2017 16th International Conference on Optical Communications and Networks (ICOCN)
Latency and Efficiency Driven Dynamic Content Replacement in Elastic Optical Datacenter Networks Tao Gao, Xin Li, Bingli Guo, Shan Yin, Haibin Huang, Shanguo Huang State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijing, 100876, China,
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ABSTRACT We study the problem of dynamic content replacement in terms of network state variation in elastic optical datacenter networks. A dynamic content replacement scheme is proposed to minimize spectrum consumption, blocking probability and network latency. Keywords: Dynamic content replacement, Elastic optical datacenter networks, Low-latency, Spectrumefficient
result in high cost of storage and long content consistency latency (i.e. synchronization time) [6]. Furthermore, the distribution of content should be dynamically replaced to be nearer to the users requesting it such that the spectrum resource consumption can be decreased. With the factors above taken into consideration, we proposed a latency and efficiency driven dynamic content replacement (LEDCR) scheme in elastic optical datacenter networks. Simulation results show that the LE-DCR scheme achieves great network performance including spectrum resource utilization, blocking probability, and network latency.
1. INTRODUCTION
2. LATENCY AND EFFICIENCY MEASUREMENT
Recently, the rapid growth of high-rate applications has accelerated advanced optical network technology such as optical orthogonal frequency-division multiplexing (OFDM) [1] employed in datacenter networks, which refers to the elastic optical datacenter networks. The requests of users can be served by the closest datacenter hosting the corresponding content (applications) with low latency and high spectrum efficiency in elastic optical datacenter networks, as the concept of content connectivity defined in [2]. The new-type end-to-content requests further improve the survivability and decrease the spectrum consumption compared with traditional endto-end requests due to its high flexibility and redundancy of routing paths [3]. Nevertheless, the distribution of content and its adaptation to the variation of network state have a direct impact on the performance of networks such as resource utilization and network latency since the location of the datacenter is difficult to readjust as long as it has been constructed. Consequently, the optimal design and dynamic replacement of content appears to be a crucial problem. Authors in [4] proposed a dynamic content placement scheme to reduce expected content loss. A fast and coordinated content backup scheme among datacenters was proposed in [5]. Compared with disaster based content placement, researches on dynamic content replacement as per network state variation to improve spectrum efficiency and user QoS are rare. In this study, we address the problem of dynamic content replacement in elastic optical datacenter networks for achieving better network performance as well as greater user experience (i.e. QoS). Though requests of users can be served with low latency in the case of content being extensively distributed, more replications of content
In elastic optical datacenter networks, the users are supposed to be served by the closest datacenter hosting the requested content in terms of access latency. We introduce the concept of access latency Lat(u, d) between a user u and a datacenter d in [6]. Lat(u, d)=dis(u, d)/s+h(u, d)·LATh where dis(u, d) and h(u, d) are the distance and hops of path from u to d respectively, s is the propagation speed of light on fiber and LATh is an average latency per hop. Since the content among datacenters should remain the same, we define the consistency latency Lat(d1, d2) as the time required to synchronize content from datacenter d1 to d2. Access latency and consistency latency are contradictory as placing content in distant datacenters can reduce access latency for widely distributed users but increase consistency latency. We minimize access latency for users on the premise that consistency latency constraint is satisfied. To minimize the spectrum consumption over all networks, we evaluate the frequency slots (FSs) occupied by all the users requesting content c by the equaltion FSO = ¦ h ( r )
