Quality Of Service In Wireless Sensor Networks Research Articles

Recurring Network Node Performance Evaluation Model for Enhancing the QOS Levels in 6G Enabled WSN

Among the many promising qualities of the Sixth Generation (6G) are its ultra-dense connection, integrated sensing and communication, secure communication, very high data rate, energy and spectrum efficiency, and ultra-reliable low latency communication. Novel approaches to environmental protection and resource monitoring have evolved with new forms of communication networks made possible by technological advancements. When it comes to environmental research and science, 6G enabled Wireless Sensor Networks (WSNs) plays a key role. There are several fields that can benefit from WSNs, including robotics, environmental monitoring, medicine, and the military. The Quality-of-Service (QoS) is a critical concern in wireless sensor applications because to the increasing demand for their use in various domains. Because the resources accessible from sensors and the many applications operating over these networks have varied limits in nature and requirements, ensuring QoS in WSNs is complex and increasingly demanding. Delays, throughput, jitter, and other network-level indicators used to be the main focus of QoS efforts. In this research, a model for providing suitable QoS measures for WSN is proposed, including service, reliability, and availability, all of which contribute to the preservation of high-quality service. Availability, Dependability, and Serviceability are the parameters considered for providing QoS. 6G wireless networks are largely focused on enhanced intelligence, synchronization of resources and topology from beginning to end, and the inherent support for high-bandwidth, low-latency communication. With these features, cyber physical user experiences that are rich in context are feasible. As a result, defining and identifying the function of quality of experience in 6G networks is crucial, particularly for network administration. To optimize application service satisfaction, a WSN should learn to govern the network's overall performance based on QoS characteristics, which guarantee the transfer of information. This research proposes a Recurring Network Node Performance Evaluation Model (RNN-PEM) for enhancing the QoS levels in 6G enabled WSN. The proposed model when compared with the traditional models, provided enhanced QoS levels.

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

Enhancing Quality of Service in WSN Through a Routing Algorithm Based on Self-Organizing Maps

Many scholars have focused their attention on Wireless Sensor Networks (WSN) within the last ten years. QoS control, Energy intake, MAC protocols, routing protocols, statistics aggregation, self-organizing net algorithms, Internet of Things (IoT), and so forth are among the research topics that have been thoroughly studied recently. Historically, the potential of artificial intelligence (AI) has not been fully realized due to constraints in data processing capabilities and energy efficiency. Nonetheless, the unique characteristics of neural networks can be harnessed for complex tasks, such as the role of travel advisors. This research aims to combine IoT and WSN technologies to enhance Quality of Service (QoS) parameters including reliability, energy, conservation, system scalability and response time. It provides an overview of the key components and techniques utilized in WSNs to achieve QoS. The objective of the proposed article is to compare the performance of two widely used route paradigms, Energy-Aware Routing and Directed Diffusion, with the proposed routing technique called Sensor Intelligence Routing (SIR). The foundation of Sensor Intelligence Routing (SIR) is the incorporation of neural networks into discrete sensor networks. WSN simulation, OLIMPO (an ad-hoc wireless sensor network simulator for optimal scada-applications) has been used in multiple simulations to examine how well neural networks perform within the system. The results obtained from every routing method have been compared and analyzed. The paper also aims at fostering the use of IoT-based synthetic intelligence techniques.

Self-detection based fault diagnosis for wireless sensor networks

Wireless sensor network (WSN) is a collection of low-power and low-cost sensor nodes (SNs) deployed stochastically in the monitoring area to support various applications. The random occurrence of faulty sensor nodes affects the quality of service in WSN. Most of the existing fault detection algorithms are based on statistics, thresholds, majority voting, hypothetical tests, comparison, or machine learning and depend on the neighbor's sensing information to detect the fault status of SNs. Hence, these fault detection algorithms suffer from low detection accuracy (DA) and a high false alarm rate (FAR). Moreover, existing fault detection techniques are not scalable for large-scale WSNs, as they suffer from high energy overhead and detection latency. Furthermore, existing fault diagnosis algorithms burden an SN's resources while estimating the fault status of the WSN. This paper proposes a deep belief network (DBN) based self-detection algorithm to address these issues. The performance of the proposed DBN based self-detection algorithm has been evaluated using google colab, and MATLAB. The simulation results of the proposed algorithm has been compared with the existing fault detection algorithms. Simulation results show that the proposed algorithm performs better than the existing algorithms in terms of DA, FAR, and false positive rate. The performance of the proposed algorithm has also been evaluated in other network parameters such as energy consumption, and fault detection latency.

HFLFO: Hybrid fuzzy levy flight optimization for improving QoS in wireless sensor network

In IoT-based WSN applications, energy is a vital parameter since limited residual energy of a node often leads to packet loss, diminished network lifetime, and end-to-end delay. IoT nodes are often resource-constrained, with limited computational and storage capabilities, communication range, and energy-saving potential. To offer an improved Quality of Service (QoS) guarantee, the network lifetime and energy consumption of the WSN-based IoT applications need to be improved. QoS is an important parameter in time-sensitive IoT applications. Hence this paper introduces a novel QoS improvement framework for the WSN-IoT networks, and the objective of this work is twofold. In the first phase, we utilize an Aquila optimizer (AO) for an efficient and reliable cluster head selection which is based on different factors such as node level, distance to the sink node, energy level, etc. The AO algorithm enhances the lifetime of the WSN network by electing the QoS-aware relay node as the cluster head. In the next phase, the Hybrid Fuzzy Levy Flight Particle swarm optimization algorithm (HFLPSO) is presented to enhance the QoS of the network even further by identifying a set of optimal paths to route the packets and measure the reliability of each path via different metrics (packet loss rate, residual energy, end-to-end delay, link stability, and the number of hops). The simulation experiments were conducted using different metrics such as End to End delay, Packet loss rate, and Packet delivery ratio to prove that the proposed model is capable of improving the QoS of the WSN-IoT networks when compared to the different state-of-art methodologies. When compared to the existing techniques, the proposed model offers a 10% improvement in the packet loss rate and a 17% improvement in the packet delivery rate.

ILSM: Incorporated Lightweight Security Model for Improving QOS in WSN

In the network field, Wireless Sensor Networks (WSN) contain prolonged attention due to afresh augmentations. Industries like health care, traffic, defense, and many more systems espoused the WSN. These networks contain tiny sensor nodes containing embedded processors, Tiny OS, memory, and power source. Sensor nodes are responsible for forwarding the data packets. To manage all these components, there is a need to select appropriate parameters which control the quality of service of WSN. Multiple sensor nodes are involved in transmitting vital information, and there is a need for secure and efficient routing to reach the quality of service. But due to the high cost of the network, WSN components have limited resources to manage the network. There is a need to design a lightweight solution that ensures the quality of service in WSN. In this given manner, this study provides the quality of services in a wireless sensor network with a security mechanism. An incorporated hybrid lightweight security model is designed in which random waypoint mobility (RWM) model and grey wolf optimization (GWO) is used to enhance service quality and maintain security with efficient routing. MATLAB version 16 and Network Stimulator 2.35 (NS2.35) are used in this research to evaluate the results. The overall cost factor is reduced at 60% without the optimization technique and 90.90% reduced by using the optimization technique, which is assessed by calculating the signal-to-noise ratio, overall energy nodes, and communication overhead.

Efficient Energy and Delay Reduction Model for Wireless Sensor Networks

In every network, delay and energy are crucial for communication and network life. In wireless sensor networks, many tiny nodes create networks with high energy consumption and compute routes for better communication. Wireless Sensor Networks (WSN) is a very complex scenario to compute minimal delay with data aggregation and energy efficiency. In this research, we compute minimal delay and energy efficiency for improving the quality of service of any WSN. The proposed work is based on energy and distance parameters as taken dependent variables with data aggregation. Data aggregation performs on different models, namely Hybrid-Low Energy Adaptive Clustering Hierarchy (H-LEACH), Low Energy Adaptive Clustering Hierarchy (LEACH), and Multi-Aggregator-based Multi-Cast (MAMC). The main contribution of this research is to a reduction in delay and optimized energy solution, a novel hybrid model design in this research that ensures the quality of service in WSN. This model includes a whale optimization technique that involves heterogeneous functions and performs optimization to reach optimized results. For cluster head selection, Stable Election Protocol (SEP) protocol is used and Power-Efficient Gathering in Sensor Information Systems (PEGASIS) is used for driven-path in routing. Simulation results evaluate that H-LEACH provides minimal delay and energy consumption by sensor nodes. In the comparison of existing theories and our proposed method, H-LEACH is providing energy and delay reduction and improvement in quality of service. MATLAB 2019 is used for simulation work.

A Non-Dominated Sorting Genetic Algorithm Based on Voronoi Diagram for Deployment of Wireless Sensor Networks on 3-D Terrains

The deployment strategy for wireless sensor networks (WSNs) affects the quality of service (QoS). Adopting a reasonable deployment strategy can improve the QoS of WSNs. In this paper, the problem regarding sensor node deployment for WSNs on three-dimensional (3D) terrain is modeled as a multi-objective optimization problem. The coverage rate of the WSNs, their unbalanced energy consumption, and the number of sensor nodes are used as fitness functions for the optimization problem. We propose a non-dominated sorting genetic algorithm based on a Voronoi diagram (VNSGA) for solving the wireless sensor network deployment issue and improving the QoS of WSNs on 3D terrain. The proposed algorithm applies the Voronoi diagram to obtain the node-sensing radius and communication radius, which are suitable for 3D terrain with respect to calculating the fitness function of the optimization problem. The Pareto optimal solution is obtained by retaining the solution close to the reference point. The experiments compare the proposed algorithm with the Multi-Objective Particle Swarm Algorithm (MOPSO) and the Non-Dominated Sorting Genetic Algorithm III (NSGA-III) on two terrains with different ranges. The experimental results show that the proposed algorithm outperforms the comparison algorithm on both terrains with different range sizes. The proposed algorithm can improve the coverage to 97.95% and reduce the imbalance in energy consumption to 9.13% on large range terrain.

Hardware Implementation of Effective Framework for the Trade-off between Security and QoS in Wireless Sensor Networks

The trade-off between security and quality of service (QoS) in wireless networks has attracted great attention in recent years. This paper presents a hardware implementation of a novel framework for realizing the trade-off between security and QoS in wireless sensor networks (WSNs) regarding the hostility of the operating environment and the available resources of our objects. For evaluating the hostility of the operating environment, we developed an effective intrusion detection unit that sends an alarm signal to a control unit that also collects the data-carrying information about the available resources. As our work is concerned with WSNs, we focus on the power consumption of sensor nodes as the considered object resources. According to the collected data from the intrusion detection unit and resources status unit, the control unit can evaluate the situation of the object in the operating environment and sends control signals to a security unit to select the appropriate level of security among three levels (low, medium, and high) available in our developed framework. The three security levels consider different combinations of the cryptographic algorithms Hash-based Message Authentication Code (HMAC) and Advanced Encryption Standard (AES), with different key lengths, regarding the required security services (confidentiality, authentication and integrity) and available resources. To reinforce the QoS, we considered the advantages of hardware implementation in addition to maintaining the object resources. Our framework has been implemented using Field Programmable Gate Array (FPGA), Virtex-7 (xc7v585tffg1761–3), which helps in achieving reasonable performance with a maximum operating frequency of 206.838 MHz and throughput of 2.3 Gbps.

Intelligent Optimization of QoS in Wireless Sensor Networks Using Multiobjective Grey Wolf Optimization Algorithm

With the advancement of technology and the emergence of new types of communication networks, new solutions have emerged to protect the environment and monitor natural resources. Wireless sensor networks (WSNs) have revolutionized environmental science and research by embedding sensors in environments where constant access and monitoring by manpower is difficult. WSNs have a variety of uses in the military, environmental monitoring, medicine, robotics, and so on. With the advent of applications in WSNs, the fundamental problem of the network has also increased. The performance of WSNs is influenced by various parameters that are varied according to the applications. In general, the performance of a WSN is typically specified through its average energy use, which determines the lifespan of the grid. A WSN should acquire the ability for controlling the overall performance of the network for ensuring the transmission of information based on quality of service (QoS) parameters in order to maximize the satisfaction of the services for the application. Therefore, we provided a multiobjective grey wolf optimization algorithm (QAMO-GWO) in order to optimize routing and improve QoS in WSNs. In the proposed method, sensor nodes receive information about the environment over regular periods of time and send it to the cluster heads in each. The selection of cluster heads in each cluster is done using a multiobjective grey wolf optimization algorithm. MO-GWO algorithm via balancing QoS parameters tries for selecting the optimal cluster heads. Finally, simulation outputs showed that the proposed method has been able to improve QoS criteria due to balancing the goals in the network.

Overlapped hierarchical clusters routing protocol for improving quality of service

The rapid development in communications and sensors technologies make wireless sensor networks (WSNs) as essential key in several advanced applications such as internet of things (IoT). The increasing demands on using WSNs required high quality of services (QoS) because most WSNs applications have critical requirements. This work aims to offer a routing protocol to improve the QoS in WSNs, taking in consideration its ability to prolong the lifetime of the network, optimize the utilization of the limited bandwidth available, and decrease the latency that accompanies the packets transmitted to the gateway. The proposed protocol is called overlapped hierarchical cluster routing protocol (OHCRP). OHCRP is compared with the traditional routing protocols such as SPEED, and THVR. The results show that OHCRP reduces latency effectively and achieve high energy conservation, which lead to increase the network lifetime and insure network availability.

A Grey-Wolf based Optimized Clustering approach to improve QoS in wireless sensor networks for IoT applications

Wireless sensor networks (WSNs) have gained much attention in public and research communities due to their incredible capabilities and ever-growing range of applications. The WSN is equipped with a specialized transducer that adds the sensing services to IoT. This equipment is limited to battery and resource capacity, which introduces many challenges to academia and industry. Hence WSN has to be utilized in an energy-efficient manner to maximize the network’s lifetime while providing a precise QoS guarantee. QoS is an essential issue in many IoT applications such as environmental monitoring, smart cities, weather monitoring, animal tracking, disaster management, bio-medical applications. An optimal clustering technique for WSN, which includes the formation of clusters, and cluster head (CH) selection, can significantly improve the QoS to increase the lifespan of a WSN. This paper proposes a Grey wolf optimization-based cluster head selection technique for WSN considering distinct factors like energy level of the node, node degree, sink distance, intracluster distance, and priority factor. This paper also addresses the routing through QoS aware relay node selection for effective and reliable inter-cluster routing from CHs to Base station (BS). The proposed technique is simulated and evaluated based on the Quality of Service (QoS) parameters viz. residual energy, stability period, throughput, network lifetime, and delay. The proposed techniques improve the overall network performance by 10.00%, 23.75%, and 54.54% corresponding to ESO, GECR, and LEACH. Hence, the study infers that the protocol is well suited to design WSNs in IoT applications.

An Enhanced Multi-Objective Non-Dominated Sorting Genetic Routing Algorithm for Improving the QoS in Wireless Sensor Networks

In recent years, Wireless Sensor Networks (WSNs) have benefitted from their integration with Internet of Things (IoT) applications. WSN usage for monitoring and tracing applications shows massive acceleration, whether indoors or outdoors. WSN is constructed from interconnected sensors, limited resource (battery), which requires considerable importance on deployment and routing strategies, to improve the performance of Quality of Service (QoS) in WSNs. Many of the existing strategies are based on metaheuristics algorithms such as Genetic Algorithms to resolve the problem. This research proposes a new algorithm, Enhanced Non-Dominated Sorting Genetic Routing Algorithm (ENSGRA), to improve the QoS in WSNs. The proposed algorithm relies on Non-Dominated Sorting Genetic Algorithm 3 (NSGA-III), but adjusts reference points through the use of a dynamic weighted clustered scheduled vector to obtain new solutions. Moreover, ENSGRA can be used to find an integration between two parents crossover with multi-parent crossover (MPX), to produce multiple children and improve new offspring to obtain the optimal Pareto Fronts (PF). This algorithm excels when compared with the lagged multi-objective jumping particle swarm optimization, Non-dominated Sorting Genetic Algorithm–II and NSGA-III in terms of the QoS model (31% optimization percentage). Results show that the proposed ENSGRA is superior over other algorithms in evaluation measures for multi-objective algorithms.

Performability of Retransmission of Loss Packets in Wireless Sensor Networks

Latest progress in wireless communication technology has enabled the development of low-cost sensor networks with major concern on quality of service (QoS) provisioning. Wireless sensor networks (WSNs) can be adopted in various application domains but each use is likely to pose peculiar technical issues. Basically, we demonstrate that congestion, packet loss and delay have strong influence on the performance of WSNs. In order to implement a realistic sensor network policy to resolve the problem of data delay and avoidance of collisions that lead to packet losses, we develop a system that guarantees QoS in WSNs using Fuzzy Logic Controller (FLC) for sensitivity analysis of the effect of adaptive forward error correction (AFEC). The AFEC approach improves the throughput by dynamically tuning FEC subject to the nature of wireless channel loss thereby optimizing throughput, sensor power utilization, while minimizing traffic retransmission, bit error rate (BER), and energy consumption. Basically, parameters such as packet delivery ratio, packet loss, delay, error rate, and throughput are appraised. The system has a spread procedure which is able to schedule the transmission of the nodes in order to have a data flow that converges from the furthest nodes toward the fusion centre. The key benefit of the scenario showed that, after extensive simulation using realistic field data, the procedure permits a practical approach to obtaining optimal solution to loss packets retransmission problem in WSNs giving a strong improvement on QoS provisioning.

Inter Cluster Group Management in Wireless Sensor Networks

Wireless Sensor Networks (WSNs), an emerging large-scale network system can be embedded for any application. The designers of wireless sensor network have to consider the quality of service agreements from a user perspective. The WSN is very rapid in dynamic changing topology and has less energy, computing and communication resources. The network design has to fulfill the QoS parameters like reliability, timeliness and lifetime of the network. In wireless sensor network, when two nodes transmit messages through a common visible node and collision occurs between these nodes is refers to as Hidden Node Problem. Many researchers have reviewed the Hidden node problem affecting the throughput and lifetime of the network. This paper proposed Inter-Cluster Grouping Mechanism (ICGM) to handles the problem of inter-cluster grouping and hidden node for the improvement of Quality of Service (QoS) factors in WSN. The performance of WSN degrades due to the occurrence of inter-cluster interference caused by different grouping mechanism as imposed in different clusters. The proposed mechanism (ICGM) overcome the problem of inter-cluster interference and increases the QoS in WSNs.

Impacts of wireless sensor networks strategies and topologies on prognostics and health management

In this article, we used wireless sensor network (WSN) techniques for monitoring an area under consideration, in order to diagnose its state in real time. What differentiates this type of network from the traditional computer ones is that it is composed by a large number of sensor nodes having very limited and almost nonrenewable energy. A key issue in designing such networks is energy conservation because once a sensor depletes its resources, it will be dropped from the network. This will lead to coverage hole and incomplete data arriving to the sink. Therefore, preserving the energy held by the nodes so that the network keeps running for as long as possible is a very important concern. If we achieve to improve the network lifetime and Quality of Service (QoS). Diagnosing the state of area will be more accurate for a longer time. One of the most important elements to achieve a QoS in WSN is the network coverage which is usually interpreted as how well the network can observe a given area. Obviously, if the coverage decreases over time, the diagnosis quality decreases accordingly. Various coverage strategies are thus proposed by the WSN community, in order to guarantee a certain coverage rate as long as possible, to reach a certain QoS that in turn will impact the diagnosis and prognostic quality. Various other strategies are in common use in WSN like data aggregation and scheduling, to preserve a QoS in wireless sensor networks, as long as possible. We argue that such strategies are not neutral if this network is used for prognostic and health management. Some politics may have a positive impact while other ones may blur the sensed data, like data aggregation or redundancy suppression, leading to erroneous diagnostics and/or prognostics. In this work, we will show and measure the impact of each WSN strategy on the resulting estimation of diagnostics. We emphasized several issues and studied various parameters related to these strategies that have a very important impact on the network, and therefore on data diagnostics over time. To reach this goal, to evaluate both prognostic and health management with the WSN strategies, we have used six diagnostic algorithms.

Instilling QoS in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have been a desired choice for monitoring and automatic control of remote and unreachable objects and environments due to their low cost. However, such deployment requires quality-of service (QoS) techniques to assure reliable performance. Furthermore, provision of QoS in WSNs is a challenging task due to hardware limitations. A cross-layer approach is a promising option where information from different layers can be used to make QoS decisions. In this paper, we present a routing protocol where information from the application layer is used to make differentiated routing decisions based on data packets classifications. In our case, data packets are classified into: normal, urgent, and critical. Based on this classification each data packet class is treated differently by storing each data packet class in a designated buffer. Different buffers will have different routing priority decided by the protocol designer.

Analysing the Mobility Based Serious Effects in Achieving QOS in Wireless sensor Networks

Wireless Sensor Network is a collection of sensor nodes which are used to sense the environment and forward the sensed information to the outside world. A sensor plays a major role and it is based on the underlying application either static sensors or mobile sensors. The nature of movement of the sensors is also under concern. In this paper, the serious effects caused by the mobility factor in the performance of the network in terms of Quality of Service (QOS) parameters such as throughput, stability and coverage are investigated. Simulation experiments are conducted by varying the speed of the nodes, number of nodes and Communication Radius. Results indicate that the network performs well at high speeds when compared to low speed. Also, a notable improvement is achieved in terms of coverage, stability and throughput on increasing the communication radius and number of nodes.

PRIN: A Priority-Based Energy Efficient MAC Protocol for Wireless Sensor Networks Varying the Sample Inter-Arrival Time

Wireless sensor networks (WSNs) are used in a variety of applications to sense and transfer information to the centralized node with energy efficiency increasing the network's lifespan. Other factors, such as quality of service (QoS) is also important to improve the performance of the WSNs, by increasing throughput and reducing end-to-end delay. In this paper, we evaluate the importance of QoS in the Medium Access Control (MAC) protocol for WSNs using different metrics and parameters such as energy efficiency, throughput, delay, and the network lifespan. We propose a new QoS MAC protocol, "PRIority in Node" (PRIN), using static priority in the source and the intermediate node and priority among the node which is one hop from the sink node to achieve QoS in WSNs. Simulation results are compared with those of the synchronous MAC protocol in terms of QoS parameters to show the improved performance of the proposed MAC protocol.

A Survey on Protocols Involving QoS in Wireless Sensor Networks

Background: The fast emerging Wireless Sensor Networks (WSNs) and its growing demand in each and every sphere of our lives has shifted our focus on the performance of the networks involved in varied fields. Recent studies depict that the performance of network and its utilization can be enhanced by QoS (Quality of Service) routing protocol. Thus, QoS is the essence of the WSNs. So, in this paper, we would like to present a detailed survey of the various routing protocols which play a vital role in attaining the QoS in WSNs. Methods: There are various levels of QoS which are required by the WSNs depending on the applications that they focus upon. The QoS support to WSNs can be achieved by various routing protocols. Thus, a detailed research on various routing protocols is done depicting their strengths and weakness and a comparison table of various protocols on various parameters is provided. Results: The QoS basically aims to focus on the quality that is perceived by the users of various applications. The QoS facilitates the above aim in terms of delay, packet delivery ratio, reduction in power of the sensor nodes, energy efficiency, bandwidth utilization, amount of through put generated and many other factors. However, there are few challenges faced by QoS which may occur due to dynamic topology and constrained resources. Even after these challenges the research suggests QoS is undisputedly the essence of WSNs. Conclusion: The QoS is very advantageous as it helps in improving the service provided to the users, and is accountable in improving the quality of output perceived by the users of various applications. Researchers have started working to overcome the challenges of QoS with the aim to minimize its constraints and maximize its multiple objectives. Keywords: Delay, QoS, Quality, Reduction, Routing, Vital.