Energy Drain Rate Research Articles

Dynamic topology control algorithm for node deployment in mobile underwater wireless sensor networks

AbstractSensors in underwater wireless sensor networks (UWSNs) can drift up to 3 m/s due to ocean currents, marine organisms, or passing vessels. In existing node deployment and localization techniques, node mobility and network disconnections are not taken into account. This article proposes a dynamic topology control algorithm for node deployment (DTCND) in mobile UWSN. This work aims to monitor the node mobility to predict nodes' location for ensuring coverage and connectivity. The sensor nodes are deployed randomly at different depths. The anchor nodes observe the signal quality index, energy drain rate, and node density at every time interval and detect node disconnections based on the variations in these observed metrics. After receiving the beacon messages from the anchor nodes, the courier nodes incline to move toward the target region for satisfying the coverage and connectivity constraints. Simulation results show that the proposed algorithm attains 5% higher connectivity when compared to energy‐efficient localization algorithm (EELA) and 9% higher connectivity when compared to adaptive triangular deployment algorithm (ATDA). The residual energy is also higher by 3% and 18% when compared to EELA and ATDA, respectively. The deployment cost and delay of DTCND also decrease when compared to EELA and ATDA, which results into efficient data collection.

Improved Energy Based Multi-Sensor Object Detection in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are spatially distributed to independent sensor networks that can sense physical characteristics such as temperature, sound, pressure, energy, and so on. WSNs have secure link to physical environment and robustness. Data Aggregation (DA) plays a key role in WSN, and it helps to minimize the Energy Consumption (EC). In order to have trustworthy DA with a rate of high aggregation for WSNs, the existing research works have focused on Data Routing for In-Network Aggregation (DRINA). Yet, there is no accomplishment of an effective balance between overhead and routing. But EC required during DA remained unsolved. The detection of objects belonging to the same event into specific regions by the Bayes Node is distributed through the Sensor Nodes (SNs). Multi-Sensor Data Synchronization Scheduling (MSDSS) framework is proposed for efficient DA at the sink in a heterogeneous sensor network. Secure and Energy-Efficient based In-Network Aggregation Sensor Data Routing (SEE-INASDR) is developed based on the Dynamic Routing (DR) structure with reliable data transmission in WSNs. Theoretical analysis and experimental results showed that in WSN, the proposed Bayes Node Energy Polynomial Distribution (BNEPD) technique reduced Energy Drain Rate (EDR) by 39% and reduced 33% of Communication Overhead (CO) using poly distribution algorithm. Similarly, the proposed MSDSS framework increased the Network Lifetime (NL) by 15%. This framework also increased 10.5% of Data Aggregation Routing (DAR). Finally, the SEE-INASDR framework significantly reduced EC by 51% using a Secure and Energy-Efficient Routing Protocol (SEERP).

Designing a Energy Efficient Node Disjoint Multipath Routing technique to achieve energy efficiency in Mobile Ad Hoc Networks

Mobile Ad Hoc Networks (MANETs) are wireless networks which comprise of mobile nodes with limited energy resources. Every node cooperates to perform routing and expends energy on a frequent basis. Nodes are mobile thus link breakages are common and new routes need to be established quickly. Traditional routing protocols tend to find shortest routes to destination providing best-effort delivery service. However due to limited energy and bandwidth resources shortest path routes may not suffice and may usually degrade the performance of the network. In this paper an Energy aware Node Disjoint routing technique END-AODV is proposed that is based on the traditional AODV protocol. The technique designed is based on the argument that node disjoint multipath routing can conserve energy more efficiently as compared to link disjoint routing. Link Disjoint routing leads to overuse of a subset of nodes thus decreasing the overall network lifetime. The technique proposed incorporates energy drain rate metric to establish energy aware routes which are node disjoint in nature. Simulation results with ns2.34 simulator show efficiency of the proposed technique in terms of packet delivery ratio, average energy consumption per data bit delivered, network lifetime and average end to end delay.

Weighted Multipath Energy-Aware Clustered Stable Routing Protocol for Mobile Ad Hoc Networks

Background & Objective: Mobile ad hoc networks are defined as highly dynamic, leading to frequent disconnections and changing topologies. The energy and stability of power limited nodes needs to be managed while designing the protocol & clustering helps in reducing the problem of network congestion due to information overhead in large sized networks. Multipath routing helps in balancing the load and node failures in a dynamic environment thereby helping to solve the problem of congestion. This paper proposes a new multipath, energy-aware and stable routing protocol – Weighted Multipath Energy-aware Clustered Stable routing protocol (WMECS). Methods: It uses weighted approach in clustered mobile adhoc networks. In this, both cluster head as well as path selection is done using an optimal energy and mobility model. This helps in attaining stable and energy efficient network with prolonged lifetime. The energy model considers energy metrics like transmission power, drain rate and power load that helps in constructing a network with lower energy consumption. We have also considered Gauss-Markov Mobility Model to handle the mobility of nodes and attain a stable network with less re-clustering and re-affiliations by choosing low relative mobility nodes in every cluster. Multipath selection is done based on a weighted metric that considers energy and mobility coefficients whereas Optimal Paths are selected on the basis of lower weight. Results: Simulation results show that the proposed protocol has better performance when compared with other related protocols in terms of Energy Consumption, Network Lifetime and end to end delay.

Long-Lifetime and Low Latency Data Aggregation Scheduling for Wireless Sensor Network

Abstract Wireless Sensor Networks contain an incredible number of hubs with limited registering, detecting, and wireless communication capacities. These systems have been utilized as a part of a wide zone of utilizations, such as human services, contamination checking, and target-following frameworks. The dynamic clustering of sensors into bunches is a prevalent procedure to expand the system lifetime and increment adaptability. To accomplish this, in this article the sensor hubs are adjusted to ensure a long lifetime and the activities are arranged into rounds that use fixed time intervals. In the first phase, a clustering topology is found, and a group head is picked in view of the outstanding energy level. Then the cluster head screens the network energy threshold value to identify the energy drain rate of all its cluster members. In the second stage, the Long-Lifetime and Low-Latency Data Aggregation Scheduling method is used. This scheduling method assigns schedule openings to group part information parcels. Here, congestion occurrence is completely kept away from the scenario. In the third stage, an Energy-Efficient Distributed Schedule–based convention is used to keep up greatest residual energy level over the network. The experimental outcome shows the steps proposed in this article ensure an increase in the network lifetime and decrease in the energy utilization.

Efficient traffic control and lifetime maximization in mobile ad hoc network by using PSO–BAT optimization

Recent developments in dynamic mobile ad-hoc network enhance the network speed and reliability. The nodes in the dynamic ad-hoc network are moving in nature. Due to the increased subscribers in this network, the network traffic has increased to manifold which in turn creating the challenge of maintaining the energy level. In path optimization process in mobile ad-hoc network consumes more energy and the draining of the energy is dependent on network reliability and connectivity. Further, the network also suffers by harmful attacks such as denial of service attack, black hole attack and warm hole attack. The primary focus of this paper is to prevent these attacks with the help of dynamic mobile ad-hoc network on demand protocol and hybrid meta-heuristics methodologies, and also to reduce the energy drain rate. This is achieved by estimating the velocity and fitness value of the nodes. Finally, the empirical simulation results of hybrid particle swarm optimization with bat algorithm (PSO–BAT) shows that the energy drain rate level is reduced 90% as 1 mJ/s than ad-hoc on demand vector. The end-to-end delay minimized to 50% than existing Ad hoc on-demand distance vector routing. The performance metrics routing overhead and execution time has been reduced and throughput is gradually increased in PSO–BAT optimization in dynamic mobile ad hoc network scenario.

Ant-based efficient energy and balanced load routing approach for optimal path convergence in MANET

Ant colony optimization, a swarm intelligence technique, inspired by the foraging behavior of ants in colonies was used in the past research works to compute the optimal path. The existing works of routing using ant colony optimization of MANETS face challenges in load balancing and energy efficiency. The proposed A-EEBLR approach chooses the next hop node based on metrics like delay, energy drain rate, congestion, link quality. Based on these metrics the probability of choosing next hop node as neighbor node is determined. The next hop probability determines the forward and backward ant agents to establish multiple paths among which the most optimal path is selected for transmission. The implementation results shows that the proposed A-EEBLR approach outperforms the existing A-ESR approach when evaluated by varying the number of packets, number of nodes and node mobility.

Network coding based energy efficient LEACH protocol for WSN

Wireless Sensor Network (WSN) consists of low cost tiny sensor nodes with limited energy resource, so it is a tedious task to develop energy efficient routing schemes that enhances the network lifetime. In WSN, clustering is used to improve the efficiency of finite energy resource. LEACH protocol is one of the widely used clustering techniques in WSN. So, in this paper, an energy efficient LEACH protocol is designed with network coding for WSN. Initially, the clusters are formed with the LEACH protocol, where it uses the residual energy metric and drain rate to select the cluster heads. Since network coding is an optimal technique to enhance the network performance by minimizing the number of transmissions, it is incorporated into the LEACH Protocol, where it has been applied at the cluster head levels. Furthermore, the next level of network coding is processed at a node by selecting any of the nodes as a master node. The simulation results show that the proposed scheme performs better than the EE-LEACH and LEACH protocol in terms of network lifetime, packet delivery ratio.

Fault Tolerance and QoS based Pervasive Computing using Markov State Transition Model

Fault-tolerance is significant in pervasive computing environments. Recently, few research works has been developed for reducing the fault, occurring in pervasive computing. However, there is a need for a fault tolerance mechanism to reduce the link failures and unwanted mobile node access (in pervasive computing environment). In order to overcome these limitations, Markov State Transition Based Fault Tolerance (MST-FT) Model is proposed. The main objective of MST-FT Model is to achieve resource efficient QoS in pervasive computing environment by avoiding the link failures and unwanted mobile node usages. Initially, the optimization of link failures is achieved by maintaining Markov chain of high energy mobile nodes on the wireless network communication path. The mobile nodes with higher energy and minimal drain rate are combined to form a chain in its corresponding path of communication in order to minimize the link failures in pervasive computing. Next, the inappropriate mobile node usage is avoided by selecting only the authorized mobile nodes for Markov chain construction to effective network communication, which resulting in improved fault tolerant rate. Therefore, MST-FT Model provides higher resource efficient QoS as compared to existing works. The performance of MST-FT Model is measured in terms of fault tolerant rate, execution time, energy consumption rate and quality of service level. The simulation results show that the MST-FT Model is able to improve the fault tolerant rate by 13% and also reduces the energy consumption rate of resource efficient QoS by 25%, when compared to previous works.

A Fuzzy Trust Relationship Perspective-Based Prevention Mechanism for Vampire Attack in MANETs

The trustworthiness and connectivity of the network depends on the energy drain rate of mobile nodes. Colluders like vampire nodes in ad hoc network make it more vulnerable as they rapidly drain considerable amount of energy. This generic vampire attacks seem to capitalize on the potential features of the incorporated baseline protocol used for facilitating trustworthy data dissemination. The main goal of this paper is to formulate an attack prevention scheme that uses fuzzy trust relationship perspective for detecting vampire attacks and enforcing reduced energy drain rate of colluding mobile nodes. This fuzzy trust relationship perspective-based prevention mechanism (FTRPPM) initially estimates the associative trust and associative reputation of mobile nodes. Further, it quantifies the impact of factors that could induce vampire attack in the network under its influence. Finally, it facilitates the detection of vampire nodes based on the established ranges of threshold that are dynamically adjusted based on quantified level of probability factor. The empirical and simulation results of FTRPPM is confirmed to be exceptional as it ensures a remarkable improvement in mean PDR of 16% and mean throughput of 14% under the impact of increasing number of mobile nodes on par with the existing vampire attack mitigation schemes.

Secondary route Establishment for QoS routing using Genetic Algorithm underwater Sensor networks

Network topology changes frequently due to dynamic nature and leads to frequent link failures, reliability problem, also causes stability issues. To overcome the issues and to increase the link reliability various routing methods such as multi-path routing, on-demand routing and backup path routing are developed. A primary back up route establishment for QoS routing protocol is designed to detect the potential failures of nodes in the network. For detection of failures, a path evaluation function is determined based on the metrics energy drain rate and interference, congestion status are measured. once failure is detected, back up routes are established and transmission is redirected on these back up routes. Simulation results show that the proposed protocol has reduced recovery delay and improved throughput as compared with the existing protocol.

Derived Genetic Algorithm Optimizer for Energy Efficient Routing in Wireless Sensor Network

Wireless sensor network is a type of network with spatially distributed nodes for the application of particular data. It consists of large number of sensor nodes with one or more base stations. The data is sent from sensor nodes to base station straightly or in multihop manner. Increasing the lifetime of network and less energy utilization are two key concerns for WSNs. Some energy-saving routing algorithms decrease total energy utilization of WSN, but they are difficult one in sending the data packets on many key nodes in order that these nodes drain out battery energy quickly through reducing network lifetime. In order to increase the energy efficiency and network lifetime, Derived Genetic Algorithm Optimizer for Energy Efficient Routing (DGAO-EER) scheme is introduced. GA is an effective one for energy efficient path finding in sensor network. GA collects the useful information about individuals from current nodes (i.e., gene). Initially, fitness function is presented to allocate the fitness value for every individual node. This function is used to find the nearby nodes to send the packets from source to sink node. Then, the data transfer of genetic information is carried out between two neighboring node to find another two neighboring nodes is called as crossover operation. Mutation restores the lost genetic values quickly when the node chooses the neighboring node. This process helps in increasing the lifetime of the network and energy efficiency. Performance results shows that the proposed DGAO-EER obtains the better performance in terms of energy consumption rate, energy drain rate, routing over head and routing delay as compared to the state-of-the-art works.

Dynamic fuzzy logic and reinforcement learning for adaptive energy efficient routing in mobile ad-hoc networks

In this paper, a dynamic fuzzy energy state based AODV (DFES-AODV) routing protocol for Mobile Ad-hoc NETworks (MANETs) is presented. In DFES-AODV route discovery phase, each node uses a Mamdani fuzzy logic system (FLS) to decide its Route REQuests (RREQs) forwarding probability. The FLS inputs are residual battery level and energy drain rate of mobile node. Unlike previous related-works, membership function of residual energy input is made dynamic. Also, a zero-order Takagi Sugeno FLS with the same inputs is used as a means of generalization for state-space in SARSA-AODV a reinforcement learning based energy-aware routing protocol. The simulation study confirms that using a dynamic fuzzy system ensures more energy efficiency in comparison to its static counterpart. Moreover, DFES-AODV exhibits similar performance to SARSA-AODV and its fuzzy extension FSARSA-AODV. Therefore, the use of dynamic fuzzy logic for adaptive routing in MANETs is recommended.

Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network.

Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead.

An energy-efficient cluster-based vehicle detection on road network using intention numeration method.

The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN) is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate.

Energy Efficient Cluster Based Scheduling Scheme for Wireless Sensor Networks.

The energy utilization of sensor nodes in large scale wireless sensor network points out the crucial need for scalable and energy efficient clustering protocols. Since sensor nodes usually operate on batteries, the maximum utility of network is greatly dependent on ideal usage of energy leftover in these sensor nodes. In this paper, we propose an Energy Efficient Cluster Based Scheduling Scheme for wireless sensor networks that balances the sensor network lifetime and energy efficiency. In the first phase of our proposed scheme, cluster topology is discovered and cluster head is chosen based on remaining energy level. The cluster head monitors the network energy threshold value to identify the energy drain rate of all its cluster members. In the second phase, scheduling algorithm is presented to allocate time slots to cluster member data packets. Here congestion occurrence is totally avoided. In the third phase, energy consumption model is proposed to maintain maximum residual energy level across the network. Moreover, we also propose a new packet format which is given to all cluster member nodes. The simulation results prove that the proposed scheme greatly contributes to maximum network lifetime, high energy, reduced overhead, and maximum delivery ratio.

Particle swarm optimization (PSO)-based node and link lifetime prediction algorithm for route recovery in MANET

In the conventional mobile ad hoc network (MANET) systems' route rediscovery methods, there exists route failure in all route discovery methods resulting in data loss and communication overheads. Hence, the routing has to be done in accordance with mobility character of the network. In this manuscript, a particle swarm optimization (PSO)-based lifetime prediction algorithm for route recovery in MANET has been proposed. This technique predicts the lifetime of link and node in the available bandwidth based on the parameters like relative mobility of nodes and energy drain rate, etc. Using predictions, the parameters are fuzzified and fuzzy rules have been formed to decide on the node status. This information is made to exchange among all the nodes. Thus, the status of every node is verified before data transmission. Even for a weak node, the performance of a route recovery mechanism is made in such a way that corresponding routes are diverted to the strong nodes. With the aid of the simulated results, the minimization of data loss and communication overhead using PSO prediction has been discussed in detail.

A fuzzy based secure QoS routing protocol using ant colony optimization for mobile Ad hoc network

Ensuring secure communication in mobile ad hoc network (MANET) is the main challenging task due to the network characteristics. In this paper, we apply fuzzy logic method and method of ant colony optimization (ACO) to establish a secure routing path with minimum delay for mobile ad hoc network. The ACO algorithm is used to establish a virtual backbone connecting cluster heads (CHs). The general ACO algorithm is modified to allow selection of routing path, based on trust value of the nodes lying in the routing path and delaying experienced in the path. The procedure uses a fuzzy logic controller to evaluate the trust value of the nodes based on node's QoS parameters: energy drain rate, lifetime of the node, packet drop rate and packet forwarding status of the node. The behavior of the protocol under various attacks is analyzed. Experimentation shows that the algorithm results in secure shortest routing path for data communication. Additionally, the packet drop rate and routing delay of the proposed routing protocol in presence of malicious nodes is fewer compared to secure cluster based routing protocol (SCBRP) and Fuzzy Logic based Security Level routing protocol (FLSL).

SELFISH SCHEDULER FOR PACKET SCHEDULING BASED ON PACKET WEIGHTED ENERGY DRAIN RATE IN MANETS

The aim of our selfish scheduler based on packet weighted energy drain rate in Mobile ad-hoc networks mainly depends on the available least highest-limit of the residual value of a mobile node. The projected work comprises of mechanisms for detecting the selfish node as well as an attitude called rehabilitate-before-malicious behavior for justifying against the malicious behavior of nodes having selfishness. It provides an immediate solution for separating the selfish nodes based on the parameter namely the packet weighted energy drain rate. If PWEDRSS is deployed in an ad hoc environment it not only provides an energetic and immediate solution to become aware of malicious nodes but also can detect selfish nodes which may be fruitless due the deficient energy available, since the restricted battery power is one of the main constraint for all the mobile nodes. The effective and well-organized performances of the projected work are done through ns-2 simulations. The parameters used are the Packet delivery ratio, Throughput, Control overhead, Total overhead and End to end delay. These parameters are computed based upon varying the number of nodes. The outcome forecast that the planned mechanism performs well.

Data Aggregation Tree Approach in Aodv Protocol to Select Dynamic Route for Sensor Network

Design an energy efficient data aggregation tree approaches sensor network using localized power efficient data aggregation protocols. Using LMST and RNG topologies approximate minimum spanning tree and calculate position and distance information of one hop neighbors. A new node is added or fails route maintenance procedure is executed. The shortest weighted path – based approaches, can achieve 90 percent of the upper bound on lifetime. AODV proposed algorithm to assess the node lifetime and link lifetime utilizing the dynamic nature of energy drain rate and relative mobility estimation rate of nodes. Using node lifetime and link lifetime algorithm select least dynamic route with the longest lifetime. On prediction AODV protocol is a loop – free routing and has self – starting in network behavior as node mobility, link fail and packet losses.