mtCloudSim: A Flow-Level Network Simulator for Multi-Tenant Cloud

Currently, novel topologies and advanced resource allocation strategies for multi-tenant cloud datacenters are two research hotspots. Due to the high convenience and efficiency, researchers tend to use simulation to evaluate the proposed topologies or strategies. However, the current network simulators do not support the multi-tenant cloud environment inherently. Moreover, the low simulation speed and high memory consumption limit the traditional packet-level simulators to estimate the scenario of large-scale datacenters. In this paper, we propose a new flow-level network simulator, mtCloudSim, to overcome the above issues. The simulator estimates the data flow's behavior in the real world, i.e., 1) increasing the sending rate when the network is not busy and 2) suspending when the congestion occurs. Bandwidth isolation is inherently provided and users are allowed to define bandwidth requirement for the experiments with our simulator. Object-oriented programming (OOP) makes it easy to evaluate novel network topologies. The tracing system is also able to generate abundant and detailed statistics for experiments. The experiments demonstrate that mtCloudSim is available for multi-tenant cloud evaluation.

[1]  Dzmitry Kliazovich,et al.  GreenCloud: A Packet-Level Simulator of Energy-Aware Cloud Computing Data Centers , 2010, GLOBECOM.

[2]  Vishal Misra,et al.  Fluid-based analysis of a network of AQM routers supporting TCP flows with an application to RED , 2000, SIGCOMM.

[3]  Haitao Wu,et al.  BCube: a high performance, server-centric network architecture for modular data centers , 2009, SIGCOMM '09.

[4]  David A. Maltz,et al.  Data center TCP (DCTCP) , 2010, SIGCOMM 2010.

[5]  Sujata Banerjee,et al.  ElasticSwitch: practical work-conserving bandwidth guarantees for cloud computing , 2013, SIGCOMM.

[6]  Helen J. Wang,et al.  SecondNet: a data center network virtualization architecture with bandwidth guarantees , 2010, CoNEXT.

[7]  Ross Mcnab,et al.  Simjava: A Discrete Event Simulation Library For Java , 1998 .

[8]  Hiroyuki Ohsaki,et al.  Design and Implementation of Flow-Level Simulator for Performance Evaluation of Large Scale Networks , 2007, 2007 15th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems.

[9]  Haitao Wu,et al.  FiConn: Using Backup Port for Server Interconnection in Data Centers , 2009, IEEE INFOCOM 2009.

[10]  Amin Vahdat,et al.  PortLand: a scalable fault-tolerant layer 2 data center network fabric , 2009, SIGCOMM '09.

[11]  Amin Vahdat,et al.  A scalable, commodity data center network architecture , 2008, SIGCOMM '08.

[12]  Amin Vahdat,et al.  Jupiter Rising: A Decade of Clos Topologies and Centralized Control in Google's Datacenter Network , 2015, Comput. Commun. Rev..

[13]  Yuhui Deng,et al.  Skewly replicating hot data to construct a power-efficient storage cluster , 2015, J. Netw. Comput. Appl..

[14]  Yifeng Zhu,et al.  Predictively booting nodes to minimize performance degradation of a power-aware web cluster , 2014, Cluster Computing.

[15]  Kaishun Wu,et al.  Rethinking the architecture design of data center networks , 2012, Frontiers of Computer Science.

[16]  Amin Vahdat,et al.  Hedera: Dynamic Flow Scheduling for Data Center Networks , 2010, NSDI.

[17]  Jogesh K. Muppala,et al.  DCNSim: A Data Center Network Simulator , 2013, 2013 IEEE 33rd International Conference on Distributed Computing Systems Workshops.

[18]  Amin Vahdat,et al.  Less Is More: Trading a Little Bandwidth for Ultra-Low Latency in the Data Center , 2012, NSDI.

[19]  Sujata Banerjee,et al.  Application-driven bandwidth guarantees in datacenters , 2015, SIGCOMM.

[20]  Yuhui Deng,et al.  Totoro: A Scalable and Fault-Tolerant Data Center Network by Using Backup Port , 2013, NPC.

[21]  Rajkumar Buyya,et al.  GridSim: a toolkit for the modeling and simulation of distributed resource management and scheduling for Grid computing , 2002, Concurr. Comput. Pract. Exp..

[22]  Ion Stoica,et al.  FairCloud: sharing the network in cloud computing , 2011, SIGCOMM '12.

[23]  Rajkumar Buyya,et al.  Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: Challenges and opportunities , 2009, 2009 International Conference on High Performance Computing & Simulation.

[24]  Albert G. Greenberg,et al.  EyeQ: Practical Network Performance Isolation at the Edge , 2013, NSDI.

[25]  Lei Shi,et al.  Dcell: a scalable and fault-tolerant network structure for data centers , 2008, SIGCOMM '08.

[26]  Donald F. Towsley,et al.  Fluid models and solutions for large-scale IP networks , 2003, SIGMETRICS '03.