Improving QoS in WSN Based on an Optimal Path from Source to Sink Node Routing Algorithm

Wireless Sensor Networks (WSNs) comprise of groups of tiny sensor nodes that are deployed for collaborative missions such as environmental monitoring, target tracking and surveillance. Due to the miniature size of the nodes, they are typically deployed in large numbers and communicate via multiple hops through a wireless shared communication channel. The successful implementation of such networks is dependent on the enabling technologies (such as digital electronics and wireless communications), as well as the provisioning of Quality of Service (QoS) in the network. While there have been many efforts in QoS provisioning in traditional networks such as the Internet and Mobile Ad Hoc Networks (MANETs), these networks have very different characteristics from that of WSNs. Consequently, the QoS models and protocols that have been designed for the Internet and MANETs cannot be directly applied to WSNs. In this paper, we look at some of the existing QoS mechanisms in the networking literature, and the inherent characteristics of WSNs which make it challenging to provision for QoS in the network. We then identify some key performance metrics for WSN QoS and outline some mechanisms to achieve QoS in the sensor network. Finally, we propose WISER - a framework to enhance QoS in WIreless SEnsoR networks.

Using wireless sensor networks (WSNs) in delay and reliability critical environments is highly desired due to their unique advantages such as low cost, ease of deployment, and redundancy. However, successful deployment of resource-limited WSNs in such applications requires strict quality-of-service (QoS) provisioning techniques to meet the desired latency and reliability targets of those applications. Implementation of QoS techniques in WSNs is significantly challenging since WSNs have been initially devised for low-data-rate non-real-time applications. Therefore, WSN designers and developers resort to different cross-layer interaction and optimization techniques to provision QoS in WSNs. In this paper, we present a survey on the state of the art of cross-layer QoS approaches in wireless terrestrial sensor networks to achieve delay and reliability bounds in critical applications. Our paper provides a unique classification of cross-layer QoS approaches in WSNs that allows surveying a large amount of studies with utmost clarity. Furthermore, we highlight the main challenges of implementing QoS protocols in WSNs and present an overview of QoS-aware WSN applications.

The selection of routing protocols is playing a major role in the device and proper utilization of wireless sensor networks (WSNs) that can help to provide better interconnection networks. On preserving the role of key performance, metric related to routing protocols is also an important and challenging task in the WSNs. Therefore, the sensor nodes life can be improved in efficient manner by using routing protocols that preserve the energy consumption and quality of service (QoS). Three different kinds of categories are used in the design of routing protocols which are data centric, hierarchical, and location-based approaches. Energy consumption can be improved by reducing the effect of redundancy level and transferring the passive motes sleep mode. The data transmission time also impacts on the energy conservation and QoS in WSNs. The surveillance and monitoring-related applications are the demanding research field in the WSNs that has to resolve the issue QoS routing in the manner of reliable data delivery. Energy consumption and QoS constraints are two complementary factors in the routing protocol, but the time delay factor can be involved in such a manner to satisfy both the performance metrics in routing protocol in WSNs.

Wireless sensor networks (WSNs) are emerging rapidly as a new generation of sensor networks. Despite intensive research in wireless sensor networks (WSNs), limited work has been found in the open literature in the field of WSNs. In particular, quality-of-service (QoS) management in WSNs remains an important issue yet to be investigated. As an attempt in this direction, this paper develops a logic for QoS management (LFQMS) scheme for WSNs with constrained resources and in dynamic and unpredictable environments. Taking advantage of the feedback control technology, this scheme deals with the impact of unpredictable changes in traffic load on the QoS of WSNs. It utilizes a logic controller inside each source sensor node to adapt sampling period to the deadline miss ratio associated with data transmission from the sensor to the sensor. The deadline miss ratio is maintained at a pre-determined desired level so that the required QoS can be achieved. The (LFQMS) has the advantages of generality, scalability, and simplicity. Simulation results show that the (LFQMS) can provide WSNs with QoS support.

Wireless Sensor Networks (WSN) have emerged as an important technology due to their unique characteristics and have a number of promising applications, such as remote environmental monitoring and target tracking. Sensor networks are made up of small sensing devices equipped with processors, memory, and short-range wireless communications that can form distributed networks. It has been shown that the design of a WSN depends on the application and it must consider many factors, such as environment, application's design objectives, cost, hardware, and system constraints. Quality of Service (QoS) is an important factor in most fields, where applicable layers and specific scenarios can be submitted. QoS faces many difficulties as a result of computational resource sensors and high energy needs. In this study, we analyze the prerequisites for QoS provisioning in WSN. We also introduce the top-down technique of QoS, also discussed the medium technique for QoS in WSN. Finally, we classify applications of QoS depending on delay and tolerance sensitivity, into two ways; cross-layered and layered techniques.

An energy-efficient cross-layer-based opportunistic routing protocol and partially informed sparse autoencoder for data transfer in wireless sensor network

In Wireless Sensor Networks (WSNs), performance and availability are important in providing Quality of Service (QoS). WSNs are prone to failures that may result from software and hardware malfunctions, battery drain, tampering and link failures. In addition, sensors are resource constrained in terms of inadequate processing capacity, limited storage memory and restricted power supply. Alternating sensor operations between sleep and active modes whilst saving energy, has also introduced more challenges to the performance and dependability of WSN systems. This paper therefore seeks to investigate performance and availability concerns resulting from link and node failures in addition to the buffer restrictions and challenges caused by alternating sensor operations between active and sleep states. First, a finite queue capacity analytical model integrating performance and availability in the presence of node and channel failures and repairs is developed. Using the model, we analyse performance and availability of WSNs in terms of network throughput, delays and dependability. Finally, the model is used to evaluate tradeoffs between performance metrics. The analytical solutions using Spectral Expansion and Kolmogorov Forward equations as well as the simulation results are in good agreement.

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.

Wireless sensor networks (WSNs) are used to collect large amounts of data over a wide area. However, the sensor nodes used in WSNs have a short lifespan because they are generally battery-operated. Research is actively underway to increase the lifespan of WSNs via techniques such as energy harvesting and wireless power transfer (WPT). This study proposes a scheme for clustering and adjusting the WSN data collection rate to alleviate the hotspot problem and improve network connectivity. The proposed scheme is targeted at WSNs in which the sensor nodes harvest solar energy. In addition, an unmanned aerial vehicle (UAV) traverses along a given path and delivers energy to sensor nodes using WPT, while collecting data as a sink node. In this scheme, the number of cluster heads is determined by considering the number of nodes at each hop distance and the maximum amount of data that can be transferred with the available energy. Further, sensor nodes limit the amount of data they collect to reduce the relay load on intermediate nodes. To achieve this, nodes consider the amount of data transferred by parent nodes, especially nodes in the hotspot, and the number of child nodes. The sink node traverses along a given path, and collects the data accumulated in the cluster head while supplying its remaining energy to the cluster head. The amount of energy it transfers is determined by considering the number of cluster heads. Consequently, nodes in the hotspot are prevented from becoming blacked out from a lack of energy, and the energy harvesting efficiency is increased. Simulation results indicate that the proposed scheme reduces the number of blackout nodes in the hotspot areas near cluster heads. Furthermore, the data collection and monitoring performance increases with the increase in network connectivity.

Over the past few years, great importance has been given to wireless sensor networks (WSNs) as they play a significant role in facilitating the world with daily life services like healthcare, military, social products, etc. However, heterogeneous nature of WSNs makes them prone to various attacks, which results in low throughput, and high network delay and high energy consumption. In the WSNs, routing is performed using different routing protocols like low-energy adaptive clustering hierarchy (LEACH), heterogeneous gateway-based energy-aware multi-hop routing (HMGEAR), etc. In such protocols, some nodes in the network may perform malicious activities. Therefore, four deep learning (DL) techniques and a real-time message content validation (RMCV) scheme based on blockchain are used in the proposed network for the detection of malicious nodes (MNs). Moreover, to analyse the routing data in the WSN, DL models are trained on a state-of-the-art dataset generated from LEACH, known as WSN-DS 2016. The WSN contains three types of nodes: sensor nodes, cluster heads (CHs) and the base station (BS). The CHs after aggregating the data received from the sensor nodes, send it towards the BS. Furthermore, to overcome the single point of failure issue, a decentralized blockchain is deployed on CHs and BS. Additionally, MNs are removed from the network using RMCV and DL techniques. Moreover, legitimate nodes (LNs) are registered in the blockchain network using proof-of-authority consensus protocol. The protocol outperforms proof-of-work in terms of computational cost. Later, routing is performed between the LNs using different routing protocols and the results are compared with original LEACH and HMGEAR protocols. The results show that the accuracy of GRU is 97%, LSTM is 96%, CNN is 92% and ANN is 90%. Throughput, delay and the death of the first node are computed for LEACH, LEACH with DL, LEACH with RMCV, HMGEAR, HMGEAR with DL and HMGEAR with RMCV. Moreover, Oyente is used to perform the formal security analysis of the designed smart contract. The analysis shows that blockchain network is resilient against vulnerabilities.

Among important issues in the current energy-efficient routing protocols for wireless sensor networks (WSNs) based on clustering approaches are how to determine the optimal number of clusters, how to generate clusters and how select cluster-heads to improve WSNs performance. These approaches aim to reduce energy consumption of the WSN nodes and to extend the network lifetime. This paper reviews and compares the performance of three clustering techniques for determining number of clusters: rule of thumb, elbow, and silhouette. Each of these techniques involves a distributed K-means approach to generate clusters. Moreover, we compare these three clustering methods with low energy adaptive clustering hierarchy (LEACH), Imp LEACH and MODLEACH in terms of network lifetime, energy consumption and the number of packets sent to the base station (BS). The results obtained indicate that rule of thumb method provides better performance compared to other clustering techniques in terms of energy consumption and network lifetime.

Wireless Sensor Networks (WSNs) is the vast area and developing very speedily now-a-days. This paper gives some of the major applications and critical limitations of WSNs like power and lifespan, communication bandwidth, memory size. Sensor nodes are working by node energy so the energy consumption is the essential issue in WSN. Routing in WSN consumes more energy than any other phase. Various routing techniques in WSNs are discussed and different routing protocols are illustrated. Low Energy Adaptive Clustering Hierarchy (LEACH) is one of the popular and feasible hierarchical clustering routing protocols in WSN. Working of LEACH is explained in brief. Furthermore, the descendants of LEACH e.g. LEACH-C (Centralized LEACH), LEACH-B (Balanced LEACH), LEACH-F, Multihop LEACH, MS-LEACH (Multihop and Single hop LEACH), MH-LEACH etc. are discussed in terms of the energy utilization. By analyzing the variants of LEACH, it is observed that the energy requirement in the cluster set up phase or data transmission phase is minimized to minimize the total energy consumption of the WSN. To elect the proper cluster head node, centralized approach is followed. Afterwards, data transmission will use the multihop communication technique. This will help to save some energy when base station is located far away from the cluster head node. Proposed protocol aims to decrease the energy overhead of the sensor nodes. The new approach is proposed entitled PV-LEACH which will save the energy consumption in cluster setup phase and also in data transmission phase of the conventional LEACH protocol. So, this will enhance the performance ratio in terms of energy consumption and life time of the sensor nodes.

Wireless Sensor Networks (WSNs) are essential in fields such as agriculture, education, industry, and environmental monitoring. However, given their limited energy supplies and occasional maintenance, creating energy-efficient network topologies and routing methods is a considerable problem. This work presents an approach to enhance the longevity of networks in WSN. This approach employs advanced fuzzy C-means clustering, modified particle swarm optimization (MPSO) for cluster head selection, and routingbased adaptive zebra optimization (AZO). The adaptive zebra optimization approach relies on efficient routing paths chosen for every relay nodes to send data to the base station (BS). The proposed method illustrates that the relay node facilitates and optimizes communication between the sink and the cluster head, thereby enhancing energy efficiency. Ultimately, the quality of service (QoS) in WSNs improves, enabling the system to sustain long performance. The suggested technique demonstrated superior performance compared to prior methods for energy consumption, throughput, node viability, end-to-end latency (E2E), and packet delivery ratio (PDR).

The domain of wireless sensor networks (WSNs) is one of the most rapidly growing scientific fields. This is because not only the technological advances have enabled the development of advanced sensor nodes with extremely low cost but the potential applications of such structures are ever growing too. WSNs differ from traditional wireless communication networks in several of their characteristics. One of them is power awareness, due to the fact that the batteries of sensor nodes have a restricted lifetime and are difficult to be replaced. Therefore, all protocols must be designed in such a way as to minimize energy consumption and preserve the longevity of the network. That is why, routing protocols in WSNs aim mainly to accomplish power conservation while in traditional networks they focus primarily on the quality of service (QoS). Recent advances in WSNs have led to many new protocols specifically designed for sensor networks where energy awareness is an essential issue. This work suggests the development of such hierarchical routing protocol, named SHPER (scaling hierarchical power efficient routing), which proves to be particularly effective.

Wireless Sensor Networks (WSN) represent actually one of the challenging type of Delay-tolerant networks due their sparse connectivity and hard coverage. In addition, the emergence of applications with different types of traffic in these networks, assurance of Quality of Service (QoS) becomes more and more important. In recent years, lot of research has been conducted to improve the QoS in WSN. In this article, we introduce a Quality of Service (QoS) routing algorithm based on dynamic state-dependent policies. The proposed algorithm uses a bio-inspired approach based on trial/error paradigm to optimize two QoS different criteria: Energy and end-to-end delay. Our proposal, called EDEAR "Energy and Delay Efficient Adaptive Routing", is based on explorer agent who is responsible for collecting information in terms of energy and delay by using continuous learning parameters on the network and update routing maintained at each node of the network. The exploration of routes has been optimized by proposing a new algorithm based on multipoint relay for energy consumption, thus reducing the overhead generated by the packets exploration. Numerical results obtained with NS simulator for different levels of traffic's load and mobility show that EDEAR gives better performances compared to traditional approaches.