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Research on routing algorithm for Wireless Sensor Cooperative Communication Networks

AGRO FOOD INDUSTRY HI-TECH 2017年第3期28卷 3202-3206页

作者： Song, Xiuping Chong Qing Coll Elect Engn Chongqing Peoples R China

In order to reduce the energy consumption and improve the efficiency, routing algorithm for wireless sensor cooperative communication networks is proposed in this paper. This paper seeks to investigate the problem of UEC and maximization of network klife time for both homogeneous and heterogeneous WSNs. To achieve this goal, some of no velenergy-efficient protocols are proposed. In these proposed protocols, energy consumption namong all nodes in the network is balanced in expectation that all nodes should run out of energy at nearly the same time. The experiment result shows the proposed method can improve the overall system performance substantially.

关键词： routing algorithm wireless sensor cooperative communication networks

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FXY: A HIERARCHICAL routing algorithm TO BALANCE PERFORMANCE AND FAULT TOLERANCE IN NETWORKS-ON-CHIP

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JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS 2014年第10期23卷 1450146-1450146页

作者： Fakhrali, Saleh Zarandi, Hamid R. Amirkabir Univ Technol Dept Comp Engn & Informat Technol Tehran Polytech Tehran 158754413 Iran Inst Res Fundamental Sci IPM Sch Comp Sci Tehran Iran

This paper presents a hierarchical fault-tolerant routing algorithm called FXY, which is a hybrid method based on flooding and XY, and can balance performance and fault tolerance based on a predefined parameter m. First, FXY partitions the whole network into different equal size square submeshes with the size of m x m. At the first level of the hierarchy, packet routing within these submeshes is performed based on flooding routing algorithm. When the packets are received at effective boundary of each submesh, XY routing is performed to route the packet inter submeshes i.e., from one submesh to the neighbor submesh which is certainly one of its neighbor nodes. Here, the size of the submesh is defined as fault-tolerant granularity. As fault-tolerant granularity is increased, the size of the submeshes will be increased, therefore the method mainly floods packets in large-size submeshes and finally packets are received at their destinations correctly. On the other hand, when fault-tolerant granularity is decreased, the method mainly routes packets as XY method, which is not fault-tolerant, but has the best performance. The method is evaluated for various packet injection rates and fault rates. The experimental results reveal that the method presents a fault-tolerant routing algorithm, and can be adjusted so that it shows better fault-tolerance and performance trade-offs compared to XY and flooding which are two end-to-end cases of having the best performance and no fault-tolerance, having the least performance and the best fault tolerance, respectively. The experimental results for an 8 x 8 NoC size, have shown that 2-FXY, which is the proposed method with fault-tolerant granularity of two, offers the best trade-off between performance and fault tolerance compared to other methods, XY, flooding and probabilistic flooding.

关键词： Networks-on-chip routing algorithm fault tolerant routing performance analysis

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Auto-tune: An efficient autonomous multi-path payment routing algorithm for Payment Channel Networks

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COMPUTER NETWORKS 2023年第1期225卷

作者： Hong, Hsiang-Jen Chang, Sang-Yoon Zhou, Xiaobo Univ Colorado Colorado Springs Dept Comp Sci Colorado Springs CO 80918 USA

Payment Channel Network (PCN) is a scaling solution for Cryptocurrency networks. We advance the PCN multi-path routing by better modeling the system and incorporating the cost of routing fee and the privacy requirement of the channel balance. We design an autonomous routing algorithm, Auto-Tune, optimizing the routing concerning the success rate and the routing fee and utilizing the limited channel capacity information. The simulation result shows a significant performance gain in the success rate of Auto-Tune over the current PCN implementation based on single-path routing. To analyze the performance cost from the system requirement of the channel balance privacy, we compare Auto-Tune against the state-of-the-art Flash algorithm assuming the availability of the channel-balance information (such channel-balance information violates the PCN privacy requirement and does not comply with the current PCN implementations and practices). The simulation results show that the success rate and fee obtained by Auto-Tune are close to that obtained by Flash (which achieves the optimal fee result by using the exact channel-balance information).

关键词： Blockchain Cryptocurrency Multi-path payment Payment Channel Network routing algorithm Bitcoin Lightning Network

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GTR: GAN-Based Trusted routing algorithm for Underwater Wireless Sensor Networks

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SENSORS 2024年第15期24卷 4879页

作者： Wang, Bin Ben, Kerong Naval Univ Engn Coll Elect Engn Wuhan 430033 Peoples R China

The transmission environment of underwater wireless sensor networks is open, and important transmission data can be easily intercepted, interfered with, and tampered with by malicious nodes. Malicious nodes can be mixed in the network and are difficult to distinguish, especially in time-varying underwater environments. To address this issue, this article proposes a GAN-based trusted routing algorithm (GTR). GTR defines the trust feature attributes and trust evaluation matrix of underwater network nodes, constructs the trust evaluation model based on a generative adversarial network (GAN), and achieves malicious node detection by establishing a trust feature profile of a trusted node, which improves the detection performance for malicious nodes in underwater networks under unlabeled and imbalanced training data conditions. GTR combines the trust evaluation algorithm with the adaptive routing algorithm based on Q-Learning to provide an optimal trusted data forwarding route for underwater network applications, improving the security, reliability, and efficiency of data forwarding in underwater networks. GTR relies on the trust feature profile of trusted nodes to distinguish malicious nodes and can adaptively select the forwarding route based on the status of trusted candidate next-hop nodes, which enables GTR to better cope with the changing underwater transmission environment and more accurately detect malicious nodes, especially unknown malicious node intrusions, compared to baseline algorithms. Simulation experiments showed that, compared to baseline algorithms, GTR can provide a better malicious node detection performance and data forwarding performance. Under the condition of 15% malicious nodes and 10% unknown malicious nodes mixed in, the detection rate of malicious nodes by the underwater network configured with GTR increased by 5.4%, the error detection rate decreased by 36.4%, the packet delivery rate increased by 11.0%, the energy tax decreased by 11.4%, and

关键词： underwater wireless sensor networks (UWSNs) routing algorithm trust evaluation model generative adversarial network (GAN) Q-Learning

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Graph based routing algorithm for torus topology and its evaluation for the Angara interconnect

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JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 2024年 183卷

作者： Mukosey, Anatoly Semenov, Alexander Tretiakov, Aleksandr JSC NICEVT Varshavskoe Shosse 125 Moscow 117587 Russia Russian Acad Sci Joint Inst High Temp Izhorskaya 20 Bld 2 Moscow 125412 Russia Natl Res Univ Higher Sch Econ Myasnitskaya 20 Moscow 101000 Russia

Several approaches and techniques exist to resolve load balancing problem in general and torus topology networks. Graph methods are natural ways to perform balancing of routing paths. A routing balancing algorithm must operate within the constraints of the underlying network architecture that limits several parameters, such as the number of logical paths in the network. In this paper, we consider a torus topology that is one of the common topologies that are used in high performance computing systems. We introduce a routing graph that corresponds to a interconnect topology, abstracts interconnect routing rules, providing one-to-one correspondence of network routes and graph paths. We propose a deadlock-free routing algorithm based on a fast single-source shortest path algorithm in a routing graph for the deterministic routing of a torus topology interconnect with a single virtual channel. The proposed algorithm is a tradeoff between two existing routing algorithms, also the algorithm is optimized for multidimensional torus topology and can be applied to any torus topology HPC system. We present a complete description of a routing graph that abstracts the Angara interconnect with 4D torus topology. We evaluated the proposed routing algorithm and benchmarked the maximum performance improvement of 71% for the Alltoall pattern for torus topology systems up to 432 nodes on the Angara interconnect simulator. The performance improvement of more than 5% was obtained for the NPB FT and IS application kernels on a 32-node supercomputer.(c) 2023 Elsevier Inc. All rights reserved.

关键词： Networks routing algorithm High performance computing Angara Torus topology

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Towards a throughput-optimal routing algorithm for data collection on satellite networks

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2016年第7期12卷 1-1页

作者： Chen, Jianzhou Liu, Lixiang Hu, Xiaohui Chinese Acad Sci Inst Software Univ Chinese Acad Sci Beijing 100190 Peoples R China Chinese Acad Sci Inst Software Beijing Peoples R China

To perform Earth observation, more and more satellites are equipped with high-resolution sensors like hyperspectral imagers, which generate data at tens of Gbps. Researchers aim to maximize the volume of data available for use on the ground in near-real time. To achieve this goal, many solutions have recently been proposed to perform data collection through satellite networks. Most of these solutions have so far been focusing on either source rate control and load balancing, or heuristic routing. However, optimizing routing together with resources allocation is critical for improving delivery performance. In this paper, we challenge the fact that transmission paths have to be built under high link variability with limited resources, and develop a throughput-optimal solution based on the utility maximization framework. For delay performance, we embed a distance factor into the objective of the framework and derive a geographic-location-aware backpressure algorithm. Further, we exploit transmission opportunities missed by backpressure-type algorithms to accelerate data transfer. The simulation results show that our algorithms are able to deliver large volumes of data in time, and scale well in all scenarios tested.

关键词： Satellite networks data collection throughput optimality routing algorithm backpressure

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DeepNR: An adaptive deep reinforcement learning based NoC routing algorithm

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MICROPROCESSORS AND MICROSYSTEMS 2022年 90卷 104485-104485页

作者： Raj, Reshma R. S. Rohit, R. Shahreyar, Mushrif Shaikh Raut, Akash Pournami, P. N. Kalady, Saidalavi Jayaraj, P. B. Natl Inst Technol Calicut Dept Comp Sci & Engn Kozhikode 673601 Kerala India Natl Inst Technol Calicut Dept Elect Engn Kozhikode 673601 Kerala India

Network-on-Chip (NoC) has become a cost-effective communication interconnect for Tiled Chip Multicore Processor systems. The communication between cores is done through packet exchange. As the computational intensity of applications increases, the amount of packet exchange between cores will also increase. The improper routing of these packets will result in high congestion thereby degrading the system performance. This marks the need for congestion-aware routing in NoC. In the real world, the applications running in NoC create diverse traffic, which in turn creates challenges in routing. Such challenges have resulted in more researchers relying on machine learning algorithms to tackle them. However, the issues pertaining to storage overhead and packet latency prevail in such methodologies. This paper presents an adaptive routing algorithm DeepNR, which uses a deep reinforcement learning approach. The proposed approach considers network information for state representation, routing directions for actions, and queuing delay for reward function. Experiments carried out on synthetic as well as real-time traffics to demonstrate the effectiveness and efficiency of DeepNR using the Gem5 simulator. The results obtained for DeepNR indicate a reduction of up to 21.25% and 44% in overall packet latency under high traffic conditions on real and synthetic traffic respectively, as compared to the existing approaches. Also, DeepNR achieves a throughput of above 90% in both the traffic scenarios.

关键词： Network-on-Chip routing algorithm Deep reinforcement learning Packet latency Throughput

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Uneven clustering routing algorithm based on glowworm swarm optimization

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AD HOC NETWORKS 2019年 93卷 101923-000页

作者： Yu Xiuwu Liu Qin Liu Yong Hu Mufang Zhang Ke Xiao Renrong Univ South China 28 West Changsheng Rd Changsha 421001 Hunan Peoples R China Univ South China Hunan Prov Engn Technol Res Ctr Uranium Tailings 28 West Changsheng Rd Hengyang City 421001 Hunan Peoples R China Univ South China Hunan Prov Engn Res Ctr Radioact Control Technol Changsha 421001 Hunan Peoples R China

An uneven clustering routing algorithm based on glowworm swarm optimization for wireless sensor networks (UCRA-GSO) is proposed to solve the Wireless sensor network (WSN) energy balance problem. We introduce factors such as cluster head density, cluster head proximity distance, cluster head energy, and compactness of the cluster into a glowworm swarm optimization (GSO) method to find the optimal clustering method. The test case involves a forwarding-tree of two level gradients (single and multi-hop transmission) such that the distance between the sensor and the base station is determined by a cost function. The simulation results show that UCRA-GSO effectively extends the network's life cycle while balancing the network's energy dissipation. (C) 2019 Published by Elsevier B.V.

关键词： Wireless sensor networks Glowworm swarm optimization Uneven clustering routing algorithm

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Vehicle Authentication-Based Resilient routing algorithm With Dynamic Task Allocation for VANETs

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IEEE ACCESS 2024年 12卷 195344-195357页

作者： Pacharla, Nagaraju Reddy, K. Srinivasa VIT AP Univ Sch Comp Sci & Engn Amaravati 522241 Andhra Pradesh India

Vehicles of the future will have built-in means of communication that will allow them to exchange data with one another. One use of this kind of communication between vehicles that ultimately results in an Intelligent Transport System (ITS) is used by Vehicular Ad hoc Networks (VANETs). Parameters, such as environmental changes, that impact the performance of actual VANET applications were mostly disregarded by most techniques. Both VANET performance and throughput are susceptible to environmental variations. The great dynamism of VANETs makes data routing in such a network a difficult challenge. There are constraints in VANET regarding processing power, bandwidth, time, and high-speed mobility in vehicles. In VANETs, fog computing can significantly improve fog-based service quality. The evolution of cloud computing, the Internet of Things (IoT), and intelligent transportation systems has elevated the significance of fog computing's integration with VANETs. While transferring tasks to the fog layer, it is essential to meet the vehicles' needs for low latency and quick response times. With the goal of reducing task offloading delay and improving enhanced reaction time, a VANET-based task scheduling system is proposed after selecting an optimal route in the VANET. Taking into account the limited resources of vehicle nodes, the suggested technique efficiently moves workloads to the fog computing layer. The requirement for means to guarantee the constant and secure functioning of vehicles is directly proportional to their numbers. This research proposes a Vehicle Authentication based Resilient routing algorithm with Dynamic Task Allocation (VARRA-DTA) Scheme for selecting the optimal and secured route in VANET with effective task allocation strategy that reduces the latency in the network. The proposed model exhibits better results when contrasted with the traditional models. The proposed model achieved 98.7% accuracy in task scheduling, 99.1% accuracy in route selectio

关键词： Vehicular ad hoc networks routing Resource management Vehicle dynamics Security routing protocols Heuristic algorithms Authentication Edge computing Dynamic scheduling Dynamic task allocation latency reduction routing algorithm security vehicular ad-hoc networks vehicle-to-vehicle vehicle-to-infrastructure

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An Adaptive routing algorithm Based on Relation Tree in DTN

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SENSORS 2021年第23期21卷 7847-7847页

作者： Chen, Diyue Cui, Hongyan Welsch, Roy E. Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Beijing Lab Adv Informat Networks Beijing 100876 Peoples R China MIT Sloan Sch Management Cambridge MA 02139 USA MIT Ctr Stat & Data Sci Cambridge MA 02139 USA

It is found that nodes in Delay Tolerant Networks (DTN) exhibit stable social attributes similar to those of people. In this paper, an adaptive routing algorithm based on Relation Tree (AR-RT) for DTN is proposed. Each node constructs its own Relation Tree based on the historical encounter frequency, and will adopt different forwarding strategies based on the Relation Tree in the forwarding phase, so as to achieve more targeted forwarding. To further improve the scalability of the algorithm, the source node dynamically controls the initial maximum number of message copies according to its own cache occupancy, which enables the node to make negative feedback to network environment changes. Simulation results show that the AR-RT algorithm proposed in this paper has significant advantages over existing routing algorithms in terms of average delay, average hop count, and message delivery rate.

关键词： DTN routing algorithm relation tree adaptive

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