Mobile On-demand Computing: The Future Generation of Cloud

Md. Abdullah-Al-Shafi,Ali Newaz Bahar,Sajeeb Saha 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.11

Cloud computing furnishes a unique term of computing and becomes a buzzword to its overwhelming trade prospects. Cloud computing achieved an impetus and is remodeling the internet based computing framework as well as raise the proficiency of mobile systems. Mobile cloud computing or on-demand computing is attaining fame among mobile users and mobile devices can use clouds for various exhaustive applications like storage or information processing. Mobile cloud computing overcomes performance-related difficulties such as battery and storage capacity as well as communication and environment connected affairs like security, availability, and privacy. Still, mobile on-demand computing beneath anticipation because of privacy and security perils. This paper presents an analysis of mobile cloud computing along with its architectural basis and challenges as well as the security considerations. The objective of this paper is to subsidize a superior perceptive on mobile cloud computing and identify further imminent research directions.

Mobile Computing: Wireless Networking Security Issues

Javed Ahmad Shaheen 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.10

Mobile wireless has detonated in popularity just of its simplicity, revolution in communication and Mobile computing has become very famous now days in reward of the services offered during the mobile communication and. Mobile computing has become the reality not the luxury. Mobile wireless market is increasing by leaps and bounds as Cell phones, mobile computing and communication devices have become very trendy because of their ease and portability. However, the use of such devices in this platform is accompanied by new security risks that must be recognized and addressed to protect the physical devices, the communication medium, and the information used. Security is key issue that needs to be considered. For this security protocols are proposed for different applications like Wireless Application Protocol, 802.11a etc. Most of them are based on the public and private key cryptography. The challenge for mobile network is in providing very large footprint of mobile services with high speed and security. In this paper, we have discussed security issues arising due to wireless networking of mobile computing in distributed systems. We discussed the operational model of mobile computing environment, and try to demonstrate proposed solutions. We also discuss security problems and mechanisms that can be applied one of three main components of mobile computing. The goal of paper is to point out some of the limitations, characteristics, applications and issues on security of mobile computing.

Cloud- Based Mobile Augmentation in Mobile Cloud Computing

Alshamaileh Mohammad,Li Chunlin 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.8

Mobile devices are increasingly becoming famous in the current times. Limited computing resources are still a hindrance for resource intensive computations. Several frameworks have been established to enable cloud -based mobile augmentation (CMA) approach be followed by mobile applications. CMA has a strategy of dynamic outsourcing resource intensive tasks to the external resources. CMA’s state of art mobile augmentation model employs resource- rich clouds to increase, enhance and optimize mobile device. Augmented mobile devices in the cloud are geared towards extensive computations and storage of big data beyond the device capabilities with little or no traceable footprint and vulnerabilities. CMA has made efforts towards exploiting various cloud- based computing resources especially the distant clouds and proximate mobile nodes to augment mobile devices. Task scheduling is one of the approaches that are well elaborated using computations in this paper that is employed to reduce execution time.

An Energy-efficient Approach based on Learning Automata in Mobile Cloud Computing

Mostafa Ghobaei Arani,Najmeh Moghadasi 보안공학연구지원센터 2015 International Journal of Grid and Distributed Comp Vol.8 No.4

In recent years, using mobile devices, in daily life, has found a special place and because of the applicability of these devices are increasing the number of users day by day. Business companies have integrated them with cloud computing technology and have provided mobile cloud in order to improve using mobile devices and overcome the energy consumption of mobile devices. Therefore, energy efficiency is a fundamental factor for mobile devices and cloud computing has the potential to save energy and power of mobile devices. In mobile cloud computing, computations and storages of mobile devices applications are transferred to cloud data centers and mobile devices are used merely as user interface to access services. The cloud computing will help to reduce energy consumption of mobile devices. In this paper, a new approach is given to reduce energy consumption of based on Learning Automata in mobile cloud computing. Simulation results show that our proposed approach significantly saves energy consumption through determining the appropriate location for application.

모바일 클라우드 컴퓨팅의 작업 실행 시간에 대한 연구

정성민,김태경 (사)디지털산업정보학회 2012 디지털산업정보학회논문지 Vol.8 No.1

Given the numbers of smartphones, tablets and other mobile devices shipped every day,more and more users are relying on the cloud as the main driver for satisfying their computing needs, whether it is data storage, applications or infrastructure. Mobile cloud computing is simply cloud computing in which at least some of the devices involved are mobile. Each node is owned by a different user and is likely to be mobile. Using mobile hardware for cloud computing has advantages over using traditional hardware. These advantage include computational access to multimedia and sensor data without the need for large network transfer, more efficient access to data stored on other mobile devices and distributed ownership and maintenance of hardware. It is important to predict job execution time in mobile cloud computing because there are many mobile nodes with different capabilities. This paper analyzes the job execution time for mobile cloud computing in terms of network environment and heterogeneous mobile nodes using a mathematical model.

Computational Offloading for Mashup Services in Mobile Cloud Computing Environment

Kuljeet Kaur,Dr. Pankaj deep Kaur 보안공학연구지원센터 2015 International Journal of Grid and Distributed Comp Vol.8 No.3

The cloud system is considered as the hub of hosted services in which a particular user can access the cloud system remotely by using applications or by using the browsers. Compared to desktop devices, mobile device have inherent constraints such as limited processing power, memory, and battery capacity. With the propagation of mobile cloud applications, researches are looking for new solutions to address these limitations. One of the major solution is mobile cloud computing, which uses cloud infrastructure to enhance the capabilities of mobile device. This paper focuses on an emerging technology known as mobile offloading and mashup. The offloading uses the quality of services concept to remove mobile application limitations. Cloud services are the application programming platform where users can create new applications and mashup their functionalities. The paper describes the quality of services parameters used for offloading in mobile applications and also describes the existing approaches for mobile cloud computing.

이동 컴퓨팅을 위한 이동 에이전트 이주전략

황인선,박경우 한국정보전략학회 2003 한국정보전략학회지 Vol.6 No.1

This paper describes distributed mobile computing architecture which supports mobility of user mobile station. In mobile computing efficiently and improve the response time of a mobile transaction. During handoff processing flow control mechanism was considered to correct packet loss and out of packet sequence problem. The mobile station and mobile agent process which logically represents mobile station in the fixed/wireless network, and trace agent process to track the location of mobile agent for providing application service to mobile station. With trace agent process application program which is used in Non-mobile computing environment can be used without changing its code in mobile computing.

User Mobility Model Based Computation Offloading Decision for Mobile Cloud

Lee, Kilho,Shin, Insik Korean Institute of Information Scientists and Eng 2015 Journal of Computing Science and Engineering Vol.9 No.3

The last decade has seen a rapid growth in the use of mobile devices all over the world. With an increasing use of mobile devices, mobile applications are becoming more diverse and complex, demanding more computational resources. However, mobile devices are typically resource-limited (i.e., a slower-speed CPU, a smaller memory) due to a variety of reasons. Mobile users will be capable of running applications with heavy computation if they can offload some of their computations to other places, such as a desktop or server machines. However, mobile users are typically subject to dynamically changing network environments, particularly, due to user mobility. This makes it hard to choose good offloading decisions in mobile environments. In general, users' mobility can provide some hints for upcoming changes to network environments. Motivated by this, we propose a mobility model of each individual user taking advantage of the regularity of his/her mobility pattern, and develop an offloading decision-making technique based on the mobility model. We evaluate our technique through trace-based simulation with real log data traces from 14 Android users. Our evaluation results show that the proposed technique can help boost the performance of mobile devices in terms of response time and energy consumption, when users are highly mobile.

Computational Analytics of Client Awareness for Mobile Application Offloading with Cloud Migration

( Uma Nandhini ),( Latha Tamilselvan ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.11

Smartphone applications like games, image processing, e-commerce and social networking are gaining exponential growth, with the ubiquity of cellular services. This demands increased computational power and storage from mobile devices with a sufficiently high bandwidth for mobile internet service. But mobile nodes are highly constrained in the processing and storage, along with the battery power, which further restrains their dependability. Adopting the unlimited storage and computing power offered by cloud servers, it is possible to overcome and turn these issues into a favorable opportunity for the growth of mobile cloud computing. As the mobile internet data traffic is predicted to grow at the rate of around 65 percent yearly, even advanced services like 3G and 4G for mobile communication will fail to accommodate such exponential growth of data. On the other hand, developers extend popular applications with high end graphics leading to smart phones, manufactured with multicore processors and graphics processing units making them unaffordable. Therefore, to address the need of resource constrained mobile nodes and bandwidth constrained cellular networks, the computations can be migrated to resourceful servers connected to cloud. The server now acts as a bridge that should enable the participating mobile nodes to offload their computations through Wi-Fi directly to the virtualized server. Our proposed model enables an on-demand service offloading with a decision support system that identifies the capabilities of the client`s hardware and software resources in judging the requirements for offloading. Further, the node`s location, context and security capabilities are estimated to facilitate adaptive migration.

User Mobility Model Based Computation Offloading Decision for Mobile Cloud

Kilho Lee,Insik Shin 한국정보과학회 2015 Journal of Computing Science and Engineering Vol.9 No.3

The last decade has seen a rapid growth in the use of mobile devices all over the world. With an increasing use of mobile devices, mobile applications are becoming more diverse and complex, demanding more computational resources. However, mobile devices are typically resource-limited (i.e., a slower-speed CPU, a smaller memory) due to a variety of reasons. Mobile users will be capable of running applications with heavy computation if they can offload some of their computations to other places, such as a desktop or server machines. However, mobile users are typically subject to dynamically changing network environments, particularly, due to user mobility. This makes it hard to choose good offloading decisions in mobile environments. In general, users’ mobility can provide some hints for upcoming changes to network environments. Motivated by this, we propose a mobility model of each individual user taking advantage of the regularity of his/her mobility pattern, and develop an offloading decision-making technique based on the mobility model. We evaluate our technique through trace-based simulation with real log data traces from 14 Android users. Our evaluation results show that the proposed technique can help boost the performance of mobile devices in terms of response time and energy consumption, when users are highly mobile.