Energy Efficient Routing Mechanism Research Articles

Energy Efficient Routing Mechanism Based on Similarity Guided Graph Neural Network and Decision Tree with Golden Eagle Optimization in VSN

Energy Efficient Routing Mechanism Based on Similarity Guided Graph Neural Network and Decision Tree with Golden Eagle Optimization in VSN

A Reliable Transmission on Cluster Based Wireless Ad Hoc Network with Adaptive Negotiations Using Vector Assisted Energy Efficient Dynamic Opportunistic Routing Mechanism

A Reliable Transmission on Cluster Based Wireless Ad Hoc Network with Adaptive Negotiations Using Vector Assisted Energy Efficient Dynamic Opportunistic Routing Mechanism

Energy aware data harvesting strategy based on optimal node selection for extended network lifecycle in smart dust

Smart Dust environment face additional challenges as a result of the use of movable Smart Dust basestation(BS), despite its benefits. The main point of contention is the BS positioning updates to the smart dust nodes. Each smart object ought to be aware of the BS location so that it can send its data to the BS. According to the prevailing Flooding approach, the moveable BS must continuously distribute its location throughout the network in order to inform smart dust nodes about the BS location. In every case, visit positioning upgrades from the BS can result in maximal power usage as well as enhanced network breakdowns. Different sorts of routing architectures can be used to reduce BS position updating. A routing strategy based on the movable BS is successful if it preserves the network network’s power consumption and latencies to a minimum. The study’s main goal is to develop an energy-efficient routing mechanism focused on adaptive movable BS modification. In the Smart Dust Head (SDH) establishing the inferred surroundings, the most latest movable BS location will be preserved. As a result, rather than soliciting SDH in the environment, the location of the BS is propagated to the smart dust nodes located at the sectors in integrated networking. By transmitting request information to the nearest sector, the remaining SDH can find the most current BS location. The message’s recipient is determined based on the information gathered. The best fuzzy related clustering algorithm will be used to accomplish this. The Enhanced Oppositional grey wolf optimization (EOGWO) methodology can be used to perform the improvement. Optimum network throughput, low latency, and other metrics are used to assess performance. To enhance productivity, the findings will be analyzed and compared to previous routing methodologies.

CEER: Cooperative Energy-Efficient Routing Mechanism for Underwater Wireless Sensor Networks Using Clusters

Underwater acoustic sensor networks (UWASNs) aim to find varied offshore ocean monitoring and exploration applications. In most of these applications, the network is composed of several sensor nodes deployed at different depths in the water. Sensor nodes located at depth on the seafloor cannot invariably communicate with nodes close to the surface level; these nodes need multi-hop communication facilitated by a suitable routing scheme. In this research work, a Cluster-based Cooperative Energy Efficient Routing (CEER) mechanism for UWSNs is proposed to overcome the shortcomings of the Co-UWSN and LEACH mechanisms. The optimal role of clustering and cooperation provides load balancing and improves the network profoundly. The simulation results using MATLAB show better performance of CEER routing protocol in terms of various parameters as compared to Co-UWSN routing protocol, i.e., the average end-to-end delay of CEER was 17.39, Co-UWSN was 55.819 and LEACH was 70.08. In addition, the average total energy consumption of CEER was 9.273, Co-UWSN was 12.198, and LEACH was 45.33. The packet delivery ratio of CEER was 53.955, CO-UWSN was 42.047, and LEACH was 30.31. The stability period CEER was 130.9, CO-UWSN was 129.3, and LEACH was 119.1. The obtained results maximized the lifetime and improved the overall performance of the CEER routing protocol.

Sustainable Multipath Routing for Improving Cross-Layer Performance in MANET Using an Energy Centric Tunicate Swarm Algorithm

Generally, battery power is a valuable resource for mobile devices in a Mobile Ad Hoc Network (MANET). Therefore, energy efficiency and network lifetime should be taken into account when developing control strategies. However, designing an energy-efficient routing mechanism necessitates consideration of many nodes from many layers, such as remaining energy, overall traffic load, and channel assumptions. The traditional layered strategy is unsuccessful in dealing with power-related issues that might affect all layers of the stack. In this paper, the Energy Centric Tunicate Swarm Algorithm (ECTSA) is proposed to perform the cross-layer routing over MANET. The fitness metrics considered in the ECTSA to improve the cross-layer routing are residual energy, communication cost, Data Success Rate (DSR), and mobility. Additionally, an Adaptive Competition Window (ACW) adjustment is used for minimizing the energy consumption caused by the contentions. The performance of the proposed ECTSA is analyzed by means of energy consumption, Packet Delivery Ratio (PDR), End-to-End Delay (EED), and routing overhead. Next, the existing techniques, namely, CEELBRP and EECRP-PSO, are used to evaluate the efficiency of the ECTSA method. The energy consumption of the ECTSA is 7.1 joules and prolongs the network lifetime up to 1603 s for 50 nodes, which is better when compared to the existing CEELBRP and EECRP-PSO techniques.

DCM–RPL: A Distributed Competition Mobility Management Scheme for RPL/6LoWPAN

The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) as a reliable and energy-efficient routing mechanism has become the de facto standard routing protocol of IPv6 over Low-powered Wireless Personal Area Network (6LoWPAN). However, it is designed for static wireless sensor networks and is not suitable for mobile scenarios. When mobile nodes (MNs) exist in the 6LoWPAN network, repeated link disruptions and topology changes lead to data packets loss and affect network stability. An increasing number of mobile applications force the improvement of RPL protocols for supporting mobility. In this study, a distributed competition and mobility-aware RPL routing protocol (DCM–RPL) is proposed to carry out mobility management and alleviate the network burden in the mobile scenario. A new preferred parent-discovering mechanism for MNs based on a distributed competition algorithm integrated with Objective Function is designed, which can dramatically reduce power consumption in the new parent node (PN)-discovering phase. To reduce data loss during the node-moving process, a packet-caching mechanism is proposed in the PN update phase. Finally, test-beds are set up and simulated in the Cooja simulator. Comparing the performance of the DCM–RPL in terms of switching delay, energy consumption, and PDR with the RPL and its mobility-aware variant (mRPL and EC–MRPL); the simulation results show that the proposed scheme maintains efficiency.

Learning automata based energy efficient and reliable data delivery routing mechanism in wireless sensor networks

Wireless Sensor Networks (WSNs) emerged as major data gathering paradigm due to its wide variety of applications. Achieving energy efficient reliable data delivery is an important concern in WSNs. In a network, packet loss reduces the reliable data transmission rate. Retransmissions are required to increase the reliable data transmission rate. However, number of retransmissions also increase the network energy consumptions and packet delivery delay. Packet loss rate can be reduced by selecting a best successor node in a routing path. In this work, a Learning Automata based Routing mechanism is proposed for wireless sensor networks to achieve energy efficiency and reliable data delivery. In this paper, learning automata has been adopted to calculate next node’s selection probability in a routing path using node’s score, quality of link and previous selection probability. Further, an energy efficient reliable routing mechanism is proposed using combination of learning automata and A-star search algorithm. The proposed mechanism determines energy efficient and reliable routing paths in WSNs by favoring highest residual energy, good quality of link , more free buffer space and less distance. Finally, simulation results indicate that the proposed algorithm reduces the energy consumptions, data delivery delay, data transmissions and increases the network lifetime.

Survey on Recent Advancements in Energy-Efficient Routing Protocols for Underwater Wireless Sensor Networks

Underwater wireless sensor networks (UWSNs) have become highly efficient in conducting various operations in maritime environments. Compared to terrestrial wireless sensor networks, routing protocols in UWSNs are prone to high propagation delay, high energy consumption, low bandwidth, and low throughput. UWSNs are remotely located and operate without the need for human intervention. Most sensor batteries are energy restricted and very difficult to replace. One of the major challenges of UWSNs is the uneven utilization of energy resources, which reduces the network lifetime. Therefore, an energy-efficient routing mechanism is necessary to overcome the aforementioned problems. Many significant studies have attempted to realize this goal by designing energy-efficient routing protocols to provide efficient packet routing from source to destination. In this paper, we focus on discussing various energy-efficient routing protocols that are currently available for UWSNs, categorize them with a new taxonomy, and provide a comparative discussion. Finally, we present various research problems that remain open and challenges for future research.

Efficient Performance Analysis of Energy Aware on Demand Routing Protocol in Mobile Ad‐Hoc Network

AbstractIn a networking scenario, energy protocols with shortest path routing mechanisms are prevalent. The challenging issue in designing the routing protocols for a mobile ad hoc network (MANET) is to have a network, which is energy efficient so as to maximize network performance. This research article proposes a novel and energy efficient shortest path routing mechanism called the energy aware on demand routing protocol. The protocol maximizes the lifetime of the MANET and provides an economically efficient routing mechanism for the packets depending on the routing condition. The energy efficient routing in MANET simply establishes routes amongst the mobile nodes and protocol functions in the network as long as its energy is available. The protocol is set to minimize transmitter/receiver energy, or inactivate energy consumption when a mobile node is in idle/sleep mode. At the same time, it monitors the wireless medium for any possible communication requests from other nodes in the network. To validate the proposed energy efficient routing protocol, its performance is compared with the performance of other well‐known routing protocols wherein the energy utilization in the network is also considered, namely, the dynamic source routing protocol and conditional max‐min battery capacity routing protocol in the network simulator‐2. The comparison is performed in terms of its packet loss, packet delivery ratio, average energy consumption, and network lifetime. The performance analysis shows that the proposed protocol is superior in terms of energy consumption for the transmission of data in the network.

Energy Efficient Dynamic Routing Mechanism (EEDRM) with Obstacles in WSN

In Wireless Sensor Networks, the in-built energy and processing capacity of sensors should be reliably used to ensure effective use of resources. The major pitfalls in WSN include network lifetime management, energy management and Obstacle avoidance. The paramount aim of proposed EEDRM protocol is to deliver better network efficiency thus uses the concept called clustering of sensor nodes. Cluster Heads are chosen based on energy, distance between cluster head (CH) and sink. Mobility enables high resource usage, hence in proposed work Cluster Heads are made mobile and routes in computed path. Obstacles in sensing environment is an important thing to be considered. EEDRM is designed in a way that it resists obstacles using travelling salesman problem, Hamiltonian Circuit algorithms and with the help of binary grid pattern in sensing environment. Data latency is reduced as CH is available all the time for receiving data from CM inside Cluster and all CH are independent to each other so data collected by CH will be transferred dynamically to the sink. Based on Obstacle avoidance model and node states an FSM is constructed using hidden Markov model. The increased network lifetime and throughput of EEDRM is analysed and compared with M-GEAR protocol. Analysis comes out with the result that EEDRM is 1.82 times better than M-GEAR and 3.92 times better than LEACH ME in terms of throughput and in terms of network lifetime EEDRM outperforms M-GEAR by 1.2 times and LEACH ME by 1.54 times.

IMPLEMENTATION BASED ON 0.18 µM CMOS TECHNIQUES FOR DIGITAL PLL SYNTHESIZER IN LOW LOCKING TIME .

Currently, Mobile Ad-hoc networks (MANET) are consider as an important portion of the wireless networks and for the communication in MANET, routing mechanism is also play a vital role. MANET routing protocol generates a different performance when it is implemented in a different network scenario. It is a challenge to find the suitable characteristic of MANET routing protocol which conforms to a certain network condition scenario. In the last ten years, many research have been done by the research to analyze the performance of MANET routing protocol but still lots of problems are faces. However, those research are related to the scope of routing protocol based MANET scenario. Basically, there two types of routing mechanism that is known as the Proactive and the Reactive routing protocol. Alternatively, there is a routing protocol which is a combination of both proactive as well as reactive, namely the Hybrid routing protocol. Hybrid routing protocols especially capable to solve the MANET energy consumption by constructing a zone routing protocol (ZRP) and it is superior to over proactive and reactive routing protocols. So, in this research, we proposed an optimized Artificial Neural Network (ANN) based Improved Energy Efficient ZRP (IEE-ZRP) mechanism for MANET with the help of the Grasshopper Optimization Algorithm (GOA). The total MANET simulation area is divided into different zones or clusters or regions to create a secure and energy efficient routing mechanism. The IEE-ZRP mechanism perform better as compare to others routing protocols that clearly mentioned in the results analysis section based on the Quality of Service (QoS) parameters such as Throughput, Packet Delivery Ratio (PDR), Packet Drop Ratio, Delay, Energy Consumption and Control Overhead.

Scalable energy efficient routing mechanism prolonging network lifetime in wireless sensor networks

Scalable energy efficient routing mechanism prolonging network lifetime in wireless sensor networks

Scalable energy efficient routing mechanism prolonging network lifetime in wireless sensor networks

Due to the tiny size, nodes in a wireless sensor network (WSN) are restricted in battery capacity. As a result, a node and in turn a network of such nodes is not operational for a long time. Further, in some hostile area, battery cannot be replaced easily once deployed. Therefore, an energy conservation scheme or algorithm is needed to prolong the network lifetime. In this paper, an energy efficient routing scheme (EERS) is proposed and evaluated. This scheme extends the lifetime of network by selecting the finest shortest path to transmit data packets to the destined nodes. EERS selects a path/quality link over which it has minimum number of hops with maximum remaining energy over that path. Proposed scheme EERS is compared with other existing schemes for different parameters and varying size of network (1001,000 nodes). The simulation results shows that the EERS scheme prolongs the network lifetime 10%-15% as compared to other considered schemes. EERS also minimises the delay for transmitting data packets and increases the packet delivery ratio.

Hybrid Energy and Trust Efficient Reactive Routing Mechanism for MANETs

The facilitation of quality of service (QoS) under routing in Mobile Ad Hoc NETworks (MANETs) is a challenging issue due to its resource constraints, bandwidth sharing and topology dynamism. Moreover, security is considered as another complex issue of provisioning QoS as the prevalence of maliciousness nodes introduces all types of threats to the MANETs. In spite of a diversified number of mechanisms contributed for securing MANETs, majority of the solutions are potential in preventing some particular category of attacks or facilitate security by sacrificing the QoS cost. In this paper, Hybrid Energy and Trust Efficient Reactive Routing Mechanism (HETERRM) was proposed for ensuring trust-oriented QoS routing process that integrates QoS trust and social trust. This proposed HETERRM first relies on the process of mitigating maliciousness nodes by incorporating a trust mechanism that is capable in different packet forwarding misbehavior and reliable path discovery for facilitating trustworthy communication. This proposed HETERRM further aids in selecting the optimal forwarding node based on quality of channel, quality of link and residual energy to quantify the packet forwarding potential. The simulation experiments of the proposed HETERRM are conducted using ns-2 is evaluated using energy consumptions, packet delivery ratio and overhead.

Energy Efficient Routing Mechanism for Harsh Environment in Wireless Sensor Networks

Energy Efficient Routing Mechanism for Harsh Environment in Wireless Sensor Networks

An energy-efficient gossiping protocol for wireless sensor networks using Chebyshev distance

As the use of Wireless Sensor Networks grows, many challenging issues with these networks arise. The utilization of power consumption is one of the most significant issue due to the limited energy constraints of the individual sensor nodes. This limitation imposes a challenge to design the best energy-efficient routing mechanism. This work presented an Energy-Efficient Gossiping protocol (EEGossip) that routes data to the sink by choosing the optimal next node. EEGossip uses Chebyshev distance, residual energy and the sink distance as factors when determining the optimal next node. The result of the proposed work has shown that the proposed protocol improves the total energy consumption of the network and leverages the network lifetime since it decreases the computational overhead and ensures that the best next node is chosen.

A Green Routing Algorithm for IoT-Enabled Software Defined Wireless Sensor Network

Rapid growth in the domain of Internet of Things (IoT) leads to massive deployment of sensors and therefore the need to develop automatically reconfigurable complex wireless sensor network. Software defined networking (SDN) is a promising and widely adopted technique to automatic reconfigure the wireless sensor network. In SDN, control nodes are dynamically selected (to activate the functioning of the sensor network) in order to assign the tasks to other nodes and for routing data packets to control server. For residual energy of sensor nodes, and transmission distance among sensor nodes, the problem of control node selection has been formulated as an NP-hard problem. Usually, smart sensing devices of IoT suffers from low battery which are not frequently rechargeable. Therefore, an energy efficient routing mechanism is required to operate software defined wireless sensor network (SDWSN). In this paper, a green routing algorithm using fork and join adaptive particle swarm optimization (FJAPSO) is proposed to maximize the lifetime of sensor network. FJAPSO acts at two levels for auto optimization: optimal number of control nodes and optimal clustering of control nodes. Experimental results evidenced that FJAPSO outperforms other state of the art and significantly maximizes the lifetime of the sensor network.

Energy-efficient routing for mobile data collectors in wireless sensor networks with obstacles

This paper proposes an energy-efficient routing mechanism by introducing intentional mobility to wireless sensor networks (WSNs) with obstacles. In the sensing field, Mobile Data Collectors (MDCs) can freely move for collecting data from sensors. An MDC begins its periodical movement from the base station and finally returns and transports the data to the base station. In physical environments, the sensing field may contain various obstacles. A research challenge is how to find an obstacle-avoiding shortest tour for the MDC. Firstly, we obtain the same size grid cells by dividing the network region. Secondly, according to the line sweep technique, the spanning graph is easily constructed. The spanning graph composed of some grid cells usually includes the shortest search path for the MDC. Then, based on the spanning graph, we can construct a complete graph by Warshall-Floyd algorithm. Finally, we present a heuristic tour-planning algorithm on the basis of the complete graph. Through simulation, the validity of our method is verified. This paper contributes in providing an energy-efficient routing mechanism for the WSNs with obstacles.

Neural Network Enabled WSN Management for Energy Efficient Routing Mechanism

Background/Objectives: To design a model for Wireless Sensor Network which manage the routing mechanism efficiently and reduce the power consumption during packet routing. Methods: Neural Network Approach e.g. Self-Organized Map and K-Means Algorithms used for cluster selection and election to improve the energy efficiency. Findings: Neural Networks algorithms in combination of cluster head load sharing and self-silence model provides a better performance than the existing Wireless Sensor Network routing protocols. Improvements/Applications: This design approach can be further enhanced through Fuzzy based neural network model.

Topology control of tactical wireless sensor networks using energy efficient zone routing

The US Department of Defense (DoD) routinely uses wireless sensor networks (WSNs) for military tactical communications. Sensor node die-out has a significant impact on the topology of a tactical WSN. This is problematic for military applications where situational data is critical to tactical decision making. To increase the amount of time all sensor nodes remain active within the network and to control the network topology tactically, energy efficient routing mechanisms must be employed. In this paper, we aim to provide realistic insights on the practical advantages and disadvantages of using established routing techniques for tactical WSNs. We investigate the following established routing algorithms: direct routing, minimum transmission energy (MTE), Low Energy Adaptive Cluster Head routing (LEACH), and zone clustering. Based on the node die out statistics observed with these algorithms and the topological impact the node die outs have on the network, we develop a novel, energy efficient zone clustering algorithm called EZone. Via extensive simulations using MATLAB, we analyze the effectiveness of these algorithms on network performance for single and multiple gateway scenarios and show that the EZone algorithm tactically controls the topology of the network, thereby maintaining significant service area coverage when compared to the other routing algorithms.