed clustering methodology, with a novel algorithm to elect cluster heads in each round, is applied and tested. The elected CH is the node that has the minimal estimated broadcast cost and the highest residual energy. The estimated broadcast cost of each node is the estimated cost needed for sending a message to all other nodes within the same cluster and to the base-station. LBEACH performance is measured using network lifetime, power consumption and throughput. By comparing LBEACH performance with other protocols, Low Energy Adaptive Clustering Hierarchy (LEACH) and Stable Election Protocol (SEP) protocols, it was found that LBEACH shows a significant improvement in the network lifetime, power consumption and throughputs toward Base-Station (BS).

An adaptive competition-based clustering approach for wireless sensor networks

Hierarchical architecture is an effective scheme to make wireless sensor networks (WSNs) scalable and energy-efficient. Clustering the sensor nodes is a well-known two-layered architecture suitable for WSNs and has been extensively explored for different purposes and applications. In this paper a novel clustering approach called the adaptive competition-based clustering approach (ACCA) is proposed for WSNs. Selecting the cluster heads in the proposed ACCA is performed based upon a hybrid of local competition and the distances among the cluster heads. First, by the new proposed competition scheme, the nodes which are with the high residual energy and closer to the centre of the density of the nodes are elected and form an initial set of cluster head candidates. Then the candidates with suitable distances to other neighbor candidates are elected as the cluster heads. The proposed algorithm is fast with a low time and message complexity. It offers a longer lifetime for the networks, and at the same time, a proper level of fault tolerance. The proposed ACCA is simple enough to be implemented in real systems. Different simulation experiments are performed on different states and the algorithm is compared with some well-known and related clustering approaches. The experiments suggest that in terms of longevity and fault-tolerance, ACCA outperforms the well-known and relevant clustering protocols LEACH, HEED, and EECABN.

Clustering Routing Algorithm for Heterogeneous WSN with Energy Harvesting

Focus on the character of energy harvesting sensor network in heterogeneous sensor network and some shortage in SEP algorithm, an improved algorithm for EH-SEP is been proposed. EH-SEP considers both residual energy and energy support of nodes in cluster-head election process .Improved algorithm achieves higher probability that the advanced nodes with high residual energy to be cluster-head, and lower probability that the traditional nodes with low residual energy to be cluster-head. During the state of data sensing, this paper adopted multiple hop data transmission to avoid long distance communication between the cluster head and base station, so it can improve the network energy utilization. The simulation result shows that: EH-SEP algorithm is not only suitable for energy harvesting of wireless sensor network, but also effectively prolong the work time in the network stable stage.

EC-STCRA: Energy Conserved – Supervised Termite Colony based Role Assignment scheme for Wireless Sensor Networks

Conserving energy and ensuring security are the main challenges of Wireless sensor Networks (WSNs). Energy at the sensors must be preserved to increase the lifetime of the network. Clustering helps in reducing the number of transmissions between the Cluster Head (CH) and the Base Station (BS). In this paper, an Energy Conserved - Supervised Termite Colony based Role Assignment (EC-STCRA) scheme is proposed to conserve energy. The network is trained to provide better performance by incorporating efficient clustering, routing and security schemes. The CHs are randomly selected, and the soldier and the worker nodes are appointed based on their location and Residual Energy (RE). Efficient paths to the BS are found by selecting the worker nodes with high RE. The soldiers protect the network from attacks like Denial of Service (DoS), flooding and spoofing by maintaining an Active List (AL) of reliable nodes along with a Warning List (WL) and a Dead List (DL) of malicious nodes. EC-STCRA outperforms the existing Genetic algorithm (GA) and Ant Colony Optimization (ACO) based clustering and routing schemes in terms of Packet Delivery Ratio (PDR), Packet Loss Ratio (PLR), throughput, delay, Residual Energy (RE) and network lifetime.

Data Transmission Scheme Using Mobile Sink in Static Wireless Sensor Network

Multihop communication in wireless sensor network (WSN) brings new challenges in reliable data transmission. Recent work shows that data collection from sensor nodes using mobile sink minimizes multihop data transmission and improves energy efficiency. However, due to continuous movements, mobile sink has limited communication time to collect data from sensor nodes, which results in rapid depletion of node’s energy. Therefore, we propose a data transmission scheme that addresses the aforementioned constraints. The proposed scheme first finds out the group based region on the basis of localization information of the sensor nodes and predefined trajectory information of a mobile sink. After determining the group region in the network, selection of master nodes is made. The master nodes directly transmit their data to the mobile sink upon its arrival at their group region through restricted flooding scheme. In addition, the agent node concept is introduced for swapping of the role of the master nodes in each group region. The master node when consuming energy up to a certain threshold, neighboring node with second highest residual energy is selected as an agent node. The mathematical analysis shows that the selection of agent node maximizes the throughput while minimizing transmission delay in the network.

LOCATION AWARE CLUSTER BASED ROUTING IN WIRELESS SENSOR NETWORKS

Wireless sensor nodes are usually embedded in the physical environment and report sensed data to a central base station. Clustering is one of the most challenging issues in wireless sensor networks. This paper proposes a new cluster scheme for wireless sensor network by modified the K means clustering algorithm. Sensor nodes are deployed in a harsh environment and randomly scattered in the region of interest and are deployed in a flat architecture. The transmission of packet will reduce the network lifetime. Thus, clustering scheme is required to avoid network traffic and increase overall network lifetime. In order to cluster the sensor nodes that are deployed in the sensor network, the location information of each sensor node should be known. By knowing the location of the each sensor node in the wireless sensor network, clustering is formed based on the highest residual energy and minimum distance from the base station. Among the group of nodes, one node is elected as a cluster head using centroid method. The minimum distance between the cluster node’s and the centroid point is elected as a cluster head. Clustering of nodes can minimize the residual energy and maximize the network performance. This improves the overall network lifetime and reduces network traffic.

An Energy-Balanced Mechanism for Hierarchical Routing in Wireless Sensor Networks

In wireless sensor networks (WSNs), energy-constrained sensor nodes are always deployed in hazardous and inaccessible environments, making energy management a key problem for network design. The mechanism of RNTA (redundant node transmission agents) lacks an updating mechanism for the redundant nodes, causing an unbalanced energy distribution among sensor nodes. This paper presents an energy-balanced mechanism for hierarchical routing (EBM-HR), in which the residual energy of redundant nodes is quantified and made hierarchic, so that the cluster head can dynamically select the redundant node with the highest residual energy grade as a relay to complete the information transmission to the sink node and achieve an intracluster energy balance. In addition, the network is divided into several layers according to the distances between cluster heads and the sink node. Based on the energy consumption of the cluster heads, the sink node will decide to recluster only in a certain layer so as to achieve an intercluster energy balance. Our approach is evaluated by a simulation comparing the LEACH algorithm to the HEED algorithm. The results demonstrate that the BEM-HR mechanism can significantly boost the performance of a network in terms of network lifetime, data transmission quality, and energy balance.