Low Routing Delay Research Articles

BMUDF: Hybrid Bio-inspired Model for fault-aware UAV routing using Destination-aware Fan shaped clustering

Routing data between unmanned aerial vehicles (UAVs) involves identifying node locations, analyzing residual energy levels, evaluating temporal throughput and packet delivery performance, and identifying other network and node parameters. It assists in forming quality of service (QoS) aware routes. Existing routing models require large data samples to find the optimized path or are highly complex, increasing their computational requirements. Low-complexity models showcase low-performance routing QoS when deployed on large-scale networks. To solve these limitations, a hybrid bioinspired model is proposed for fault-aware UAV routing that uses destination awareness with a fan-shaped clustering process (BMUDF). The model initially collects data from different UAV nodes and their node-level and network-level constraints. These parameters are processed through the particle swarm optimization (PSO) model, which enforces fan-shaped clustering (FSC) for effective routing operations. Our scheme uses the PSO model to identify the initial routing paths cascaded with a genetic algorithm (GA) based destination-aware routing model. These routing paths are evaluated through the QoS matrices like maximum temporal throughput, packet delivery ratio (PDR), delay, and energy consumption. A grey wolf optimization (GWO) model further scrutinizes this routing performance, integrating fault tolerance and route optimization during continuous operations. The GWO model evaluates a trust-based fitness function, which helps to identify faulty nodes, and reconfigures the network with non-faulty nodes to improve its QoS performance under node failures and faults. Integrating the bioinspired models into the proposed system maximizes performance under different network scenarios. This performance compares and validated with an analysis of variance (ANOVA) test with various state-of-the-art models. It is observed that the proposed model showcased an 8.3% lower routing delay, 5.9% lower energy consumption, 1.5% higher packet delivery ratio, and 9.1% higher throughput, which makes it useful for a wide variety of real-time UAV routing scenarios.

A New Deep Q-Network Design for QoS Multicast Routing in Cognitive Radio MANETs

In this paper, we propose a new deep Q-network (DQN) design for quality-of-service (QoS) multicast routing (DQMR) protocol to establish efficient QoS multicast (EQM) trees in cognitive radio mobile ad hoc networks (CR-MANETs). An EQM tree is a shortest-path multicast tree with minimum end-to-end (E2E) cost (a combination of queuing size ratio and link stability) subject to QoS constraints such as queuing size ratio, link stability, number of hops, number of time slots and avoiding the licensed channel of primary users. Particularly, we propose an NP-complete optimization problem such that its feasible solution is an EQM tree. To address this problem, we design a new DQN model and a new game-based model to form EQM trees in real-time by offline training instead of online training as done in previous papers. Moreover, the DQMR protocol is also guaranteed to have high stability, low routing delay, low control overhead, and high packet delivery ratio (PDR). Furthermore, one more new contribution of the paper is that exact closed-form expressions for the E2E queuing delay of a multicast routing tree are also derived assuming random waypoint mobility and the reference point group mobility models to compare with simulation results of routing delay. Simulation results show that the DQMR protocol outperforms multicast ad hoc on-demand distance vector routing protocol in terms of routing delay, control overhead, and PDR.

6CN‐driven routing and content delivery scheme for building the smart physical education

The development of smart physical education is subject to the large transmission delay from providers to consumers due to the large‐scale and cross‐domain network deployment. In this letter, we propose 6CNRD, a novel system framework based on IPv6 Content Networking (6CN) to facilitate the building of smart physical education. 6CNRD consists of two parts, that is, one is the content request stage based on segment routing, and the other one is the content delivery stage based on identity forwarding. We compare 6CNRD with two cutting‐edge schemes over a constructed physical education topology, and the experimental results show that 6CNRD has lower routing delay and delivery delay. It further indicates that 6CNRD has the wide application value including but not limited to the field of smart physical education.

Delay Tolerance in Wireless Networks through Optimal Path Routing Algorithm

A Delay Tolerant Network (DTN) is a mesh network designed to operate effectively over great distances. DTNs have not custom to vindicate complete track from source to destination most of the time during communication. Existing data routing approaches used in DTNs were based on multi-copy routing. However, these existing methods incur overhead due to exorbitant transmissions and increases seer side processing. Hence there is a necessity to propose an optimal path routing algorithm to overcome the above issues. The optimal path routing reduces the proposition of message dropping and wax the throughput. The design approximate also uses random path generation that can reveal the path that affirms active connection for a longer duration to achieve a desired routing delay. In addition, this system has an effective buffer management mechanism to increase throughput and decrease routing delay. The analysis and as well as the simulation results clearly shows that the optimal path routing algorithm, provides high throughput and low routing delay compared to existing routing approaches.

SEDUM: Exploiting Social Networks in Utility--Based Distributed Routing for DTNs

This work focuses on Delay Tolerant Networks (DTNs) in a social network environment. DTNs do not have a complete path from a source to a destination most of the time. Previous data routing approaches in DTNs are primarily based on either flooding or single-copy routing. However, these methods incur either high overhead due to excessive transmissions or long delays due to suboptimal choices for relay nodes. Probabilistic forwarding that forwards a message to a node with a higher delivery utility enhances single-copy routing. However, current probabilistic forwarding methods only consider node contact frequency in calculating the utility while neglecting the influence of contact duration on the throughput, though both contact frequency and contact duration reflect the node movement pattern in a social network. In this paper, we theoretically prove that considering both factors leads to higher throughput than considering only contact frequency. To fully exploit a social network for high throughput and low routing delay, we propose a Social network oriented and duration utility-based distributed multicopy routing protocol (SEDUM) for DTNs. SEDUM is distinguished by three features. First, it considers both contact frequency and duration in node movement patterns of social networks. Second, it uses multicopy routing and can discover the minimum number of copies of a message to achieve a desired routing delay. Third, it has an effective buffer management mechanism to increase throughput and decrease routing delay. Theoretical analysis and simulation results show that SEDUM provides high throughput and low routing delay compared to existing routing approaches. The results conform to our expectation that considering both contact frequency and duration for delivery utility in routing can achieve higher throughput than considering only contact frequency, especially in a highly dynamic environment with large routing messages.

FSR Evaluation Using the Suboptimal Operational Values

In mobile ad-hoc networks, routing protocols are becoming more complicated and problematic. Routing in mobile ad-hoc networks is multihop because of the limited communication range of wireless radios. Since nodes in the network can move freely and randomly, an efficient routing protocol is needed for such networks to be able to perform well in such an environment. In this environment, the routing strategy is applied such that it is flexible enough to handle large populations and mobility and is able to minimize the use of the battery. Also it should be designed to achieve maximum packet delivery ratio. Furthermore, the routing protocol must perform well in terms of fast convergence, low routing delay, and low control overhead traffic. In this article, an improved implementation of the fisheye state routing (FSR) protocols is presented, where a new selection routing criteria that utilizes a minimum number of hops is a selection metric. The results obtained from simulation indicate that the fewer number of hops used, the better and more efficient the output for packet delivery ratio was generated