A Simple Analysis of Service Oriented Architecture for Mobile Cloud Computing

Transcription

1 A Simple Analysis of Service Oriented Architecture for Mobile Cloud Computing Y.Padma 1, K.Pavan Kumar 2, A.Durgabhavani 3 1 Prasad V. Potluri Siddhartha Institute of Technology, Vijayawada, AP, India 2,3 Usharama College of Enggineering &Technology, Vijayawada, AP, India Abstract Cloud-based Mobile Augmentation (CMA) is thestate-of-the-art augmentation model that leverages proximate and distant clouds to increase, enhance, and optimize computing capabilities of mobile devices aiming at execution of RMAs, which breeds Mobile Cloud Computing (MCC). This study analyzes impacts of mobile-cloud distance and number of intermediate hops as influential factors on CMA performance which are not yet investigated. The results indicate the correlation between distance and intermediate hops on overall execution costs (time and energy) of RMAs. Exploitation of cloud computing by mobile handhelds breeds a new research domain called Mobile Cloud Computing (MCC), which is the state-ofthe-art computing paradigm comprised of three heterogeneous domains of mobile computing, cloud computing, and networking. Such non-uniformity stems several challenges such as portability, interoperability, and fragmentation that are deemed to be alleviated leveraging SOA as a promising design philosophy embraced by mobile computing and cloud computing communities to stimulate portable, complex application using prefabricated building blocks called Services. Services are prefabricated codes that are developed in languages like Java,.Net, and PHP and are often publicized in a publicly accessible repository to be discovered and invoked by clients to provide specific functionality. Keywords cloud, Computing, mobile, devices, architecture, service, analysis. I. INTRODUCTION Recent consumer electronic technologies have created momentous ground for smart phones in various domains, particularly healthcare and education. However, smart phones' miniature nature imposes intrinsic limitations on computational capabilities and battery lifetime that encumber performing Resource-intensive Mobile Applications (RMAs). The vision of augmenting computing capabilities of mobile devices, especially smart phones with least cost is likely transforming to reality leveraging cloud computing. Cloud exploitation by mobile devices breeds a new research domain called Mobile Cloud Computing (MCC). However, issues like portability and interoperability should be addressed for mobile augmentation which is a non-trivial task using component based approaches. Service Oriented Architecture (SOA) is a promising design philosophy embraced by mobile computing and cloud computing communities to stimulate portable, complex application using prefabricated building blocks called Services. Utilizing distant cloud resources to host and run Services is hampered by long WAN latency. Exploiting mobile devices in vicinity alleviates long WAN latency, while creates new set of issues like Service publishing and discovery as well as client server security, reliability, and Service availability. In this paper, we propose a market-oriented architecture based on SOA to stimulate publishing, discovering, and hosting Services on nearby mobiles, which reduces long WAN latency and creates a business opportunity that encourages mobile owners to embrace Service hosting. Group of mobile phones simulate a nearby cloud computing platform. We create new role of Service host by enabling unskilled mobile owners/users to host Services developed by skilled developers. Evidently, Service availability, reliability, and Serviceoriented mobile application portability will increase towards green ubiquitous computing in our mobile cloud infrastructure. The paid Service hosting and execution is deemed to be embraced by mobile owners if issues such as Service publishing and discovery as well as client-server security, reliability, and Service availability are addressed. Services can be hosted on a hosting toolkit like which is a lightweight hosting toolkit for resource-poor mobile devices. In this paper, we propose an approach to publish, discover, and host Services on nearby mobiles, which not only alleviates aforementioned issues, but also creates a business opportunity that encourages mobile owners to embrace Service hosting and execution. We create new role of Service host to enable unskilled mobile client to host Services developed by skilled developers. A proper billing system can divide the income according to a negotiated agreement between engaging parties. To the best of our knowledge, this is the first proposal that aims to utilize nearby mobile devices under supervision of a supervisory body to host and run services based on an agreement. II. PROPOSED ARCHITECTURE Several sequential or parallel Services are bind together to build a new complex functionality. SOA has been utilized in computing domains such as grid computing or was cornerstone for technologies such as cloud computing to alleviate several fundamental challenges such as portability, interoperability, and integration of applications and software systems. This is due to the fact that Services are autonomous and platform-neutral meaning that different Services running on heterogeneous platforms can still collaborate toward fulfilling a complex task. Service is providing higher-level ISSN: Page 33

2 abstraction compared with components which makes them suitable technology for large scale computing domains such as MCC. Time analysis: The overall execution time in mobile-cloud applications is the total values of mobile computation time, round-trip delay, and cloud computation time represented in (1). The mobile computation is the time to perform native computations. The round-trip latency is the delay of sending request to the cloud and receiving the response. The cloud computation delay is the time that request is processed in server side and results are produced. It is feasible to shrink the volume of native computations and demand rich computing resources in the cloud, but decreasing the round-trip delay sounds non-trivial due to very large number of influential factors which are briefly discusses as follows. The overall execution time is represented by Ttotal as T Total = T Mobile + T RT + T Cloud Where Tmobile is the time to perform native computation that is negligible in this model, TRT is the round-trip delay, and Tcloud is the computing latency of the cloud. Computation latency depends on the computational capabilities (CPU clock speed, RAM volume, I/O performance, and environmental context like temperature) of the computing server, whereas round-trip delay comprises of four delays, including transmission, propagations, processing, and queuing delay. Thus, roundtrip latency is: TRT = 2 x ( T prog + T tran + T proc + T Q ) III. MOBILE SERVICE HOST The mobile host is a mobile device like smart phone or Tablet which is able and desired to host the implemented Service code and execute it for Service requester on demand. The host activity is a trade-off between resource and money. In order to host a Service, a mobile device must communicate with the Service Governor to find the appropriate Services according to its computing abilities and benefits. In this architecture, Service hosting is a paid Service, hence, Service governor should negotiate with developer (if wishes to provide paid Services), requester, and host to agree on a certain revenue percentage. In generic SOA, Service provider implements or purchase Service implementation, supply its description, and provide technical and business maintenance. However, due to lack of mobile owners/users technical competency, we argue that majority of technical and business maintenance of the Services should be accomplished by the Service provider. Every functional and non-functional failure should be reported to the Service provider for escalation. An alternative approach to utilize SOA in MCC is to deploy Services on nearby mobile devices to be invoked with reduced latency (utilizing alternative communication technologies such as cellular networks and Wi-Fi can enhance performance) without accessing the risky channel of Internet. Nevertheless, there is no publicly acceptable incentive and motivation neither for Service developer nor mobile hosts (except volunteers who are willing to collaborate freely). Developers are required to build publicly available, reusable Services to be utilized by other programmers in creating complex systems and applications, while mobile owners are needed to lease their computational resources such as CPU, memory, and most importantly battery to host and run the Services. In order to encourage the public and realize the vision of utilizing resources of nearby mobile devices (such as smart phones and Tablets), we propose a market-oriented architecture in which Service developers, brokers, and hosts can earn for their public Services whereas Service consumers should pay as they use (similar to the concept of Cloud computing and utility). Figure 1: Major Building Blocks of an Exemplary CMA System. TABLE 1: Initial Features of Mobile Empowerment Approaches. In this Section, we present a definition on mobile computing augmentation based on the available definitions on the elevant concepts, particularly remote execution and cyber foraging. Additionally, the motivation for performing mobile computation augmentation is described and taxonomy of mobile Indeed, empowering computation capabilities of ISSN: Page 34

3 mobile devices is not a new concept and there have been different approaches to achieve this goal, including load sharing, remote execution, cyber foraging, and computation off loading that are described as follows. We have analyzed them and summarized the analysis results in Table II. Results in this Table are extracted from the early efforts in each category, which are already deviated from their original characteristics due to the research achievements. Beside finacial benefits of hosting a Service, mobile device will become voulnerable to attack and privacy violation. To avoid such threats, certain mechanisms such as Sandboxing and Service signing (signing Service code by the service governor) can be deployed. IV. MOBILE SERVICE LISTINGS Service profiler monitors the overall functionality and performance of various Services. Service provider is responsible to maintain the Service in case of any malfunction. However, to enhance the quality of the Services, their overall functionality, availability, and vulnerability is 10 monitored by Service profiler to substitute low quality services with more efficient ones if required. Listing 1: Service requirement specification in a sample SOAP message <? xml v e r s i on = 1. 0 encoding = UTF 8?>... <Hos trequi rment s> <P l a t f o rm> <OS>Android</OS> <MinVer s ion>3. 2</ MinVer s ion> </ P l a t f o rm> <MinRequi r edre sour c e s> <CPU>512</CPU> <Memory>2</Memory> <S t o r a g e>5</ S t o r a g e> <Energy>500</ Energy> </ MinRequi r edre sour c e s> </ Hos trequi rment s> Figure 2: The Block Diagram of MOMCC Figure 3: Layered Architecture of MOMCC Mobile device is any non-stationary, battery-operating computing entity able to interact with end-user and execute transactions, store data, and communicate with the environment using wireless technologies and varied sensors. Smartphone, tablet, handheld/wearable computing devices, and vehicle mount computers are mobile device instances. Approaches that can augment mobile devices include hardware and software. Hardware approach involves manufacturing high-end physical components, particularly CPU, memory, storage, and battery. Software approaches can be but are not limited to computation offloading, remote data storage, wireless communication, resource-aware computing, fidelity adaptation, and remote service request (e.g., context acquisition). Augmentation approaches can increase computing capabilities of mobile devices and conserve energy. They can be leveraged in three main categories of applications, namely (i) computing-intensive software such as speech recognition and natural language processing, (ii) data-intensive programs such as enterprise applications, and (iii) communication-intensive applications such as online video streaming applications. The augmented mobile device performs complex tasks that would not be done, otherwise. Hence, the mobile application developers do not take into account resource shortcomings of mobile devices in developing mobile applications and users will not consider their devices weaknesses in utilizing varied complex applications. Moreover, cloud infrastructures are available to end-users via Virtual Machine (VM)9 to increase resource utilization ratio and enhance overall security and privacy. Virtualization technology aims to enable resource sharing in an isolated environment called VM. It realizes execution of multiple operating systems on a single machine and enables sharing of large resources among multiple end-users. Users can only access to infrastructures allocated to their VMs and cannot access prohibited resources and contents. Table II summarizes the comparison results of traditional and cloud-based ISSN: Page 35

4 resources and advocates differentiations between the conventional servers and clouds. High computing power, elasticity, mobility support, low utilization overhead, and security are some of the significant advantages of cloud resources compare to the surrogates that advocate the latest paradigm shift in mobile augmentation. TABLE II: Initial Features of Mobile Empowerment Approaches. V. CONCLUSION The goal is to realize the vision of unrestricted functionality, storage, and mobility regardless of underlying constraints. Based on Service governor responsibilities we argue that mobile network operators are likely the best candidate to serve as the Service governor, because they are centralized, well-established, and reputed organizations that have been serving mobile users since long and could establish high degree of trust with users. Successful mobile Service hosting architecture can be utilized in various domains such as supply chain management in which various organizations (e.g. billing and transport) can collaborate to perform a business activity. A Service hosted on a driver s mobile can notify customer orders and update delivery scheduling to the recipient. In this paper, impacts of exploiting geographically distributed cloud resources on performance of RMAs running on resource-constraint smart phone are mathematically and experimentally analyzed. Mathematical analysis of overall execution time and energy consumption unveils that number of intermediary hops and. data transmission volume have significant impacts on RMA s performance. Findings are validated using series of experiments in real environment. Benchmarking results advocate that exploiting distant cloud to augment computational capabilities of resource-constraint mobile devices is a time- and energy-intensive approach that degrades the performance of augmented mobile applications in MCC. Also, increase in distance, significantly degrades predictability of RMAs time and energy. REFERENCES 1. M. Sharifi, S. Kafaie, and O. Kashefi, A survey and taxonomy of cyber foraging of mobile devices, Communications Surveys & Tutorials, IEEE, vol. PP, no. 99, pp. 1 12, E. Marinelli, Hyrax: cloud computing on mobile devices using mapreduce, Master Thesis, Computer Science Deptartment, CMU, G. Huerta-Canepa and D. Lee, A virtual cloud computing provider for mobile devices, in Proc. MCS. ACM, 2010, pp. 6:1 6:5. 4. Z. Sanaei, S. Abolfazli, A. Gani, and R. H. Khokhar, Tripod of requirements in horizontal heterogeneous mobile cloud computing, in Proc. CISCO, T. Erl, Service-oriented architecture: concepts, technology, and design. 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5 Author s Profile Y.Padma, PVPSIT K.Pavan kumar, Usharama College Of Engg. & Tech. A.DurgaBhavani, Usharama College Of Engg. & Tech. Y.Padma is Assistant Professor in department of Information Technology, PVPSIT, Kanuru, and Vijayawada, India. She holds M.Tech and B.Tech in 2006 and 2002 respectively. She has 11 years of teaching experience. Her research interests are Software Architecture, Agile Technologies and Natural Language Processing. K.Pavan kumar received the M Tech degree from ANU in Currently he is working as Assistant Professor in UsharamaCollegeofEngineeri ng&technology,telaprolu, Andhra Pradesh, India.He has seven years of teaching experience.his research interests are networks, Network security and compiler design. A.DurgaBhavani received the M Tech degree from JNTUH in Currently she is working as Assistant Professor in Usharama College of Engineering & Technology, Telaprolu, Andhra Pradesh, India. She has seven years of teaching experience. Her research interests are networks, Network security and compiler design. ISSN: Page 37