scholarly journals Data Transmission Evaluation and Allocation Mechanism of the Optimal Routing Path: An Asynchronous Advantage Actor-Critic (A3C) Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Yahui Ding ◽  
Jianli Guo ◽  
Xu Li ◽  
Xiujuan Shi ◽  
Peng Yu
Keyword(s):  
Data Transmission ◽  
Buffer Management ◽  
Routing Algorithms ◽  
Optimal Routing ◽  
Allocation Mechanism ◽  
Q Learning ◽  
Throughput Improvement ◽  
Network Transmission ◽  
End To End ◽  
Delay Tolerant

The delay tolerant networks (DTN), which have special features, differ from the traditional networks and always encounter frequent disruptions in the process of transmission. In order to transmit data in DTN, lots of routing algorithms have been proposed, like “Minimum Expected Delay,” “Earliest Delivery,” and “Epidemic,” but all the above algorithms have not taken into account the buffer management and memory usage. With the development of intelligent algorithms, Deep Reinforcement Learning (DRL) algorithm can better adapt to the above network transmission. In this paper, we firstly build optimal models based on different scenarios so as to jointly consider the behaviors and the buffer of the communication nodes, aiming to ameliorate the process of the data transmission; then, we applied the Deep Q-learning Network (DQN) and Advantage Actor-Critic (A3C) approaches in different scenarios, intending to obtain end-to-end optimal paths of services and improve the transmission performance. In the end, we compared algorithms over different parameters and find that the models build in different scenarios can achieve 30% end-to-end delay decline and 80% throughput improvement, which show that our algorithms applied in are effective and the results are reliable.

scholarly journals MSSN: An Attribute-Aware Transmission Algorithm Exploiting Node Similarity for Opportunistic Social Networks

Information ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 299
Author(s):  
Mei Guo ◽  
Min Xiao
Keyword(s):  
Social Networks ◽  
Mobile Devices ◽  
Data Transmission ◽  
Routing Algorithms ◽  
Delivery Ratio ◽  
Relay Nodes ◽  
Similarity Degree ◽  
The Social ◽  
Node Similarity ◽  
End To End

Recently, with the development of big data and 5G networks, the number of intelligent mobile devices has increased dramatically, therefore the data that needs to be transmitted and processed in the networks has grown exponentially. It is difficult for the end-to-end communication mechanism proposed by traditional routing algorithms to implement the massive data transmission between mobile devices. Consequently, opportunistic social networks propose that the effective data transmission process could be implemented by selecting appropriate relay nodes. At present, most existing routing algorithms find suitable next-hop nodes by comparing the similarity degree between nodes. However, when evaluating the similarity between two mobile nodes, these routing algorithms either consider the mobility similarity between nodes, or only consider the social similarity between nodes. To improve the data dissemination environment, this paper proposes an effective data transmission strategy (MSSN) utilizing mobile and social similarities in opportunistic social networks. In our proposed strategy, we first calculate the mobile similarity between neighbor nodes and destination, set a mobile similarity threshold, and compute the social similarity between the nodes whose mobile similarity is greater than the threshold. The nodes with high mobile similarity degree to the destination node are the reliable relay nodes. After simulation experiments and comparison with other existing opportunistic social networks algorithms, the results show that the delivery ratio in the proposed algorithm is 0.80 on average, the average end-to-end delay is 23.1% lower than the FCNS algorithm (A fuzzy routing-forwarding algorithm exploiting comprehensive node similarity in opportunistic social networks), and the overhead on average is 14.9% lower than the Effective Information Transmission Based on Socialization Nodes (EIMST) algorithm.

A Distributed Algorithm for Data Collection in Low-Duty-Cycled WSNs

2014 ◽  
Vol 668-669 ◽  
pp. 1355-1358
Author(s):  
Feng Liu ◽  
Yu Fei Wang ◽  
Mu Lin
Keyword(s):  
Data Collection ◽  
Distributed Algorithm ◽  
Routing Algorithms ◽  
Optimal Routing ◽  
Shortest Path Algorithm ◽  
End To End Delay ◽  
Network Utility ◽  
Control Message ◽  
End To End ◽  
Better Than

In order to prolong the lifetime of WSNs, low-duty-cycled scheduling is a widely used strategy. However, there exists high latency with traditional routing algorithms. In this paper, we model the data collection scheme of WSNs to be a delay optimization problem and propose a distributed algorithm based on Network Utility Maximization. The proposed algorithm can distributed find an optimal routing to achieve minimal average end-to-end delay. The simulation results show that our algorithm performs better than the traditional shortest path algorithm on end-to-end delay with less control message.

scholarly journals Analisis Performansi Algoritma Routing First Contact dengan Stationary Relay Node pada Delay Tolerant Network

2018 ◽  
Vol 4 (2) ◽  
pp. 123 ◽  
Author(s):  
LEANNA VIDYA YOVITA ◽  
JODI NUGROHO RESTU
Keyword(s):  
Routing Algorithm ◽  
Relay Node ◽  
Routing Algorithms ◽  
Delay Tolerant Network ◽  
Delivery Probability ◽  
Average Latency ◽  
End To End ◽  
Delay Tolerant ◽  
First Contact ◽  
Overhead Ratio

ABSTRAKAlgoritma routing pada jaringan klasik dapat berjalan jika hubungan end-to-end selalu ada.Algoritma routing ini bekerja dengan menggunakan informasi mengenai seluruh jalur yang tersedia.Untuk itu, pada jaringan dengan kondisi ekstrim seperti ini diperlukan algoritma routing yang sesuai.Salah satu algoritma routing yang dapat dijalankan pada Delay Tolerant Network (DTN) adalah First Contact.Algoritma iniakanmelakukan penggandaan pesan yang dibawanyauntuk kemudian diberikan kepada node lainnya yang pertama kali ditemui.Dalam penelitian ini ditambahkan stationary relay node untuk meningkatkan delivery probability.Dengan penambahan stationary relay node diperoleh peningkatan delivery probability 2 hingga 6% dibandingkan dengan jaringan tanpa stationary relay node. Parameter overhead ratio meningkat  sebesar 7-18% dibandingkan jaringan tanpa Stationary relay node. Algoritma First Contact dengan tambahan Stationary relay nodejuga memberikan tambahan average latency, 118 – 171 detik.Nilaiini berbanding lurus dengan jumlah mobile node DTN yang ada pada area tersebut.Kata kunci: Delay Tolerant Network, first contact,Stationaryrelaynode, routing algorithm, delivery probability, overhead ratio, average latency.ABSTRACTClassical routing algorithms only works if there is end to end connection.This algorithms uses the information about every available path, and then choose the best path related to spesific metric.. For the networks with the extreme condition, it is needed the suitable routing alorithms. One of the routing algorithms that is able to be applicated in Delay Tolerant Network (DTN) is First Contact. This algorithm will make a single copy message and then forward it to the first encountered node. In this research, the stationaryrelaynodes were added to improve delivery probability. The effect of adding stationary relay node is increasing the delivery probability about 2-6%, compared to networks without stationary relay node. The overhead ratio increased about  7-18% compared to networks without stationary relay node. First Contact algorithm with stationary relay node gives bigger average latency, 118 – 171 second. This value is directly proportional to the number of mobile DTN nodes that exist in the area.Keywords: Delay Tolerant Network, first contact, Stationaryrelaynode, routing algorithm, delivery probability, overhead ratio, average latency.. 

Optimal Buffer Management Scheme to Maximize the Message Delivery Rate in Delay Tolerant Networks

2009 ◽  
Vol E92-B (11) ◽  
pp. 3499-3503 ◽  
Author(s):  
Yong LI ◽  
Depeng JIN ◽  
Li SU ◽  
Lieguang ZENG
Keyword(s):  
Buffer Management ◽  
Delay Tolerant Networks ◽  
Delivery Rate ◽  
Message Delivery ◽  
Management Scheme ◽  
Delay Tolerant

Performance Evaluation of Data Transmission in Maritime Delay-Tolerant-Networks

2013 ◽  
Vol E96.B (6) ◽  
pp. 1435-1443 ◽  
Author(s):  
Shuang QIN ◽  
Gang FENG ◽  
Wenyi QIN ◽  
Yu GE ◽  
Jaya Shankar PATHMASUNTHARAM
Keyword(s):  
Performance Evaluation ◽  
Data Transmission ◽  
Delay Tolerant Networks ◽  
Delay Tolerant ◽  
Evaluation Of Data

Design and Implementation of Buffer Control in EoS System

2013 ◽  
Vol 411-414 ◽  
pp. 684-687
Author(s):  
Wei He ◽  
Yan Gan Zhang ◽  
Xue Guang Yuan ◽  
Jin Nan Zhang
Keyword(s):  
Buffer Management ◽  
Transport Rate ◽  
Optimization Approach ◽  
Data Transport ◽  
Design And Implementation ◽  
End To End ◽  
Buffer Control ◽  
Improved Model ◽  
Eos System

We propose an optimization approach to EoS (Ethernet over SDH) buffer control which the objective is to dynamically adjust the EoS buffer management registers. We will present the improved model of the traffic buffer management based on embedded MCU to control the SDRAM of the EoS chip, and setup the end-to-end system to illustrate the feasibility and advantage of the solution in buffer management when the data transport rate suddenly exceed the bandwidth of Ethernet port.

scholarly journals Distributed Channel Ranking Scheduling Function for Dense Industrial 6TiSCH Networks

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1593
Author(s):  
Ismael Amezcua Valdovinos ◽  
Patricia Elizabeth Figueroa Millán ◽  
Jesús Arturo Pérez-Díaz ◽  
Cesar Vargas-Rosales
Keyword(s):  
Kalman Filtering ◽  
Bandwidth Allocation ◽  
Communication Systems ◽  
High Reliability ◽  
Allocation Mechanism ◽  
Elapsed Time ◽  
Packet Arrival ◽  
End To End ◽  
Ieee 802.15.4E ◽  
Number Of Cells

The Industrial Internet of Things (IIoT) is considered a key enabler for Industry 4.0. Modern wireless industrial protocols such as the IEEE 802.15.4e Time-Slotted Channel Hopping (TSCH) deliver high reliability to fulfill the requirements in IIoT by following strict schedules computed in a Scheduling Function (SF) to avoid collisions and to provide determinism. The standard does not define how such schedules are built. The SF plays an essential role in 6TiSCH networks since it dictates when and where the nodes are communicating according to the application requirements, thus directly influencing the reliability of the network. Moreover, typical industrial environments consist of heavy machinery and complementary wireless communication systems that can create interference. Hence, we propose a distributed SF, namely the Channel Ranking Scheduling Function (CRSF), for IIoT networks supporting IPv6 over the IEEE 802.15.4e TSCH mode. CRSF computes the number of cells required for each node using a buffer-based bandwidth allocation mechanism with a Kalman filtering technique to avoid sudden allocation/deallocation of cells. CRSF also ranks channel quality using Exponential Weighted Moving Averages (EWMAs) based on the Received Signal Strength Indicator (RSSI), Background Noise (BN) level measurements, and the Packet Delivery Rate (PDR) metrics to select the best available channel to communicate. We compare the performance of CRSF with Orchestra and the Minimal Scheduling Function (MSF), in scenarios resembling industrial environmental characteristics. Performance is evaluated in terms of PDR, end-to-end latency, Radio Duty Cycle (RDC), and the elapsed time of first packet arrival. Results show that CRSF achieves high PDR and low RDC across all scenarios with periodic and burst traffic patterns at the cost of increased end-to-end latency. Moreover, CRSF delivers the first packet earlier than Orchestra and MSF in all scenarios. We conclude that CRSF is a viable option for IIoT networks with a large number of nodes and interference. The main contributions of our paper are threefold: (i) a bandwidth allocation mechanism that uses Kalman filtering techniques to effectively calculate the number of cells required for a given time, (ii) a channel ranking mechanism that combines metrics such as the PDR, RSSI, and BN to select channels with the best performance, and (iii) a new Key Performance Indicator (KPI) that measures the elapsed time from network formation until the first packet reception at the root.

THE CONCEPT OF MANAGING THE DATA NETWORK BASED ON SELF-LEARNING SYSTEMS

2020 ◽  
Author(s):  
С.Р. РОМАНОВ
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Data Transmission ◽  
Network Control ◽  
Learning Systems ◽  
Optimal Routing ◽  
Transmission Network ◽  
Data Traffic ◽  
Data Network ◽  
Self Learning

Рассмотрен принцип управления сетью передачи данных (СПД)с помощью искусственной нейронной сети. Предложена концепция проведения вычислений при решении задачи оптимальной маршрутизации трафика данных. Приведен алгоритм управления сетью СПД на базе нейронной сети Хэмминга. The principle of data transmission network control using an artificial neural network is considered. The concept of carrying out calculations when solving the problem of optimal routing of data traffic is proposed. The algorithm for controlling the data transmission network based on the Hamming neural network is presented.

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