A novel IP-core mapping algorithm in reliable 3D optical network-on-chips

AbstractSurvivable virtual optical network (VON) mapping is researched to overcome the ossification of current network architectures. In this paper, we study the survivable VON mapping problem in elastic optical network (EON) with the objective of minimizing the average resource consumption of VON request. We propose a protective algorithm, namely, coordinated mapping algorithm based on minimum spanning tree (CMST), to provide the dedicated protection against the single physical link failure. In CMST, for virtual node mapping, we not only consider the resources constraint but also the node degree constraint. For virtual link mapping, we adopt the coordinated mapping method for part of the virtual nodes and virtual links. And we provide the backup path for the minimum spanning tree link of virtual topology to reduce the resource consumption. Simulation results showed that CMST can reduce the VON request blocking probability and average network resource consumption. And it can increase the revenue of physical network.

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Optimizing Crosstalk in Optical NoC through Heuristic Fusion Mapping

Electronics ◽

10.3390/electronics9061006 ◽

2020 ◽

Vol 9 (6) ◽

pp. 1006

Author(s):

Xinhao Shi ◽

Ning Wu ◽

Fen Ge ◽

Fang Zhou ◽

Muhammad Rehan Yahya

Keyword(s):

Simulated Annealing Algorithm ◽

Interconnection Network ◽

Optical Network ◽

Optical Signal ◽

Crosstalk Noise ◽

Mapping Algorithm ◽

Annealing Algorithm ◽

On Chip ◽

Mapping Scheme ◽

Better Than

Optical network-on-chip is considered to be a promising technology to solve the problems of low bandwidth and high latency in the traditional interconnection network. However, due to the inevitable leakage of optical devices, the optical signal will receive crosstalk noise during transmission. In this paper, a heuristic fusion mapping algorithm PSO_SA for crosstalk optimization is proposed. First, the initial optimal mapping is obtained by particle swarm optimization, and then the local optimization of the mapping scheme is removed by combining with simulated annealing algorithm. The experimental results show that the crosstalk optimization performance of PSO_SA algorithm is better than that of GA algorithm in 263 dec, Wavelet, DVOPD and other applications, and the maximum optimization degree is 28.7%.

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Worst-case energy consumption minimization based on interference analysis and bank mapping in multicore systems

International Journal of Distributed Sensor Networks ◽

10.1177/1550147716686969 ◽

2017 ◽

Vol 13 (2) ◽

pp. 155014771668696

Author(s):

Zhihua Gan ◽

Zhimin Gu ◽

Hai Tan ◽

Mingquan Zhang ◽

Jizan Zhang

Keyword(s):

Energy Consumption ◽

Real Time ◽

Multicore Systems ◽

Worst Case ◽

Mapping Algorithm ◽

Fine Grained ◽

Energy Consumption Reduction ◽

Deadline Constraints ◽

Core Mapping ◽

The Impact

Energy is a scarce resource in real-time embedded systems due to the fact that most of them run on batteries. Hence, the designers should ensure that the energy constraints are satisfied in addition to the deadline constraints. This necessitates the consideration of the impact of the interference due to shared, low-level hardware resources such as the cache on the worst-case energy consumption of the tasks. Toward this aim, this article proposes a fine-grained approach to analyze the bank-level interference (bank conflict and bus access interference) on real-time multicore systems, which can reasonably estimate runtime interferences in shared cache and yield tighter worst-case energy consumption. In addition, we develop a bank-to-core mapping algorithm for reducing bank-level interference and improving the worst-case energy consumption. The experimental results demonstrate that our approach can improve the tightness of worst-case energy consumption by 14.25% on average compared to upper-bound delay approach. The bank-to-core mapping provides significant benefits in worst-case energy consumption reduction with 7.23%.

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Elastic Optical Network Service-Oriented Architecture (SOA) Used for Cloud Computing and Its Resource Mapping Optimization Scheme

Journal of Nanoelectronics and Optoelectronics ◽

10.1166/jno.2020.2783 ◽

2020 ◽

Vol 15 (4) ◽

pp. 442-449

Author(s):

Xun Xia ◽

Ling Chen

Keyword(s):

Cloud Computing ◽

Load Balancing ◽

Resource Utilization ◽

Service Oriented Architecture ◽

Optical Network ◽

Spectrum Utilization ◽

Mapping Algorithm ◽

Resource Mapping ◽

Elastic Optical Network ◽

Service Oriented

In this study, starting from the elastic optical network, the layered and function isolated service-oriented architecture (SOA) is introduced, so as to propose an elastic optical network SOA for cloud computing, and further study the resource mapping of optical network. Linear mapping model, random routing mapping algorithm, load balancing mapping algorithm and link separation mapping algorithm are introduced respectively, and the resource utilization effect of different mapping algorithms for the proposed optical network is compared. During the experiment, firstly, the elastic optical network is tested. It is found that the node utilization and spectrum utilization of the underlying optical fiber level network are significantly improved. Within the average service time of 0.312 s∼0.416 s, the corresponding node utilization and spectrum utilization are 90% and 80% respectively. In the resource mapping experiment, load balancing algorithm and link separation algorithm can effectively improve the mapping success rate of services. Among them, the link separation mapping algorithm can improve the spectrum resource utilization of optical network by 15.6%. The elastic optical network SOA proposed in this study is helpful to improve the use of network resources.

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