Mathematical Optimization Modelling for Fast-Switched and Delay Minimized Scheduling for Intra-Cell Communication in an AWGR-Based PON Data Center

• 作者: Ali Hammadi
• 来源期刊: 通讯、网络与系统学国际期刊(英文)
• 学科: 医学
• 关键词: PONS Data Center Networks AWGR Energy Efficiency SCHEDULING Optimization
• 年，卷（期）: 2017,（2）
• 页码范围: 13-29
• 页数: 17页
• 分类号: R73

摘要

As the internet traffic along with the processing power in data centers are exponentially growing, the need for the design of energy efficient with highly elastic networking infrastructure to support the different applications and cloud services that can be hosted in data centers have become a hot research area. A key departure from the norm is that conventional routers and switches in conventional data centers are replaced with high performance Passive Optical Networks (PONs) to take over the role of routing and traffic forwarding through efficient resource provisioning algorithms. In this paper, the different aspects of PONs in the design of energy efficient, high capacity, and highly elastic networking infrastructures to support the applications and services hosted by modern data centers are considered. In this work, a mathematical optimization model for energy-efficient and delay-minimized scheduling in AWGR based PON data center for PON cell fabric configuration will be presented. The performance of the proposed architecture in terms of efficient scheduling against average delay and power consumption for different traffic loads and patterns will be evaluated. Different scenarios of traffic;random and unbalanced with hotspots are examined to evaluate the average delay and power consumption with and without sleep mode. Results have shown that with sleep mode enabled, power savings for two evaluated objective functions have shown similar results when examining different traffic patterns. The power savings range between 8% and 55% during low and high load activities, respectively. However, minimization of delay model has shown improvement in reducing total average delay reaching up to 42% if compared with the model with objective of minimization of power consumption.