Modeling of Clos Switching Structures with Dynamically Variable Number of Active Switches in the Spine Stage

Głąbowski, Mariusz; Sobieraj, Maciej; Stasiak, Maciej; Stasiak, Michał Dominik

doi:10.3390/electronics9071073

Cited by 8 publications

(6 citation statements)

References 41 publications

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“…The speculative demonstration has been presented by configuring 4 × 4 microring (MRRs), switch and select (S&S) to evaluate the performance of a 16 × 16 Clos network using 12.5 Gbps PAM4 signal across the network and 1.1 dB maximum power retribution at a bit error rate of 1.03 × 10 −7 [27]. Clos network has been analyzed to reduce the power consumption by switching off some switches temporarily depending on the traffic parameters at any time, also few routing techniques have been developed to improve the blocking probability, propagation time and delay along with shuffle exchange networks have been suggested for multiple stages interconnecting switch matrix [28][29][30]. For providing flexibility in terms of giving clocks to the nanocircuits the overall design has been segregated in various grids in clockwise and anticlockwise directions.…”

Section: Related Workmentioning

confidence: 99%

N譔 Clos Digital Cross-Connect Switch Using Quantum Dot Cellular Automata (QCA)

Asthana¹,

Kumar²,

Sharan³

2023

Computer Systems Science and Engineering

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Quantum dot cellular automata (QCA) technology is emerging as a future technology which designs the digital circuits at quantum levels. The technology has gained popularity in terms of designing digital circuits, which occupy very less area and less power dissipation in comparison to the present complementary metal oxide semiconductor (CMOS) technology. For designing the routers at quantum levels with non-blocking capabilities various multi-stage networks have been proposed. This manuscript presents the design of the NÂN Clos switch matrix as a multistage interconnecting network using quantum-dot cellular automata technology. The design of the Clos switch matrix presented in the article uses three input majority gates (MG). To design the 4 × 4 Clos switch matrix, a basic 2 × 2 switch architecture has been proposed as a basic module. The 2 × 2 switching matrix (SM) design presented in the manuscript utilizes three input majority gates. Also, the 2 × 2 SM has been proposed using five input majority gates. Two different approaches (1&2) have been presented for designing 2 × 2 SM using five input majority gates. The 2 × 2 SM design based on three input majority gate utilizes four zone clocking scheme to allow signal transmission. Although, the clocking scheme used in 2 × 2 SM using three input MG and in 2 × 2 SM approach 1 using five input MG is conventional. The 2 × 2 SM approach 2 design, utilizes the clocking scheme in which clocks can be applied by electric field generators easily and in turn the switch element becomes physically realizable. The simulation results conclude that the 2 × 2 SM is suitable for designing a 4 × 4 Clos network. A higher order of input-output switching matrix, supporting more number of users can utilize the proposed designs.

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Section: Related Workmentioning

confidence: 99%

N譔 Clos Digital Cross-Connect Switch Using Quantum Dot Cellular Automata (QCA)

Asthana¹,

Kumar²,

Sharan³

2023

Computer Systems Science and Engineering

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“…Based on (29), we can now compute the CBP due to lack of computational RUs and radio RUs via (30) and (31), respectively:…”

Section: Cbp Based On a Convolution Algorithmmentioning

confidence: 99%

Multiservice Loss Models for Cloud Radio Access Networks

et al. 2021

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In this paper, a cloud radio access network (C-RAN) is considered where the remote radio heads (RRHs) are separated from the baseband units which form a common pool of computational resource units. Depending on their capacity, the RRHs may form one or more clusters. Each RRH accommodates multiservice traffic, i.e., calls from different service-classes with different radio and computational resource requirements. Arriving calls follow a Poisson process and simultaneously require radio and computational resource units in order to be accepted in the serving RRH. If their resource requirements cannot be met then calls are blocked and lost. Otherwise, calls remain in the serving RRH for a generally distributed service time. Assuming the single-cluster C-RAN, we model it as a multiservice loss system, prove that a product form solution exists for the steady-state probabilities and determine call blocking probabilities via an efficient convolution algorithm whose accuracy is validated via simulation. Furthermore, we generalize the previous multiservice loss model by considering the more complex multi-cluster case where RRHs of the same capacity are grouped in different clusters.

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“…More specifically, they require a single RRU (from the RRH that will serve them) and a single CRU from the BBU pool. However, in contemporary networks it is essential, for network planning, to consider a multiservice environment where MUs generate calls of various resource requirements [34][35][36][37][38][39][40][41][42][43][44][45][46]. In [45], we introduced two such multirate loss models for the C-RAN architecture and named them multi-class single-cluster and multiclass multi-cluster models (MC-SC and MC-MC, respectively).…”

Section: Introductionmentioning

confidence: 99%

Multiservice Loss Models in C-RAN Supporting Compound Poisson Traffic

et al. 2022

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In this paper, a cloud radio access network (C-RAN) is considered where the baseband units form a pool of computational resource units (RUs) and are separated from the remote radio heads (RRHs). The RRHs are grouped into clusters based on their capacity in radio RUs. Each RRH serves different service-classes whose calls have different requirements in terms of radio and computational RUs and follow a compound Poisson process. This means that calls arrive in batches while each batch of calls follows a Poisson process. If the RUs’ requirements of an arriving call are met, then the call is accepted in the serving RRH for an exponentially distributed service time. Otherwise, call blocking occurs. We initially start our analysis with a single-cluster C-RAN and model it as a multiservice loss system, prove that the model has a product form solution, and determine time and call congestion probabilities via a convolution algorithm. Furthermore, the previous model is extended to include the more complex case of many clusters of RRHs.

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Modeling of Clos Switching Structures with Dynamically Variable Number of Active Switches in the Spine Stage

Cited by 8 publications

References 41 publications

N譔 Clos Digital Cross-Connect Switch Using Quantum Dot Cellular Automata (QCA)

N譔 Clos Digital Cross-Connect Switch Using Quantum Dot Cellular Automata (QCA)

Multiservice Loss Models for Cloud Radio Access Networks

Multiservice Loss Models in C-RAN Supporting Compound Poisson Traffic

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