IJRIT International Journal of Research in Information Technology, Volume 2, Issue 9, September 2014, Pg. 787-792

International Journal of Research in Information Technology (IJRIT)

www.ijrit.com

ISSN 2001-5569

Mobile Cloud Computing Lalit Kumar (16084), Nishant Malik (16104), Gourav Agghi (16067), Ajay Anand (16951) Department of Computer Science and Engineering Dronacharya CollegeOf Engineering,Gurgoan

I.

Abstract

Together with an explosive growth of the mobile applications and emerging of cloud computing concept, mobile cloud computing (MCC) has been introduced to be a potential technology for mobile services. MCC integrates the cloud computing into the mobile environment and overcomes obstacles related to the performance (e.g., battery life, storage, and bandwidth), environment (e.g., heterogeneity, scalability, and availability), and security (e.g., reliability and privacy) discussed in mobile computing. This paper gives a survey of MCC, which helps general readers have an overview of the MCC including the definition, architecture, and applications. The issues, existing solutions and approaches are presented. In addition, the future research directions of MCC are discussed.

II.

Introduction

Over the past few years, advances in the field of network based computing and applications on demand have led to an explosive growth of application models such as cloud computing, software as a service, community network, web store, and so on. As a major application model in the era of the Internet, Cloud Computing has become a significant research topic of the scientific and industrial communities since 2007. Commonly, cloud computing is described as a range of services which are provided by an Internet-based cluster system. Such cluster systems consist of a group of low-cost servers or Personal Computers (PCs), organizing the various resources of the computers according to a certain management strategy, and offering safe, reliable, fast, convenient and transparent services such as data storage, accessing and computing to clients. According to the top ten strategic technology trends for 2012 [1] provided by Gartner (a famous global analytical and consulting company), cloud computing has been on the top of the list, which means cloud computing will have an increased impact on the enterprise and most organizations in 2012. Meanwhile, smart phones are considered as the representative for the various mobile devices as they have been connected to the Internet with the rapidly growing of wireless network technology. Ubiquity and mobility are two major features in the next generation network which provides a range of personalized network services through numerous network terminals and modes of accessing. The core technology of cloud computing is centralizing computing, services, and specific applications as a utility to be sold like water, gas or electricity to users. Thus, the combination of a ubiquities mobile network and cloud computing generates a new computing mode, namely Mobile Cloud Computing. As an inheritance and development of cloud computing, resources in mobile cloud computing networks are virtualized and assigned in a group of numerous distributed computers rather than in traditional local computers or servers, and are provided to mobile devices such as smart phones, portable terminal, and so on. (see Fig. 1). Meanwhile, various applications based on mobile cloud computing have been developed and served to users, such as Google Gmail, Maps and Navigation systems for Mobile, Voice Search, and some applications on an Android platform, Mobile Me from Apple, Live Mesh from Microsoft, and Moto Blur from Motorola. According to the research from Juniper, the cloud computing based mobile software and application are expected to rise 88% annually from 2009 to 2014, and such growth may create US 9.5 billion dollars in 2014.

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IJRIT International Journal of Research in Information Technology, Volume 2, Issue 9, September 2014, Pg. 787-792

While mobile cloud computing make a great contribution to our daily lives, it will also, however, bring numerous challenges and problems. In short, the core of such challenges and problems is just how to combine the two technologies seamlessly. On one hand, to ensure that mobile devices adequately make best use of advantages of cloud computing to improve and extend their functions. On the other hand, to overcome the disadvantages of limited resources and computing ability in mobile devices in order to access cloud computing with high efficiency like traditional PCs and Servers. Thus, in order to solve the mentioned challenges and point out further research, getting a thorough understanding of the novel computing paradigm - mobile cloud computing, is necessary. This paper introduces the basic model of mobile cloud computing, its background, key technology, current research status, and its further research perspectives as well.

Fig. 1: Mobile Cloud Computing

III.

Architectures of Mobile Cloud Computing

Fig.2. Mobile Cloud Computing (MCC) architecture.

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IJRIT International Journal of Research in Information Technology, Volume 2, Issue 9, September 2014, Pg. 787-792

From the concept of MCC, the general architecture of MCC can be shown in Fig. 2. In Fig. 2, mobile devices are connected to the mobile networks via base stations (e.g., base transceiver station (BTS), access point, or satellite) that establish and control the connections (air links) and functional interfaces between the networks and mobile devices. Mobile users’ requests and information (e.g., ID and location) are transmitted to the central processors that are connected to servers providing mobile network services. Here, mobile network operators can provide services to mobile users as AAA (for authentication, authorization, and accounting) based on the home agent (HA) and subscribers’ data stored in databases. After that, the subscribers’ requests are delivered to a cloud through the Internet. In the cloud, cloud controllers process the requests to provide mobile users with the corresponding cloud services. These services are developed with the concepts of utility computing, virtualization, and service-oriented architecture (e.g., web, application, and database servers). The details of cloud architecture could be different in different contexts. For example, a four-layer architecture is explained in to compare cloud computing with grid computing. Alternatively, service oriented architecture, called Aneka, and is introduced to enable developers to build .NET applications with the supports of application programming interfaces (APIs) and multiple programming models. Presents architecture for creating marketoriented clouds, and [11] proposes an architecture for web delivered business services. In this paper, we focus on a layered architecture of cloud computing (Fig. 3). This architecture is commonly used to demonstrate the effectiveness of the cloud computing model in terms of meeting the user’s requirements.

Fig.2. Service-oriented cloud computing architecture. Generally, a cloud computing is a large-scale distributed network system implemented based on a number of servers in data centers. The cloud services are generally classified based on a layer concept (Fig.3). In the upper layers of this paradigm, Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) are stacked. •







Data centers layer: This layer provides the hardware facility and infrastructure for clouds. In data center layer, a number of servers are linked with high-speed networks to provide services for customers. Typically, data centers are built in less populated places, with a high power supply stability and a low risk of disaster. Infrastructure as a Service (IaaS): IaaS is built on top of the data center layer. IaaS enables the provision of storage, hardware, servers and networking components. The client typically pays on a per-use basis. Thus, clients can save cost as the payment is only based on how much resource they really use. Infrastructure can be expanded or shrunk dynamically as needed. The examples of IaaS are Amazon EC2 (Elastic Cloud Computing) and S3 (Simple Storage Service). Platform as a Service (PaaS): PaaS offers an advanced integrated environment for building, testing and deploying custom applications. The examples of PaaS are Google App Engine, Microsoft Azure, and Amazon Map Reduce/Simple Storage Service. Software as a Service (Saas): SaaS supports a software distribution with specific requirements. In this layer, the users can access an application and information remotely via the Internet and pay only for that they use. Sales force is one of the pioneers in providing this service model. Microsoft’s Live Mesh also allows sharing files and folders across multiple devices simultaneously. Although the cloud computing

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architecture can be divided into four layers as shown in Fig.3, it does not mean that the top layer must be built on the layer directly below it. For example, the SaaS application can be deployed directly on IaaS, instead of PaaS. Also, some services can be considered as a part of more than one layer. For example, data storage service can be viewed as either in IaaS or PaaS. Given this architectural model, the users can use the services flexibly and efficiently.

IV.

Advantages of Mobile Cloud Computing

Cloud computing is known to be a promising solution for mobile computing due to many reasons (e.g., mobility, communication, and portability). In the following, we describe how the cloud can be used to overcome obstacles in mobile computing, thereby pointing out advantages of MCC.  Extending battery lifetime: Battery is one of the main concerns for mobile devices. Several solutions have been proposed to enhance the CPU performance, and to manage the disk and screen in an intelligent manner, to reduce power consumption. However, these solutions require changes in the structure of mobile devices, or they require a new hardware that results in an increase of cost and may not be feasible for all mobile devices.  Improving data storage capacity and processing power: Storage capacity is also a constraint for mobile devices. MCC is developed to enable mobile users to store/access the large data on the cloud through wireless networks.  Improving reliability: Storing data or running applications on clouds is an effective way to improve the reliability since the data and application are stored and backed up on a number of computers. This reduces the chance of data and application lost on the mobile devices. In addition, MCC can be designed as a comprehensive data security model for both service providers and users.  Dynamic provisioning: Dynamic on-demand provisioning of resources on a fine-grained, self-service basis is a flexible way for service providers and mobile users to run their applications without advanced reservation of resources.  Scalability: The deployment of mobile applications can be performed and scaled to meet the unpredictable user demands due to flexible resource provisioning. Service providers can easily add and expand an application and service without or with little constraint on the resource usage.  Multi-tenancy: Service providers (e.g., network operator and data center owner) can share the resources and costs to support a variety of applications and large number of users.  Ease of Integration: Multiple services from different service providers can be integrated easily through the cloud and the Internet to meet the users’ demands.

V.

SUPPORT FOR COLLABORATIVE APPLICATIONS

Mobile participatory sensing applications are becoming increasingly popular. In such applications, large numbers of mobile devices contribute their own sensor data, such as video clips, image captures, audio snippets, temperature data, location information, and/or text metadata to a collaborative application located in the cloud. This cloud application then generates compelling crowd sourced output that could not otherwise be easily obtained. Example applications include traffic jam/congestion detection, bus arrival forecasting , parking space discovery , localization of weather phenomena, distributed pollution detection, etc. We imagine that such collaborative applications will expand to include mobile epidemiology and disease outbreak detection, spontaneously coordinated crowd activities at concerts and sporting/cultural events, etc. New cloud infrastructure beyond the application services proposed above for single mobile applications will be needed to support such large scale collaborative mobile applications. Cloud based determining services will need to scale to analyze large groups of people and the large quantities of data that they generate in order to extract collective trends among the population of users in real time. In addition, new crowd actuation services will need to be created and scaled, such as recommendation services based on collective group context rather than individual context. Privacy services that scale to large numbers of people, and preserve a sense of "collective privacy of the group" will become more important and will need to be devised. Because applications servicing a region co-locate in regional data centers, there are ample opportunities for synergy. Co-location enables intimate collaboration of applications and performance optimization which are not possible before. For example, for file sharing, traditionally, the application has to transfer the file remotely. If it is a big file, Lalit Kumar, IJRIT

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IJRIT International Journal of Research in Information Technology, Volume 2, Issue 9, September 2014, Pg. 787-792

many applications will not work, e.g. collaborative games. If the two applications are co-located, rather than sending the file, a pointer will be sufficient. If server 1 of application A talks to server 2 of application B a lot, then the cloud provider can even co-locate these two servers in the same physical machine.

VI.

Challenges and solutions

The main objective of mobile cloud computing is to provide a convenient and rapid method for users to access and receive data from the cloud, such convenient and rapid method means accessing cloud computing resources effectively by using mobile devices. The major challenge of mobile cloud computing comes from the characters of mobile devices and wireless networks, as well as their own restriction and limitation, and such challenge makes application designing, programming and deploying on mobile and distributed devices more complicated than on the fixed cloud devices . In mobile cloud computing environment, the limitations of mobile devices, quality of wireless communication, types of application, and support from cloud computing to mobile are all important factors that affect assessing from cloud computing.  Limitations of mobile devices: While discussing mobile devices in cloud the first thing is resourceconstrain. Though smart phones have been improved obviously in various aspects such as capability of CPU and memory, storage, size of screen, wireless communication, sensing technology, and operation systems, still have serious limitations such as limited computing capability and energy resource, to deploy complicated applications. By contrast with PCs and Laptops in a given condition, these smart phones like iPhone 4S, Android serials, Windows Mobile serials decrease 3 times in processing capacity, 8 times in memory, 5 to 10 times in storage capacity and 10 times in network bandwidth.  Quality of communication: In contrast with wired network uses physical connection to ensure bandwidth consistency, the data transfer rate in mobile cloud computing environment is constantly changing and the connection is discontinuous due to the existing clearance in network overlay. Furthermore, data centre in large enterprise and resource in Internet service provider normally is far away to end users, especially to mobile device users. In wireless network, the network latency delay may 200 ms in ’last mile’ but only 50 ms in traditional wired network.  Division of application services: In mobile cloud computing environment, due to the issue of limited resources, some applications of compute-intensive and data-intensive cannot be deployed in mobile devices, or they may consume massive energy resources. Therefore, we have to divide the applications and use the capacity of cloud computing to achieve those purposes, which is: the core computing task is processed by cloud, and those mobile devices are responsible for some simple tasks only. In this processing, the major issues affecting performance of mobile cloud computing are: data processing in data centre and mobile device, network handover delay, and data delivery time. The following strategies can be used to response to the challenges: 1. Upgrade bandwidth for wireless connection, make the web content more suitable for mobile network using regional data centers. 2. Deploy the application processing node at the ’edge’ of cloud in order to reduce data delivery time. 3. Duplicate mobile devices to cloud using virtualization and image technologies, to process Data-Intensive Computing (DIC) and Energy-Intensive Computing, such as virus scanning in mobile devices. 4. Dynamically optimize application push in cloud and the division with mobile terminals.

VII.

Conclusion

With the high increasing of data computation in commerce and science, the capacity of data processing has been considered as a strategic resource in many countries. Mobile cloud computing (MCC), as a development and extension of mobile computing (MC) and cloud computing (CC), has inherited the high mobility and scalability, and become a hot research topic in recent years. We conclude that there are three main optimization approaches in MCC, which are focusing on the limitations of mobile devices, quality of communication, and division of applications services. Firstly, using virtualization and image technology can address it effectively, and immigrate task from terminal to cloud is also a good way to achieve better results. Secondly, as we know the quality of communication in wired network is better than in wireless network, so reducing the proportion of data delivery in wireless environment Lalit Kumar, IJRIT

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IJRIT International Journal of Research in Information Technology, Volume 2, Issue 9, September 2014, Pg. 787-792

is an effective way to improve the quality. In addition, upgrading bandwidth is envisaged to be a simple way to increase performance but it incurs additional cost to users. Deploying an effective elastic application division mechanism is deemed to be the best solution to guarantee the application service in MCC; its complicated, but promising high impact results.

VIII. References [1]M. Cooney. (2011, Oct) Gartner: The top 10 strategic technology trends for 2012. [Online]. Available: http://www.networkworld.com/ news/2011/101811-gartner-technology-trends-252100.html [2] (2009, Sept) Mobile cloud computing subscribers to total nearly one billion by 2014. [Online]. Available: http://www.abiresearch.com/press/\ 1484 [3] C. Hewitt, “Orgs for scalable, robust, privacy-friendly client cloud computing,” Internet Computing, IEEE, vol. 12, no. 5, pp. 96–99, 2008. [4] R. Buyya, C. Yeo, and S. Venugopal, “Market-oriented cloud computing: Vision, hype, and reality for delivering it services as computing utilities,” in High Performance Computing and Communications, 2008. HPCC’08. 10th IEEE International Conference on. IEEE, 2008, pp. 5–13. [5] L. Youseff, M. Butrico, and D. Da Silva, “Toward a unified ontology of cloud computing,” in Grid Computing Environments Workshop, 2008. GCE’08. IEEE, 2008, pp. 1–10. [6] S. Shankar, “Amazon elastic compute cloud,” 2009. [7]Amazon AWS. Mobile developer center. http://aws.amazon.com/mobile. [8] M. Armbrust et al. Above the clouds: A berkeley view of cloud computing. Technical Report UCB/EECS-200928, UC Berkeley, 2009. [9] A. Beach, M. Gartrell, S. Akkala, J. Elston, J. Kelley, K. Nishimoto, B. Ray, S. Razgulin, K. Sundaresan, B. Surendar, M. Terada, and R. Han. Whozthat? Evolving an ecosystem for context-aware mobile social networks. IEEE Network, 22(4):50–55, July-August 2008. [10] A. Beach, M. Gartrell, and R. Han. q-Anon: Rethinking anonymity for social networks. In IEEE SocialCom Conference, 2010.

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