Moving from Mobile Databases to Mobile Cloud Data Services

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Department of Computer Engineering. San Jose State University. San Jose, USA jerry.gao@sjsu.edu. Abstract—Recently, mobile cloud computing has been ...
2015 3rd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering

Moving from Mobile Databases to Mobile Cloud Data Services Shuyu Li

Jerry Gao

School of Computer Science Shaanxi Normal University Xi’an, China [email protected]

Department of Computer Engineering San Jose State University San Jose, USA [email protected]

issues and challenges in mobile data services in mobile cloud computing. Section 4 gives the conclusions.

Abstract—Recently, mobile cloud computing has been named as the top one emerging technology in 2014 by IEEE Computer Society. This brings a strong demand on new emergent mobile data service solutions and technologies in the wireless world and implies that more innovative mobile data service solutions are needed to support on-demand elastic and large-scale mobile data service requests. This paper focuses on mobile data service topic. It first analyzes the existing research results on mobile data services. Then, it discusses cloud-based mobile data service solutions. Finally, the paper examines the issues and challenges on mobile data service in mobile cloud computing.

II. MOBILE DATA SERVICES ON CLOUDS As defined in [1], Mobile Cloud Computing (MCC) is “an emergent mobile cloud paradigm which leverage mobile computing, networking, and cloud computing to study mobile service models, develop mobile cloud infrastructures, platforms, and service applications for mobile clients.” Its goal is to deliver them with secure mobile cloud resources, service applications, and data using energy-efficient mobile cloud resources in a pay-as-you-use model. MCC is known to be a promising solution for mobile computing because it overcomes obstacles in mobile computing, for example, improving data storage capacity and processing power by enabling mobile users to store/access data on the cloud.

Keywords—mobile data-as-a-service, mobile cloud computing, mobile databases, mobile cloud database

I. INTRODUCTION According to the latest Visiongain’s report , the mobile cloud computing market will generate 45 billion dollars in revenues by 20161. The recent post in IEEE computer society indicated that mobile cloud is the top one technology trend in the near future2. There will be a strong demand to have innovative mobile enabled database technologies and mobile data access service to address the current issues, challenges, and emergent need in mobile cloud computing [1]. According to Chetan Sharma Consulting, mobile data service revenues for the US market are expected to $90 Billion.

As pointed out by authors in [1], new mobile data service technologies and solutions are required to cope with the new demands on mobile data services in mobile cloud computing. There are some required distinct service features and requirements for mobile cloud data service technologies in the mobile cloud computing paradigm. Here we list the primary ones: (i) Offer on-demand mobile data services on a mobile cloud based on service-level agreements; (ii) Pay-as-you-use business model; (iii) Offloading computing power demands from mobile devices to clouds; (iv) Multi-tenanted mobile data service; (v) Highly elastic and scalable data services; (vi) Highly reliable and available mobile data service.

In the past decades, the advance of mobile computing leads to numerous mobile database technologies, methods, and solutions that are developed to meet the demands of mobile data services in mobile applications. However, existing solutions have the limitations in supporting on-demand elastic and scalable mobile data services with mobility and multitenancy. With the advance of mobile cloud computing, new innovative mobile data service technologies and solutions are needed.

III. ISSUES, CHALLENGES, AND NEEDS There are a number of research issues, challenges, and needs for mobile data services in mobile cloud computing. Here we discuss them in three different areas: privacy and security in mobile data service, multi-tenancy and customization in mobile data service, mobile data transaction management.

This paper presents and classifies key features and essential requirements of mobile data-as-a-service, and examines cloudbased mobile database technologies. The major motivation is to share our observations and vision for the future trend on mobile data services. Section 2 discusses special features and requirements in mobile data service on clouds and related mobile cloud database technologies. Section 3 examines the

A. Privacy and security in mobile data service Protecting user privacy and data secrecy is a key to establish and maintain users’ trust in the mobile platform. This leads two security issues in providing cloud-based mobile database solutions: a) mobile user privacy, and b) data security.

1. http://www.visiongain.com/Press_Release/130/The-mobile-cloudcomputing-market-will-generate-45-billion-dollars-in-revenues-by-2016-saysthe-latest-visiongain-report. 2. “Top Technology Trend for 2014”, http://www.computer.org/portal/web/ /membership/Top-10-Tech-Trends-in-2014. Sponsored by China Scholarship Council

978-1-4799-8977-5/15 $31.00 © 2015 IEEE DOI 10.1109/MobileCloud.2015.33

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utilization and data access load. Though many scalability metrics have been proposed in distributed computing and high performance computing environment to evaluate the scalability of a system, most of these metrics do not meet the needs of tenant scalability of mobile cloud databases and new metrics involving factors brought in by MCC should be studied.

(a) Mobile User Privacy The authors in [2] propose a security model for locationbased services using outsourced databases to achieve location security in both privacy and authentication. And a secure algorithm that uses international mobile subscriber identity (IMSI) as user identification integrated with encryption algorithms is presented to secure the location data. WhereStore [3] is a device store that uses filtered replication for caching data in mobile cloud computing. Their idea is to use the past location history to predict the possible future locations of a mobile node and cache the data related to that location. Transition graphs were used for prediction of future location from a current location.

C. Mobile data transaction management Unlike dominance of relational data model in the mobile database, NoSQL data models are more popular in the mobile cloud databases. Two issues on transaction management are listed below. -

Query on encrypted data. A straightforward way to address data security is to encrypt the database, but an encrypted database cannot be easily queried. Processing aggregation queries is usually achieved by using a special encryption scheme called homomorphic encryption that allows addition and multiplication on cipher-texts without the need for decryption [5].

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Multi-item ACID transaction support. Though weak consistency is acceptable in some applications, many applications, for example, social networking and credit card transactions, would like to use cloud databases, yet find that weak consistency makes life very difficult. There are several ways to support multi-item ACID transactions when using a NoSQL cloud database that provides only single item transactional guarantees. One of those approaches is to extend single-key transactional support to multi-key or key group.

(b) Data Security The reliance of cloud-based, infrastructure-centric and multi-layered security solution combined with endpoint solutions could serve as the foundation for possible solution of data security. Two additional issues for future research are listed below: -

Power-efficiency and intelligent partition. Designing security mechanism for mobile cloud databases should focus more on power-efficiency and delay of such security algorithms and how to partition them on cloud and mobile devices[4].

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Scalability of security mechanism. The security mechanism is considered to be highly scalable, if the users’ increase can be adaptively handled without degradation in database performance. The computational requirements, scalability, and assumptions play a very important role in the successful application of security mechanism for mobile cloud databases.

IV. CONCLUSION This paper analyzes the existing research results on mobile data services and discusses cloud-based mobile data service solutions. The issues and challenges on mobile data service in mobile cloud computing are presented for future research.

B. Multi-tenancy and customization in mobile data service (a) Multi-tenancy As pointed out by [1], multi-tenancy is one of key characteristics of mobile cloud computing and mobile SaaS. This requires the support of multi-tenanted mobile data services. There are three basic challenges and needs to address this demand. -

REFERENCES [1]

How develop well-defined data-oriented multi-tenancy models to represent the multi-tenanted datasets and access and service behaviors?

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How to define and support well-defined tenant-based data service policies and control mechanisms?

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How to design and develop multi-tenanted mobile data services for next generation mobile data-as-a-service applications and DB technologies?

[2]

[3]

[4]

(b) Tenant scalability [5]

Handling large amount of tenants/users effectively is critical for mobile cloud databases. Besides, there are many factors that could affect the tenant scalability of mobile cloud databases, for example, multi-tenancy architecture, resource

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