Geographical Adaptive Fidelity Research Articles

An Energy-Efficient Protocol based on Recursive Geographic Forwarding Mechanisms for Improving Routing Performance in WSN

In situations where a regular network may not be appropriate or is unable to function correctly, data collection and real-time transmission are commonly done using Wireless Sensor Networks (WSNs). In order to accomplish this type of operation, the network's durability and performance are extremely vital. One of the key elements that directly affect a network's lifespan and performance is the routing protocol. This study proposes a Geographic Forwarding Energy Efficient Routing Protocol (GF-EERP), an enhanced version of the Geographic Energy Aware Routing (GEAR) protocol that helps to extend the network's lifespan and performance. The introduction of node categorization, a unique technique for choosing the region head, use of multi-hop communication method and removal of dead nodes serve as the foundation of the GF-EERP. In this study, the proposed protocol's performance is also compared to other protocols already in use, like Geographic Adaptive Fidelity (GAF), Geographic Energy Aware Routing (GEAR), Greedy Perimeter Stateless Routing (GPSR) and Multihop-Geographic Energy Aware Routing (M-GEAR), using a variety of performance metrics including Network Delay, Data Delivery Ratio and Network Throughput. The simulation outcomes prove that the performance of GF-EERP, with its distinct node categorization and region head selection mechanism is superior to the existing protocols.

Classification Method for Power Load Data of New Energy Grid based on Improved OTSU Algorithm

The classification method for power load data of new energy grid based on improved OTSU algorithm is studied to improve the classification accuracy of power load data. According to the idea of two-dimensional visualization of time series, GAF (Geographical Adaptive Fidelity) method is used to transform the current data of power load in new energy grid into two-dimensional image of power load in new energy grid. The intra class dispersion is introduced, and the improved OTSU algorithm is used to segment the foreground and background of the two-dimensional image according to the pixel gray value of the two-dimensional image and the one-dimensional inter class variance corresponding to the pixel neighborhood gray value. The two-dimensional foreground image of power load is taken as the input sample of convolution neural network. The convolution neural network extracts the features of the two-dimensional foreground image of power load through convolution layer. According to the extracted features, the classification results of power load data of new energy grid are output through three steps: nonlinear processing, pooling processing and full connection layer classification. The experimental results show that this method can accurately classify the power load data of new energy grid, and the classification accuracy is higher than 97%.

Energy Efficient Strategy for WSN Technology Using Modified HGAF Technique

<p class="0affiliation">Due to the rapid growth in technologies has led to the development of sensor nodes. As we know that wireless sensor network is collection of small and large number of sensor node. These sensor nodes are used for different domain like environmental research, health care, monitor, military, and record the physical activity. These nodes communicate with each other and forward the message to base station. For communication of these node different algorithms used Geographical adaptive fidelity (GAF) is one of them. Dropping energy utilization in wireless sensor network directly affects the network lifetime. HGAF is one of the important multiple location based on routing system algorithm. The main function of HGAF technique is to turn-off the unnecessary nodes in the network without interrupting the other connected node. In this paper we proposed a technique known as modified HGAF and it design as a power saving method. In the proposed technique the size of cell structure in grid changed and communication method improve due to those changes. Based on the result the proposed technique increase 25% in dead node ratio and also increase the network.</p>

Performance Review of Selected Topology-Aware Routing Strategies for Clustering Sensor Networks

In this paper, cluster-based routing (CBR) protocols for addressing issues pertinent to energy consumption, network lifespan, resource allocation and network coverage are reviewed. The paper presents an indepth performance analysis and critical review of selected CBR algorithms. The study is domain-specific and simulation-based with emphasis on the tripartite trade-off between coverage, connectivity and lifespan. The rigorous statistical analysis of selected CBR schemes was also presented. Network simulation was conducted with Java-based Atarraya discrete-event simulation toolkit while statistical analysis was carried out using MATLAB. It was observed that the Periodic, Event-Driven and Query-Based Routing (PEQ) schemes performs better than Low-Energy Adaptive Clustering Hierarchy (LEACH), Threshold-Sensitive Energy-Efficient Sensor Network (TEEN) and Geographic Adaptive Fidelity (GAF) in terms of network lifespan, energy consumption and network throughput.Keywords: Wireless sensor network, Hierarchical topologies, Cluster-based routing, Statistical analysis, Network simulation

Energy Aware Relay GAF algorithm for WSN using Improved Conservative schemes

Wireless sensor systems (WSN) is the system of Sensor Nodes (SNs) in which every hub have detecting, correspondence and calculation office. The fundamental impediment of WSN is that SNs have restricted vitality. So the fundamental focal point of research in WSN is to improve the Network Lifetime by falling vitality utilization. A few areas mindful directing convention has been proposed. Geographic Adaptive Fidelity (GAF) is one of the most famous vitality mindful steering conventions. It moderates vitality by recognizing equality between sensors from a steering point of view and after that killing superfluous sensors, while keeping up the availability of the system. Anyway conventional GAF can't achieve the ideal vitality use. It requires progressively number of jumps to transmit information from source to sink.so that it prompts higher bundle delay. The underlying issue of essential GAF is information can be sent in just flat and vertical. The issues which are being worked in this undertaking are minimization of jump check, parcel deferral and separation secured by the bundle postponement steering utilizing vitality mindful Relay GAF calculation Both the conventions are actualized in MATLAB. Investigation and reproduction results show critical enhancements of the projected work contrasting with customary GAF in the part of absolute jump check, arrange lifetime vitality utilization, all out separation secured by the information bundle before achieving the sink, and parcel delay.

A Heuristic Algorithm of Cooperative Agents Communication for Enhanced GAF Routing Protocol in WSNs

Rapid progress in technologies has led to the development of small sensor nodes. A wireless sensor network (WSN) is an interconnected collection of a large number of these small sensor nodes that is used to monitor and record the physical environment. WSNs have applications in diverse scenarios. They play an important role in tracking and monitoring in different domains, such as environmental research, military, and health care. In most of these applications, the WSN is composed of a large number of nodes deployed in an area of interest, and not all nodes are directly connected to the base station (BS). In some cases, batteries of nodes cannot be recharged or changed. For that, the most solution required to overcome these problems is to optimize energy consumed during communication. Data transmission in networks is maintained by routing protocols, which are responsible for discovering the required paths. This paper presents an improvement of the Geographic Adaptive Fidelity (GAF) routing protocol created on a smart actives node selection. The routing process works on cooperative agents communication where another node is activated in the same grid if the data collected are considered as important data, and a heuristic method is used to find an optimal path in terms of energy to transmit data collected until reaching the BS. Simulation results prove that the cooperative agents GAF (CAGAF) routing protocol proposed is more efficient compared to the basic version in terms of considering important data, energy consumed, and dead nodes.

FGAF-CDG: fuzzy geographic routing protocol based on compressive data gathering in wireless sensor networks

In the wireless sensor networks (WSNs), energy consumption is one of the significant factors. Most of the energy in a WSN is consumed by communication between nodes. To minimize energy consumption, routing protocols can be merged with data aggregation techniques. The geographic adaptive fidelity (GAF) protocol is one of the prominent geographic routing protocols which is proposed in order to reduce energy consumption in WSNs. Moreover, compressive sensing (CS) theory presented as an alternative method for data gathering in WSNs, known as compressive data gathering (CDG). CDG reduces the cost of communications and balances the energy load in the network without imposing heavy computation or transmission overhead. With CDG, instead of receiving all readings from the sensors, the sink may receive few weighted sums of all the readings by which original data can be recovered by the sink. In this paper, we propose a GAF-based routing protocol based on CDG technique named fuzzy GAF based on CDG (FGAF-CDG). In this work, we partition the sensors area into virtual hexagonal grid cells firstly and then we lay the cells according to their geographic locations. In each sampling round, cluster head (CH) sensor in each grid cell is selected based on a fuzzy logic-based algorithm. Then, CH readings will be forwarded to the sink in a multi-hop path based on a fuzzy-based routing algorithm in the CDG form. Simulation results show that the proposed method results in superior efficiency as compared to other competitive GAF-based methods. For example, the proposed model offers about 50% reduction in energy consumption as compared to FTGAF-HEX method depending on the dimensions of the sensors area.

Fuzzy logic based multihop topology control routing protocol in wireless sensor networks

Reducing energy consumption has been a recent focus of wireless sensor network as it directly affects network lifetime. Geographical adaptive fidelity (GAF) is one of the well-known topology management multihop location-based routing protocols. Its main objective is to turn-off unnecessary sensor nodes while maintaining uninterrupted connectivity between communicating sensors. It is proved to be able to extend the lifetime of self-configuring systems by exploiting redundancy to conserve energy while maintaining application fidelity. Traditional GAF introduces unreachable corners; also the symmetric property is at stake thus providing with less network utility. In this paper, we propose a fuzzy logic based geographic routing protocol named FGAF-HEX to achieve higher energy optimization. Further, we use a GAF based Honeycomb Architecture to replace the traditional square grid with the hexagonal virtual grid. Simulation and analysis results show significant improvement in proposed work over traditional GAF in terms of various parameters, i.e., network lifetime and network connectivity. Results show that FGAF-HEX provides a substantial improvement in terms of various metrics as compared to traditional GAF.

FTGAF-HEX: fuzzy logic based two-level geographic routing protocol in wireless sensor networks

Minimization of energy consumption has become a major challenge in wireless sensor networks (WSNs) as it directly corresponds to the network lifetime. In WSNs, geographic adaptive fidelity (GAF) is one of the most energy efficient location based protocol which extends the network lifetime by identifying equivalence between sensors using geographic location information and then keeping unnecessary sensors in sleep state, while maintaining application fidelity. Still traditional GAF cannot reach to the optimum energy usage since it needs more hop count to transmit data packets to the base station called sink. As a result, it leads to higher energy usage and packet delay due to participation of more sensors. In this paper, a fuzzy logic based topology management protocol named FTGAF-HEX, which bases on GAF is proposed to achieve minimum packet delay with higher energy conservation. Furthermore, we propose to use a generalized version of GAF based on honeycomb virtual grid architecture called Hexagonal GAF (GAF-HEX) to replace the square grid with hexagonal one. Analysis and simulation results show significant improvement of the proposed work compared to traditional GAF in the aspect of various performance metrics i.e., total hop count, energy consumption and distance covered by the data packet before reaching the sink. As a result, compared to traditional GAF-HEX, it needs 37–44% less hop count and consumes 17–24% less energy to prolong the network lifetime.

New Smart nodes distribution using Kmeans Approach to enhance Routing in WSN

Objectives: Wireless Sensor Network (WSN) is an advanced technology, applied to many fields of research. However, it still limited due to some drawbacks, the energy consumed is one of them, which presents a critical issue. So that, our objective in this paper is to decrease the energy consumed during communication and prolong the network lifetime in Geographic Adaptive Fidelity (GAF) protocol. Methods/Statistical analysis: The Kmeans method was been exploited for improving the energy consumed in the network during routing data, which permit extending the network lifetime. It aims at distributing the sensor nodes. Where, the gravity center is determined as an active node, considering the least distance to the center of gravity and respecting the multihop communication between Active nodes. Findings: Simulation results confirmed that our new improved protocol reduces significantly nodes energy, which improves the network lifetime. Application/Improvements: By introducing our enhanced version Kmeans GAF, we can improve localization systems.

A Novel Scheme to Minimize Hop Count for GAF in Wireless Sensor Networks: Two-Level GAF

In wireless sensor networks, geographic adaptive fidelity (GAF) is one of the most popular energy-aware routing protocols. It conserves energy by identifying equivalence between sensors from a routing perspective and then turning off unnecessary sensors, while maintaining the connectivity of the network. Nevertheless, the traditional GAF still cannot reach the optimum energy usage since it needs more number of hops to transmit data packets to the sink. As a result, it also leads to higher packet delay. In this paper, we propose a modified version of GAF to minimize hop count for data routing, called two-level GAF (T-GAF). Furthermore, we use a generalized version of GAF called Diagonal-GAF (DGAF) where two diagonal adjacent grids can also directly communicate. It has an advantage of less overhead of coordinator election based on the residual energy of sensors. Analysis and simulation results show significant improvements of the proposed work comparing to traditional GAF in the aspect of total hop count, energy consumption, total distance covered by the data packet before reaching the sink, and packet delay. As a result, compared to traditional GAF, it needs 40% to 47% less hop count and consumes 27% to 35% less energy to extend the network lifetime.

GAFBone: A New Backbone Construction for Increasing Lifetime in Wireless Sensor Networks

Wireless sensor networks, which have been used in many applications in recent years, consist of tiny sensor nodes with restriction in processing ability and the battery unit. Because of that, one of the crucial problems in this field is power consumption and network lifetime. Geographic Adaptive Fidelity is a routing protocol which tries to reduce energy consumption by powering off unnecessary nodes. In this paper, we proposed a new backbone algorithm for this protocol to saving more energy which causes to improving the lifetime and performance of the networks. The results of simulation show that active grids will be halved approximately.

A Novel Sensor Deployment Approach Using Multi-Objective Imperialist Competitive Algorithm in Wireless Sensor Networks

A wireless sensor network is a set of spatially distributed sensor nodes that work together to cover a monitored area. Usually, a large number of sensor nodes are densely deployed because of the limited energy resources available to them. An efficient way to save energy in the system at any particular time is to activate the minimum number of sensors needed and put the remaining sensors in sleep mode. In this study, a novel multi-objective Imperialist Competitive Algorithm, called MOICA, is proposed for handling sensor deployment. The main goal is to minimize the number of active sensor nodes while achieving the maximum coverage. To illustrate the efficiency of the proposed algorithm, a set of experiments from previous studies are carried out. Numerical results indicate that with the same number of deployed sensors, MOICA can provide more accurate solutions in less computational time when compared to the existing methods, namely, coverage configuration protocol, optimal geographical density control, energy-efficient coverage control algorithm and improved geographical adaptive fidelity.

A Study of Geographic Adaptive Fidelity Routing Protocol in Wireless Sensor Network

The Energy consumption is a great challenge in the field on Wireless Sensor Network (WSN). It affects the performance of the whole network. There are two basic functions of nodes in the WSN. First is to collect the information from other sensor nodes and second is to pass the information to the base station. A variety of routing protocols have been proposed to reduce the energy consumption of nodes and increase the network lifetime. One of the most popular energy efficient routing protocol is Geographic Adaptive Fidelity (GAF). This is the location based routing protocol which uses the nodes location information to transfer the data. This reduces the use of energy by turning off the radio of some nodes which share the same functionalities. This paper focuses on the GAF protocol and its working. Also this paper reviews the variety of new versions based on GAF protocol to make it better.

TOPOLOGY MANAGEMENT IN WIRELESS SENSOR NETWORKS: MULTI-STATE ALGORITHMS

In order to maximize the network’s lifetime and ensure the connectivity among the nodes, most topology management practices use a subgroup of nodes for routing. This work provides an in-depth look at existing topology management control algorithms in Multi-state structure. We suggest a new algorithm based on Geographical Adaptive Fidelity (GAF) and Adaptive Self-Configuring Sensor Networks Topology (ASCENT). The new proposed algorithm outperforms both GAF and ASCENT algorithms.

Hierarchical Low Power Consumption Technique with Location Information for Sensor Networks

In the wireless sensor networks composed of battery-powered sensor nodes, one of the main issues is how to save power consumption at each node. The usual approach to this problem is to activate only necessary nodes (e.g., those nodes which compose a backbone network), and to put other nodes to sleep. One such algorithm using location information is GAF (Geographical Adaptive Fidelity), and the GAF is enhanced to HGAF (Hierarchical Geographical Adaptive Fidelity). In this paper, we show that we can further improve the energy efficiency of HGAF by modifying the manner of dividing sensor-field. We also provide a theoretical bound on this problem.

Minimizing Energy Consumption in Wireless Ad hoc Networks with Meta heuristics

The objective of this study is to describe an energy function model base on Geographic Adaptive Fidelity (GAF), which is one of the best known topology management schemes used in saving energy consumption in ad-hoc wireless networks. In wireless ad-hoc network, the nodes responsible for the transmission of data are battery-operated and as a result, there is a need for energy to be conserved in order to prolong the battery lifespan. Genetic Algorithm (GA) and Simulated Annealing (SA) metaheuristics are compared to minimize the energy consumption in ad-hoc wireless networks modelled by rectangular GAF. Results show that GA and SA meta-heuristics are useful optimization techniques for minimizing the energy consumption in ad-hoc wireless networks.

Topology Management in Wireless Sensor Networks: Multi-State Algorithms

In order to maximize the network’s lifetime and ensure the connectivity among the nodes, most topology management practices use a subgroup of nodes for routing. This paper provides an in-depth look at existing topology management control algorithms in Multi-state structure. We suggest a new algorithm based on Geographical Adaptive Fidelity (GAF) and Adaptive Self-Configuring Sensor Networks Topology (ASCENT). The new proposed algorithm outperforms both GAF and ASCENT algorithms.

Topology control based on optimally rigid graph in wireless sensor networks

This paper presents an optimization scheme of sensor networks for node scheduling and topology control, aiming to reduce energy consumption for heterogeneous Wireless Sensor Networks (WSNs) with non-uniform transmission ranges. Motivated by geographical adaptive fidelity (GAF), we partition sensors into groups based on the location of sensors, such that a connected backbone network can be maintained by keeping only one arbitrary node from each group in active status while putting others to sleep. In addition, optimally rigid geographical adaptive fidelity (ORGAF) approach is proposed to decrease the communication complexity and reduce the energy dissipation. Furthermore, we prove the topology derived under ORGAF is 2-connected; and the average degree of nodes in the topology converges to four approximately. Simulation results show that ORGAF can improve the network performance as well as reducing the energy consumption.

Geographic Adaptive Fidelity and Geographic Energy Aware Routing in Ad Hoc Routing

Location based routing protocols are the kinds of routing protocols, which use of nodes’ location information, instead of links’ information for routing. They are also known as position based routing. In position based routing protocols, it is supposed that the packet source node has position information of itself and its neighbors and packet destination node. In recent years, many location based routing protocols have been developed for ad hoc and sensor networks. In this paper we shall present the concept of location-based routing protocol, its advantages and disadvantages. We shall also look into two popular location-based protocols: Geographic Adaptive Fidelity (GAF) and Geographic and Energy Aware Routing (GEAR).