iCanCloud: A Flexible and Scalable Cloud Infrastructure Simulator

Abstract

Simulation techniques have become a powerful tool for deciding the best starting conditions on pay-as-you-go scenarios. This is the case of public cloud infrastructures, where a given number and type of virtual machines (in short VMs) are instantiated during a specified time, being this reflected in the final budget. With this in mind, this paper introduces and validates iCanCloud, a novel simulator of cloud infrastruc-tures with remarkable features such as flexibility, scalability, performance and usability. Further-more, the iCanCloud simulator has been built on the following design principles: (1) it's targeted to conduct large experiments, as opposed to oth-ers simulators from literature; (2) it provides a flexible and fully customizable global hypervisor for integrating any cloud brokering policy; (3) it reproduces the instance types provided by a given cloud infrastructure; and finally, (4) it contains a user-friendly GUI for configuring and launching simulations, that goes from a single VM to large cloud computing systems composed of thousands of machines.Keywords Cloud computing · Cloud computing simulator · Cloud hypervisor · Validation · Scalability 1 to solve a given computational problem. If the same software and configurations are needed, the VMs may be started using the same image. This way, a machine offered by a computing cloud may become whatever the user needs, from a standalone computer to a cluster or Grid node.Nowadays, cloud computing systems are increasing their role due to the fast (r)evolution of computer networks and communication technologies. A very clear proof of this fact is that very important companies like Amazon, Google, Dell, IBM, and Microsoft are investing billions of dollars in order to provide their own cloud solutions [28].As soon as the scientific community had access to cloud production infrastructures, the first applications started to run on the cloud [26,34]. In many Research areas, the leap from traditional cluster and Grid computing to this new paradigm has been mandatory, being the main reason an evolution in the computational needs of the applications [10]. A remarkable fact from this evolution is that in a pre-cloud environment, hardware defines the level of parallelism of an application. In cloud computing, the level of parallelism is defined by the application itself, as there is no restriction in the number of machines, and CPU availability is 100% guaranteed by standard.There

A Study on Simulation Tools in Cloud Computing

“…Nunez et al [23] have built up the recreation stage "iCanCloud". This test system can foresee the exchange offs amongst cost and execution of a given arrangement of utilizations executed in a particular equipment.…”

ICARO Cloud Simulator exploiting knowledge base

“…MDCSim is a library and does not provide a user interface, thus forcing to cloud configuration and related workload programming; therefore it shows limited capabilities in both modeling and simulating complex business configurations which change over time. iCanCloud [18] was developed with the aim of solving some of the limitation of CloudSim, GreenCloud and MDCSim. It is based on SIMCAN, OMNET, MPI, and provides the modeling of the infrastructure permitting the modeling of the hypervisor (with its related math model that could be used for any estimation of power consumption, temperature, costs, etc.)…”

“…To this purpose, a number of simulators are based on direct math model for: energy consumption (relating clock, storage access, and bandwidth to power consumption and temperature), network simulation in terms of packets, storage and database simulation in terms of latency, etc. For such reasons, it is very complex to make a full comparison of the different clouds, since the consumed memory and speed in simulation strongly depend on the resource and the adopted mathematical models [18] .…”

“…In the literature, a number of cloud simulators allows any reasoning on cloud configurations, mainly addressing low level aspects of communicating processes on cloud such as CloudSim [7] , NetworkCloudSim [10] , and MDCSim [13] , or on energy consumption as GreenCloud [11] , iCanCloud [18] even modeling the hardware aspects. A survey on mathematical models for cloud simulation is offered in [23] .…”

A survey on formal active and passive testing with applications to the cloud

“…Researchers have designed cloud models and then performed adhoc testing by manually simulating different scenarios and comparing obtained results. Among the available simulation tools that can be used to model and simulate cloud computing environments are CloudSim [12], GreenCloud [38], SimGrid [14], Virtual-GEMS [26] and iCanCloud [61].…”