Adaptive Routing Strategy for Large Scale Rearrangeable Symmetric Networks

2010 ◽  
Vol 2 (2) ◽  
pp. 53-63 ◽  
Author(s):  
Amitabha Chakrabarty ◽  
Martin Collier ◽  
Sourav Mukhopadhyay
Keyword(s):  
Large Scale ◽  
Blocking Probability ◽  
Routing Algorithm ◽  
Adaptive Routing ◽  
Low Complexity ◽  
Deterministic Algorithms ◽  
Routing Strategy ◽  
The Status ◽  
Extensive Computation ◽  
Symmetric Networks

This paper proposes an adaptive unicast routing algorithm for large scale symmetric networks comprising 2 × 2 switch elements such as Bene?s networks. This algorithm trades off the probability of blocking against algorithm execution time. Deterministic algorithms exploit the rearrangeability property of Bene?s networks to ensure a zero blocking probability for unicast connections, at the expense of extensive computation. The authors’ algorithm makes its routing decisions depending on the status of each switching element at every stage of the network, hence the name adaptive routing. This method provides a low complexity solution, but with much better blocking performance than random routing algorithms. This paper presents simulation results for various input loads, demonstrating the tradeoffs involved.

Adaptive Routing Strategy for Large Scale Rearrangeable Symmetric Networks

2012 ◽  
pp. 212-222
Author(s):  
Amitabha Chakrabarty ◽  
Martin Collier ◽  
Sourav Mukhopadhyay
Keyword(s):  
Large Scale ◽  
Blocking Probability ◽  
Routing Algorithm ◽  
Adaptive Routing ◽  
Low Complexity ◽  
Deterministic Algorithms ◽  
The Status ◽  
Extensive Computation ◽  
Benes Networks ◽  
Symmetric Networks

This paper proposes an adaptive unicast routing algorithm for large scale symmetric networks comprising 2 × 2 switch elements such as Beneš networks. This algorithm trades off the probability of blocking against algorithm execution time. Deterministic algorithms exploit the rearrangeability property of Beneš networks to ensure a zero blocking probability for unicast connections, at the expense of extensive computation. The authors’ algorithm makes its routing decisions depending on the status of each switching element at every stage of the network, hence the name adaptive routing. This method provides a low complexity solution, but with much better blocking performance than random routing algorithms. This paper presents simulation results for various input loads, demonstrating the tradeoffs involved.

scholarly journals CSA: A Route Clonal Selection Algorithm for Dynamic WDM Networks

2011 ◽  
Vol 7 (4) ◽  
pp. 121
Author(s):  
M.Taynnan Barros ◽  
P.R. Lins Junior ◽  
M.Sampaio Alencar
Keyword(s):  
Clonal Selection ◽  
Fitness Function ◽  
Blocking Probability ◽  
Optical Network ◽  
Routing Algorithm ◽  
Adaptive Routing ◽  
Traffic Grooming ◽  
Wdm Networks ◽  
Clonal Selection Algorithm ◽  
Network Equipment

The minimization of blocking probability is an important problem for the design of next generation high speednetworks. This problem is usually approached with an adaptive routing algorithm with traffic grooming, that is costly regarding improvements on network equipment. This paper presents the Clonal Selection Adaptive Routing Algorithm (CSA), a new routing algorithm for use in dynamic optical network. The algorithm uses a fitness function which adapts the route selection cost, minimizing the blocking. Its performance was evaluated considering the blocking probability with three different topologies, for high traffic, compared to the adaptive routing algorithm with traffic grooming. The results present a higher gain for the proposed approach, with no need to improvement on network equipment or conversion capabilities.

An adaptive routing algorithm for integrated information networks

2019 ◽  
Vol 16 (7) ◽  
pp. 195-206 ◽  
Author(s):  
Feng Wang ◽  
Dingde Jiang ◽  
Sheng Qi
Keyword(s):  
Routing Algorithm ◽  
Adaptive Routing ◽  
Information Networks ◽  
Integrated Information

scholarly journals Low-complexity sparse-aware multiuser detection for large-scale MIMO systems

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Rong Ran ◽  
Hayoung Oh
Keyword(s):  
Large Scale ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Finite Alphabet ◽  
Multiuser Detectors ◽  
Input Multiple Output ◽  
Error Detector ◽  
Significant Performance

AbstractSparse-aware (SA) detectors have attracted a lot attention due to its significant performance and low-complexity, in particular for large-scale multiple-input multiple-output (MIMO) systems. Similar to the conventional multiuser detectors, the nonlinear or compressive sensing based SA detectors provide the better performance but are not appropriate for the overdetermined multiuser MIMO systems in sense of power and time consumption. The linear SA detector provides a more elegant tradeoff between performance and complexity compared to the nonlinear ones. However, the major limitation of the linear SA detector is that, as the zero-forcing or minimum mean square error detector, it was derived by relaxing the finite-alphabet constraints, and therefore its performance is still sub-optimal. In this paper, we propose a novel SA detector, named single-dimensional search-based SA (SDSB-SA) detector, for overdetermined uplink MIMO systems. The proposed SDSB-SA detector adheres to the finite-alphabet constraints so that it outperforms the conventional linear SA detector, in particular, in high SNR regime. Meanwhile, the proposed detector follows a single-dimensional search manner, so it has a very low computational complexity which is feasible for light-ware Internet of Thing devices for ultra-reliable low-latency communication. Numerical results show that the the proposed SDSB-SA detector provides a relatively better tradeoff between the performance and complexity compared with several existing detectors.

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