Abstract

Datacenter-based Cloud Computing services provide a flexible, scalable and yet economical infrastructure to host online services such as multimedia streaming, email and bulk storage. Many such services perform geo-replication to provide necessary quality of service and reliability to users resulting in frequent large inter- datacenter transfers. In order to meet tenant service level agreements (SLAs), these transfers have to be completed prior to a deadline. In addition, WAN resources are quite scarce and costly, meaning they should be fully utilized. Several recently proposed schemes, such as B4, TEMPUS, and SWAN have focused on improving the utilization of inter-datacenter transfers through centralized scheduling, however, they fail to provide a mechanism to guarantee that admitted requests meet their deadlines. Also, in a recent study, authors propose Amoeba, a system that allows tenants to define deadlines and guarantees that the specified deadlines are met, however, to admit new traffic, the proposed system has to modify the allocation of already admitted transfers. In this paper, we propose Rapid Close to Deadline Scheduling (RCD), a close to deadline traffic allocation technique that is fast and efficient. Through simulations, we show that RCD is up to 15 times faster than Amoeba, provides high link utilization along with deadline guarantees, and is able to make quick decisions on whether a new request can be fully satisfied before its deadline.

Highlights

  • Cloud Computing [5] has changed the way IT services are provisioned, managed, and delivered to users

  • Elastic: Traffic requests of this type have to be fully satisfied before their deadline

  • We proposed Rapid Close to Deadline Scheduling (RCD), a technique that makes fast scheduling of bandwidth resources possible for large transfers with specific deadlines, provides deadline guarantees, and allows for maximum bandwidth utilization

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Summary

INTRODUCTION

Cloud Computing [5] has changed the way IT services are provisioned, managed, and delivered to users. To improve service provisioning, such infrastructures are usually spanned over multiple physical sites (multiple datacenters) closer to customers [8] This allows for higher reliability by keeping extra copies of user data on different datacenters. Many applications require traffic exchange between datacenters to synchronize data, access backup copies or perform geo-replication; examples of which include content delivery networks (CDNs), cloud storage and search and indexing services. Most of these transfers have to be completed prior to a deadline which is usually within the range of an hour to a couple of days and can be as large as petabytes [2]. We first explain the problem of scheduling, present the rules based on which RCD operates, and compare RCD with Amoeba through simulations

THE SCHEDULING PROBLEM
Background
RAPID CLOSE TO DEADLINE SCHEDULING
SIMULATION RESULTS
RCD IN NETWORK
CONCLUSIONS AND FUTURE WORK
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