Quality Of Service Parameters Research Articles

Next‐generation energy‐efficient optical networking: DQ‐RGK algorithm for dynamic quality of service and adaptive resource allocation

SummaryIn green optical networking, designing an adaptive energy‐saving scheme plays a vital role, in optimizing energy consumption by dynamically adjusting resources based on network traffic and environmental conditions, to a more sustainable and efficient optical communication infrastructure. Traditional methods in optical networking face challenges such as static resource allocation, limited adaptability, inefficient power usage, environmental insensitivity, and scalability issues. Therefore this article proposed a novel method named Dynamic Quality of Service based Random update Genghis Khan (DQ‐RGK) algorithm, the proposed model can tackle the abovementioned complexities. In this study, cluster head dynamic placement is utilized to optimize the network's performance by adapting the placement of cluster heads to the current topology, load distribution, and energy levels in the network nodes. Additionally, Dynamic Quality of Service (QoS) is employed to respond dynamically to changes in network conditions, adapting to varying traffic patterns and resource availability. In this work, the Genghis Khan Shark optimization with a random update strategy is implemented for hyperparameter optimization to enhance the performance of the DQ‐RGK method. The DQ‐RGK adjusts the parameters of QoS in real‐time, and this ensures that network resources based on the requirements changed and priorities of applications, which ultimately optimizes performance and enhances user experience. By dynamically assigning and reallocating resources based on the current demand the algorithm enhances overall network efficiency and reduces energy consumption. Then, this work analyzes the experimental results, where some evaluation measures estimate the DQ‐RGK method's performance. Routing efficiency, latency, scalability, spectral efficiency, Packet Delivery Ratio, throughput, network lifetime, energy consumption, jitter, and energy consumption are the measures employed by the DQ‐RGK model. In The results, other routing models that do not provide efficiency are utilized, a comparison of these other routing models is represented in results. The overall DQ‐RGK model's effectiveness is represented in the experimental results and its effectiveness is greater among other methods.

Latency and Residual Energy Analysis of MIMO Heterogeneous Wireless Sensor Networks

Energy-constrained Wireless Sensor Networks (WSNs) have garnered significant research interest in recent years. Multiple-Input Multiple-Output (MIMO), or Cooperative MIMO, represents a specialized application of MIMO technology within WSNs. This approach operates effectively, especially in challenging and resource-constrained environments. By facilitating collaboration among sensor nodes, Cooperative MIMO enhances reliability, coverage, and energy efficiency in WSN deployments. Consequently, MIMO finds application in diverse WSN scenarios, spanning environmental monitoring, industrial automation, and healthcare applications. This research paper presents a comparative performance analysis of MIMO wireless sensor networks and traditional wireless sensor networks without MIMO using Network Simulator NS2.35 for analysis of End to End Delay for packet transmission and Residual energy of nodes. The research work shows application of MIMO in Wireless Sensor Networks with considerable improvements in Quality of Service parameters which is achieved through Spatial Multiplexing and Diversity Gain. MIMO enables multiple spatial streams, allowing several data streams to be transmitted simultaneously on the same channel. This increases the overall throughput as multiple sensors can transmit their data concurrently without interference. MIMO systems also provide diversity gain by transmitting multiple copies of the same data over different antennas which helps in mitigating the effects of fading and interference, resulting in a more reliable and higher-throughput communication link as compared to a SISO channel. Another advantage of employing MIMO in WSN is reduction in End-to-End delays in data transmission. Last but not the least, MIMO can be configured to optimize the power consumption of individual sensors by adjusting the number of antennas used and transmission power levels based on channel conditions. Hence, MIMO can help to extend the network's lifetime by conserving energy in resource-constrained sensor nodes by preservation of Residual Energy.

Performance and QoS Assessment in WSN: Comparative Analysis of MBC, ECHERP, and PDCH Routing Methods

Objective: The objective of this research is to assess the performance and Quality of Service (QoS) provided by PDCH when compared with ECHERP and MBC routing protocols(RPs) within Wireless Sensor Networks (WSNs). Methods: Utilizing the NS2 Simulator, this paper provides an in-depth exploration of three hierarchical RPs viz. Equalized Cluster Head Election RP (ECHERP), Mobility Based Clustering (MBC), and PDCH (PEGASIS with Double Cluster head). A thorough examination of each protocol's performance is conducted, focusing on a range of QoS metrics such as Energy Consumption, Packet Drop Ratio, Throughput, and Delay. Findings: A comparative assessment is conducted between PDCH, ECHERP, and MBC, extracting QoS parameters. The examination and findings reveal that PDCH exhibits superior performance over ECHERP by 26.15%, 20%, 15.71%, and 37.73%. Similarly, PDCH outperforms MBC by 23.19%, 14.29%, 4.87%, and 15.13% across the mentioned parameters. Novelty: In this simulation, the NS2 software is utilized, with a specific emphasis on the suggested parameters. These metrics are crucial for evaluating the overall performance of different RPs in Wireless Sensor Networks (WSNs).

PSO-Controlled WSN Environment to Mitigate Flooding and Improve Network Lifetime

The Restricted Flooding-based Route Discovery (RFBRD) – Particle Swarm Optimization (PSO) routing scheme introduced for Wireless Sensor Networks (WSNs) in this article not only reduces the energy loss due to unwanted RREQ (Route Request) flooding but also improves the lifetime of the network. Excessive flooding depletes energy and affects the lifetime of the network. Nodes in scarce regions are allowed to forward first and subsequent RREQ packets freely in the network and are relocated using PSO to improve their neighborhood for better neighbor connectivity and coverage. Whereas, nodes in the populated region or dense region are governed by energy ratios and are allowed to forward first RREQ packets only when they satisfy the energy conditions. This scheme is efficient in maintaining a proper balance of QoS (Quality of Service) parameters works well for high-density networks for more than 50 nodes and can restructure network topology obtaining better connectivity. Experimental analysis showed that the performance of AODV is superior in the case of a low-density network (N=40 nodes) while RFBRD-PSO outperforms in all other configurations (60, 80, and 100 nodes). The Packet delivery ratio was increased by 0.08% and the throughput was higher by 11 kbps in the case of RFBRD-PSO. The routing overhead is low by approximately 40% and the average end-to-end delay is found low by 0.04 as compared to the AODV routing. The energy residue in the case of RFBRD-PSO is less than the value of AODV is the cost paid for a higher packet delivery ratio. The neighborhood connectivity is improved by approximately 32%.

Transforming data‐intensive workflows: A cutting‐edge multi‐layer security and quality aware security framework

SummaryThe data‐intensive workflow application executes tasks on edge servers and cloud platforms in a heterogeneous big‐data computing environment. Cloud and edge servers are vulnerable to node attacks and malicious links due to their wireless connections. Thus, detecting and mitigating rogue nodes in edge server communication environments during workflow execution is crucial. In today's workflow execution landscape, there is a rising emphasis on resolving Quality of Service (QoS) and security concerns within homogeneous execution settings. Workflow execution on diverse computing platforms has received limited research. We are developing an edge‐cloud‐specific Multi‐Layer Security and Quality‐Aware (MLSQA) framework to solve research issues in this area. Node attacks are detected via reputation‐based security features in the MLSQA framework, whereas link attacks are detected using machine learning. A unique trade‐off metrics technique optimizes workflow security and QoS parameters, reducing energy usage and makespan. In addition, a fault‐tolerant, energy‐efficient job offloading technique is described in detail to improve the system's resilience to errors. The experiment is conducted using complex (i.e., memory and CPU intensive) scientific procedures with intermediate job dependencies, namely Inspiral workflow. The MLSQA framework excels in threat detection, demonstrating lower false alarms, reduced energy consumption, and quicker implementation than the recent secure workflow execution architecture.

Improve quality of service for the Internet of Things using Blockchain & machine learning algorithms

The quality of service (QoS) parameters in IoT applications plays a prominent role in determining the performance of an application. Considering the significance and popularity of IoT systems, it can be predicted that the number of users and IoT devices are going to increase exponentially shortly. Therefore, it is extremely important to improve the QoS provided by IoT applications to increase their adaptability. Majority of the IoT systems are characterized by their heterogeneous and diverse nature. It is challenging for these systems to provide high-quality access to all the connecting devices with uninterrupted connectivity. Considering their heterogeneity, it is equally difficult to achieve better QoS parameters. Artificial intelligence-based machine learning (ML) tools are considered a potential tool for improving the QoS parameters in IoT applications. This research proposes a novel approach for enhancing QoS parameters in IoT using ML and Blockchain techniques. The IoT network with Blockchain technology is simulated using an NS2 simulator. Different QoS parameters such as delay, throughput, packet delivery ratio, and packet drop are analyzed. The obtained QoS values are classified using different ML models such as Naive Bayes (NB), Decision Tree (DT), and Ensemble, learning techniques. Results show that the Ensemble classifier achieves the highest classification accuracy of 83.74 % compared to NB and DT classifiers.

Advancing Wireless Sensor Networks through Performance Evaluation of M-PDCH Routing Protocol for Enhanced Quality of Service

Objective: The decisive aim of this investigation is to improve the capabilities and limitations of PEGASIS with Double Cluster Head (PDCH), for enhancing the overall Quality of Service (QoS) in Wireless Sensor Networks (WSNs). Methods: This research is intended at the application of efficient routing protocol for wireless sensor networks. It works on the principle of the formation of cluster head and clustering. This is accomplished to achieve high QoS for WSN. Improving the efficacy of a WSN protocol is decisive for optimizing communication, resource utilization, and overall effectiveness. An innovative and novel protocol named Mobile-PDCH (M-PDCH) has been devised, developed, and tested. Here several parameters have been carefully investigated for enhancing the performance of a WSN protocol such as energy consumption, delay, and packet loss. A simulation environment has been created to evaluate, compare, and validate the performance and to suggest the desired applications of the proposed protocol. Findings: In the hierarchical category, PDCH performs better compared to all the other protocols. But it suffers from high packet drop, which decrease the performance of the protocol. To improve the performance of sensor networks, there is a need for adaptive routing protocol. The examination of simulation outcomes for the recommended protocol, M-PDCH, has been conducted in comparison with PDCH. The findings indicate that the protocol exhibits superior performance. The proposed algorithm improves the packet drop by 29.75%, reduces delay by 23.28%, and lowers energy consumption by 19.18% when compared to PDCH. Novelty: A novel adaptive routing protocol termed M-PDCH has been proposed for the enhancement of the WSN life span and durability of the sensor nodes. The simulation results show that the proposed algorithm produces better results compared to PDCH protocol. The various QoS parameter results are compared, verified, and validated with existing protocol PDCH. Keywords: WSN, PDCH, Design issues, Metrics, QoS, HRP

COMPARISON OF QUALITY OF SERVICE PARAMETERS FOR FOUR CELLULAR NETWORK PROVIDERS IN PUNGGUR KECIL VILLAGE

This research aims to analyze Quality of Service (QoS) parameters on cellular networks using four providers by measuring throughput, packet loss, delay and jitter parameters when conducting Video Streaming and Online Games using the Wireshark application. The research method involves direct measurement of QoS parameters in several strategic locations in Punggur Kecil village, data was taken at three different location points with a distance comparison of ±500 meters. From all the recapitulations of QoS parameter measurement results, it can be concluded that the value of each QoS parameter can vary for each package which includes the categories poor, medium, good and very good because the bandwidth received by each provider is different. The cause of high and low values of different QoS parameters, Throughput is caused by the number of packet arrivals measured during the observation process, Packet Loss is caused by the number of queues exceeding capacity, Delay is caused by low Throughput values and the number of packets sent, while the Jitter value is influenced by the Delay value. The results obtained are that the Indosat provider is the recommended provider when carrying out Video Streaming and Online Games, because the Quality of Service value produced is superior to other providers. The average values of the Throughput, Packet Loss, Delay and Jitter parameters at each location for the Indosat provider are respectively 796kbps, 2.63%, 22.6ms and 22.6ms. Provider XL is 708kbps, 1.67%, 12.6ms, and 12.6ms. Provider Telkomsel 667kbps, 0.33%. 55.9ms, and 56ms. As well as the Smartfren provider 50kbps, 0.38%, 102.6ms, and 102.7ms.

Mobile Network Operators’ Assessment Based on Drive-Test Campaign in Urban Area for iPerf Scenario

The development of new telecommunication services requires the implementation of advanced technologies and the next generations of networks. Currently, the Long-Term Evolution (LTE) is a widely used standard. On the other hand, more and more mobile network operators (MNOs) are implementing the fifth-generation (5G) New Radio standard in their networks. It allows for increasing throughput, spectral, and energy efficiency and maximizing coverage, while reducing latency. The effectiveness of the introduced changes is measured by assessing the quality of service (QoS) in mobile networks. The paper presents the result evaluation of the QoS measurement campaign carried out using the drive test method in an urban area for four MNOs. We analyze the data transmission scenario, which is the basis of most modern telecommunications services. The result comparison provides an assessment of the 5G service implementation advancement by MNOs. In this analysis, we consider many QoS metrics (e.g., session time, throughput, and round-trip time) and parameters defining the radio signal quality (i.e., reference signal received power, signal-to-interference-plus-noise ratio). Our work also included searching for relationships between these parameters, using a correlation analysis. It allows for the selection of uncorrelated parameters to assess the quality of network, i.e., MNO evaluation, in terms of the provided QoS.

Performance Analysis of BGP Dynamic Routing Protocol using QOS for TCP and UDP Services

The Border Gateway Protocol (BGP) is commonly used for TCP and UDP services, but it poses challenges in terms of Quality of Service (QoS) analysis. Parameters like throughput, packet loss, delay, and jitter are crucial for assessing network service quality. This study aims to analyze the performance and influence of the BGP routing protocol on TCP and UDP services using QoS parameters. The research used a GNS3 network simulation to conduct multiple packet transmission tests for TCP and UDP protocols, lasting 15, 30, and 60 seconds; and monitored using Wireshark. For TCP services, the average QoS index value is 3.75, categorizing the quality as "Good". The tested network topology and routing configuration exhibit reliable performance, providing good throughput, low packet loss rates, minimal delays, and stable jitter. Similarly, UDP services demonstrate “Good” performance with an average QoS index of 3.75. The BGP routing protocol in the tested network topology ensures high-quality service with good delivery speed, low packet loss rate, minimal delay, and stable jitter. Overall, the study concludes that the BGP routing protocol effectively provides satisfactory QoS for TCP and UDP services. This research contributes to understanding network performance and optimizing routing protocols for improved telecommunications services. The findings highlight the significance of routing protocols in facilitating efficient data transmission on the Internet, reinforcing the importance of QoS analysis for enhancing service quality.

Quality of services in software defined networking: challenges and controller placement problems

<span>Quality of service (QoS) is pivotal for ensuring effective and reliable network performance, yet achieving end-to-end QoS within current network architectures remains a persistent challenge. The emergence of software defined networking (SDN) addresses limitations in traditional networking by offering a centralized control plane. This allows dynamic resource management and efficient enforcement of QoS policies by network administrators. However, the controller placement problem (CPP) within SDN poses a significant challenge, as identifying the optimal placement of controllers is a non-deterministic polynomial-time hardness (NP-hard) problem. Researchers are actively working on solutions to address this challenge, especially in large-scale networks where deploying controllers becomes complex. Additionally, maintaining QoS in terms of controller management presents another hurdle. This paper explores these challenges, delving into the literature and providing a comprehensive analysis of controller performance metrics related to QoS parameters such as load balancing, reliability, consistency, and scalability. By addressing these challenges, the research aims to enhance QoS within the SDN framework.</span>

An improved ACO based service composition algorithm in multi-cloud networks

In recent years, with the rapid development of mobile communication networks, some new services such as cloud virtual reality, holographic communication, and etc. continue to emerge. Service composition has been researched in cloud computing. however, as the fast development of edge clouds, the service components can be deployed on the edge clouds to reduce the composition latency, so the more flexible and intelligent service composition algorithms are urgently need to study. Based on this, we propose a service composition strategy under the multi-cloud environment, and we propose an ant colony optimization algorithm (ACO) based on the multi-pheromone mechanism to optimize the quality of service (QoS). To avoid the occurrence of local optima, we further introduce the mutation operation of the genetic algorithm. Finally, the simulation results show that the proposed algorithm can achieve better QoS parameters such as latency and response time while ensuring the stability of services.

Comparative Quality of Service Analysis of VPN Protocols on IPv6

The increase in internet users has led to the depletion of IPv4 supplies and the increase in cyber attacks, one of which is data leakage incidents. Several innovations were created such as switching to IPv6 which provides more addresses and implementing VPN technology to secure internet communications. The solution using VPN is believed to secure the network from various types of attacks from outside the network by creating a tunnel with a certain encryption algorithm as a data exchange path. Some studies reveal that using VPN can cause delay which will affect QoS performance. Therefore, this research will be conducted to provide evidence as well as a comparison between the WireGuard and L2TP / IPSec VPN protocols on IPv6 based on Quality of Service parameters which include delay, jitter, packet loss, throughput, and MOS with three tests namely iPerf3, FTP, and remote desktop . The measurement is done by making a sample model with mikrotik and 6to4 tunnel. From the series of tests, it is known that the L2TP/IPSec protocol is better than the WireGuard protocol judging by the performance generated in tests with FTP and remote desktop. This discovery can be used by end users or other researchers to use VPN more objectively based on the technology.

Enhancing Security in Cloud-Based VM Migration: A Trust-Centric Hybrid Optimization Approach

Virtual Machine (VM) migration in cloud computing is essential to accomplishing various resource management goals, such as load balancing, power management, and resource sharing. Ensuring Quality of Service (QoS) is crucial while migrating Virtual Machines (VMs), which means that VMs must run continuously during the procedure. The dynamic nature of resource requirements in cloud computing, driven by "service-on-demand," poses security risks, even while live VM migration mechanisms help to maintain VM availability. This paper addresses changing resource requirements and improves overall system security by introducing a novel method for safe live virtual machine migration. In this paper, a robust optimization approach has been proposed for live virtual machine migration named the Gorilla-based Shuffled Shepherd Optimization Approach (GBSSOA). The proposed approach maximizes the number of fitness targets, such as migration time, QoS parameters, and job runtime. The method takes into account trust values in addition to the previously described performance measures, with a focus on security. Key performance indicators QoS as workload, migration time, trust, and GBSSOA-based secure live virtual machine migration are taken into account during the evaluation. The obtained values of 0.141, 0.654, 342.254 ms, and 0.569, respectively, show noteworthy accomplishments in the results. These results highlight how well the strategy developed may simultaneously improve performance metrics and strengthen the security of live virtual machine migration in dynamic cloud computing environments.

Enhancing Security in Cloud-Based VM Migration: A Trust-Centric Hybrid Optimization Approach

Virtual Machine (VM) migration in cloud computing is essential to accomplishing various resource management goals, such as load balancing, power management, and resource sharing. Ensuring Quality of Service (QoS) is crucial while migrating VMs, which means that VMs must run continuously during the procedure. The dynamic nature of resource requirements in cloud computing, driven by “service-on-demand,” poses security risks, even while live VM migration mechanisms help to maintain VM availability. This paper addresses changing resource requirements and improves overall system security by introducing a novel method for safe live VM migration. In this paper, a robust optimization approach has been proposed for live VM migration named the Gorilla-based Shuffled Shepherd Optimization Approach (GBSSOA). The proposed approach maximizes the number of fitness targets, such as migration time, QoS parameters, and job runtime. The method takes into account trust values in addition to the previously described performance measures, with a focus on security. Key performance indicators QoS as workload, migration time, trust, and GBSSOA-based secure live VM migration are taken into account during the evaluation. The obtained values of 0.141, 0.654, 342.254ms, and 0.569, respectively, show noteworthy accomplishments in the results. These results highlight how well the strategy developed may simultaneously improve performance metrics and strengthen the security of live VM migration in dynamic cloud computing environments.

A hybrid meta-heuristic algorithm for multi-objective IoT service placement in fog computing environments

The fog computing paradigm is promising for deploying various delay-sensitive Internet of Things (IoT) applications. The resource-constrained fog devices restrict the number of application deployments due to a lack of efficient resource estimation and discovery mechanisms for various emergent heterogeneous IoT applications. An efficient resource allocation strategy is one of the best choices to meet these application’s Quality of Service (QoS) requirements and improve system performance. However, finding the best allocation strategy for IoT applications with more than one QoS parameter is a challenge, and it has been proved as a non-deterministic polynomial time (NP)-complete problem. This article formulates a classical weighted multi-objective IoT service placement to optimize three parameters, i.e., makespan, cost, and energy. The non-convexity nature of the solution space motivates us to focus on the population-based meta-heuristic algorithm, i.e. Genetic Algorithm (GA), Simulated Annealing (SA) and Particle Swarm Optimization (PSO), along with their combination GA-SA, and GA-PSO. It implements the algorithm and compares it with the greedy-based random placement approach, varying the number of IoT applications with different parameters. The final results reveal that the hybrid method GA-SA outperforms other state-of-the-art algorithms.

Improvising QoS through Cross-Layer Optimization in MANETs

In Mobile Adhoc Networks (MANETs), nodes are mobile and interact through wireless links. Mobility is a significant advantage of MANETs. However, due to the unpredictable nature of mobility, the link may fail frequently, degrading the Quality of Service (QoS) of MANETs applications. This paper outlines a novel Ad hoc On-Demand Distance Vector with Proactive Alternate Route Discovery (AODV-PARD) routing protocol that uses signal strength-based link failure time estimation. The node predicts the link failure time and warns the upstream node through a warning message about the failure. On the basis of this information, a mechanism for identifying alternate routes is started in order to reroute traffic to the alternate route prior to the link failure. It significantly reduces packet loss and improves all the QoS parameters. The suggested protocol is compared to the traditional Ad hoc On-Demand Distance Vector (AODV) routing protocol and shows that the outlined protocol results in an improvement in QoS.

QUALITY OF EXPERIENCE FOR VOICE OVER INTERNET PROTOCOL (VoIP)

Today, the service of Voice over Internet Protocol or (VoIP) is one of the most used service around the globe in many fields, especially with video conferencing applications. Different applications and also many communications companies around the world use the VoIP service. Communication stakeholders aim to keep old customers happy and attract new customers. There was a need for some kind of service quality measures. Metrics are used to quantify the quality of transmission link are known Quality of Service (QoS). Whereas, user satisfaction level is identified by using Quality of Experience (QoE). This paper conducted a simulation model for VoIP service over heterogeneous, using OPNET modeler. This work aims to compare the user satisfaction level of the VoIP service by using different coding schemes in the application level of the User Equipment (UE). The measured QoS parameters over the heterogeneous transmission link were IP packet delay, IP Packet jitter, IP packet loss, MAC layer delay, PHY layer throughput in the network. Additionally, in this simulation model the use of E-Model to assess QoE level using Mean Opinion Score (MOS) metric in predicting the VoIP call quality. The results using the vocoder G.729A during the (30) sec of the voice call simulation time were as follows: Delay 0.57 mSec, Throughput of 290 Kbits/sec, Jitter of 0.02 uSec, MOS value of 3.76. The results using the vocoder G.711 during the same aforementioned time were as follows: Delay 0.25 mSec, Throughput of 70 Kbits/sec, Jitter of 0 Sec), MOS value of 3.08.

Performance Analysis of MIMO Heterogeneous Wireless Sensor Networks

Wireless Sensor Networks (WSN) are widely used in remote applications related to defence and healthcare. A network with nodes having different capabilities like sensing, various computational capabilities, power-efficient communication, and a varied sensing range is called a heterogeneous wireless sensor network. Heterogeneous wireless sensor networks using MIMO wireless channels are more useful for energy-efficient multi-channel communication. MIMO applications in wireless sensor networks have the potential to enhance throughput, reduce End-to-End Delay, improve packet delivery ratios, and conserve energy in wireless sensor networks. Its implementation needs to be carefully considered in light of the specific deployment conditions and resource constraints of the network, considering proper antenna design, synchronisation mechanisms, and energy-efficient algorithms. This paper presents a comparative performance analysis of MIMO wireless sensor networks and traditional wireless sensor networks without MIMO for various Quality of Service parameters like Packet Delivery Ratio, End to End Delay, Throughput and Residual energy. The research work shows that the application of MIMO in Wireless Sensor Networks enables sensor nodes to collaborate effectively, leading to improved reliability and coverage, and also increases the network's lifetime by conserving energy in resource-constrained sensor nodes through the preservation of Residual Energy.

Dragon fly algorithm based approach for escalating the security among the nodes in wireless sensor network based system

A new technology that is gaining popularity today is the Wireless Sensor Network. Smart sensors are being used in a variety of wireless network applications, including intruder detection, transportation, the Internet of Things, smart cities, the military, industrial, agricultural, and health monitoring, as a result of their rapid expansion. Sensor network technologies improve social advancement and life quality while having little to no negative impact on the environment or natural resources of the planet are examined in sensor networks for sustainable development. Real-world applications face challenges ensuring Quality of Service (QoS) due to dynamic network topology changes, resource constraints, and heterogeneous traffic flow. By enhancing its properties, such as maintainability, packet error ratio, reliability, scalability, availability, latency, jitter, throughput, priority, periodicity, deadline, security, and packet loss ratio, the optimized QoS may be attained. Real-world high performance is difficult to attain since sensors are spread out in a hostile environment. The performance parameters are divided into four categories: network-specific, deployment phase, layered WSN architecture, and measurability. Integrity, secrecy, safety, and security are among the privacy and security levels. This article leads emphasis on the trustworthiness of the routes as well as the nodes involved in those routes from where the data has to pass from source to destination. First of all, the nodes are deployed and cluster head selection is done by considering the total number of nodes and the distance from the base station. The proposed work uses AODV architecture for computing QoS parameters that are throughput, PDR and delay. K-means clustering algorithm is used to divide the aggregated data into three possible segments viz. good, moderate and bad as this process does not involve the labelling of aggregated data due to its supervised behavior. The proposed trust model works in two phases. In first phase, data is divided into 3 segments and labelling is done. In second phase, uses generated class objects are to be applied viz. the route records to publicize the rank of the routes followed by the rank of nodes. The proposed technique employed the statistical machine learning and swarm intelligence strategy with dragon fly algorithm in order to address the issues related effective rank generation of nodes and improving the network lifetime. Deep learning concepts can be combined with fuzzy logics approach for resolving issues like secure data transmission, trustworthiness of ranking nodes and efficient route discovery.