Reliable Data Routing Research Articles

Q-RPL: Q-Learning-Based Routing Protocol for Advanced Metering Infrastructure in Smart Grids.

Efficient and reliable data routing is critical in Advanced Metering Infrastructure (AMI) within Smart Grids, dictating the overall network performance and resilience. This paper introduces Q-RPL, a novel Q-learning-based Routing Protocol designed to enhance routing decisions in AMI deployments based on wireless mesh technologies. Q-RPL leverages the principles of Reinforcement Learning (RL) to dynamically select optimal next-hop forwarding candidates, adapting to changing network conditions. The protocol operates on top of the standard IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL), integrating it with intelligent decision-making capabilities. Through extensive simulations carried out in real map scenarios, Q-RPL demonstrates a significant improvement in key performance metrics such as packet delivery ratio, end-to-end delay, and compliant factor compared to the standard RPL implementation and other benchmark algorithms found in the literature. The adaptability and robustness of Q-RPL mark a significant advancement in the evolution of routing protocols for Smart Grid AMI, promising enhanced efficiency and reliability for future intelligent energy systems. The findings of this study also underscore the potential of Reinforcement Learning to improve networking protocols.

Z number improved reference ideal method‐based decision‐making process for enforcing cooperation during data dissemination in mobile ad hoc networks

SummaryIn mobile ad hoc networks (MANETs), cooperative communication and resource constraint are the two important core characteristics essential to guarantee trusted data dissemination. The cooperative communication between mobile nodes depends on the trust rendered by them towards the process of reliable data routing. However, stringent resource constraints of mobile nodes such as energy, memory, communications, and computations result in the introduction of selfish and malicious node that completely degrades the network performance in different dimensions. In this paper, Z number improved reference ideal method (RIM)‐based decision‐making process (NIRIMDMP) is proposed with the merits of maximizing deviation method (MDM) and best–worst method (BWM) to ensure reliable data routing by modeling the cooperation degree in terms of Z number. This NIRIMDMP adopted Z number to represent the information reliability and handle the problem of inherent uncertainty during the process of evaluating each mobile node in the routing process. In specific, MDM and BWM are included into the proposed NIRIMDMP to determine comprehensive attribute weights based on the calculated objective and subjective weights that could be possible derived in routing. It extended the merits of classical RIM using Z numbers to confirm reliable ranking of mobile nodes, even when the optimal solution exists amid extreme values taken into consideration for assessing the mobile nodes during decision making. Simulation investigations of the proposed NIRIMDMP confirmed improved throughput and network lifetime with reduced control overhead, energy consumptions, and delay independent of the amount of malicious and non‐cooperative nodes.

A reliable routing mechanism with energy-efficient node selection for data transmission using a genetic algorithm in wireless sensor network

Energy-efficient and reliable data routing is critical in Wireless Sensor Networks (WSNs) application scenarios. Due to oscillations in wireless links in adverse environmental conditions, sensed data may not be sent to a sink node. As a result of wireless connectivity fluctuations, packet loss may occur. However, retransmission-based approaches are used to improve reliable data delivery. These approaches need a high quantity of data transfers for reliable data collection. Energy usage and packet delivery delays increase as a result of an increase in data transmissions. An energy-efficient data collection approach based on a genetic algorithm has been suggested in this paper to determine the most energy-efficient and reliable data routing in wireless sensor networks. The proposed algorithm reduced the number of data transmissions, energy consumption, and delay in network packet delivery. However, increased network lifetime. Furthermore, simulation results demonstrated the efficacy of the proposed method, considering the parameters energy consumption, network lifetime, number of data transmissions, and average delivery delay.

A classy energy efficient spider monkey optimization based clustering and data aggregation models for wireless sensor network

SUMMARYEstablishment of energy efficient and reliable data routing in wireless sensor network (WSN) is one of the most critical and challenging task in the recent days. Also, the overall performance and lifetime of WSN is highly depends on the energy level of sensor nodes, hence it is most essential to save the energy of network. For this purpose, the different types of clustering and data aggregation mechanisms are developed in the conventional works, which are focusing on improving both the energy conservation and lifetime of network. Yet, it facing the challenges of increased computational complexity, inefficient routing of data, high controlling overhead, and reduced reliability. Thus, the proposed work objects to develop a novel energy efficient mechanism by integrating the functionalities of advanced clustering, path selection, and data aggregation methodologies. Here, the spider monkey optimization based energy efficient routing protocol is developed for optimally selecting the cluster head (CH) based on certain parameters of energy, distance, and weight value. In this framework, the data transmission is performed between the source to destination nodes through the relay nodes and CHs, which helps to minimize the energy consumption of network. Then, the Classy Bellman‐Ford algorithm is deployed for identifying the best paths having shortest distance with the sink nodes. Consequently, an anticipated data aggregation mechanism is utilized for ensuring the security and reliability of data transmission in WSN. For evaluation assessment, various performance metrics have been utilized to validate the results of proposed methodology, and also the obtained values are compared with some other recent state‐of‐the‐art models for proving the betterment of proposed mechanism.

An Efficient Multipath Routing Protocol for Decentralized Wireless Sensor Networks for Mission and Safety-Critical Systems

Background: Wireless Sensor Network (WSN) is a useful integral part of mission and safety-critical systems, whose failure may result in injury, loss of life, serious environmental damage and/or may result in the failure of some goal-directed activities. Its major challenges are reliability, and security related issues during data delivery. To mitigate these, the development of secure routing protocols, which are capable of optimum utilization of WSNs’ nodes resources for effective data delivery, has been one of the major research interests. However, most of the existing single path routing protocols for WSNs are not able to meet with up with the performance requirements of the mission and safety-critical systems. Meanwhile, a few that are multipath require high computational power, energy and their multiple paths are not ranked, this makes them unsuitable as routing protocol for WSNs in mission and safety-critical systems. Objective: In this work, we propose a secure multipath routing protocol based on sectorisation and best neighbouring nodes selection models to meet up with the performance requirements of WSNs in the mission and safety-critical systems. The protocol is capable of providing optimal multiple ranked route paths for reliable data delivery. Methods: A route management technique, using direct approach, is developed for selecting different optimal data paths for reliable data routing. Also, simple but efficient lightweight privacy preserving authentication scheme is proposed for the protocol to ensure security and privacy during data routing. Computational and security analysis were performed to ascertain its efficiency in terms of computational cost, energy consumption and security. Results: The results showed that SMRP achieved better performance compared to the two stateof- the-art solutions in terms of end-to-end delay, energy consumption and data routing reliability. Conclusion: The proposed protocol is suitable for wireless sensor network due to its low delay, low energy consumption and routing reliability metrics.

V2VR: Reliable Hybrid-Network-Oriented V2V Data Transmission and Routing Considering RSUs and Connectivity Probability

Vehicular ad hoc networks (VANETs) have been widely used in intelligent transportation systems (ITSs) for purposes such as the control of unmanned aerial vehicles (UAVs) and trajectory prediction. However, an efficient and reliable data routing decision scheme is critical for VANETs due to the feature of self-organizing wireless multi-hop communication. Compared with wireless networks, which are unstable and have limited bandwidth, wired networks normally provide longer transmission distances, higher network speeds and greater reliability. To address this problem, this paper proposes a reliable VANET routing decision scheme based on the Manhattan mobility model, which considers the integration of roadside units (RSUs) into wireless and wired modes for data transmission and routing optimization. First, the problems of frequently moving vehicles and network connectivity are analyzed based on road networks and the motion information of vehicle nodes. Second, an improved greedy algorithm for vehicle wireless communication is used for network optimization, and a wired RSU network is also applied. In addition, routing decision analysis is carried out in accordance with the probabilistic model for various transmission ranges by checking the connectivity among vehicles and RSUs. Finally, comprehensive experiments show that our proposed method can support real-time planning and improve network transmission performance compared with other baseline protocol approaches in terms of several metrics, including package delivery ratio, time delay and wireless hops.

Mobility and energy prediction models: Approach toward effective route management in mobile wireless sensor networks

AbstractMobile wireless sensor network (MWSN), as a backbone of most communication and embedded systems, is characterized by low data delivery as a result of the energy constraint and in‐deterministic movement of the nodes. To select optimal route path for a reliable data routing, protocols need to select neighbouring nodes with low mobility and residual energy parameters along the route. However, obtaining these parameters from the targeted nodes may encourage mischievous nodes to manipulate their energy and mobility parameters in their favor, leading to the selection of non‐optimal route path and/or exposing the network to other attacks. Rather than depending on the targeted nodes for these parameters, they can be accurately and securely obtained by sink node or base station using effective predictive models. However, most of the existing predictive models engaged by MWSN routing protocols either provide only the energy level or mobility factor of the nodes for optimal route path selection. This, therefore, reduces the reliability of the obtained optimal route paths in terms of data delivery. In this article, we propose predictive models for an accurate prediction of mobility and residual energy parameters of nodes in MWSN for efficient route management. The models are simulated on an existing MWSN protocol to determine their performance. The simulation results show that the adoption of these models in the development of routing protocol will not only lead to optimal route paths' selection but also enhance data delivery rate in MWSN.

Efficient parent selection for RPL using ACO and coverage based dynamic trickle techniques

Routing protocol for low-power and lossy networks (RPL) plays a vital role in the architecture of the IoT. The RPL follows the trickle algorithm and the distance based parent node selection. The trickle algorithm establishes a destination oriented directed acyclic graph (DODAG) with suppressed broadcasting. The broadcast suppression lacks in handling network coverage and load imbalance issues under the nonuniform node distribution. In addition, the DODAG construction exclusively depending on a single routing metric to identify an energy efficient and reliable routing paths. This article proposes an energy efficient RPL (E-RPL) protocol that consists of ACO based multi-factor optimization for parent selection and coverage based dynamic trickle algorithm for energy efficient DODAG construction without compromising network coverage and reliable data routing. The ACO considers the expected transmission count (ETX) and rank value as pheromone factors, whereas the residual energy and children count as heuristic factors. To balance the conflicting factors of ETX, rank, delay, and energy consumption, the E-RPL exploits the parent–child relationship factor as a pheromone evaporation factor. Moreover, the weight based algorithm is utilized to combine pheromone, heuristic, and pheromone evaporation factors towards a single objective function. To build an optimal DODAG structure with a reduced routing overhead, the E-RPL introduces concentric corona based network partition and decides the value of broadcast count dynamically concerning the node density and coverage. Finally, the performance of E-RPL is evaluated using Cooja simulator. The E-RPL attains 90% of the packet delivery ratio while spending 0.532 mJ over 30 node topology.

Congestion Control Techniques in WSNs: A Review

Congestion control has a great importance in wireless sensor network (WSN), where efficient application of congestion control mechanisms can prolong the network lifetime. Thus, proper examination is needed to improve more refine way to address the congestion occurrence and resolution. While designing congestion control techniques, the maximum output can be achieved by efficient utilization of required resources within WSN. From last few years several approaches have been brought in, that consist of routing protocols which provide support with congestion control, congestion prevention, and reliable data routing. In old schemes the topology reset and extent traffic drop take place because sink node executes the congestion avoidance. Therefore, node level congestion avoidance, detection, congestion preventing, and resolution mechanisms have been proposed during past few years. Our paper provides a brief overview and performance comparison of centralized and distributed congestion control algorithms in WSN.

A Topology Control Strategy with Reliability Assurance for Satellite Cluster Networks in Earth Observation.

This article investigates the dynamic topology control problem of satellite cluster networks (SCNs) in Earth observation (EO) missions by applying a novel metric of stability for inter-satellite links (ISLs). The properties of the periodicity and predictability of satellites’ relative position are involved in the link cost metric which is to give a selection criterion for choosing the most reliable data routing paths. Also, a cooperative work model with reliability is proposed for the situation of emergency EO missions. Based on the link cost metric and the proposed reliability model, a reliability assurance topology control algorithm and its corresponding dynamic topology control (RAT) strategy are established to maximize the stability of data transmission in the SCNs. The SCNs scenario is tested through some numeric simulations of the topology stability of average topology lifetime and average packet loss rate. Simulation results show that the proposed reliable strategy applied in SCNs significantly improves the data transmission performance and prolongs the average topology lifetime.

A P2P-Based Market-Guided Distributed Routing Mechanism for High-Throughput Hybrid Wireless Networks

In a hybrid wireless network that combines a mobile ad-hoc network and an infrastructure network, efficient and reliable data routing is important for high throughput. Existing routing schemes that simply combine ad-hoc and infrastructure routings inherit the drawbacks of ad-hoc routing including congestion and high overhead for route discovery and maintenance. Although current reputation systems help increase routing reliability, they rely on local information exchanges between nodes to evaluate node reputations, so they are not sufficiently effective and efficient. A challenge here is if we can coordinately develop an efficient routing algorithm and effective cooperation incentives for reliable routing. To handle this challenge, this paper presents a peer-to-peer (P2P)-based Market-guided Distributed Routing mechanism (MDR). MDR takes advantage of widespread base stations to coordinately realize highly efficient data routing, and effective reputation management and trading market management for reliable data routing. The packets from a source node are distributively transmitted to base stations directly or indirectly, and then they are transmitted to the destination. The base stations form a P2P structure for reputation collection and querying to avoid local information exchanges, and for managing the service transactions between nodes in the trading market. By leveraging the single-relay transmission feature, base stations can monitor the actual transmitted packets of relay nodes to more accurately and efficiently evaluate their reputations and execute trading market management, as well as detect falsely reported reputation information. We further propose market-based policies to strengthen cooperation incentives. Simulation results show that MDR outperforms the traditional hybrid routing schemes and reputation systems in achieving high throughput.

Cognitive routing for multi-hop mobile cognitive radio ad hoc networks

Mobility can lead to continual loss of data and service interruptions during communications in multi-hop cognitive radio networks. Mobility of primary users (PUs) or cognitive users (CUs) requires adjustment of multi-hop communications among CUs to avoid any interference to PUs. To provide durable and reliable data routing that ensures continuous network service, we propose mobility-aware cognitive routing (MCR) for multi-hop cognitive radio networks. MCR examines the risk level of each node against interference regions and selects the most reliable path for data delivery using a Markov predictor. Through simulation, we verify that the proposed scheme can avoid route destruction preemptively and achieve reliable data delivery.