Gathering In Sensor Information Systems Research Articles

Evaluation on Data Transmission in Wireless Sensor Networks Based on Computer Technology

Traditional network data transmission (DT) has certain limitations in terms of processing, storage, and communication capabilities. Moreover, DT is easily affected by the network environment, which can reduce the real-time performance of DT. In severe cases, network transmission failures, DT interruptions, and other issues may even occur. As a new network, wireless sensor networks (WSN) have been widely used in military, industrial, agricultural, medical and other fields. In this paper, WSN was regarded as an important research method, and in-depth research was carried out around the real-time and energy consumption (for the convenience of the following text, the abbreviation for energy consumption is EC) of WSN DT. This paper focused on the issues of real-time performance, EC, and real-time transmission. It balanced EC and improved real-time performance through the low energy adaptive clustering hierarchy (LEACH) protocol and the power-efficient gathering in sensor information systems (PEGASIS) protocol. The experimental results showed that the real-time rates of LEACH under single reaction nodes were 45.5% and 48.6%, respectively. The lowest and highest real-time rates of PEGASIS were 86.2% and 89.5%, respectively. The real-time rate of PEGASIS was much higher than that of LEACH, proving that the proposed PEGASIS had high real-time performance and reduced DT delay.

Design of ant lion optimization-based PEGASIS routing protocol for energy efficiency in networks

<p>In sensor networks the main problem facing by many researchers is regarding the energy efficiency. Different protocols are evaluated for communicating between the sensor nodes. The routing protocol when combined with evolutionary algorithms gives best optimal solution for the problem incurred in wireless sensor networks. In this paper, ant lion energy efficient-power efficient gathering in sensor information systems (ALEEPEGASIS) is used to develop the chain. This technique can achieve a global optimization solution by finding the best cluster head or the leader node for data communication. The techniques help in distributing the paths equally while the transmission of data process is performed. By performing this process, the power consumption near the sensor nodes can be reduced. The proposed technique is compared with other techniques like energy efficient PEGASIS and swarm energy efficient PEGASIS. The parameters used to compare are number of alive nodes, number of dead nodes and residual energy. The performance is observed using MATLAB simulation results.</p>

Cluster-Factors of Mobile Sensor Network Technology for Security Enhanced PEGASIS

Mobile wireless sensor networks (MWSNs) have been a hot topic of research, and numerous routing methods have been developed to increase energy efficiency and extend longevity. Nodes close to the sink often use more energy to transmit data from their neighbors to the sink, which causes them to run out of energy faster. These places are also referred to as rendezvous points, and choosing the best one is a hard task. The likelihood of choosing an ideal node as the rendezvous point will be extremely low because hierarchical algorithms only use their local information to select these places. The warm spot problem is addressed from four angles in this work using the Enhanced Power-Efficient Gathering in Sensor Information Systems (EPEGASIS) technique. In order to limit the amount of energy used during transmission, the ideal communication distance is first calculated. To balance the energy consumption among the nodes, mobile sink technology is employed once a threshold value is set to safeguard the dying nodes. The node can then modify its communication range based on how far away the sink node is from it. Thorough testing has been done to demonstrate that our suggested EPEGASIS works better in terms of longevity, drive usage, and web latency.

Swarm energy efficient power efficient gathering in sensor information systems protocol in wireless sensor networks

Wireless sensor network (WSN) is a network, which has more numbers of sensors that are small in nature and are self organised. The inbuilt battery system is provided in the sensor nodes through which the nodes can communicate and do good operations among the other nodes available in the network. Lifetime is the most essential parameter which needs to be maximised for the WSN. This measure is more important for conservation of energy, for adequate and efficient performance of sensor networks. This paper proposes a swarm energy efficient power efficient gathering in sensor information systems (PEGASIS) (SEE-PEG) based energy optimization algorithm for WSN in which clustering and clustering head selection are done by using modified particle swarm optimization (MPSO) algorithm with respect to minimizing the consumption of power in WSN. The parameters evaluated for the proposed method is compared with existing technique like energy efficient PEGASIS without optimization. The simulation results are obtained using matlab tool.

EEGT: Energy Efficient Grid-Based Routing Protocol in Wireless Sensor Networks for IoT Applications

The Internet of Things (IoT) integrates different advanced technologies in which a wireless sensor network (WSN) with many smart micro-sensor nodes is an important portion of building various IoT applications such as smart agriculture systems, smart healthcare systems, smart home or monitoring environments, etc. However, the limited energy resources of sensors and the harsh properties of the WSN deployment environment make routing a challenging task. To defeat this routing quandary, an energy-efficient routing protocol based on grid cells (EEGT) is proposed in this study to improve the lifespan of WSN-based IoT applications. In EEGT, the whole network region is separated into virtual grid cells (clusters) at which the number of sensor nodes is balanced among cells. Then, a cluster head node (CHN) is chosen according to the residual energy and the distance between the sink and nodes in each cell. Moreover, to determine the paths for data delivery inside the cell with small energy utilization, the Kruskal algorithm is applied to connect nodes in each cell and their CHN into a minimum spanning tree (MST). Further, the ant colony algorithm is also used to find the paths of transmitting data packets from CHNs to the sink (outside cell) to reduce energy utilization. The simulation results show that the performance of EEGT is better than the three existing protocols, which are LEACH-C (low energy adaptive clustering hierarchy), PEGASIS (power-efficient gathering in sensor information systems), and PEGCP (maximizing WSN life using power-efficient grid-chain routing protocol) in terms of improved energy efficiency and extended the lifespan of the network.

Joint Shortest Chain and Fair Transmission Design for Energy-Balanced PEGASIS in WSNs

The conventional routing protocol considers several local transmission factors in a single node for the many-to-one packet transmission. These factors lead to rapid energy consumption in some specific nodes, thereby generating energy holes to reduce network lifetime. In this article, a novel energy-balanced power-efficient gathering in sensor information systems (EB-PEGASISs) is proposed to improve energy efficiency and utilization for wireless sensor networks (WSNs). In the original power-efficient gathering in sensor information system (PEGASIS), the protocol constructs a chain-based network with the locally shortest distance rather than the globally optimal network length. To improve this, two construction algorithms are proposed to achieve the shortest network length in the EB-PEGASIS, including centralized formation and distributed construction schemes. In the centralized algorithm, the chain length of each starting node is computed, and the minimum chain length can be subsequently determined in the following packet transmission phase. In order to reduce formation complexity, a distributed method uses the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -means clustering algorithm to partition the network into clusters. In particular, it forms a subchain in each cluster and connects each subchain into the final shortest chain. Additionally, to balance the energy consumption among all nodes in the packet transmission phase, Jain’s fairness index for residual battery capacity is designed to minimize the fluctuation of energy consumption among nodes in a network. As a result, not only energy efficiency is achieved with the shortest chain length but also energy utilization is balanced for packet transmission. Ultimately, simulation results validate that the network lifetime of the EB-PEGASIS is about 2.46 times the original PEGASIS and 3.36 times the random projection-polar coordinate-chain (RPC) protocol for WSNs.

Efficient Energy and Delay Reduction Model for Wireless Sensor Networks

In every network, delay and energy are crucial for communication and network life. In wireless sensor networks, many tiny nodes create networks with high energy consumption and compute routes for better communication. Wireless Sensor Networks (WSN) is a very complex scenario to compute minimal delay with data aggregation and energy efficiency. In this research, we compute minimal delay and energy efficiency for improving the quality of service of any WSN. The proposed work is based on energy and distance parameters as taken dependent variables with data aggregation. Data aggregation performs on different models, namely Hybrid-Low Energy Adaptive Clustering Hierarchy (H-LEACH), Low Energy Adaptive Clustering Hierarchy (LEACH), and Multi-Aggregator-based Multi-Cast (MAMC). The main contribution of this research is to a reduction in delay and optimized energy solution, a novel hybrid model design in this research that ensures the quality of service in WSN. This model includes a whale optimization technique that involves heterogeneous functions and performs optimization to reach optimized results. For cluster head selection, Stable Election Protocol (SEP) protocol is used and Power-Efficient Gathering in Sensor Information Systems (PEGASIS) is used for driven-path in routing. Simulation results evaluate that H-LEACH provides minimal delay and energy consumption by sensor nodes. In the comparison of existing theories and our proposed method, H-LEACH is providing energy and delay reduction and improvement in quality of service. MATLAB 2019 is used for simulation work.

Adaptive Threshold Residual Energy‐Based Efficient Sensor Network Protocol (ATREEN)

Wireless sensor network (WSN) hierarchical (clustering) routing involves the gathering of sensor nodes to form clusters in which sensor node communicates to cluster head (CH). The CH is responsible for data aggregation and forwarding collected data toward base station (BS). Energy expenditure in usual protocols becomes unequal because of clusters having diverse lengths. In this paper, we propose another new enhanced clustering protocol called adaptive threshold residual energy‐based efficient sensor network protocol (ATREEN) for adaptive selection of CH in WSNs. In ATREEN, CHs are chosen by comparing threshold of node value with respect to distance between cluster member and CH, residual energy of sensor nodes, and position of sensor node with respect to BS. Simulation results show that ATREEN protocol extends network lifetime and stability with decline in energy dissipation compared to clustering protocols such as low‐energy adaptive clustering hierarchy (LEACH), power‐efficient gathering in sensor information systems (PEGASIS), and distributed energy‐efficient clustering (DEEC) scheme for heterogeneous WSNs.

Energy Efficient Routing and Dynamic Cluster Head Selection Using Enhanced Optimization Algorithms for Wireless Sensor Networks

A large number of spatially dispersed nodes on the wireless network create Wireless Sensor Networks (WSNs) to collect and analyze the physical data from the environment. The issues that affected the network and had an impact on network energy consumption were cluster head random selection, working node redundancy, and cluster head transmission path construction. Consequently, this energy constraint also has an impact on the network lifetime and energy-efficient routing. Therefore, the primary goals of this research are to decrease energy consumption and lengthen the network’s lifespan. So, using improved optimization algorithms, this paper presents a dynamic cluster head-based energy-efficient routing system. The Improved Coyote Optimization Algorithm (ICOA), in this case, consists of three phases setup, transmission, and measurement phase. The Improved Jaya Optimization Algorithm with Levy Flight (IJO-LF) then determines the route between the BS and the CH. It selects the most effective course based on the distance, node degree, and remaining energy. The proposed approach is compared with traditional methods and the routing protocols Power-Efficient Gathering in Sensor Information Systems (PEGASIS) and Threshold sensitive Energy Efficient Sensor Network protocol (TEEN) during implementation on the MATLAB platform. Performance indicators for the suggested methodology are evaluated based on data packets collected by the BS, energy usage, alive nodes, and dead nodes. The outputs of the suggested methodology performed better than the conventional plans.

D2CRP: A Novel Distributed 2-Hop Cluster Routing Protocol for Wireless Sensor Networks

Typically, wireless sensor networks (WSNs) use limited-capacity batteries that cannot be recharged or replaced. In general, designing an energy-efficient routing protocol has a significant impact on prolonging the network lifetime. In this article, a novel distributed 2-hop cluster-routing protocol (D2CRP) is introduced to achieve energy efficiency in WSNs. In the cluster formation phase, each node obtains the information of its neighbor nodes within the 2-hop range to form the 2-hop cluster in a fully distributed manner. The transmission distance and residual energy are jointly considered to determine the energy-efficient cluster head (CH) in each 2-hop cluster. After the CH is generated, each member node can transmit packets to its 1-hop neighbor or the CH directly. To reduce the overall transmission distance for intercluster communication, multiple chains can be formed among CHs via their adjacent CHs that are closer to the base station (BS). As a result, energy-efficient intracluster and intercluster routing can be achieved for packet transmission. In addition, the optimal cluster number of 2-hop clustering is formulated and derived to minimize the energy consumption for both intracluster and intercluster communications. Simulation results show that the optimal cluster number of D2CRP can be achieved and D2CRP is effectively improved on the performances of network lifetime, energy consumption, and packet transmission than the other four state-of-the-art competitive routing protocols, including low-energy adaptive clustering hierarchy (LEACH), R-LEACH, power-efficient gathering in sensor information system (PEGASIS), and two-tier distributed fuzzy logic-based protocol (TTDFP).

A Novel Approach for Energy-Efficient of WSN Using PEGASIS Protocol

Wireless Sensor Networks (WSNs) have hardware and software limitations and are deployed in hostile environments. The problem of energy consumption in WSNs has become a very important axis of research. To obtain good performance in terms of the lifetime of the WSN, several routing protocols have been proposed. We present in this article a new approach for the energy efficiency of WSN by using the PEGASIS (Power Efficient Gathering In Sensor Information Systems) routing protocol in order to reduce sensor energy consumption and to achieve good performance in terms of the lifetime of the network in WSN. The simulation results have shown that our proposed protocol excels regarding energy consumption in wireless sensor networks, resulting in an extension of a lifetime for the network. We simulated the proposed technique compared with traditional LEACH (Low-Energy Adaptive Clustering Hierarchy) protocol using MATLAB environment.

Integration of fault-tolerant feature to OMIEEPB routing protocol in wireless sensor network

PurposeWhereas a human operator is hard to observe the networking infrastructure and its functions on a continuous basis, wireless sensor network (WSN) nodes must overcome faults and route the perceived data to the sink/base stations (BS). The main target of this research article is to ensure the fault-tolerance (FT) capability, especially for transmission of sensed data to its destination without failure. Thus, through this paper, a fuzzy-based subordinate support (FSS) system is introduced as an additional feature to the existing optimized mobile sink improved energy efficient Power-Efficient Gathering in Sensor Information Systems (PEGASIS)-based (OMIEEPB) routing protocol, which lacks focus on ensuring the FT capabilities to the selected leaders of the corresponding chain. The central focus of FSS is to prevent the incident of fault, especially to the cluster heads.Design/methodology/approachWSNs encounter several issues owing to random events or different causes such as energy exhaustion, negative influences of the deployed region, signal interference, unbalanced supply routes, instability of motes due to misalignments and collision, which ultimately intends the failure of the network. Throughout the past investigation periods, researchers gain an understanding of fault-tolerant strategies that may improve the data integrity or reliability, precision, energy efficiency, the life expectancy of the system and reduce/prevent the failure of deployed components. If that is the case, the maximum chances of data packets (sensed) needed to be transferred reliably and accurately to the sink node or BS are degraded.FindingsThe FSS system utilizes the fuzzy logic concepts that have been proved to be beneficial since it permits several parameters to be combined effectively and evaluated. Here, near-point, residual energy, total operation time and past average processing time are considered as vital parameters. Moreover, the FSS system ensures the key performance activities of the network, such as optimization of response time, enhancing the data transmission reliability and accuracy. Simulation-based experiments are carried out through the Mannasim framework. After several experimental executions, the outcome of the proposed system is analyzed through elaborated comparison with the advanced existing systems.Originality/valueFinally, it has been observed that the FSS system not only enhanced the FT features to OMIEEPB but also assures the improved accuracy level (>95%) with optimized response time (<0.09 s) during data communication between leaders and the normal nodes.

Reducing Power Consumption in Hexagonal Wireless Sensor Networks Using Efficient Routing Protocols

Power consumption and network lifetime are vital issues in wireless sensor network (WSN) design. This motivated us to find innovative mechanisms that help in reducing energy consumption and prolonging the lifetime of such networks. In this paper, we propose a hexagonal model for WSNs to reduce power consumption when sending data from sensor nodes to cluster heads or the sink. Four models are proposed for cluster head positioning and the results were compared with well-known models such as Power Efficient Gathering In Sensor Information Systems (PEGASIS) and Low-Energy Adaptive Clustering Hierarchy (LEACH). The results showed that the proposed models reduced WSN power consumption and network lifetime.

Sector Tree-Based Clustering for Energy Efficient Routing Protocol in Heterogeneous Wireless Sensor Network

One of the main challenges for researchers to build routing protocols is how to use energy efficiently to extend the lifespan of the whole wireless sensor networks (WSN) because sensor nodes have limited battery power resources. In this work, we propose a Sector Tree-Based clustering routing protocol (STB-EE) for Energy Efficiency to cope with this problem, where the entire network area is partitioned into dynamic sectors (clusters), which balance the number of alive nodes. The nodes in each sector only communicate with their nearest neighbour by constructing a minimum tree based on the Kruskal algorithm and using mixed distance from candidate node to base station (BS) and remaining energy of candidate nodes to determine which node will become the cluster head (CH) in each cluster? By calculating the duration of time in each round for suitability, STB-EE increases the number of data packets sent to the BS. Our simulation results show that the network lifespan using STB-EE can be improved by about 16% and 10% in comparison to power-efficient gathering in sensor information system (PEGASIS) and energy-efficient PEGASIS-based protocol (IEEPB), respectively.

A Segment-based Tree Traversal Algorithm for Enhancing Data Gathering in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are sink-based networks in which assigned sinks gather all data sensed by lightweight devices that are deployed in natural areas. The sensor devices are energyscarce, therefore, energy-efficient protocols need to be designed for this kind of technology. PowerEfficient GAthering in Sensor Information Systems (PEGASIS) protocol is an energy-efficient data gathering protocol in which a chain is constructed using a greedy approach. This greedy approach has appeared to have unbalanced distances among the nodes which result in unfair energy consumption. Tree traversal algorithms have been used to improve the constructed chain to distribute the energy consumption fairly. In this research, however, a new segmentbased tree traversal approach is introduced to further improve the constructed chain. Our new proposed algorithm first constructs initial segments based on a list of nodes that are sorted according to post-order traversal. Afterwards, it groups these segments and concatenates them one by one according to their location; thus, our proposed approach uses location-awareness to construct a single balanced chain in order to use it for the data gathering process. This approach has been evaluated under various numbers of sensor devices in the network field with respect to various crucial performance metrics. It is shown in our conducted simulation results that our proposed segment-based chain construction approach produces shorter chains and shorter transmission ranges which as a result has improved the overall energy consumption per round, network lifetime, and end-to-end delay.

Energy optimized hybrid PSO and wolf search based LEACH

In wireless sensor networks (WSN), computational challenges exist in determining a global energy optimized communication routing in large spaced network. WSN challenges can be handled by applying heuristic bio-inspired computational intelligence optimization methods. In WSN, Low Energy Adaptive Clustering Hierarchy (LEACH) algorithm is most frequently used hierarchical routing algorithm in spite of certain limitations. The proposed work is addressed in this direction, to improve issues of LEACH, such as identification of reliable CH, selection of energy efficient inter and intra route communication using relay nodes, so as to extend the network lifespan. The proposed work applies Particle Swarm Optimization (PSO) and Wolf Search optimization methods to improve the performance of LEACH algorithm. PSO is castoff for cluster formation and Wolf search for identification of two relay nodes: intra and inter relay node. The Spyder-py3 tool is used to simulate the proposed algorithm: LEACH PSO Wolf search based Optimization (LEACH-PWO). The proposed work compared with original LEACH, power-efficient gathering in sensor information systems, Ant Cuckoo optimized using energy-efficient data aggregation, and Genetic Algorithm data Aggregation LEACH protocols indicate prolonged lifetime of network and increased throughput.

"Energy Cost Calculations for Enhanced Power Efficient Gathering in Sensor Information Systems Algorithm with Mobile-Sink "

"The issue of energy consumption in wireless sensor networks is an important issue nowadays, Power efficient gathering in sensor information systems (PEGASIS) acts as routing protocols improve the energy consumed, which is one of the most important hierarchical directives used and that works to collect and transfer data to and from a neighbor to reduce duplication of data transfer by transferring data to bypass the dead node. In this research paper, experimental results have been made to improve the performance with new location for nodes trajectory to mobile sink, Finally, minimum cost for data gathering calculated to optimize network performance and life time with parameters of enhanced PEGASIS criteria to show the impact of factors changing.

Pegasis Double Cluster Head Hybrid Congestion Control in Wireless Sensor Networks

Wireless sensor network (WSN) is the fastest growing technology that dominates the future world into wireless communication. It is a collection of a number of self-governing sensor nodes responsible to sense, process and manipulate the nodes. The sensor nodes are regulated by a battery where the network gets failed if the battery is dead. Thus, energy is an important factor to be efficiently used. Furthermore, congestion occurs in WSN when the incoming traffic load exceeds the capacity of the network. The major factors that lead to congestion are buffer overflow, varying rates of transmission, packet collision, and many-to-one data transmission. Due to these, the network suffers from packet loss, queuing delay, end-to-end delay, decrease in network lifetime, and increase in energy consumption. Hence, a clustering-based routing protocol is introduced in this paper to improve the performance of the network and reduce congestion. In the proposed method, Power-Efficient Gathering in Sensor Information Systems (PEGASIS) double cluster head with artificial neural network (ANN) is utilized to analyze the overall network lifetime. The proposed technique is comprised of four phases: clustering the network nodes, cluster head (CH) selection, chain formation, and secondary CH (SCH) selection. The sensor nodes are initially clustered with the firefly algorithm in which the cluster heads of each node are elected via an artificial neural network. Meanwhile, chain formation is processed by PEGASIS double cluster head (PDCH) and the SCH is selected through grey wolf optimizer (GWO) to afford equivalent energy utilization between the sensor nodes. The simulation outcomes proved that the proposed method efficiently increases the lifetime of the network and reduces congestion level in WSN.

Enhanced Energy Efficient Routing for Wireless Sensor Network Using Extended Power Efficient Gathering in Sensor Information Systems (E-PEGASIS) Protocol

Recent technological advancement in wireless communication and sensors made Wireless Sensor Networks (WSNs) as one of the demanding platforms in the current scenario. In WSN, tiny sensor nodes are collecting and monitoring the biological data or physical data or environmental data and transmitted to the base station (BS) through gateway routers. These data can be accessed anywhere and anytime. Usually sensor nodes have restrained battery power which creates the rigorous lifetime duration issues in WSN. Sensor nodes can communicate with each other using various routing protocols. Data transmission devours more amounts of energy and power. So, energy preservation is an important factor in WSN. There are plenty of researches going on in designing less energy consuming protocols for data transmission which helps to increase the lifetime of WSN. In this paper we have proposed Extended Power Efficient Gathering in Sensor Information Systems (E-PEGASIS) protocol for enhanced energy efficient data transmission based on PEGASIS protocol. In this proposed method average distance between the sensor nodes are considered as the criterion for chaining and fix the outermost node’s radio range value the base station. Later it chains the related nodes available in the radio range. Consequently, the chained node checks their distance with the next nearest end node to go on with the chaining procedure which will enhance the performance of data transmission between the sensor node and the base station. The simulation of the proposed work shows that lifetime of the network is increased when comparing to the LEACH and PEGASIS protocol.

Comparison of LEACH and PEGASIS Hierarchical Routing Protocols in WSN

&lt;p&gt;Wireless Sensor Networks is a group of sensor nodes dispatched in a geographical area for a defined objective. These sensor nodes are characterized by limited capacity of communicating, computing and especially of energy. The performance of these WSN is resting on a good routing protocol, hence the need to choose the routing protocol able to satisfy the wsn's objectives, and to satisfy the common challenge to prolong network life time.&lt;/p&gt;&lt;p&gt;Several routing concepts have been proposed for the WSN, hierarchical routing is one of the most used concepts. It is divided into 3 types: cluster based routing, grid based routing and chain based protocol. In this paper, we are interested to Study, analyse and compare two popular routing protocols for Wireless sensor networks (WSNs), Low-Energy Adaptive Clustering Hierarchy (LEACH) using clusters based concept and Power-Efficient Gathering in Sensor Information System (PEGASIS) with chain based concept. The both protocols are simulated with Matlab simulator, in order to evaluate its performances against the different users and the WSNs objectives defined.&lt;/p&gt;