Nodes In Wireless Networks Research Articles

Power Amplifier Design for 25.1 km Long-Distance Transmission Under 214 km/h High-Speed Movement of Air-to-Ground Wireless Self-Assembled Network Nodes

In this paper, we design a power amplifier for this network protocol to combat the Doppler effect caused by the high-speed movement of network nodes and the rapid signal fading failure caused by the long-distance transmission of network nodes, and to extend the communication distance between network nodes, to realize the long-distance transmission under the high-speed movement of network nodes. The overall design of the power amplifier for bi-directional transmission structure, power amplifier transmitter, and low-noise amplifier receiver is used in a four-stage cascade current series negative feedback structure mode, where the signal transmitter selected RFPA5208 and MAX4003 chip, the signal receiver selected TQP3M9037 and SKY16602 chip. The above overall design enables the self-assembled nodes to ensure stable topology and achieve long-spacing transmission even in the high-speed mobile state. The test results show that the output power is 41.5dBm-44.3dBm, the gain is 44dB-45dB, and the noise is 1.6dB when the frequency band range is 2.4GHz-2.5GHz. The experimental results show that when the self-assembling nodes maintain the relative speed of 214km/h, the longest transmission distance of the point-to-point of the amorphous flat terrestrial wireless self-assembling network reaches 16300m, and the longest transmission distance of the point-to-point of the amorphous flat air-to-ground wireless self-assembling network reaches 25100m. The power amplifier designed in this paper has good application value. It provides an individual research basis for future research on the framework of a low-altitude economic fly-by-wire network.

Development of an Energy-Efficient Routing Algorithm for Long Distant Wireless Sensor Network Infrastructure

This paper presents the performance of Wireless Sensor Networks in an energy-efficient test-bed to mitigate the undesired consequence of increased energy consumption. The Wireless Network Nodes constitute the main component of Wireless infrastructure and the major contributor to the energy consumption of Wireless Sensor Networks. Therefore, there is a need for a well-designed and planned infrastructure to effectively serve customers to avoid incessant collisions, attacks and shut downs. This work developed and designed a MATLAB Model for simulation and analysis of the Wireless Sensor Network energy saving that has a functional capacity that lasted an estimated value of 330 rounds of simulation (82.5% energy efficient), unlike the conventional that lasts 120 rounds of simulation (30% energy efficient). Variation in the packet delivery ratio when cluster-based Routing Technique was activated and when it was not activated showed that the packet delivery ratio of 96% was achieved with the Proposed Model as against 64% of the conventional (existing) Model. The Sensor Network lifetime for the proposed technique increased by 52.5% compared to the conventional technique which implied better network performance.

A novel method for optimizing energy consumption in wireless sensor network using genetic algorithm

Advancements in information technology and wireless sensors networks (WSN) create new possibilities in a variety of industries, including environmental testing, healthcare, and industrial control. The sensor has become more intelligent, has begun to go wireless, and has become smaller. WSN is used in various industries thanks to its benefits such low cost, simple installation, consistent transmission, and excellent anti-interference ability. Although wireless network sensors have numerous benefits, they also have certain drawbacks. The main obstacle limiting the lifespan of wireless sensor networks is energy, and it might be difficult or even impossible to charge or replace the power sources on wireless network nodes. The battery puts limits on the network nodes responsible for data processing and information transfer. The key to network optimization is thus to increase the network's overall life. WSN have a wide range of recognized uses, and this diversity necessitates improvements to the existing protocols and their particular properties. The lifespan of the network and energy usage for routing are two important criteria that are important in every application. In order to create the perfect set of parameters for routing and application-based WSNs, the study discussed here improved network coverage, clustering, node placement, and data aggregation. A unique fitness function was created, enhanced, and customised for usage in all stages of WSN operation based on the outcomes of evolutionary algorithms and NS simulations. The results of the comparison indicated that, while to varied degrees, these logarithms and methods might reduce that energy. It has been determined that the suggested methodology could lead to a 50% reduction in energy consumption.

Application of Intelligent Sensor in Mining Electrical Equipment Collection

In order to meet the informatization requirements of coal mine safety monitoring, the author proposes a method for the application of smart sensors in the acquisition of mine electrical equipment. The system uses a variety of sensor fusion methods, with the help of Zigbee wireless network nodes, and passes the data collected by the sensor to the MCU core processor; thus, the collected data are processed, and then, the RS-485 communication protocol is used to upload the data to the upper station; finally, the monitoring of coal mine safety is realized through the background monitoring interface. Experimental results show that, among the five randomly selected nodes, most of the errors between the actual measured results and the collected results are concentrated within the 2% error range. Conclusion. The effect of the abovementioned acquisition scheme in coal mine application is verified, so as to realize the scientific monitoring of coal mine safety.

Fuzzy optimization based detection of attacker nodes in wireless networks using deep neural network

SummaryNowadays, information security attacks are emerging as the main threat to network behavior. The deployment of sensor nodes in the open environment will be subjected to various kinds of DoS attacks and it needs to be analyzed. In this article, we considered two attacks namely, black hole attack and wormhole attack. The number of sensor nodes in the wireless network deployed in the network is taken as input data. Data packet drop and transmission latency are considered as two significant drawbacks of black hole and wormhole attack. Therefore, to conquer such limitations, the deep neural network based fuzzy imperialist competitive algorithm (DNN‐FICA) is developed which accurately detects the presence of attacker node in the wireless network. Here, the FICA approach is utilized to optimize the weights of DNN. The simulation is conducted using MATLAB software considering the performance metrics such as detection rate, packet delivery ratio, energy consumption, network lifetime, end‐to‐end delay, communication overhead, throughput, and residual energy. The comparative results are carried out and the result analysis proved that the proposed DNN‐FICA technique achieved greater overall performance than other compared methods.

Bidirectional robust and fault-tolerant [formula omitted] non-sensitive compensation filter controller based on amorphous flattened air-to-ground wireless self-assembly system

With the cross-fertilization development of automatic control technology, electronic science and technology, and wireless communication technology, a single filter is no longer able to solve the fault problem of the control system and communication system simultaneously and in a balanced manner. In this paper, we design a bidirectional robust fault-tolerant H∞ non-sensitive compensation filter controller based on the robust adaptive fault-tolerant control algorithm, and further optimize the fault-tolerance correction factor and robust adaptive factor by the LMI (Linear-Matrix-Inequation) method under the regulation of the feedback matrix K, so that the system estimation error can converge to zero asymptotically. It can simultaneously solve the optimization problems of unknown faults (including external disturbances, partial failure of internal actuators, and random interruptions) of the self-assembling node and the acquisition of SNR (Signal-Noise-Ratio) by wireless self-assembling nodes. The simulation results show that the system eventually tends to be asymptotically stable in all performance metrics with feedback adjustment under the designed filter controller, and the estimation error asymptotically tends to zero. The robustness and fault tolerance performance indicators are good against external disturbances and internal actuator failure of the wireless self-assembling network node. The control rate of the network system all increases significantly as the total feedback constraint rate of the system increases, allowing the system to eventually obtain the optimal SNR. The experimental results show that the network nodes of the amorphous flat wireless air-to-ground self-organizing network system can change flexibly and adaptively with the change of scenes, and the wireless communication distance between the network nodes is relatively improved by 86.36%, 110%, and 79.91%, and the loop success rate appears to be stable fluctuation interval, which can greatly improve the survival rate of the self-organizing network nodes. This paper is of great research significance for further realizing the long-spacing transmission of self-organizing nodes and laying the foundation for future low-altitude fly-by-wire research.

Mobility Models as a Key-Performance Factor for Wireless Networks

Nodes in wireless networks can be static or dynamic. Static nodes are stationary and their positions are fixed and their distribution may follow a particular topology. On the other hand, dynamic nodes are considered mobile and their positions changed over time due to following a specific pattern of movement, which also lead to the concept of the topology being irrelated. Simulating such networks needs a lot of attention and many requirements should be held. For instance, nodes in dynamic wireless networks are distributed according to a distribution that reflects the nature of the environment (e.g., Gaussian, Power-Law, Uniform distribution, etc.). Moreover, describing the movement patterns of nodes in dynamic wireless networks need to follow a particular mobility model that describes the movements of nodes in terms of speed and direction (e.g., Individual mobility model, Levy Flight Model, Cauchy Model). In addition to the aforementioned requirements, it is needed to incorporate a routing protocol that governs data spread within the simulation environment. This work designed a variety of experiments that combine the mentioned requirements and measure the performance of dynamic wireless networks under colorful settings and configurations. The metrics used in this approach are the amount of data exchanged, coverage area, and power and memory consumption. Mobility models, node deployment strategy (distributions), and routing protocols are the three factors that will be involved in the experiments. The experiments deal with four mobility models Random Way Point Mobility Model (RWPM), Street Random Way Point Mobility Model (SRWPM), Manhattan Mobility Model (MM), and Levy Flight Mobility Model (LFM). Three distribution models will be used in the experiments Power-Law Distribution, Chi-Squared Distribution, and Normal Distribution. The third factor that will be involved in the routing protocol, is Probabilistic Flooding Routing Protocol. Different experiments are benchmarked using these metrics. The results of this work will reveal facts about dynamic network simulations and provide some recommendations to network developers and architects.

CPAOR: Control Packet Aware On-demand Routing Protocol for WBANs

Background & Objective: The core problem of wireless body area network (WBAN) nodes is their limited energy resource. Thus, an energy-efficient routing protocol is crucial to this type of network. A major drawback of current routing protocols is that they do not consider the monitoring of a large number of patients, which may be problematic in the event of disasters. In addition, most routing algorithms fail to consider balancing energy consumption between nodes. Furthermore, routing overhead (RO) and reduced complexity are required in this type of network. Methods: In this paper, we propose a control packet aware on-demand routing (CPAOR) protocol to overcome the aforementioned drawbacks. The proposed protocol decreases the number of control packets and adds awareness for the transmission of control packets, which can extend the network lifetime. Results and Discussion: We analyze and examine the simulation results of the CPAOR protocol using MATLAB in terms of energy consumption, the energy factor, RO, and changing the number of nodes to more than 60 nodes. The CPAOR protocol demonstrates an improvement of 70.9% compared to the DMQoS, ORACE-Net, and DLQoS protocols in terms of energy consumption. This finding proves that the CPAOR protocol is an efficient routing protocol for WBANs. Conclusion: The CPAOR protocol has been proven to be an effective routing protocol for WBANs.

Improving Trust Levels in Wireless Networks Using Blockchain Powered Dempster Shaffer Route Optimization

Improved node and network trust levels in wireless networks assist the network to have better security and quality of service (QoS) performance. Security performance is measured in terms of number of attacks detected and mitigated by the network, while QoS performance is measured in terms of end-to-end delay, communication throughput, energy requirement, and packet delivery ratio metrics. In order have good trust levels in the network, a wide variety of methods, including reputation evaluation, historical analysis, temporal network, and node analysis, are proposed by network researchers. Implementation of these algorithms increases computational complexity of the network, thereby increasing end-to-end delay during communication. During routing, repeated calculations of trust in the network further increases number of computational steps required for route selection. These added calculations improve network security but reduce overall QoS at node and network level. Moreover, if these calculations are simplified for reducing computational complexity, then QoS improves but network security is compromised. In order to maintain a high network QoS with sufficient level of security, this paper proposes a novel blockchain powered routing model that uses Dempster Shaffer (DS) route optimization. The model utilizes node-to-node distance, energy efficacy, and temporal packet forwarding capabilities in order to select the most efficient routing strategy. This strategy is combined with a proof-of-work (PoW) based blockchain solution that allows the network to have high trust levels. Due to decentralized processing, the network is able to have good QoS levels along with high security.

Reduction of secondary lobes in joint angle and delay estimation in angle of arrival localization to detect MAC address spoofing in wireless networks

in this paper, we solve the problem of secondary lobes that are due to noise that comes from constructive and destructive multipath interference that are resulted in received signal strength (RSS) variation over time. This is to develop a very efficient localization algorithm that uses a unique fingerprint angle of arrivals (AOAs), in a specified range, with associated time delays (TDs), in the surrounded sparsity design promoting multipath parameter (i.e:RSS). We solve this problem to detect physical identity spoofing of nodes in radio wireless networks, and localize adversaries and jammers of wireless networks. All radio waves are vulnerable to many types of attacks due to the ability to capture them and sniff or eavesdropping on them in the open space. Physical identity spoofing is used to launch many types of attacks against wireless networks like Denial of Service (DOS), Man-In-The-Middle and Session Hijacking and eavesdropping. Eavesdropping is a human-based social engineering attack. Active adversaries are able to jam and eavesdrop simultaneously, while passive adversaries can only eavesdrop on passed signals. In TCP/IP protocol for example, Media Access Card (MAC) Address is transferred in 802.11 frames. Detection process was carried out by analyzing electromagnetic radio waves that are used to transfer data, in the form of radio wave signals that are formed by the modulation process which mixes the electromagnetic wave, with another one of different frequency or amplitude to produce the signal with a specified pattern of frequency and amplitude. We depended on the angle of arrival of vectors and time delay across scattered areas in the surrounded space to solve the problem of co-location in detection and localization of jammers. We used Maximum Likelihood (ML) angle of arrival determination because ML approaches, known to their higher accuracy and enhanced resolution capabilities. And we assessed their computational complexity that was considered as the major drawback for designers to their implementation in practice. Our solution was tested on a jammer that changed the signal strength of received signal at the receiver at an angle of arrival 30 degree. And we used scatterers density to determine the angle of arrival of the sender. The simulation has observed that the power of the received signal has changed from the range of angles 20 to 40 degrees. We used scatterers because they describe the density of the signal power, and also enhance the signal to noise ratio, that resulted from the multipath fading of the signal strength. And also overcoming the problem of secondary lobes that are due to signal propagation, while determining the angle of arrival of a signal sender. So, we developed a new passive technique to detect MAC address spoofing based on angle of arrival localization. And assessed the computation complexity of the localization technique through depending on a range angle to estimate the angle of arrival of the adversary within it. And we reduced number of secondary lobes, and their peaks, in the importance function, while determining the angle of arrival, and so increasing the accuracy of angle of arrival measurement. We compared our work to other techniques and find that our technique is better than these techniques.

A Novel Secure Patient Data Transmission through Wireless Body Area Network: Health Tele-Monitoring

The security of sensitive data obtained from a patient has not been implemented properly because of energy issues of sensor nodes in Wireless Body Area Network (WBAN) and constrained resources such as computational power and low battery life. The main of this paper is to enhance the security level of data transmission between patient and health service provider by considering the availability of energy at sensor nodes. The proposed system consists of a hybrid Advanced Encryption Standard (AES) and Elliptic Curve Cryptography (ECC), which provides simple, fast and high cryptographic strength of data security. ECC is used for securing AES encryption keys, and AES algorithm is used for encrypting/decrypting text. A scenario where sensor nodes are continuously supplied energy from solar power is considered and based upon the energy availability; respective encryption technique is implemented. The result shows that the proposed EEHEE algorithm increases the encryption of the data file by more than 19% compared to the State of Art's solution. The proposed EEHEE system is 11% faster in encrypting data file and reduces the energy consumption by 34 % compared to the current best solution. The proposed system concentrates on reducing the energy consumption in WBAN and increasing cryptographic strength to the system by using the hybrid symmetric and asymmetric algorithm. Thus, this study provides an efficient scheme to enhance security for real-time data transmission in telemedicine.

RSS-Based Localization of Multiple Radio Transmitters via Blind Source Separation

This letter proposes a methodology for counting and locating the nodes of an uncooperative wireless network using power measurements collected by sensors. The approach is blind, allowing the detection and localization of the nodes without knowing the network&#x2019;s specific features (i.e., the number of nodes, modulation type, and medium access control (MAC)). Because the signals captured by the radio-frequency (RF) sensors are additively mixed, blind source separation (BSS) is used to separate transmitted power profiles. Then, received signal strength (RSS) is extracted from the reconstructed signals and localization is performed through conventional least square (LS) and maximum likelihood (ML) techniques. Numerical results reveal that the BSS-ML approach reaches a rather low localization error in mild shadowing regimes, even when the ratio between the number of RF sensors and nodes, <inline-formula> <tex-math notation="LaTeX">$\rho $ </tex-math></inline-formula>, is close to 1. Finally, it is shown how the performance degradation introduced by the imperfect BSS is slight and that the root mean square error (RMSE) approaches the Cram&#x00E9;r-Rao lower bound (CRLB) when increasing <inline-formula> <tex-math notation="LaTeX">$\rho $ </tex-math></inline-formula>.

Efficient energy for one node and multi-nodes of wireless body area network

&lt;span&gt;Compression sensing approaches have been used extensively with the idea of overcoming the limitations of traditional sampling theory and applying the concept of pressure during the sensing procedure. Great efforts have been made to develop methods that would allow data to be sampled in compressed form using a much smaller number of samples. Wireless body area networks (WBANs) have been developed by researchers through the creation of the network and the use of miniature equipment. Small structural factors, low power consumption, scalable data rates from kilobits per second to megabits per second, low cost, simple hardware deployment, and low processing power are needed to hold the wireless sensor through lightweight, implantable, and sharing communication tools wireless body area network. Thus, the proposed system provides a brief idea of the use of WBAN using IEEE 802.15.4 with compression sensing technologies. To build a health system that helps people maintain their health without going to the hospital and get more efficient energy through compression sensing, more efficient energy is obtained and thus helps the sensor battery last longer, and finally, the proposed health system will be more efficient energy, less energy-consuming, less expensive and more throughput.&lt;/span&gt;

Chaotic Krill Herd with Fuzzy Based Routing Protocol for Wireless Networks

Energy is considered a valuable source in wireless sensor networks (WSN) for effectively improving the survivability of the network. The non-uniform dispersion of load in the network causes unbalanced energy dissipation which can result in network interruption. The route selection process can be considered as an optimization problem and is solved by utilize of artificial intelligence (AI) techniques. This study introduces an energy efficient chaotic krill herd algorithm with adaptive neuro fuzzy inference system based routing (EECKHA-ANFIS) protocol for WSN. The goal of the EECKHA-ANFIS method is for deriving a better set of routes to destination in such a way as to improve the survivability in the wireless networks. Primarily, the ANFIS model utilizes the models of fuzzy logic and neural networks (NN) to effectively select the relay nodes for energy efficient communication. Besides, a group of fuzzy rules with membership functions (MF) are designed for selecting the next hop node in wireless networks based on distinct input parameters. Moreover, the optimal selection of MF takes place by the use of chaotic krill herd algorithm (CKHA). In order to showcase the improved performance of the EECKHA-ANFIS approach, a series of simulations are implemented and outcomes are inspected under several aspects. The extensive result analysis demonstrates the betterment of the EECKHA-ANFIS technique over the existing techniques interms of different measures.

Research on Classroom Online Teaching Model of "Learning" Wisdom Music on Wireless Network under the Background of Artificial Intelligence.

This article uses a multimodal smart music online teaching method combined with artificial intelligence to address the problem of smart music online teaching and to compensate for the shortcomings of the single modal classification method that only uses audio features for smart music online teaching. The selection of music intelligence models and classification models, as well as the analysis and processing of music characteristics, is the subjects of this article. It mainly studies how to use lyrics and how to combine audio and lyrics to intelligently classify music and teach multimodal and monomodal smart music online. In the online teaching of smart music based on lyrics, on the basis of the traditional wireless network node feature selection method, three parameters of frequency, concentration, and dispersion are introduced to adjust the statistical value of wireless network nodes, and an improved wireless network is proposed. After feature selection, the TFIDF method is used to calculate the weights, and then artificial intelligence is used to perform secondary dimensionality reduction on the lyrics. Experimental data shows that in the process of intelligently classifying lyrics, the accuracy of the traditional wireless network node feature selection method is 58.20%, and the accuracy of the improved wireless network node feature selection method is 67.21%, combined with artificial intelligence and improved wireless, the accuracy of the network node feature selection method is 69.68%. It can be seen that the third method has higher accuracy and lower dimensionality. In the online teaching of multimodal smart music based on audio and lyrics, this article improves the traditional fusion method for the problem of multimodal fusion and compares various fusion methods through experiments. The experimental results show that the improved classification effect of the fusion method is the best, reaching 84.43%, which verifies the feasibility and effectiveness of the method.

A Comprehensive Analysis of QoS in Wired and Wireless SDN Based on Mobile IP

Software-Defined Networking (SDN) is the new network paradigm whose primary focus is to create a dynamic, scalable and flexible network. It provides programmable functions for implementation of network configuration management. The demand for wireless network functionality is rising simultaneously. Mobility management for a large network is an issue in Internet Engineering Task Force (IETF). There are also a number of solutions to support mobility within the network. The Mobile Internet Protocol (MIP) is used for managing mobility. Furthermore, for the SDN platform, mobility adds roaming capability for mobile nodes in the software-defined wireless network (SDWN). In the wired scenario, SDN has different capabilities to deliver network services according to the fixed node. This study provides a quality of service (QoS) analysis in both SDN and SDWN. Mininet WiFi and RYU network emulator as a controller is used to implement the mobility API. The random walk model is applied as mobility functionality toward the final nodes. Moreover, several QoS measurement matrices are analyzed according to the network topology. At the end, round trip time (RTT), cumulative distributed function (CDF), packet loss and throughput are analyzed for quality of service comparable in the SDN and SDWN scenarios according to the MIP.

Optimized Gaming based Multipath Routing Protocol with QoS Support for High-Speed MANET

Mobile ad hoc (MANET) network is a multitude of adaptable nodes communicating without a set physical structure. MANET nodes usually have processing, partial power and memory capabilities as well as great degrees of mobility. Because of the low contact rate, several wireless network nodes are normally required for a server to share data with any other network node. Therefore, routing is a key challenge for the building of a MANET. In this article, we explicitly address multipath routing difficulties in MANETs. In addition, MANETs can also be built into upcoming technologies, such as IoT and machine-learning to fulfil Industry 4.0 vision. All delicate real-time requests based on MANET need secure and dependable data transfer to deliver the quality of service required (QoS). A safe and energy efficient transfer of data is an extremely difficult task in MANET. To achieve this difficult goal, a safe multi-way routing protocol must be designed to improve the QoS of the MANET. We have proposed in this article the optimized multi-way gaming-driven protocol to improve the overall performance of MANET. It addresses several elements such as congestion control, the loss of packets, malicious detection of nodes, and safe data transfer to strengthen the MANET QoS as the key strength of the projected protocol. Simulation in the NS2 evaluates the performance of the suggested protocol.

Fault-Tolerant Placement of Additional Mesh Nodes in Rural Wireless Mesh Networks: A Minimum Steiner Tree Based Centre of Mass With Bounded Edge Length

Wireless mesh networks are presented as an attractive solution to reduce the digital divide between rural and developed areas. In a multi-hop fashion, they can cover larger spaces. However, their planning is subject to many constraints including robustness. In fact, the failure of a node may result in the partitioning of the network. The robustness of the network is therefore achieved by carefully placing additional nodes. This work tackles the problem of additional nodes minimization when planning bi and tri-connectivity from a given network. We propose a vertex augmentation approach inspired by the placement of Steiner points. The idea is to incrementally determine cut vertices and bridges in the network and to carefully place additional nodes to ensure connectivity, bi and tri-connectivity. The approach relies on an algorithm using the centre of mass of the blocks derived after the partitioning of the network. The proposed approach has been compared to a modified version of a former approach based on the Minimum Steiner Tree. The different experiments carried out show the competitiveness of the proposed approach to connect, bi-connect, and tri-connect the wireless mesh networks.

Design and Implementation of Low Energy Wireless Network Nodes Based on Hardware Compression Acceleration

Background: With the fast development of information, the information data is increasing in geometric multiples, and the speed of information transmission and storage space are required to be higher. Objective: In order to reduce the use of storage space and further improve the transmission efficiency of data, data need to be compressed. In the process of data compression, it is very important to ensure the lossless nature of data, and lossless data compression algorithms appear. The gradual optimization design of the algorithm can often achieve the energy-saving optimization of data compression. Similarly, the effect of energy saving can also be obtained by improving the hardware structure of node. Methods: In this paper, a new structure is designed for sensor node, which adopts hardware acceleration, and the data compression module is separated from the node microprocessor. Result: On the basis of the ASIC design of the algorithm, by introducing hardware acceleration, the energy consumption of the compressed data was successfully reduced, and the proportion of energy consumption and compression time saved by the general-purpose processor was as high as 98.4 % and 95.8 %, respectively. It greatly reduces the compression time and energy consumption.

Energy Optimization in a Multihop Sensor Network for a WBAN Application

Movement and posture change of human body plays a crucial role in energy consumption while data transmission between strategically deployed nodes in wireless body area networks (WBANs). The majority of energy is used in transmission rather than processing of the data. Nodes within body are there for long time and need to be energy efficient so that the network lifetime is increased. In this paper, we propose an energy efficient data transmission for multi-hop network that uses particle swarm optimization (PSO) for optimizing the parameters on which energy consumption relies. An energy efficient data transmission and reception takes place by altering the parameters like node to node distance and packet size of data. The obtained results show a significant reduction of energy consumed by reducing the packet size and keeping the node-to-sink distance a constant value. The total energy consumed per hop per bit length of data packet Emh/L shows 75% optimization. The energy consumed in data transmission per bit length of data E tx /L and the energy consumed for data received per bit length of data packet E rx /L is optimized by approximately 70% and 50% respectively for hope count 2 to 5.