Smart Virtual Machine Research Articles

On the Carbon Footprint Optimization in an InterCloud Environment

In this paper, we address the problem of Virtual Machine (VM) placement in an InterCloud with regard to the reduction of carbon footprint in such computing environment. In order to minimize data centers’ Greenhouse Gas (GhG) emissions, this paper proposes a mathematical formulation, where the placement approach is stated as a Mixed-Integer Nonlinear Programming (MINLP) problem which aims at minimizing the carbon footprint of the InterCloud. The proposed formulation presents an accurate carbon footprint evaluation based on joint optimization techniques, such as smart and performance-aware workload consolidation, along with cooling efficiency maximization, while considering the greenness factor of the data centers and the dynamic behavior of the equipment cooling fans. Simulations with an exact method showed that, compared with other baseline approaches, the proposed mathematical model leads to optimal configurations with minimal GhG emissions in a single cloud, as well as in an InterCloud environment, and can yield savings of up to 65 percent. The proposed model has also been compared with an approach that performs blind VM consolidation, and the obtained results showed that such model can simultaneously lead to VM configuration that yields the minimum carbon footprint while performing smart VM consolidation in order to prevent Service Level Agreement (SLA) violations.

Offloading Method for Efficient Use of Local Computational Resources in Mobile Location-Based Services Using Clouds

With the development of mobile computing, location-based services (LBSs) have been developed to provide services based on location information through communication networks or the global positioning system. In recent years, LBSs have evolved into smart LBSs, which provide many services using only location information. These include basic services such as traffic, logistic, and entertainment services. However, a smart LBS may require relatively complicated operations, which may not be effectively performed by the mobile computing system. To overcome this problem, a computation offloading technique can be used to perform certain tasks on mobile devices in cloud and fog environments. Furthermore, mobile platforms exist that provide smart LBSs. The smart cross-platform is a solution based on a virtual machine (VM) that enables compatibility of content in various mobile and smart device environments. However, owing to the nature of the VM-based execution method, the execution performance is degraded compared to that of the native execution method. In this paper, we introduce a computation offloading technique that utilizes fog computing to improve the performance of VMs running on mobile devices. We applied the proposed method to smart devices with a smart VM (SVM) and HTML5 SVM to compare their performances.

Design and Implementation of the Debugger for Smart Cross Platform

Virtual machine technology is one of core technologies for mobile, cloud, and IoT, which is intended to provide environments independent of certain hardware. The scope of utilization of virtual machines is being widened further because virtual machines simplify complicated execution and development environments fragmented by type of devices or platforms and provide consistent program development methods and common execution methods. Smart virtual machine (SVM) is a software processor that can be loaded on various devices such as smart devices and embedded devices and are core modules of smart cross platforms for providing language/platform-independent functions to users in order to improve the reusability of contents. SVM supports programming languages such as C/C++, Java, and Objective C and diverse execution environments such as Android, iOS, Linux, and Windows. In the present paper, a debugger for more effective support for the development of SVM applications was designed and implemented. Through analysis of existing diverse debug file formats, a debug file format that can cover the diverse languages and execution environments supported by SVM was designed, assemblers and compilers were expanded based on the designed debug file format, and debugging processes were shown in which a debugger was implemented using the proposed debug file format.

Design and Implementation of a Native Interface for using Native Features on Smart Virtual Machine

Unlike physical systems consisting of hardware, virtual machines are conceptual computers in logical configurations made of software. Although programs implemented in virtual machine environments have platform-independent characteristics, their performance is low in terms of implementation speed and they cannot implement those parts that are dependent on the platform by themselves. In addition, they have the shortcoming of being unable to reuse those libraries and programs that are written in the native language. In the present paper, a study for provision of native interfaces of smart virtual machines (SVMs) is introduced. The native interfaces of existing systems were analyzed to define a native interface protocol for SVMs, an interface definition language and an interface generator were designed for effective use of the defined native interface protocol, and the operation of the implemented native interface was verified through experiments. The native interface proposed in the present paper consists of items and rules necessary for information transmission between virtual machine environments and native environments, interface definition files necessary to deliver information on native functions to virtual machines, and functions and data types necessary for native environment to receive information from virtual machine environments. Through such native interfaces, virtual machine environment developers can use environment-dependent function without modifying virtual machine environments.

Smart Virtual Machine Placement Using Learning Automata to Reduce Power Consumption in Cloud Data Centers

Today, cloud computing is one of the most challenging research topics in the field of information technology. It is so important for computer researchers that it was included on a list of top ten technologies in the world. Data centers include reservoirs where processing power can meet the needs of many users computing. The popularity and acceptance of cloud computing has increased the number of these centers in recent years. One of the challenging issues in cloud computing environments is high energy consumption in data centers, which has been ignored in the corporate competition to develop data centers. High energy consumption by data centers leads to increased costs, as well as CO2 emissions. Researchers are now struggling to find an effective approach to decrease energy consumption in data centers. In recent years, many attempts have been made to reduce the power consumption of data centers, and many approaches have been proposed to reduce power consumption, such as hardware and software approaches and approaches using virtualization technology. In fact, placement of a virtual machine (VM) means finding a suitable physical place for the VM. The placement goal can either maximize the usage of available resources or it can save power by being able to shut down some servers. In this paper, we present an approach based on a best-fit decreasing (BFD) algorithm, which uses learning automata to reach a compromise between decreasing energy consumption and violating service level agreements.

Design and Implementation of HTML5 based SVM for Integrating Runtime of Smart Devices and Web Environments

Current mobile environments, smart device platforms and web based platform are emerged. The smart device platforms are represented by Apple’s iOS and Google's Android, and web based platform’s core is HTML5. Our previous researches are focused on integrating the developmental environments of smart devices and producing the same runtime environment. The Smart Cross Platform - our research result - guarantees content compatibility on various smart devices and supports multiple programming languages like C/C++, Java, and Objective-C which is a solution to increase developmental productivity. The SVM (Smart Virtual Machine) is the core virtual machine of the smart cross platform. But the Smart Cross Platform and the SVM is not cover the web environment like HTML5. In this paper, a technique which allows previous SVM which operates on smart devices to operate on web environment is introduced. In order to provide SVM in a web environment, an interpreter includes SIL code that was designed and implemented in JavaScript. Each SIL code’s semantics are reflected by JavaScript and an HTML5 based API and event model was combined to construct the overall SVM. In the whole design and implementation of the SVM which operates in the web based environment, this paper focuses on the interpreter which is a method to execute the contents. The implemented interpreter loads the SVM contents, creates a list of commands, analyzes on a stack base, executes the commands and reflects the results on the internal memory and status.

Design and Implementation of the Smart Virtual Machine on iOS Platform for the Mobile Game Portability

Development of computing environments and mobile devices lead to rapid growth of smart device, mobile OS and application market. Especially, the mobile platform sector with major runners of Apple and Google, compose the core technology for mobile applications. iOS and Android represent mobile platforms each supporting individual execution environment, development tools and development methodology. Applications and contents developed in each platform inevitably have exclusive properties in the other platforms. Therefore, generally it is not possible to execute a mobile application on a different platform. In order to provide service to multiple platforms by portability, additional costs and development period is required. Particularly, the lifespan and development duration of mobile applications are becoming shorter at this point in time. Therefore, fast development and deployment is required and has been standing out as a weakness. Smart Cross Platform is a virtual machine based solution developed to resolve this weakness. In this paper, Smart Cross Platform's content execution component, Smart Virtual Machine based on an independent neutral language was designed and implemented to be run in iOS. In the Smart Virtual Machine, the programmer can make a program not being restricted to the development language of a particular platform environment, making it is easier to port previous contents or provide service of a single program to multiple platforms.

A Study on the Interpretation Optimization to Improve the Performance of the Stack based Virtual Machine on Smart Platforms

The previous development environments for smart phone contents are needed to generate specific target code depending on target devices or platforms, and each platform has its own developing language. Therefore, even if the same contents are to be used, it must be redeveloped depending on the target machine and a compiler for that specific machine is needed, making the contents development process very inefficient. The Smart Cross Platform was developed for executing contents written in various programming languages – C, C++, Java, and Objective-C – on iOS or Android based smart devices. The contents developed in each programming language are translated into intermediate language called SIL (Smart Intermediate Language) by the compiler. And, the translation results - intermediate programs are executed on the SVM (Smart Virtual Machine) – a core module of the Smart Cross Platform – without device dependency. Intermediate language based SVM has an advantage of execution on multiple target devices without considerations about device specific features, but it has also a problem which low performance by the software-based execution, consequently. Therefore, to improve the performance of SVM is very important issue. In this paper, we deal with two kinds of optimization technique to optimize stack based SVM which can execute on various smart devices. And, to improve performance of the SVM on execution engine aspect, we apply the one of these optimization techniques. For verification of this optimization technique, we profile and analyze performance of the original/optimized SVM. As a result of the experiments, the optimized SVM has 23~27% reduced execution times than the original SVM.

A Study on the SIL Codes based Java Compiler for Supporting the Java Contents in the Smart Cross Platform

The Smart Cross Platform is a virtual machine based solution that supports various programming languages and platforms, and its aims are to support programming languages like C++, Java and Objective-C and smart phone platforms such as Android and iOS. Various contents that developed by supported language on the Smart Cross Platform can be execute on Android and iOS platforms at no additional cost, because it has the platform independent characteristic by using SIL(Smart Intermediate Language) as an intermediate language. In this paper, we will introduce a Java compiler for the Smart Cross Platform to support Java contents. Proposed compiler translates given Java programs into stack based intermediate SIL codes to execute on the SVM(Smart Virtual Machine). Thus, existing JVM’s contents can be easily ported and executed on the Android or iOS with SVM.

스마트 크로스 플랫폼을 위한 스마트 가상기계의 설계 및 구현

Since domestic and foreign platform companies and mobile carriers adopt and use different kinds of smart platforms, developers should develop or convert contents according to each smart platform to provide a single smart content for customers. It takes long time and a lot of money to convert the conventional smart contents in order to serve other smart platforms. For the reason, more attention has been paid on Smart Cross Platform or Hybrid Platform, the core technologies of OSMU(One Source Multi Use) in which, once a program is coded, it can be executed in any platforms regardless of development languages. As a result, PhoneGap and HTML5 based Sencha Touch have been introduced. In this paper, we developed the smart virtual machine, which is built in smart cross platform based smart devices, unlike Android, iOS, Windows Phone devices being dependent of platforms, and helps to download and execute applications, being independent of platforms. the smart virtual machine supports C/C++, and Java language, being differentiated from JVM by sun microsystems that supports only Java language and .NET framework by microsoft that supports only C, C++ and C#. Therefore, it provides contents developers with the environment where they can get a wide range of options in choosing a language and develop smart contents.