Explore the vast range of titles available.

Wireless sensor networks (WSNs) are one of the key enabling technologies for the internet of things (IoT). WSNs play a major role in data communications in applications such as home, health care, environmental monitoring, smart grids, and transportation. WSNs are used in IoT applications and should be secured and energy efficient in order to provide highly reliable data communications. Because of the constraints of energy, memory and computational power of the WSN nodes, clustering algorithms are considered as energy efficient approaches for resource-constrained WSNs. In this paper, we present a survey of the state-of-the-art routing techniques in WSNs. We first present the most relevant previous work in routing protocols surveys then highlight our contribution. Next, we outline the background, robustness criteria, and constraints of WSNs. This is followed by a survey of different WSN routing techniques. Routing techniques are generally classified as flat, hierarchical, and location-based routing. This survey focuses on the deep analysis of WSN hierarchical routing protocols. We further classify hierarchical protocols based on their routing techniques. We carefully choose the most relevant state-of-the-art protocols in order to compare and highlight the advantages, disadvantage and performance issues of each routing technique. Finally, we conclude this survey by presenting a comprehensive survey of the recent improvements of low-energy adaptive clustering hierarchy routing protocols and a comparison of the different versions presented in the literature.

Energy-efficient routing has become a critical issue for advanced energy-hungry unmanned aerial vehicles (UAVs). Routing in a flying ad hoc network is always challenging and becomes even more critical when a small number of UAVs must cover a large area. The routing protocols based on the delay-tolerant network (DTN) are best suited for such scenarios. However, traditional DTN-based routing protocols depend on data dissemination to offer a better packet delivery ratio, leading to congestion and excess transmissions, causing heavy and unnecessary energy consumption. We propose a location estimation-based congestion-aware routing protocol (LECAR) to balance these two issues. Considering outdated location information, LECAR takes advantage of the mobility model to estimate the current location of the destination. In addition, LECAR routes a packet by considering both the distance to destination and buffer occupancy of the neighboring UAVs. Simulation results show that LECAR could ensure both a high packet delivery ratio and low energy consumption. Moreover, LECAR could provide a minimal number of transmissions, while minimizing the number of copies per packet at a time.

Quality of Service (QoS) is a method of measurement used to determine the capacity of a network to perform services. One of the QoS implementations is to manage the performance of routing protocol. The routing protocol is a method used to connect one router to another, to convey information correctly and to provide a guaranteed service. This study discusses the QoS of the Enhanced Interior Gateway Routing Protocol (EIGRP) applied to campus area network. EIGRP is a routing protocol which only available on Cisco routers and often refers to the proprietary protocol on Cisco. EIGRP can only be applied by Cisco routers and their fellow. Campus area network is an interconnection of computer networks within the campus area. Data exchange on campus network should be undertaken quickly and precisely to facilitate campus operations. The method used in this study was Network Development Life Cycle (NDLC) which consisted of several phases, namely analysis, design, simulation prototyping, implementation, monitoring, and management. The results of this study provided QoS with a throughput value of 77 bps, 0.53 percent of the packet loss value, 1.89 ms of latency, and 1.87 ms of jitter value. This indicates that the EIGRP routing protocol has a strong QoS value to be applied to campus area networks.

Mobile Ad Hoc Networks (MANETs) are decentralized wireless networks characterized by dynamic topologies and the absence of fixed infrastructure. These unique features make MANETs critical for applications such as disaster recovery, military operations, and IoT systems. However, they also pose significant challenges for efficient and effective routing. This study evaluates the performance of eight MANET routing protocols: Optimized Link State Routing (OLSR), Destination-Sequenced Distance Vector (DSDV), Ad Hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR), Ad Hoc On-Demand Multipath Distance Vector (AOMDV), Temporally Ordered Routing Algorithm (TORA), Zone Routing Protocol (ZRP), and Geographic Routing Protocol (GRP). Using a custom simulation environment in OMNeT++ 6.0.1 with INET-4.5.0, the protocols were tested under four scenarios with varying node densities (20, 80, 200, and 500 nodes). The simulations utilized the Random Waypoint Mobility model to mimic dynamic node movement and evaluated key performance metrics, including network load, throughput, delay, energy consumption, jitter, packet loss rate, and packet delivery ratio. The results reveal that proactive protocols like OLSR are ideal for stable, low-density environments, while reactive protocols such as AOMDV and TORA excel in dynamic, high-mobility scenarios. Hybrid protocols, particularly GRP, demonstrate a balanced approach; achieving superior overall performance with up to 30% lower energy consumption and higher packet delivery ratios compared to reactive protocols. These findings provide practical insights into the optimal selection and deployment of MANET routing protocols for diverse applications, emphasizing the potential of hybrid protocols for modern networks like IoT and emergency response systems.

In the wireless network advancement, Mobile Ad-hoc Networks (MANET) has been one of the developing areas of research. MANET is a group of wireless mobile nodes, which dynamically interchange information by modeling a short-term network without any framework. In MANET, routing is a highly challenging problem. Routing refers to discovering a path between the source (transmitter) and the destination (recipient) to forward the data packets. In a dynamic environment like MANET, another challenging issue is to prolong the network lifetime by optimizing the energy to avoid broken links. An improved version of hybrid Zone based Hierarchical Routing Protocol (ZHRP) based on Dynamic Cuckoo Search (DCS) algorithm has been proposed to optimize the path selection process and energy utilization. Initially, the DCS algorithm has been applied to zone based hierarchical routing protocol to discover and sustain the best routes for each node. Then, the stability of the wireless link is evaluated using this meta-heuristic technique. In the DCS algorithm, to maintain the balance between the global and the local random walks, a dynamic switching parameter has been applied. Different versions of dynamic switching parameters in the cuckoo search algorithm such as linear decreasing, linear increasing, exponential increasing, and power increasing are implemented to enhance the performance of the routing process in MANETs. The simulation results show that the proposed dynamic cuckoo search based hybrid routing technique has comparatively improved the performance of zone based hierarchical routing in terms of energy consumption, average delay, packet delivery rate, and throughput. Finally, the simulation results indicate that the DCS algorithm with a switching parameter, which increases exponentially, outperforms the variants of the DCS algorithm.

Due to the limited battery energy of underwater wireless sensor nodes and the difficulty in replacing or recharging the battery underwater, it is of great significance to improve the energy efficiency of underwater wireless sensor networks (UWSNs). We propose a novel energy-efficient clustering routing protocol based on data fusion and genetic algorithms (GAs) for UWSNs. In the clustering routing protocol, the cluster head node (CHN) gathers the data from cluster member nodes (CMNs), aggregates the data through an improved back propagation neural network (BPNN), and transmits the aggregated data to a sink node (SN) through a multi-hop scheme. The effective multi-hop transmission path between the CHN and the SN is determined through the enhanced GA, thereby improving transmission efficiency and reducing energy consumption. This paper presents the GA based on a specific encoding scheme, a particular crossover operation, and an enhanced mutation operation. Additionally, the BPNN employed for data fusion is improved by adopting an optimized momentum method, which can reduce energy consumption through the elimination of data redundancy and the decrease of the amount of transferred data. Moreover, we introduce an optimized CHN selecting scheme considering residual energy and positions of nodes. The experiments demonstrate that our proposed protocol outperforms its competitors in terms of the energy expenditure, the network lifespan, and the packet loss rate.

In recent years, the vehicular ad-hoc network (VANET), which is an ad-hoc network used by connected autonomous vehicles (CAV) for information processing, has attracted the interest of researchers in order to meet the needs created by the accelerating development of autonomous vehicle technology. The enormous amount of information and the high speed of the vehicles require us to have a very reliable communication protocol. The objective of this paper is to determine a topology-based routing protocol that improves network performance and guarantees information traffic over VANET. This comparative study was carried out using the simulation of urban mobility (SUMO) and network simulator (NS-3). Through the results obtained, we will show that the choice of the type of protocol to use depends on the size of the network and also on the metrics to be optimized.

Mobile Ad-hoc Network (MANET) is a group of self-sustaining movable nodes which are communicating to other nodes in the networks through wireless connections. The motile nodes within the communication range can directly communicate with each other, whereas other nodes require the support of neighbouring nodes by using routing protocols. Most routing protocols are utilizing the rebroadcasting techniques to reduce the path overhead. An energy efficient zone based routing protocols are developed to reduce the redundant broadcasting through on-demand parallel collision guided broadcasting. Nevertheless, the broadcast storm is occurring due to transmit of simultaneous collision guided broadcasting which causes larger power consumption. Hence, this paper deals with a novel algorithm to increase the energy efficient zone based routing protocols which control the network topology by estimating node die out rate. Furthermore, a game theory approach with energy efficient zone based routing protocol to improve QoS routing for MANET. Finally, the experimental outcomes proved the efficiency of the proposed algorithm compared with other routing algorithms.

Wireless body area network (WBAN) is the subfield of Wireless Sensor Network, employs in the area of monitoring the health of the patient. WBAN is also known as wireless body sensor network in which sensor nodes are fused inside the body of the person to detect their physiological changes. After processing or comparing those obtained data with the pre-stored default value, the packets are transmitted to the base station. Due to the inner-body sensor node, replacement of the battery may hazardous for the person. So, storing up and saving of energy is the main focus inside the WBANs. In this research, we employ the critical data routing code for transmitting the relevant data from inner-body node to the on-body medical super sensor (MSS) node. Here, MSS act as a controller that can manage all the injected sensor node inside the body of the person as their member. And, if inner-body sensor node is detecting any corporal activities from the human body then it compares those data with the pre-stored threshold level value of that sensor node, and if sensor obtained more deviation in their results then it follows the critical data routing (CDR) for the transmission process, unless it goes to the rest mode. In other words, the sensor node can only be transmitted the critical packet data to their near-by controller and avoiding the redundant picking of normal packet data. By following this procedure we can save the maximum of energy for the sensor so that it alive for the greatest period of time that lead to continuous monitoring of the patient and also maximizes the lifespan of the network. Simulation can be done on MATLAB that can show the finest outcomes in terms of energy spending, network lifespan, throughput- efficiency, hold up by any one of the steering protocol when there is a comparison between CDR, REEC, and SIMPLE respectively.

Wireless sensor networks (WSNs) play a major role in various applications, but the main challenge is to maintain security and balanced energy efficiency. Classical routing protocols struggle to achieve both energy efficiency and security because they are more vulnerable to security risks and resource limitations. This paper introduces QSEER, a novel approach that uses quantum technologies to overcome these limitations. QSEER employs quantum-inspired optimization algorithms that leverage superposition and entanglement principles to efficiently explore multiple routing possibilities, thereby identifying energy-efficient paths and reducing redundant transmissions. The proposed protocol enhances the security of data transmission against eavesdropping and tampering by using the principles of quantum mechanics, thus mitigating potential security vulnerabilities. Through extensive simulations, we demonstrated the effectiveness of QSEER in achieving both security and energy efficiency objectives, which achieves 15.1% lower energy consumption compared to state-of-the-art protocols while maintaining 99.8% data integrity under various attack scenarios, extending network lifetime by an average of 42%. These results position QSEER as a significant advancement for next-generation WSN deployments in critical applications such as environmental monitoring, smart infrastructure, and healthcare systems.