Bidirectional Routing Research Articles

A comprehensive analysis of security mechanism for CSMA/CD Networks: A Survey

In this essay, we examine security against several types of harmful assaults. We also include several known practicable assaults in this. We also learn about secure communication for various mechanisms that offer confidentiality, security, and authentication for the majority of security concerns. An active repeater in CSMA/CD for network comparison for data transfer between two addresses is what we learn about in a logical part. If there is no match, the logic portion instructs the transmitter to switch from broadcasting the data packet to transmitting the clock signal. Bidirectional routing messages are sent from the wireless network to the wired network.At the conclusion, we receive comparison results for the transmitted and received messages to determine if a collision has happened.

The application prospects of robot pose estimation technology: exploring new directions based on YOLOv8-ApexNet.

Service robot technology is increasingly gaining prominence in the field of artificial intelligence. However, persistent limitations continue to impede its widespread implementation. In this regard, human motion pose estimation emerges as a crucial challenge necessary for enhancing the perceptual and decision-making capacities of service robots. This paper introduces a groundbreaking model, YOLOv8-ApexNet, which integrates advanced technologies, including Bidirectional Routing Attention (BRA) and Generalized Feature Pyramid Network (GFPN). BRA facilitates the capture of inter-keypoint correlations within dynamic environments by introducing a bidirectional information propagation mechanism. Furthermore, GFPN adeptly extracts and integrates feature information across different scales, enabling the model to make more precise predictions for targets of various sizes and shapes. Empirical research findings reveal significant performance enhancements of the YOLOv8-ApexNet model across the COCO and MPII datasets. Compared to existing methodologies, the model demonstrates pronounced advantages in keypoint localization accuracy and robustness. The significance of this research lies in providing an efficient and accurate solution tailored for the realm of service robotics, effectively mitigating the deficiencies inherent in current approaches. By bolstering the accuracy of perception and decision-making, our endeavors unequivocally endorse the widespread integration of service robots within practical applications.

BiFormer Attention‐Guided Multiscale Fusion Mask2former Networks for Fish Abnormal Behavior Recognition and Segmentation

To address the issues of accurately identifying and tracking individual fish abnormal behaviors and poor adaptability in the aquaculture field, this paper proposes a Mask2former model combined with a bidirectional routing attention mechanism (BiFormer) and a multiscale dilated attention (MSDA) module for fish abnormal behavior recognition and segmentation. To compensate for the lack of publicly available datasets on fish abnormal behavior, we created the “FISH_segmentation_2023” abnormal behavior dataset, which includes four types of fish behaviors. First, by introducing the BiFormer attention mechanism, the model can better capture critical temporal and spatial information in image sequences, significantly enhancing feature representation. Second, after processing the feature maps with the pixel decoder, the MSDA module is introduced to perform multiscale fusion on these features. The fused features are then passed to the transformer decoder, further enhancing the model’s ability to recognize fish abnormal behaviors. Finally, to further improve model performance and address class imbalance issues in the dataset, we designed a composite loss function combining focal loss and dice loss (FD loss). This loss function can balance the influence of easy and difficult‐to‐classify samples while optimizing segmentation performance, thereby improving the model’s recognition accuracy and mean intersection over union (mIoU) metrics. Experimental results show that the BiFormer multiscale dilated attention FD loss (BMF)‐Mask2former model exhibits high performance, achieving average intersection over union (IoU), accuracy, and recall values of 92.33%, 95.63%, and 94.82%, respectively, on the self‐built FISH_segmentation_2023 dataset, representing improvements of 6.10%, 4.50%, and 5.09%, respectively, compared to the Mask2former model. The study demonstrates that the proposed model can accurately capture both local and contextual features of fish abnormal behaviors through multiscale fusion methods, resulting in high‐quality segmentation outcomes.

Composite acousto-optical modulation.

We propose a composite acousto-optical modulation (AOM) scheme for wide-band, efficient modulation of CW and pulsed lasers. We show that by adjusting the amplitudes and phases of weakly-driven daughter AOMs, diffraction beyond the Bragg condition can be achieved with exceptional efficiencies. Furthermore, by imaging pairs of AOMs with opposite directions of sound-wave propagation, high contrast switching of output orders can be achieved at the driving radio frequency (rf) limit, thereby enabling efficient bidirectional routing of a synchronized mode-locked laser. Here we demonstrate a simplest example of such scheme with a double-AOM setup for efficient diffraction across an octave of rf bandwidth, and for routing a mode-locked pulse train with up to frep = 400 MHz repetition rate. We discuss extension of the composite scheme toward multi-path routing and time-domain multiplexing, so as to individually shape each pulses of ultrafast lasers for novel quantum control applications.

Fuzzy-Constrained Graph Pattern Matching in Medical Knowledge Graphs

Abstract The research on graph pattern matching (GPM) has attracted a lot of attention. However, most of the research has focused on complex networks, and there are few researches on GPM in the medical field. Hence, with GPM this paper is to make a breast cancer-oriented diagnosis before the surgery. Technically, this paper has firstly made a new definition of GPM, aiming to explore the GPM in the medical field, especially in Medical Knowledge Graphs (MKGs). Then, in the specific matching process, this paper introduces fuzzy calculation, and proposes a multi-threaded bidirectional routing exploration (M-TBRE) algorithm based on depth first search and a two-way routing matching algorithm based on multi-threading. In addition, fuzzy constraints are introduced in the M-TBRE algorithm, which leads to the Fuzzy-M-TBRE algorithm. The experimental results on the two datasets show that compared with existing algorithms, our proposed algorithm is more efficient and effective.

Minimum dose path planning based on three-degree vertex algorithm and FLUKA modeling: Radiation source discrimination and shielding considerations

Minimum dose path planning in radioactive environments has received significant attention because workers need to be protected from undue radiation risks. The conventional approaches use the innovative shortest path algorithms to search for the optimal path. However, the methods are limited in complex geometries, large navigation space, and when shielding is considered. Also, the traditional approaches lack source discrimination capability (multiple sources terms, type of radiation, and size of source). This study presents a novel application of the Three-Degree of Vertex (TDV) shortest path algorithm with FLUKA Monte Carlo modeling for optimal protection of workers in radioactive environments. TDV algorithm solves the shortest path problem with bidirectional routing in complex environments. The implementation considers multiple radiation sources with diverse geometry and characteristics such as different radiation types. The current work also presents the algorithm performance with shielding consideration and complex geometry. The merits of the TDV are also evaluated in real scenarios using accuracy, reliability, and speed as evaluation metrics. In addition, the performance of the TDV is also compared with the Dijkstra algorithm for all scenarios considered.

A Multigrid Dynamic Bidirectional Coupled Surface Flow Routing Model for Flood Simulation

Surface flow routing is an important component in hydrologic and hydrodynamic research. Based on a literature review and comparing the different coupling models (the hydrologic model and hydrodynamic model), a multigrid dynamic bidirectional coupled surface flow routing model (M-DBCM), consisting of diffusion wave equations (DWEs) and shallow water equations (SWEs), is proposed herein based on grids with different resolutions. DWEs were applied to obtain runoff routing in coarse grid regions to improve the computational efficiency, while the DWEs and SWEs were bidirectionally coupled to detail the flood dynamics in fine grid regions to obtain good accuracy. In fine grid zones, the DWEs and SWEs were connected by an internal moving boundary, which ensured the conservation of mass and momentum through the internal moving boundary. The DWEs and SWEs were solved by using the time explicit scheme, and different time steps were adopted in regions with different grid sizes. The proposed M-DBCM was validated via three cases, and the results showed that the M-DBCM can effectively simulate the process of surface flow routing, which had reliable computational efficiency while maintaining satisfactory simulation accuracy. The rainfall runoff in the Goodwin Creek Watershed was simulated based on the proposed M-DBCM. The results showed that the discharge hydrographs simulated by the M-DBCM were closer to the measured data, and the simulation results were more realistic and reliable, which will be useful in assisting flood mitigation and management.

Robust triple extraction with cascade bidirectional capsule network

Recent approaches have witnessed the success of neural models for triple extraction. However, we empirically observe that previous approaches may fail for those disambiguate text expressed in a similar context and generate triples that contradict the commonsense. Such issues severely hinder the generalization of triple extraction in real-world applications. Motivated by the capsule networks’ power of modeling latent structures and the implicit entity-relation schema, we propose a novel Cascade Bidirectional Capsule Network (CBCapsule) to address those issues. We firstly introduce a cascade capsule network to dynamically aggregate context representations and then propose a bidirectional routing mechanism to encourage interaction between the high level (e.g., relations) and low level (e.g., entities) capsules. Experimental results on three benchmarks show that our proposed approach is more efficient than baselines and has a more robust generalization ability with complex surface forms.

BDARS_CapsNet: Bi-Directional Attention Routing Sausage Capsule Network

In order to improve the accuracy of capsule network in disentangled representation, and further expand its application in computer vision, a novel BDARS_CapsNet (bi-directional attention routing sausage capsule network) architecture is proposed in this paper. Firstly, the bi-directional routing, namely bottom-up and top-down attention is used to achieve information feed-forward and feedback mechanism, which contributes to describing the attributes of object entity more accurately and completely. Secondly, inspired by the concept of covering learning, the sausage measure model is introduced into the network. The sausage model measures both the similarities and differences of the capsules and projects them into a more complex curved surface, which makes it possible to approximate any nonlinear function with arbitrary precision and preserving the local responsiveness of capsule entity to the maximum. Finally, the BDARS_CapsNet combines the CNN (Convolutional Neural Network), bi-directional attention routing, and sausage measure into capsule network modeling, and makes full use of high-level category information and low-level vision information; as a result, the reconstruction and classification accuracy is accordingly improved. Experiments demonstrate the effectiveness of proposed information routing, sausage measure, and new framework. Furthermore, the proposed BDARS_CapsNet provides a foundation for future research on disentangled representation learning.

Solving the collaborative bidirectional multi-period vehicle routing problems under a profit-sharing agreement using a covering model

Solving the collaborative bidirectional multi-period vehicle routing problems under a profit-sharing agreement using a covering model

Matrix: Multihop Address allocation and dynamic any-To-any Routing for 6LoWPAN

Standard routing protocols for IPv6 over Low power Wireless Personal Area Networks (6LoWPAN) are mainly designed for data collection applications and work by establishing a tree-based network topology, enables packets to be sent upwards, from the leaves to the root, adapting to dynamics of low-power communication links. In this work, we propose Matrix, a platform-independent routing protocol that utilizes the existing tree structure of the network to enable reliable and efficient any-to-any data traffic in 6LoWPAN. Matrix uses hierarchical IPv6 address assignment to optimize routing table size while preserving bidirectional routing. Moreover, it uses a local broadcast mechanism to forward messages to the right subtree when a persistent node or link failures occur. We implemented Matrix on TinyOS and evaluated its performance both analytically and through simulations on TOSSIM. Our results showed that the proposed protocol is superior to available protocols for 6LoWPAN when it comes to any-to-any data communication, concerning reliability, message efficiency, and memory footprint.

Use ’em or lose ’em: On unidirectional links in reactive routing protocols

In reactive unicast routing protocols, Route Discovery aims to include only bidirectional links in discovered routing paths. This is typically accomplished by having routers maintain a “blacklist” of links recently confirmed (through Route Reply processing) to be unidirectional – which is then used for excluding subsequent Route Discovery control messages received over these links from being processed and forwarded.This paper first presents an analytical model, which allows to study the impact of unidirectional links being present in a network, on the performance of reactive routing protocols. Next, this paper identifies that despite the use of a “blacklist”, the Route Discovery process may result in discovery of false forward routes, i.e.,routes containing unidirectional links – and proposes a counter-measure denoted Forward Bidirectionality Check. This paper further proposes a Loop Exploration mechanism, allowing to properly include unidirectional links in a discovered routing topology – with the goal of providing bidirectional connectivity even in absence of bidirectional paths in the network.Finally, each of these proposed mechanisms are subjected to extensive network simulations in static scenarios. When the fraction of unidirectional links is moderate (15–50%), simulations find Forward Bidirectionality Check to significantly increase the probability that bidirectional routing paths can be discovered by a reactive routing protocol, while incurring only an insignificant additional overhead. Further, in networks with a significant fraction of unidirectional links ( ≥ 50%), simulations reveal that Loop Exploration preserves the ability of a reactive routing protocol to establish bidirectional communication (possibly through non-bidirectional paths), but at the expense of a substantial additional overhead.

Modified Bi-directional Routing with Best Afford Path (MBRBAP) for Routing Optimization in MANET

A Mobile Adhoc NETwork (MANET) is an independent wireless network in which mobile nodes can communicate with each other by forwarding the packets without support of any infrastructure. Since it is a dynamic mobile network, it cannot assure seamless packet transmission between the mobile nodes; making the open network vulnerable to various malicious attacks. MANET uses acknowledgement based schemes, for the assurance of packet transmission by overriding the malicious attacks. Since most of the existing intrusion detection systems (IDS) use two hop information for acknowledging the packets, flooding over multiple outgoing paths and acknowledgement (ACK) overhead occurs when transmitted over a long distance and finally it doesn’t have any prevention system to solve the malicious attacks. In this paper, Modified Bi-directional Routing Abstraction method is proposed to resolve these problems by reducing the ACK overhead and eliminating the malicious attacks. The Best Afford Path using cluster heads is embraced with the proposed technique which utilizes the maximum bandwidth to transfer the packets by routing the nodes around clockwise and anticlockwise routing procedures that detects and overcomes the malicious attacks with an IDS/IPS coupled mechanism. This technique utilizes the cluster heads that are used to get the ACK from the cluster nodes when the packets are sent through it. The proposed technique reduces the ACK overhead, eliminates the malicious attack, increases the bandwidth utilization and improves the delivery of packet with minimum delay compared with the existing schemes.

Design, Implementation, and Performance Evaluation of Efficient PMIPv6 Based Mobile Multicast Sender Support Schemes

Proxy Mobile IPv6 (PMIPv6) is proposed as a promising network-based mobility management protocol, which does not need any participation of mobile nodes. PMIPv6 does not support the multicast well and most of the current research concentrates on the mobile multicast receiver. However, the mobile multicast sender is also very important and challenging, which has not been addressed well. Therefore, in this paper we propose two efficient PMIPv6 based mobile multicast sender support schemes which are PMIP bidirectional tunneling (PMIP-BT) and PMIP direct routing (PMIP-DR). In the PMIP-BT, the multicast traffic can be delivered through the PMIPv6 bidirectional tunnel, while, in the PMIP-DR, the multicast data can be transmitted via an optimized direct multicast routing. Both of them can support the multicast sender mobility transparently enabled in the PMIPv6 networks. We evaluate the performance of the proposed schemes by theoretical analysis, and the numerical results show that the proposed schemes have a better performance in terms of the signaling cost than the current schemes. Meanwhile, the proposed schemes are also implemented on the test bed, and the experimental results not only verify the validity and feasibility of our proposed schemes, but also conclude the different scenarios to which they are applicable.

A Cross-layer Energy-efficient Bidirectional Gradient Routing Algorithm for Wireless Sensor Networks

A Cross-layer Energy-efficient Bidirectional Gradient Routing Algorithm for Wireless Sensor Networks

Research of Routing Protocol for Wireless Meter Reading System

To improve the data transmission reliability of wireless meter reading system, a bidirectional routing algorithm is proposed. The routing algorithm is developed to make all nodes in the network establish optimal routing and register a complete neighbor table for routing maintenance. The neighbor exchange mechanism based on Hello Packet can timely detect changes in network topology and solve the problem of nodes flexibly coming in or out of the network. Simulation and system testing have all verified the reliability and usefulness of the algorithm which can satisfy the need of wireless meter reading application.

BHAR: a bidirectional hierarchy-based anycast routing protocol for wireless sensor networks

This paper presents a bidirectional hierarchy-based anycast routing (BHAR) protocol to facilitate data collection in multi-hop wireless sensor networks (WSNs). In contrast to existing HAR mechanisms (Thepvilojanapong et al., 2005), the proposed BHAR is able to prolong network lifetime as it constructs hierarchical trees and repairs routes faster. BHAR is unique in letting sinks and sources initialise the construction of a hierarchical tree. Whenever a node knows its own parent and neighbour nodes, it can join a tree, exchange/refresh the routing table, and perform route repair without the aid of geographical information or being controlled remotely. As simulation results have demonstrated, such a design makes BHAR a faster and better protocol in constructing trees and repairing routes than HAR.

An Improved Resource Query and Location Algorithm Based on Cloud Computing

With the continuous development of cloud computing applications, the problems of cloud computing are more and more obvious, such as the lower efficiency of resource search, the lack of network scalability, and some difficulties in management. In this paper, the problems of P2P network and the structural characteristics of the IS-P2P network are studied. On the basis of traditional Chord algorithm, the improvement of the speed of search is made. BiChord: a resource locator and query algorithm based on cloud computing is put forward. The bidirectional routing tables FingerTable and RefingerTable are designed by this algorithm, which adopts the query strategy of bidirectional location of keywords. In addition, the paper also proposes XP query: a message query mechanism based on the structure of the cloud computing. Simulation results show that BiChord has better routing performance than traditional Chord algorithm and the message query mechanism also improves the efficiency of resource queries. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3356

Design and Verification of a "Soft" eFPGA Using New Method

A novel design methodology for soft eFPGA is proposed. In comparison with the previous soft core design approach, a structured-description strategy is applied and the process of logic synthesis is bypassed in the new design flow. Thus, the capability of processing the bidirectional routing architectures of the mainstream eFPGAs is obtained, while the conventional soft core design method could only handle the eFPGA with directional routing structure. Moreover, the experiment result shows eFPGA designed with this new method is 2 times denser than that designed with the conventional method. To verify this method, a proof-of-concept eFPGA prototype is designed and also presented.

ProHet: A Probabilistic Routing Protocol with Assured Delivery Rate in Wireless Heterogeneous Sensor Networks

Due to different requirements in applications, sensors with different capacities are deployed. How to design efficient, reliable and scalable routing protocols in such wireless heterogeneous sensor networks (WHSNs) with intermittent asymmetric links is a challenging task. In this paper, we propose ProHet: a distributed probabilistic routing protocol for WHSNs that utilizes asymmetric links to reach assured delivery rate with low overhead. The ProHet protocol first produces a bidirectional routing abstraction by finding a reverse path for every asymmetric link. Then, it uses a probabilistic strategy to choose forwarding nodes based on historical statistics using local information. Analysis shows that ProHet can achieve assured delivery rate ρ if ρ is set within its upper-bound. Extensive simulations are conducted to verify its efficiency.