USING NEURAL NETWORKS TO SOLVE THE MULTICAST ROUTING PROBLEM IN PACKET RADIO NETWORKS

1996 ◽  
Vol 07 (05) ◽  
pp. 617-626 ◽  
Author(s):  
THOMAS L. HEMMINGER ◽  
CARLOS A. POMALAZA-RAEZ
Keyword(s):  
Multicast Routing ◽  
Optimal Solution ◽  
Packet Delay ◽  
Hopfield Neural Network ◽  
Routing Problem ◽  
Packet Radio ◽  
Packet Radio Network ◽  
End To End Delay ◽  
Packet Delays ◽  
End To End

The primary function of a packet radio network is the efficient transfer of information between source and destination nodes using minimal bandwidth and end-to-end delay. Many researchers have investigated the problem of minimizing the end-to-end delay from a single source to a single destination for a variety of networks; however, very little work is reported about routing mechanisms for the common case where a particular information packet is intended to be sent to more than one destination in the network. This is known as multicasting. A simplified version of the problem is to ignore the packet delay at each node, then the problem becomes one of finding solutions which require the least number of transmissions. Determination of an optimal solution is NP-complete meaning that suboptimal solutions are frequently tolerated. The problem becomes more rigorous if packet delays are included in the network topology. This paper describes a practical technique for the computation of optimum or near optimum solutions to the multicasting problem with and without packet delay. The method is based on the Hopfield neural network and experiment has shown this method to yield near optimal solutions while requiring a minimum of CPU time.

Multicast Routing Protocols, Algorithms and its QOS Extensions

2005 ◽  
pp. 2036-2041
Author(s):  
D. Chakraborty ◽  
G. Chakraborty ◽  
N. Shiratori
Keyword(s):  
Data Storage ◽  
High Speed ◽  
Multicast Routing ◽  
Multicast Communication ◽  
Delay Jitter ◽  
End To End Delay ◽  
End To End ◽  
Storage Technologies ◽  
New Applications ◽  
Audio Video

The advancement in optical fiber and switching technologies has resulted in a new generation of high-speed networks that can achieve speeds of up to a few gigabits per second. Also, the progress in audio, video and data storage technologies has given rise to new distributed real-time applications. These applications may involve multimedia, which require low end-to-end delay. The applications’ requirements, such as the end-to-end delay, delay jitter, and loss rate, are expressed as QoS parameters, which must be guaranteed. In addition, many of these new applications involve multiple users, and hence the importance of multicast communication. Multimedia applications are becoming increasingly important, as networks are now capable of carrying continuous media traffic, such as voice and video, to the end user. When there is a lot of information to transmit to a subset of hosts, then multicast is the best possible way to facilitate it. This article addresses different multicast routing algorithms and protocols. We have also discussed about the QoS multicast routing and conclude this article with mobile multicasting.

scholarly journals Comparative Performance Evaluation of On-Demand Multicast Routing Protocols for MANET

2018 ◽  
Vol 7 (S1) ◽  
pp. 123-129
Author(s):  
K. Kavitha
Keyword(s):  
Routing Protocol ◽  
Multicast Routing ◽  
High Mobility ◽  
On Demand ◽  
Control Overhead ◽  
End To End Delay ◽  
Multicast Routing Protocol ◽  
Membership Management ◽  
End To End ◽  
And Control

A Mobile Ad hoc NETwork (MANET) is a collection of wireless nodes communicating with each other in the absence of any infrastructure. Each device in a MANET is free to move independently in any direction, and will therefore change its links to other devices frequently. Each must forward traffic unrelated to its own use, and therefore be a router. The primary challenge in building a MANET is equipping each device to continuously maintain the information required to properly route traffic. Such networks may operate by themselves or may be connected to the larger Internet. In this paper, we compare the performance of On-Demand Multicast Routing Protocol (ODMRP), Adaptive demand driven Multicast Routing Protocol (ADMR) With Efficient Geographic Multicast Routing Protocol (EGMP) under different mobility models such as Random Way Point Model, Manhattan Model and Random Drunken Model. Using these models, performance metrics such as Packet Delivery Ratio, End-to-End Delay and Control Overhead are evaluated. ODMRP dynamically builds the route and manages the group membership. In ADMR, Multicast routing state is dynamically established and maintained only for active groups and only in nodes located between multicast senders and receivers. ADMR detects the high mobility without the use of GPS or other positioning system. EGMP supports a zone-based scheme to efficiently handle the two-tier membership management, and takes advantage of the membership management structure to efficiently track the locations of all the group members. The simulation result shows that the throughput of ADMR is higher than that of ODMRP and EGMP at high mobility and EGMP is high at low mobility. End to end delay and control overhead of EGMP is higher than that of ODMRP and ADMR.

scholarly journals Research and Development of Delay-Sensitive Routing Tensor Model in IoT Core Networks

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3934
Author(s):  
Oleksandr Lemeshko ◽  
Jozef Papan ◽  
Oleksandra Yeremenko ◽  
Maryna Yevdokymenko ◽  
Pavel Segec
Keyword(s):  
Research And Development ◽  
Optimality Criteria ◽  
Internal Node ◽  
Problem Solution ◽  
Tensor Model ◽  
Routing Problem ◽  
Core Networks ◽  
Delay Sensitive ◽  
End To End Delay ◽  
End To End

In the article, we present the research and development of an improved delay-sensitive routing tensor model for the core of the IoT network. The flow-based tensor model is considered within the coordinate system of interpolar paths and internal node pairs. The advantage of the presented model is the application for IoT architectures to ensure the Quality of Service under the parameters of bandwidth, average end-to-end delay, and the probability of packet loss. Hence, the technical task of delay-sensitive routing is formulated as the optimization problem together with constraints and conditions imposed on the corresponding routing variables. The system of optimality criteria is chosen for an investigation. Each selected criterion concerning the specifics of the demanded routing problem solution aims at the optimal use of available network resources and the improvement of QoS indicators, namely, average end-to-end delay. The analysis of the obtained routing solutions under different criteria is performed. Numerical research of the improved delay-sensitive routing tensor model allowed us to discover its features and proved the adequacy of the results for the multipath order of routing.

scholarly journals Exposing End-to-End Delay in Software-Defined Networking

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Ting Zhang ◽  
Bin Liu
Keyword(s):  
Large Scale ◽  
Packet Delay ◽  
Software Defined Networking ◽  
Area Network ◽  
Delay Model ◽  
Wide Area Network ◽  
Worst Case ◽  
End To End Delay ◽  
End To End ◽  
The Impact

Software-Defined Networking (SDN) shows us a promising picture to deploy the demanding services in a fast and cost-effective way. Till now, most SDN use cases are deployed in enterprise/campus networks and data center networks. However, when applying SDN to the large-scale networks, such as Wide Area Network (WAN), the end-to-end delay of packet traversal is suspected to be very large and needs to be further investigated. Moreover, stringent time constraint is the cornerstone for real-time applications in SDN. Understanding the packet delay in SDN-based large networks is crucial for the proper design of switch architecture and the optimization of network algorithms such as flow control algorithms. In this paper, we present a thorough systematic exploration on the end-to-end delay in SDN which consists of multiple nodes, fully exposing the components which contribute to the long delay. We disclose that SDN switches cannot completely avoid the generation of flow setup even in proactive mode and conduct data mining on the probability of flow setup. We propose an analytical model for the end-to-end delay. This model takes into account the impact of the different rule installation time consumption on different switches. Considering the delay in switches contributes a large proportion to the entire delay, we conduct various measurements on the delay of a single switch. Results for the delay at different flow setup rates and with different rule priority patterns are presented. Furthermore, we study the impact on packet delay caused by ternary content addressable memory (TCAM) update. We measure parameters in the delay model and find that if SDN is deployed in all segments of WAN, the delay of packet traversal will be increased up to 27.95 times in the worst case in our experimental settings, compared with the delay in conventional network. Such high delay may eventually lead the end-to-end connections fail to complete if no additional measures are taken.

Research on QoS Multicast Tree Based on Ant Colony Algorithm

2014 ◽  
Vol 635-637 ◽  
pp. 1734-1737 ◽  
Author(s):  
Yong Huang
Keyword(s):  
Data Transmission ◽  
Ant Colony Algorithm ◽  
Multicast Routing ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Multicast Tree ◽  
Ant Colony ◽  
Shortest Path Algorithm ◽  
Routing Problem ◽  
Delay Constraints

Ant colony algorithm is a stochastic search algorithm, evolutionary algorithm with other models, like the evolution of the composition of the population by the candidate solutions to find the optimal solution, this paper proposes a new ant colony algorithm to solve by bandwidth and QoS multicast routing problem delay constraints, k shortest path algorithm by means of genetic algorithm we propose obtained, and then use the ant colony algorithm to construct optimal multicast tree for data transmission.

Multicast

2002 ◽  
pp. 225-245
Author(s):  
D. Chakraborty ◽  
G. Chakraborty ◽  
N. Shiratori
Keyword(s):  
Data Storage ◽  
High Speed ◽  
Multicast Routing ◽  
Multicast Communication ◽  
Delay Jitter ◽  
End To End Delay ◽  
End To End ◽  
Storage Technologies ◽  
New Applications ◽  
Audio Video

The advancement in optical fiber and switching technologies has resulted in new generation high-speed networks that can achieve speeds of up to a few gigabits per second. Also, the progress in audio, video and data storage technologies has given rise to new distributed real-time applications. These applications may involve multimedia, which require low end-to-end delay. The applications’ requirements, such as the end-to-end delay, delay jitter, and loss rate, are expressed as QoS parameters that must be guaranteed. In addition, many of these new applications may involve multiple users, and hence the importance of multicast communication. In this chapter we discuss the basics of multicasting, its routing protocols and algorithms, along with different QoS-based multicast routing.

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