Multi-path routing based on load-balance for cognitive packet networks

doi:10.1016/S1005-8885(10)60106-9

The Journal of China Universities of Posts and Telecommunications

Volume 18, Issue 5, October 2011, Pages 71-75

https://doi.org/10.1016/S1005-8885(10)60106-9 Get rights and content

Abstract

Quality of service (QoS) routing algorithms have been hardly discussed in the scientific community, most previous work on QoS routing concentrates on the performance of the single route. Cognitive packet network (CPN) has been designed for providing QoS routing. In this paper, to balance the loads among networks, we present a multi-path routing algorithm based on load-balance (MPRLB), which is carried out in two steps. The algorithm with low computational complexity is firstly applied to establish multi path routing for each source and destination node pairs (SD-pair) nodes in the network. Then, we propose the hopfield neural network algorithm, which is applied to improve the efficiency of the flow deviation method for fast flow allocation among the links of the network based on load balance. Extensive simulation results demonstrate that the proposed scheme significantly improves the performance compared with the existing scheme that ignores load balancing.

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Cited by (2)

Smart data packet ad hoc routing protocol
2014, Computer Networks
Citation Excerpt :
CPN has been used as routing protocol for ad hoc network in [28,29]. In [30] the authors present a multiple path approach for CPN in order to perform load balance among all network nodes. The algorithm carried out in two steps.
This paper introduces a smart data packet routing protocol (SMART) based on swarm technology for mobile ad hoc networks. The main challenge facing a routing protocol is to cope with the dynamic environment of mobile ad hoc networks. The problem of finding best route between communication end points in such networks is an NP problem. Swarm algorithm is one of the methods used solve such a problem. However, copping with the dynamic environment will demand the use of a lot of training iterations. We present a new infrastructure where data packets are smart enough to guide themselves through best available route in the network. This approach uses distributed swarm learning approach which will minimize convergence time by using smart data packets. This will decrease the number of control packets in the network as well as it provides continues learning which in turn provides better reaction to changes in the network environment. The learning information is distributed throughout the nodes of the network. This information can be used and updated by successive packets in order to maintain and find better routes. This protocol is a hybrid Ant Colony Optimization (ACO) and river formation dynamics (RFD) swarm algorithms protocol. ACO is used to set up multi-path routes to destination at the initialization, while RFD mainly used as a base algorithm for the routing protocol. RFD offers many advantages toward implementing this approach. The main two reasons of using RFD are the small amount of information that required to be added to the packets (12 bytes in our approach) and the main idea of the RFD algorithm which is based on one kind of agent called drop that moves from source to destination only. This will eliminate the need of feedback packets to update the network and offers a suitable solution to change data packet into smart packets. Simulation results shows improvement in the throughput and reduction in end to end delay and jitter compared to AODV and AntHocNet protocols.
Research on a congestion perception routing algorithm
2014, Gaojishu Tongxin/Chinese High Technology Letters

View full text

The Journal of China Universities of Posts and Telecommunications

Multi-path routing based on load-balance for cognitive packet networks

Abstract

Design and performance of cognitive packet networks

Performance Evaluation

An efficient tile-based ECO router using routing graph reduction and enhanced global routing flow

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

Cognitive packet networks: QoS and performance

Can routing oscillations be good? the benefits of route-switching in self-aware networks

Neural networks for routing communication traffic

IEEE Control Systems Magazine

Smart data packet ad hoc routing protocol

Research on a congestion perception routing algorithm