Showing papers on "Equal-cost multi-path routing published in 2022"

Implementation of Reliability Antecedent Forwarding Technique Using Straddling Path Recovery in Manet

Abstract: In a mobile ad hoc network, packets are lost by interference occurrence in the communication path because there is no backup information for the previous routing process. The communication failure is not efficiently identified. Node protection rate is reduced by the interference that occurs during communication time. So, the proposed reliability antecedent packet forwarding (RAF) technique is applied to approve the reliable routing from the source node to the destination node. The flooding nodes are avoided by this method; the previous routing information is backed up; this backup information is retrieved if any interference occurred in the communication period. To monitor the packet flow rate of every node, the straddling path recovery algorithm is designed to provide an interference free-routing path. This path has more number of nodes to proceed with communication. These nodes have a higher resource level and also used to back up the forwarded data; since sometimes routing breakdowns occurred, data are lost, which is overcome by using a backup process. It improves the network lifetime and reduces the packet loss rate.

Implementation of Hidden Node Detection Scheme for Self-Organization of Data Packet

Abstract: The mobile nodes are infrequent movement in nature; therefore, its packet transmission is also infrequent. Packet overload occurred for routing process, and data are lossed by receiver node, since hackers hide the normal routing node. Basically, the hidden node problem is created based on the malicious nodes that are planned to hide the vital relay node in the specific routing path. The packet transmission loss occurred for routing; so, it minimizes the packet delivery ratio and network lifetime. Then, proposed enhanced self-organization of data packet (EAOD) mechanism is planned to aggregate the data packet sequencially from network structure. The hacker node present in routing path is easy to separate from network with trusty nodes. In order to secure the regular characteristics of organizer node from being confirmed as misbehaving node, the hidden node detection technique is designed for abnormal routing node identification. This algorithm checks the neighboring nodes that are hacker node, which hide the trust node in the routing path. And that trust nodes are initially found based on strength value of every node and assign path immediately. It increases network lifetime and minimizes the packet loss rate.

Proportional Fairness Based Energy Efficient Routing in Wireless Sensor Network

Abstract: Wireless Sensor Network (WSN) is an independent device that comprises a discrete collection of Sensor Nodes (SN) to sense environmental positions, device monitoring, and collection of information. Due to limited energy resources available at SN, the primary issue is to present an energy-efficient framework and conserve the energy while constructing a route path along with each sensor node. However, many energy-efficient techniques focused drastically on energy harvesting and reduced energy consumption but failed to support energy-efficient routing with minimal energy consumption in WSN. This paper presents an energy-efficient routing system called Energy-aware Proportional Fairness Multi-user Routing (EPFMR) framework in WSN. EPFMR is deployed in the WSN environment using the instance time. The request time sent for the route discovery is the foremost step designed in the EPFMR framework to reduce the energy consumption rate. The proportional fairness routing in WSN selects the best route path for the packet flow based on the relationship between the periods of requests between different SN. Route path discovered for packet flow also measure energy on multi-user route path using the Greedy Instance Fair Method (GIFM). The GIFM in EPFMR develops node dependent energy-efficient localized route path, improving the throughput. The energy-aware framework maximizes the throughput rate and performs experimental evaluation on factors such as energy consumption rate during routing, Throughput, RST, node density and average energy per packet in WSN. The Route Searching Time (RST) is reduced using the Boltzmann Distribution (BD), and as a result, the energy is minimized on multi-user WSN. Finally, GIFM applies an instance time difference-based route searching on WSN to attain an optimal energy minimization system. Experimental analysis shows that the EPFMR framework can reduce the RST by 23.47% and improve the throughput by 6.79% compared with the state-of-the-art works.

Deep-Learning-Aided Packet Routing in Aeronautical <i>Ad Hoc</i> Networks Relying on Real Flight Data: From Single-Objective to Near-Pareto Multiobjective Optimization

Abstract: Data packet routing in aeronautical ad-hoc networks (AANETs) is challenging due to their high-dynamic topology. In this paper, we invoke deep learning (DL) to assist routing in AANETs. We set out from the single objective of minimizing the end-to-end (E2E) delay. Specifically, a deep neural network (DNN) is conceived for mapping the local geographic information observed by the forwarding node into the information required for determining the optimal next hop. The DNN is trained by exploiting the regular mobility pattern of commercial passenger airplanes from historical flight data. After training, the DNN is stored by each airplane for assisting their routing decisions during flight relying solely on local geographic information. Furthermore, we extend the DL-aided routing algorithm to a multi-objective scenario, where we aim for simultaneously minimizing the delay, maximizing the path capacity, and maximizing the path lifetime. Our simulation results based on real flight data show that the proposed DL-aided routing outperforms existing position-based routing protocols in terms of its E2E delay, path capacity as well as path lifetime, and it is capable of approaching the Pareto front that is obtained using global link information.

Adaptive Routing Design for Flying Ad Hoc Networks

Abstract: Adaptive routing and efficient packet delivery in Flying Ad Hoc Networks (FANETs) are significant challenges due to underlying environment constraints, such as dynamic nature, mobility, and limited connectivity. With the increasing number of machine learning (ML) applications in wireless networks, FANETs can benefit from these data-driven predictions. This letter proposes a Packet Arrival Prediction (PAP) routing protocol to improve transmission link reliability. Primarily, we apply a Long Short-Term Memory (LSTM) model to predict the packet arrival of each UAV, seeking to avoid the high-traffic UAVs, which cause packet loss significantly. Then, we formulate the routing decision issue as an optimization problem, which attempts to find an appropriate path by a proposed constrained sorting approach, in order to make joint yet fast routing decisions. The simulation results demonstrate that the PAP routing protocol outperforms the existing manifold protocols in the aspects of Packet Delivery Ratio (PDR) and delay.

Pre-Routing Path Delay Estimation Based on Transformer and Residual Framework

Abstract: Timing estimation prior to routing is of vital importance for optimization at placement stage and timing closure. Existing wire- or net-oriented learning-based methods limits the accuracy and efficiency of prediction due to the neglect of the delay correlation along path and computational complexity for delay accumulation. In this paper, an efficient and accurate pre-routing path delay prediction framework is proposed by employing transformer network and residual model, where the timing and physical information at placement stage is extracted as sequence features while the residual of path delay is modeled to calibrate the mismatch between the pre- and post-routing path delay. Experimental results demonstrate that with the proposed framework, the prediction error of post-routing path delay is less than 1.68% and 3.12% for seen and unseen circuits in terms of rRMSE, which is reduced by 2.3~5.0 times compared with exiting learning-based method for pre-routing prediction. Moreover, this framework produces at least three orders of magnitude speedup compared with the traditional design flow, which is promising to guide circuit optimization with satisfying prediction accuracy prior to time-consuming routing and timing analysis.

Revisiting PathFinder Routing Algorithm

Abstract: PathFinder, a popular routing algorithm widely used in the state-of-the-art FPGA compilation tools such as VTR 8, has been reported to have a non-negligible variation in the routing quality under routing resource constraints. Several workaround methods have been proposed to mitigate this undesired effect while keeping the algorithm unchanged. In this paper, we take a fresh look at the PathFinder algorithm itself and identify that its inappropriate definition of routing congestion problems causes an issue in its congestion coefficient updating strategy and eventually leads to the variation in the routing quality under different routing orders. This problem is aggravated in VTR~8 and inevitably degrades the routing quality as the predefined routing order is not optimal in most cases. Based on these findings, we propose an enhanced PathFinder algorithm with redefined routing congestion problems to address the issue in the congestion coefficient updating strategy and algorithmically resolve the routing quality variation issue. This enhanced algorithm can be easily integrated into VTR~8 to benefit every researcher in our community. Evaluation results show that it reduces the longest critical path delay and the variation by up to 49.4% and 96.2% under routing resource constraints, respectively. The variation can be fully eliminated when sufficient routing iterations are performed.

Intertwine Connection-Based Routing Path Selection for Data Transmission in Mobile Cellular Networks and Wireless Sensor Networks

Abstract: In a network setting, a sensor node's round-trip delay time over hostile nodes compromises the node's ability to transmit data from the sender node to the destination node. Minimum distance path discovery causes the path failure, since aggressive nodes are available. Node connectivity is poor which should cause the packet loss; it does not control more energy consumption, since packet broadcasting is repeated for many times using that path. So, the proposed intertwine connection-based routing path selection (ICBRPS) technique allows only energy efficient routing path, path connectivity is important, and routing path is damaged because of the presence of aggressive nodes. It hacks the information from sensor and operates unpredictable manner. The objective of this presented ICBRPS scheme is to improve the routing path in efficient manner. If any damages occur during the transmission of data, then the alternate best node connectivity path is created by energetic route discovery method. The performance metrics of parameters are delay, network overhead, energy consumption, packet loss, packet delivery ratio, and connectivity ratio. It enhances the connectivity rate and reduces the energy consumption.

Efficient Detailed Routing for FPGA Back-End Flow Using Reinforcement Learning

Abstract: Over the past few years, the computation capability of field-programmable gate arrays (FPGAs) has increased tremendously. This has led to the increase in the complexity of the designs implemented on FPGAs and to the time taken by the FPGA back-end flow. The FPGA back-end flow comprises of many steps, and routing is one of the most critical steps among them. Routing normally constitutes more than 50% of the total time taken by the back-end flow and an optimization at this step can lead to overall optimization of the back-end flow. In this work, we propose enhancements to the routing step by incorporating a reinforcement learning (RL)-based framework. In the proposed RL-based framework, we use the ϵ-greedy approach and customized reward functions to speed up the routing step while maintaining similar or better quality of results (QoR) as compared to the conventional negotiation-based congestion-driven routing solution. For experimentation, we use two sets of widely deployed, large heterogeneous benchmarks. Our results show that, for the RL-based framework, the ϵ-greedy greedy approach combined with a modified reward function gives better results as compared to purely greedy or exploratory approaches. Moreover, the incorporation of the proposed reward function in the RL-based framework and its comparison with a conventional routing algorithm shows that the proposed enhancement requires less routing time while giving similar or better QoR. On average, a speedup of 35% is recorded for the proposed routing enhancement as compared to negotiation-based congestion-driven routing solutions. Finally, the speedup of the routing step leads to an overall reduction in the execution time of the back-end flow of 25%.

Attaining stable and loop-free inter-domain routing without path vectors

Abstract: A sufficient condition for loop-free routing is introduced based on path labels. A path label consists of the identifier of the first node and hop-count length of a path to a destination. This condition is applied to the policy mechanisms used in BGP, which results in BGP-ELF (BGP Enhanced for Loop Freedom). BGP-ELF uses updates, queries, and replies based on path labels to attain multi-path loop-free and stable routing across autonomous systems without the need for path vectors.

CoDiNet: Path Distribution Modeling With Consistency and Diversity for Dynamic Routing

Abstract: Dynamic routing networks, aimed at finding the best routing paths in the networks, have achieved significant improvements to neural networks in terms of accuracy and efficiency. In this paper, we see dynamic routing networks in a fresh light, formulating a routing method as a mapping from a sample space to a routing space. From the perspective of space mapping, prevalent methods of dynamic routing did not take into account how routing paths would be distributed in the routing space. Thus, we propose a novel method, termed CoDiNet, to model the relationship between a sample space and a routing space by regularizing the distribution of routing paths with the properties of consistency and diversity. In principle, the routing paths for the self-supervised similar samples should be closely distributed in the routing space. Moreover, we design a customizable dynamic routing module, which can strike a balance between accuracy and efficiency. When deployed upon ResNet models, our method achieves higher performance and effectively reduces average computational cost on four widely used datasets.

Enhancing traffic capacity of scale-free networks by employing structural hole theory

Abstract: In this paper, we propose a Structural Hole Routing (SHR) strategy based on the structural hole theory for scale-free networks. The performance of routing strategies on scale-free networks can be measured by two indicators, i.e. the traffic capacity and the average path length. With the SHR strategy, the packets can bypass those center nodes to enhance the traffic capacity of scale-free networks. The simulation results show that our SHR strategy can achieve approximately 6% higher traffic capacity than the efficient routing (ER) strategy. Moreover, the average path length of the SHR strategy is a little higher than that of the ER strategy. Therefore, our SHR routing strategy is preferable to other routing strategies and can be easily implemented through software method.

An Efficient Calculation for TI-LFA Rerouting Path

Abstract: SUMMARY Recently, segment routing, which is a modern forwarding mechanism, and Topology Independent Loop-free Alternate, which is an IP fast-reroute method using segment routing, have been proposed and have begun to be applied to real networks. When a failure occurs in a network, TI-LFA quickly restores packet forwarding without waiting for other nodes to update their routing tables. It does so by using segment routing to forward sections that may cause loops in the rerouting path. However, determining the segment routing sections has a high computational cost because it requires computation for each destination. This paper therefore proposes an algorithm to determine the egress node that is the exit of the segment routing section for all destination nodes with only three shortest- path tree calculations. The evaluation results of the proposed algorithm showed that the average tunnel lengths are at most 2.0 to 2.2 hops regardless of the size of the network. I also showed that the computational complexity of the proposed algorithm is O ( N log N ) .

THORP: Choosing Ordered Neighbors To Attain Efficient Loop-Free Minimum-Hop Routing

Abstract: We introduce THORP (Totally Hop-Ordered Routing Procedure), a simple distributed algorithm for minimum-hop routing that works in much the same way as traditional distance-vector routing algorithms do. THORP eliminates routing-table loops by having routers choose as their next hops to destinations those neighbor routers that are totally ordered based on their current distances, without requiring their next-hop routers to correspond necessarily to minimum-hop paths. THORP is shown to be loop-free, to converge to minimum-hop distances within a finite time, and to be faster than the Diffusing Update Algorithm (DUAL), which is the only loop-free shortest-path algorithm that has been used successfully in practice and is part of Cisco’s EIGRP.

Break the Blackbox! Desensitize Intra-domain Information for Inter-domain Routing

Abstract: Along with the ever-increasing amount of data generated from edge networks, cross domain (also known as Autonomous Systems, AS) transmission problem has attracted more and more attention. As mature and widely used inter-domain routing protocols, BGP-based solutions often use the number of domains (i.e. AS hops) of each path to make inter-domain routing decisions, which is simple and effective, but usually can not get the optimal routing results due to the lack of real state/information within ASes. These protocols choose the path with less AS hops as the forwarding path, even if the total latency or cost of the domains on this path is higher. While to solve this problem, directly access to intra-domain information as the assistance to make routing decisions is impractical due to data privacy.In this paper, we propose DIT, which makes near-optimal inter-domain routing decisions with desensitized intra-domain information. To do so, we design a homomorphic encrypted-based private number comparison scheme to export intra-domain information securely and thus assist in routing decisions. We conduct a series of experiments according to five real network topologies with nearly 900 simulated flows, and the results show that DIT reduces the number of forwarding hops by about 45% in average and reduces flow completion time by about 60%.

A Multi-Path Routing Method with Traffic Grooming Corresponding to Path Lengths in Elastic Optical Networks

Abstract: To accommodate an increasing amount of traffic efficiently, elastic optical networks (EON) that can use optical spectrum resources flexibly have been studied. We implement multi-path routing in case we cannot allocate the spectrum with single-path routing. However, multi-path routing requires more guard bands to avoid interference between two adjacent optical paths when compared with single-path routing in EON. A multi-path routing algorithm with traffic grooming technology has been proposed. The researchers assumed that a uniform modulation level was adopted, and so they did not consider the impact of path length on the resources needed. In this paper, we propose a multi-path routing method with traffic grooming considering path lengths. Our proposed method establishes an optical multi-path considering path length, fiber utilization, and the use of traffic grooming. Simulations show we can decrease the call-blocking probability by approximately 24.8% in NSFNET. We also demonstrate the effectiveness of traffic grooming and the improvement in the utilization ratio of optical spectrum resources.

The Acceleration Techniques for the Modified Pathfinder Routing Algorithm on an Island-Style FPGA

Abstract: The paper presents two techniques to speed up routing of user circuits within an island-style FPGA design flow. The basic algorithm is the modified Pathfinder that supports a mixed route graph representation of FPGA routing resources. The first technique reduces the number of rip-up and reroute iterations and allows decreasing routing time by 38% on average while increasing the critical path delay up to 10% only. The second technique utilizes the idea of directed pathfinding on a mixed route graph with known geometric coordinates of its vertices and edges. Various values of directed path search adjustment factor were investigated and the optimal one was discovered. The introduced routing method adjusted by an optimal factor value is shown to double a routing speedup without routability degradation. Also, the paper proposes a formal description of FPGA routing resources and a routing task itself.

Substrate Signal Routing Solution Exploration for High-Density Packages with Machine Learning

Abstract: Off-chip substrate routing for high-density packages is on the critical path for time to market. There are several substrate routing algorithms have been proposed in previously. Although routers can rapidly that produce routing results, these results might not be satisfied universally from expert's experiences. In other words, different routers tend to have strength and weakness from different SOC designs. In this paper, we propose a novel reroute framework to remedy the defect of substrate routers by using supervised machine learning. We build a classification model which extracts features from expert's experience. It will identify suboptimal routings that do not conform to manual routing style. Then, reroute these areas using different routers and produce diverse results, then feed to classification model until they are acceptable. Guided by the model, suboptimal routing areas are replaced by results that are closer to expert's manual routing. Experiments show that our rerouting framework achieves 36.5% improvement on the number of wire bends and 1.6% wirelength improvement, compared with initial results routed by recent related work.

Opportunistic Routing in Quantum Networks

Abstract: Unlike classical routing algorithms, quantum routing algorithms make use of entangled states - a type of resources that have a limited lifetime and need to be regenerated after consumption. In a nutshell, quantum routing algorithms have to use these resources efficiently, while optimizing some objectives such as the total waiting time. Current routing algorithms tend to keep a routing request waiting until all of the resources on its path are available. In this paper, we introduce a new way of managing entanglement resources in an opportunistic fashion: a request can move forward along its path as soon as possible (even if some resources on its path are not ready). We show that this opportunistic approach is fundamentally better than conventional approaches. In particular, our results indicate that this new approach achieves a 30-50% improvement in the average total waiting time and average link waiting time compared with several state-of-the-art routing algorithms. As a by-product of this work, we develop a new simulator for quantum routing, which can be used to evaluate various design choices under different scenarios.

Topology characterizing using packet forwarding distance dissimilarity in multi-greedy geographic routing

Abstract: Characterizing the topology of MANETs provides the means for packet routing protocols to perform adaptively and efficiently in the particular environments. We show that the geographic routing’s greedy packet forwarding distance dissimilarity distributions in relation to node size characterizes MANET topologies and supports efficient multi-greedy forwarding. The models we described, based on the average greedy packet forwarding distance measures, showed distinct distribution patterns of the dissimilarity indices when applied to the example multi-greedy routing environment consisting of the ELLIPSOID and the GREEDY forwarding metrics. The scheme demonstrates the potential for adaptive forwarding performance to improve successful packets delivery in environments of high node-size variations such as VANETs.

Joint Routing and Scheduling for Deterministic Networking: A Segment Routing Approach

Abstract: Deterministic networking (DetNet) provides guaranteed transmission services for the time-sensitive traffic. However, how to route and schedule the traffic to enable bounded latency and jitter remains a great research challenge. This paper proposes a joint routing and scheduling method for DetNet based on Segment Routing (SR). This method includes three parts. The first part is prediction of the end-to-end (E2E) delay based on the delay budget. The second part is probabilistic packet dropping according to its deadline information. The third part is the three-queue cyclic queuing and forwarding. SR technology is utilized to implement the above functions. Simulation results show that the proposed method improves the performance of the worst-case E2E latency bound compared with the traditional method such as the Cycle Specified Queuing and Forwarding (CSQF). The packet receiving rate within the delay budget is increased by 1.9% and the worst-case E2E latency is decreased by 14.3% when the offered load is 0.8.

QoS-SDIoV: An Efficient QoS Routing Scheme for Software Defined Internet of Vehicles

Abstract: The issue of routing and data dissemination in IoV is one of the most fundamental network issues in last decade that still a challenge to solve, where the emergence of Software defined Network (SDN) revealed newfangled capabilities in complex control and routing optimization problems. Where, the SDN updates the old IoV architecture which it did not accomplish the requisite requirements for Intelligent Transportation Systems (ITSs) and its applications such as scalability, flexibility, and global knowledge of the network. In order to solve the routing problems, we propose a Quality of Service (QoS) routing scheme for Software Defined Internet of Vehicles called (QoS-SDIoV) in which SDN technology is considered for IoV to achieve routing capability where we select the shortest path within the Open vSwitch (OVS) access points based on the well-known Djikstra’s algorithm to disseminate different data from source to destination. Results showed that our scheme achieves better performance than conventional routing in IoV in terms of end-to-end latency, throughput, and packet loss rate.

Analysis of web traffic using MPLS technology

Abstract: Multi-Protocol Label Switching provides a simplification and a substantial increase in the speed of the packet routing process in IP networks. This is done through optimization processes prior to the routing process. In the case of optical communications, there are a few problems with the routing of IP requests, which creates a large space for optimizations. This paper is a study on web traffic using MPLS technology.

An Improvement of an IP Fast Reroute Method Using Multiple Routing Tables

Abstract: The demand for high Internet availability has increased. As a routing method to recover fast from a single network component (link or node) failure, a method using multiple routing tables has been proposed. In the method, when a component failure occurs, packets which are supposed to pass through the component in the failure free state are rerouted using a backup routing table (backup table: BT) which does not use the component. Thus, it is important to decrease the increased routing cost, and because the method uses multiple BTs, it is also important to decrease the numbers of entries in BTs. In this paper, we propose a new routing method to decrease the increased routing cost. In the conventional method, there are many components that do not fail but are not used for packet forwarding in a BT. In our proposed method, we use such components as much as possible to decrease the increased routing cost. About the decreasing of the numbers of entries in BTs, we simulate packet forwarding for every node-pair and find unnecessary entries which are not used in packet forwarding in any node-pair. Numerical examples show that our proposed method is superior to the conventional method.

ADBR: Accelerated Depth-Based Routing for Underwater Sensor Networks

Abstract: It is challenging to propose an efficient routing algorithm for Underwater Wireless Sensor Networks (UWSNs) in terms of packet delivery ratio, end-to-end delay of packet delivery from the source to the destination, and energy consumption. The reasons of that are UWSNs have unique characteristics (e.g. using acoustic channels instead of radio channels for communications), and they have dynamic topology due to the movement of the sensor by the water flow. Depth-Based Routing (DBR) considers one of the well-known algorithms in this context. DBR is a very simple algorithm; however, it is inefficient in terms of packet delivery rate, end-to-end delay, and energy consumption. This study we developed DBR by adding an accelerated routine to it to improve its efficiency, the proposed algorithm; called Accelerated Depth-Based Routing (ADBR). In ADBR, a simple probabilistic mechanism is used to accelerate packet forwarding and provide more multi-path to the destination. In ADBR, each node immediately delivers received packet to the destination with a probability of and follows the DBR routine with a probability of 1 – Pf. The performance of ADBR is evaluated via a set of experiments by using J-SIM simulator. Experimental results indicate the superiority of the ADBR over the DBR algorithm.