Communication In Wireless Sensor Networks Research Articles

An Optimal Anchor Placement Method for Localization in Large-Scale Wireless Sensor Networks

Localization is an essential task in Wireless Sensor Networks (WSN) for various use cases such as target tracking and object monitoring. Anchor nodes play a critical role in this task since they can find their location via GPS signals or manual setup mechanisms and help other nodes in the network determine their locations. Therefore, the optimal placement of anchor nodes in a WSN is of particular interest for reducing the energy consumption while yielding better accuracy at finding locations of the nodes. In this paper, we propose a novel approach for finding the optimal number of anchor nodes and an optimal placement strategy of them in a large-scale WSN, based on the output of Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) methods. As an initial step in this approach, the virtual localization process is executed over a virtual coordinate system in order to optimize the efficiency of the localization process. GWO and PSO methods are compared with a coverage-based analytical method and machine learning approaches such as Support Vector Machine (SVM) regression and Multiple Regression. The simulations we run with different numbers of nodes in a WSN and different communication ranges of nodes demonstrate that the proposed approaches are superior for minimizing the localization errors while reducing the number of anchor nodes.

Novel DoS Attack Detection Based on Trust Mode Authentication for IoT

Wireless sensor networks are extensively utilized as a communication mechanism in the field of the Internet of Things (IoT). Along with these services, numerous IoT based applications need stabilized transmission or delivery over unbalanced wireless connections. To ensure the stability of data packets delivery, prevailing works exploit diverse geographical routing with multi-hop forwarders in WSNs. Furthermore, critical Denial of Service (DoS) attacks frequently has an impact on these techniques, where an enormous amount of invalid data starts replicating and transmitted to receivers to prevent Wireless Sensor Networks (WSN) communication. In this investigation, a novel adaptive endorsement method is designed by combining dimensionality reduction based Hilbert-Huang Transformation (DR-HHT) and authentication trust mode (ATM). DR-HHT and ATM defend against the severity of DoS attacks, by fulfilling trust, reliability, stability requirements. ATM also examines the state information (SI) of nodes in wireless links; this SI leverages the performance of ATM to enhance data delivery effectually. Dissimilar to existing routing protocols, DR-HHT and ATM guarantee data integrity by building Kolmogorov_Smirnov based authentication algorithms. Concerning the correlation coefficient, this model isolates DoS attacks and diminishes computational cost. This strategy also eliminates duplicate data transmission and redundant information, offering an effectual trust-based evaluation model from adaptive authentication. Extensive simulation demonstrates that the anticipated model shows a better trade-off than the prevailing techniques and the simulation is carried out in a MATLAB environment.

Performance Analysis of Deep Learning-Based Routing Protocol for an Efficient Data Transmission in 5G WSN Communication

For the past few years, huge interest and dramatic development have been shown for the Internet of Things (IoT) based constrained Wireless sensor network (WSN) to achieve efficient resource utilization and better service delivery. IoT requires a better communication network for data transmission between heterogeneous devices and an optimally deployed energy-efficient WSN. The clustering technique applied for WSN node deployment needs to be efficient; therefore, the entire architecture can obtain a better network lifetime. While clustering, the entire network is partitioned into various clusters. Moreover, the cluster head (CH) selection process also needs proper attention for achieving efficient data communication towards the sink node via selected CH and also for increasing the node reachability within the cluster. In this proposed framework, an energy efficient deep belief network (DBN) based routing protocol is developed, which achieves better data transmission through the selected path. Due to this the packet delivery ratio (PDR) gets improved. In this framework, initially, the nodes in the whole network is grouped as clusters using a reinforcement learning (RL) algorithm, which assigns a reward for the nodes that belong to the particular cluster. Then, the CH required for efficient data communication is selected using a Mantaray Foraging Optimization (MRFO) algorithm. The data is transmitted to the sink node via the selected CH using an efficient deep learning approach. At last, the performance of proposed deep network based routing protocol is evaluated using different evaluation metrics they are network lifetime, energy consumption, number of alive nodes, and packet delivery rate. Finally, the evaluated results are compared with few existing algorithms. Among all these algorithms, the proposed DBN routing protocol has achieved better network lifetime.

Energy Aware Routing Protocol with Data Fusion and Machine Learning

The current wireless and communication system may be attributed to the contributions made by the Sensor Network in a significant measure. During the last decade, several efforts have been performed to examine and propose answers to challenges about the energy efficiency of wireless sensor network communications. Several different researchers has done these efforts. The challenge of constructing economical energy-use paths has not yet been overcome. Because sensors have limited computational capabilities, which are frequently coupled with energy limitations, it is rather difficult to guarantee that a sensor’s lifespan will be longer. This is because of the energy constraints often associated with these limitations. The results of this research have led to the development of a one-of-a-kind communication system for sensor networks that is not only environmentally friendly but also supported by three distinct revolutionary frameworks. The framework that has been recommended, which goes by the name Potential Energy Efficient Data Fusion (PEE-DF), is the one that is in charge of the optimization of energy. It achieves this with the aid of probabilistic approaches and clustering. The K-SOM (Korhonen self-organizing map) framework was designed using a globular topology, which aids load balancing during data fusion. K-SOM stands for Korhonen self-organizing map. This was done to ensure we got the most out of our resources. A novel method to routing is presented by the technique, which has the potential to be used to assist in the operation of energy-efficient routing in large-scale wireless sensor networks. The framework for the Tree-Based Fusion Technique (TBFT), which has been offered, comes up with a new way for dynamic reconfiguration. This is accomplished via the introduction of the concept of routing agents. The strategy enables the system to recognise which sensor has a greater energy dissipation rate and then instantly moves data fusion work to a more energy-efficient node. This allows the system to save energy. This approach, based on thresholds, enable a sensor to act as a cluster head up until it reaches its threshold remnant energy and then as a member node once it exceeds threshold residual energy. In other words, it may play both roles simultaneously. It is possible to fulfil both of these responsibilities at the same time. The findings have been mathematically modelled using a standard radio-energy model, which has enhanced the robustness of the findings, which is highly positive. The results were encouraging because of the increased robustness of the findings. Compared to the benchmark previously established for energy-efficient strategies, the proposed system demonstrates higher performance in terms of its ability to communicate while using less energy. In contrast to LEACH, the recommended system's findings reveal an almost fifty percent decrease in energy consumption, and at the same time, a reduction in the amount of time required to carry out the operation..

Potnet: Online Potable Water Quality Monitoring Network for Overhead Water Tanks in Rural Water Supply Schemes in India

Background: Monitoring the quality of potable water is a challenging endeavor due to the significant sources of contaminants, the majority of which are human-induced. Limited access to drinking water owing to acceleration in industrialization, urbanization in consort with growing inhabitants, unprocessed sewage discharge, and toxic industrial effluents causes different life-threatening diseases. Manual water quality monitoring techniques vividly aggravate quality deterioration. Considering the significance of the automatic water quality monitoring system, we need an in-situ, real-time, continuous surveillance system to ascertain the quality of potable water. Wireless Sensor Network (WSN) motivated us for a practical water quality monitoring system due to their continuous, real-time, and adaptive infrastructure to provide an early alert in hazardous conditions. Objective: To design and implement an online potable water quality monitoring network for rural water supply schemes in Nagapattinam district, Tamilnadu, India, to sense physiochemical parameters of potable water such as pH, turbidity, conductivity and temperature. Methods: Online POTable water quality monitoring NETwork (POTNET) integrates the reimbursements of WSN and different information and communication technologies for data acquisition, data processing, and data visualization. The core hardware of POTNET contains off-the-shelf sensors (i.e., electrodes), a microcontroller, a data transmission system, a customized buoyage, and a sink node. It senses physiochemical parameters of potable water such as pH, turbidity, conductivity, and temperature in a pre-programmed time interval. Furthermore, it enables cloud storage for gathered information and generates an alert to the preregistered user via mobile phones when there is a deviation of quality measures from threshold values. Results: The system was implemented in three overhead tanks for seven days in order to validate the stability of the buoy and efficiency of energy source, storage, and data transmission. It senses physiochemical parameters of potable water such as pH, turbidity, conductivity, and temperature in its predefined interval of 30 minutes. To check the system accuracy, the measured data values from developed sensors were compared with the observed data values using a commercial multi-parameter water checker, the Horiba® probe. Measured data were sent through the transceivers to the base station for data logging in a suitable format for ease of data visualization and utilization. Conclusion: Extensive experimental results reveal that our POTNET can be employed for potable water quality surveillance to help consumers or concern authorities to make a sound decision by providing appropriate and real-time data.

Integrate the hierarchical cluster elliptic curve key agreement with multiple secure data transfer modes into wireless sensor networks

Since sensor nodes in wireless sensor networks or Internet of things have limited resources, achieving secure data transmissions among nodes is a challenge. Hence, efficient key management schemes with lightweight ciphers are essential. Many asymmetric keys or public key mechanisms have been developed. However, they are unsuitable for secure group communications in wireless sensor networks, because sensor nodes are usually devoid of sufficient memory, CPU and bandwidth to deal with complex operations. In addition, only a few group key agreements are integrated into secure data transmissions. Therefore, a key agreement using the hierarchy-based cluster elliptic curve key agreement named HCECKA is proposed in this study to deal with secure data transmissions in wireless sensor networks. The presented security mechanism relies on elliptic curves instead of logarithmic curves, and utilises a lesser key length to accomplish similar security classification than Diffie-Hellman and Rivest Shamir Adleman cryptosystems. Simultaneously, the proposed scheme provides a rapid, efficient and dynamic group key synchronisation technique in plenty of sensor nodes with no need for reorganising the whole system key if members join or leave wireless sensor networks.

Schedule-Based Cooperative Multi-agent Reinforcement Learning for Multi-channel Communication in Wireless Sensor Networks

Schedule-Based Cooperative Multi-agent Reinforcement Learning for Multi-channel Communication in Wireless Sensor Networks

Event-Triggered Globally Sequential Fusion Estimation for Clustered Wireless Sensor Networks With Variational Bayesian

This paper concentrates on a globally sequential fusion state estimation problem for clustered wireless sensor networks (WSNs). Therein, frequent data communications in WSN will significantly increase energy consumption and communication burden, and it needs to be taken into account. To reduce unnecessary data transmissions and save energy, an event-triggered mechanism that decides whether the current measurement should be transmitted or not, therefore, is introduced. Then a novel variational Bayesian based event-triggered sequential measurement fusion (VB-ESMF) estimator is proposed to produce the local fused results of the clustered WSNs, where the variational Bayesian approach is used to infer the measurement noise covariance matrices of pseudo measurement noises. Therein, the local fused measurements of the clusters in the clustered WSNs are used sequentially by the remote fusion center, and thus a global fusion state estimation, which is globally optimal when all measurements are transmitted successfully, is computed. Additionally, certain boundedness and convergence conditions of the proposed estimator are derived, and an expected compromise between communication rate and estimation accuracy can be obtained by properly turning the trigger threshold. Finally, the effectiveness of both the VB-ESMF estimation and the globally sequential fusion state estimation is illustrated by simulation results.

Contemporary secured target locality in wireless sensor networks

Communication in Wireless Sensor Networks (WSN) by its environment further disposed to danger attacks and it harms data. Secured information or maintain data confidentiality is a big challenge in today life, but main issue is which needs a security for the purpose of localization. Including to this one more complication now focused on sensation in acoustic motes which practices Particle Swarm Optimization (PSO) method for locality or Position Assessment. Here propose Contemporary Secured Target Locality (CSTL) algorithm mainly addresses security and target location issues, Sybil and on-off attack and wicked motes occurrence at altered stages of target locality at the end results are compared with existing method General Localization (GLS), Approximate Point in Triangle, Distance Vector hop localization and multi hop method with proposed method. Here outcome of simulation prove better accuracy and progressive reaction in attack recognition presently contributes in build a secured wireless sensor network.

An Efficient and Provable Multifactor Mutual Authentication Protocol for Multigateway Wireless Sensor Networks

As the most popular way of communication technology at the moment, wireless sensor networks have been widely concerned by academia and industry and plays an important role in military, agriculture, medicine, and other fields. Identity authentication offers the first line of defence to ensure the security communication of wireless sensor networks. Since the sensor nodes are resource-limited in the wireless networks, how to design an efficient and secure protocol is extremely significant. The current authentication protocols have the problem that the sensor nodes need to execute heavy calculation and communication consumption during the authentication process and cannot resist node capture attack, and the protocols also cannot provide perfect forward and backward security and cannot resist replay attack. Multifactor identity authentication protocols can provide a higher rank of security than single-factor and two-factor identity authentication protocols. The multigateway wireless sensor networks’ structure can provide a larger communication coverage area than the single-gateway network structure, so it has become the focus of recent studies. Therefore, we design a novel multifactor authentication protocol for multigateway wireless sensor networks, which only apply the lightweight hash function and are given biometric information to achieve a higher level of security and efficiency and a larger communication coverage area. We separately apply BAN logic, random oracle model, and AVISPA tool to validate the security of our authentication protocol in Case 1 and Case 2. We put forward sixteen evaluation criteria to comprehensively evaluate our authentication protocol. Compared with the related authentication protocols, our authentication protocol is able to achieve higher security and efficiency.

RETRACTED ARTICLE: Composition Rule Perception Algorithm of National Art Plane System Based on Wireless Sensor Network Communication Technology

RETRACTED ARTICLE: Composition Rule Perception Algorithm of National Art Plane System Based on Wireless Sensor Network Communication Technology

A compact omnidirectional to directional frequency reconfigurable antenna for wireless sensor network applications

AbstractIn the proposed research paper, a novel compact, ultra-wideband electronically switchable dual-band omnidirectional to directional radiation pattern microstrip planar printed rectangular monopole antenna (PRMA) has been presented. The proposed antenna system has an optimum size of 0.26 λ0 × 0.28 λ0. A combination of radiators, reflectors, and two symmetrical grounds does place on the same layer of the rectangular microstrip PRMA. The frequency agility and the radiation pattern from omnidirectional to directional are achieved using two SMD PIN diodes (SMP1340-04LF). The directional radiation patterns with 180° phase shifts are achieved at the C-band frequency spectrum. The parametric study of the proposed antenna system was performed for different design parameters, and the antenna characteristics were analyzed. An antenna prototype is fabricated using the printed circuit board etching method by using RMI UV laser etching and cutting tools. The measurements of the proposed antenna are conducted in an anechoic chamber to validate the simulations. There are three states of operations due to two SMD PIN diodes being used in switching circuits. In state-I, the proposed antenna radiates at 6.185 GHz (5.275–6.6 75 GHz) in the Ф = 270° direction with a gain of 2.1 dBi, whereas in state-II, it radiates at 5.715 GHz (5.05–6.8 GHz) in the Ф = 90° direction with a gain of 2.1 dBi. In state-III, the antenna exhibits the X-band frequency with center frequency at 9.93 GHz (8.845–10.49 GHz), and the omnidirectional pattern offers a gain of 4.1 dBi. The features of the proposed antenna are suitable for high-speed wireless sensor network communication in industries such as chemical reactors in oil and gas and pharmaceuticals. It is also well suited for IoT and 5G-sub-6-GHz applications.

Modeling and analysis of priority andrange‐based‐deterministic and synchronous multichannel extension‐guaranteed time slot allocation inIEEE802.15.4emedium access controlprotocol

AbstractInternet of Things (IoT) enabled technology in the current applications such as smart grids, smart cities, and smart health sectors utilize wireless sensor networks (WSN) to establish stable and reliable communication between the nodes. Moreover, the primary requirement of WSN in IoT applications is to provide low‐rate data communication. The IEEE 802.15.4e standard‐based medium access control (MAC) protocol is found suitable for low‐rate data communication in WSN. The IEEE 802.15.4e standard adopts a deterministic and synchronous multichannel extension (DSME) MAC protocol which employs a multisuperframe structure with multichannel data transmission during the contention free period. However, the guaranteed time slot (GTS) allocation process in DSME employed by the standard may not be suitable for an adaptive traffic network scenario that has a direct impact on the throughput and bandwidth utilization. In this article, we develop a priority and range‐based DSME‐GTS allocation algorithm based on the priorities of end nodes and range estimation. Furthermore, the proposed algorithm is developed for the two types of network scenarios encountered in a star topology‐enabled WSN. In scenario‐1, the slots allocation process is carried out based on the priorities of end nodes. Next, in scenario‐2, the slots allocation process is carried out based on the range estimation of end nodes. Detailed mathematical modeling of the proposed methodology is provided for the various performance metrics. The model is validated using the MATLAB 2017a programming tool. Simulation results show that the proposed methodology outperforms the existing DSME‐GTS approaches in terms of performance metrics such as packet delivery ratio, end‐to‐end delay, packet loss ratio, throughput, delay, bandwidth utilization, and the energy consumption.

Detection and prevention of black-hole and wormhole attacks in wireless sensor network using optimized LSTM

PurposeThis study aims to present a novel system for detection and prevention of black hole and wormhole attacks in wireless sensor network (WSN) based on deep learning model. Here, different phases are included such as assigning the nodes, data collection, detecting black hole and wormhole attacks and preventing black hole and wormhole attacks by optimal path communication. Initially, a set of nodes is assumed for carrying out the communication in WSN. Further, the black hole attacks are detected by the Bait process, and wormhole attacks are detected by the round trip time (RTT) validation process. The data collection procedure is done with the Bait and RTT validation process with attribute information. The gathered data attributes are given for the training in which long short-term memory (LSTM) is used that includes the attack details. This is used for attack detection process. Once they are detected, those attacks are removed from the network using the optimal path selection process. Here, the optimal shortest path is determined by the improvement in the whale optimization algorithm (WOA) that is called as fitness rate-based whale optimization algorithm (FR-WOA). This shortest path communication is carried out based on the multi-objective function using energy, distance, delay and packet delivery ratio as constraints.Design/methodology/approachThis paper implements a detection and prevention of attacks model based on FR-WOA algorithm for the prevention of attacks in the WSNs. With this, this paper aims to accomplish the desired optimization of multi-objective functions.FindingsFrom the analysis, it is found that the accuracy of the optimized LSTM is better than conventional LSTM. The energy consumption of the proposed FR-WOA with 35 nodes is 7.14% superior to WOA and FireFly, 5.7% superior to grey wolf optimization and 10.3% superior to particle swarm optimization.Originality/valueThis paper develops the FR-WOA with optimized LSTM detecting and preventing black hole and wormhole attacks from WSN. To the best of the authors’ knowledge, this is the first work that uses FR-WOA with optimized LSTM detecting and preventing black hole and wormhole attacks from WSN.

Thorough Performance Evaluation & Analysis of the 6TiSCH Minimal Scheduling Function (MSF)

IEEE Std 802.15.4-2015 Time Slotted Channel Hopping (TSCH) is the de facto Medium Access Control (MAC) mechanism for industrial applications. It renders communications more resilient to interference by spreading them over the time (time-slotted) and the frequency (channel-hopping) domains. The 6TiSCH architecture bases itself on this new MAC layer to enable high reliability communication in Wireless Sensor Networks (WSNs). In particular, it manages the construction of a distributed communication schedule that continuously adapts to changes in the network. In this paper, we first provide a thorough description of the 6TiSCH architecture, the 6TiSCH Operation Sublayer (6top), and the Minimal Scheduling Function (MSF). We then study its behavior and reactivity from low to high traffic rates by employing the Python-based 6TiSCH simulator. Our performance evaluation results demonstrate that the convergence pattern of MSF is the root cause of the majority of packet losses observed in the network. We also show that MSF is prone to over-provisioning of the network resources, especially in the case of varying traffic load. We propose a mathematical model to predict the convergence pattern of MSF. Finally we investigate the impact of varying parameters on the behavior of the scheduling function.

Increasing energy efficiency of rule-based fuzzy clustering algorithms using CLONALG-M for wireless sensor networks

Because of its efficiency, clustering is used for effective communication in Wireless Sensor Networks (WSNs). In the WSN clustering area, fuzzy approaches are found to be superior to crisp cluster counterparts when the boundaries between clusters are unclear. As a result, many studies have proposed some fuzzy-based solutions to the cluster problem in WSNs. Most rule-based fuzzy clustering systems employ field experts in trial and error processes, identifying and defining fuzzy rules as well as the forms of membership functions at the output; thus, considerable time has been allocated to realize and define these functions. Therefore, it is almost impossible or impractical to achieve a fuzzy system optimally. In this study, we propose a modified clonal selection algorithm (CLONALG-M) to improve the energy efficiency of rule-based fuzzy clustering algorithms. Although some studies in the literature focus on fuzzy optimization in general, to the best of our knowledge, performance improvement of rule-based fuzzy clustering algorithms is not taken into account. The CLONALG-M algorithm based on the Clonal Selection Principle is used to elucidate the basic principles of an adaptive immune system. In this study, we apply this principle to determine the approximate deployment of output-based membership functions that increase the performance of rule-based fuzzy clustering algorithms, whose rule base and shape of membership functions are previously known. Experimental analysis and evaluations of the proposed approach have been performed on selected fuzzy clustering approaches, and obtained results show that our approach performs and adapts well for improving performance of fuzzy output functions.

A secure and efficient user authentication protocol for wireless sensor network

To provide the secure communication in wireless sensor networks (WSNs) is one of the challenging issues as the channel used is wireless. User authentication is a mechanism which is used to provide the secure communication in them. In this paper, it is devised a secure and efficient user authentication protocol using hash function for WSNs. It is formally analyzed the security of the proposed protocol using random oracle model and showed informally that it is resistant to various known attacks. Its security is formally verified using AVISPA tool. Its performance analysis along with the related schemes is evaluated in terms of security features, computational, communication, storage, and energy consumption costs. It has computational cost of 9 ms and storage cost of 30 bytes, which are less than the related schemes. Also it is more secure than them.

Wireless Sensor Network Design Using Multihop Based on Arduino and NRF24L01+

The development of communication networks is very useful in daily activities such as wireless data communication, monitoring and system security. In this case, a wireless sensor network technology is known, which is very suitable when applied to a system with a large number of nodes and spread over a large enough area at a low cost. This wireless sensor network is a wireless communication network that supports communication between sensor nodes in a considerable distance by placing several sensors in an area. Generally, this Wsn consists of a sensor node and a server node in the form of a personal computer. The data from the reading of the CO gas value will be sent directly from the sensor node to the node server. This device is built using the nRF24L01 module and the CO gas sensor using the MQ-7 sensor. This wireless sensor network communication system is built using multihop. From the activities it can be concluded that the success of sending data is influenced by the distance and number of nodes working on a topology, with the amount of data sent which is influenced by long distances and the large number of nodes, not all data is successfully received because of the large number of data collisions from each node.

Localization and Tracking of Mobile Jammer Sensor Node Detection in Multi-Hop Wireless Sensor Network

Background: The jammer in a wireless sensor network is located and tracked with open access and shared nature of the wireless medium. The existing algorithms mainly track the stationary jammer. Mobile jammer often moves from one place to another becoming difficult. Mobile jammer location tracker algorithm is proposed to find the location of a mobile jammer with four steps selection i.e., initial examining node, determination of supporting node, trilateration localization and examining group handover. Objective: In this research paper an algorithm is proposed for finding the location of mobile jammer in wireless sensor network. Finding location faces a huge difficulty due to non-supportive working between the multi hop wireless sensor network and jammer. The existing algorithms are used to find the location of stationary jammers only. Mobile jammers frequently change their position from time to time. Therefore jamming increases between the node to node communications in the multi hop wireless sensor network. Methods: The multi hop wireless sensor network is deployed with n number of stationary nodes in a particular area. The omni directional antenna is fitted with those stationary nodes and the transmission powers of the nodes are also constant. The direction-finding table is maintained and keep on updating for an interval of each node. The position of the nodes is tracked with the GPS devices or by existing location finding algorithm. The nodes in the multi hop wireless sensor network are installed in A*A square area uniformly and randomly. The transmitting node is tp node. The received signal to noise ratio is threshold STNR. Neighbor list records the neighbor node of the multi hop wireless sensor networks. Results and Conclusion: The proposed idea of localization and tracking system of mobile jammer is estimated efficiently by the multi hop wireless sensor network with the simulator MATLAB. The nodes in multi hop wireless sensor network are installed in A*A area square uniformly and randomly.

Secure disjoined multi-hop communication in wireless sensor network using trust nodes based data transmission technique

Secure disjoined multi-hop communication achieved in Wireless Sensor Network (WSN) has a prominent part to play and it can be accomplished with the help of Trust nodes based data transmission technique. In this proposed technique is communicating any kinds of information to make them secure and trust node verification for the sender and receiver within the WSN. Cluster Based Trust Management schemes are helpful in identifying unauthenticated user in WSN. First, it finds the trustworthy nodes in networks, and later transmits the packets via those trusted nodes. These trusted nodes are discovered in accordance with the trust values to find the neighborhood nodes during the authentication process for achieving improvement in the values of the metrics including Packet Delivery Ratio, End To End delay time, Remaining Energy, communication link and Throughput.