A Review on Distributed Application Processing Frameworks in Smart Mobile Devices for Mobile Cloud Computing

Shiraz, Muhammad; Gani, Abdullah; Khokhar, Rashid Hafeez; Buyya, Rajkumar

doi:10.1109/surv.2012.111412.00045

Cited by 264 publications

(126 citation statements)

References 44 publications

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“…In the distributed applications on the cloud, Muhammad et al in [71] reviewed the distributed applications processing frameworks in the smart mobile devices and this under the trend of mobile cloud computing. Antonis et al in [72] presented an architecture for evaluating, collecting, modeling and evaluating of distributed application deployment in the multi-clouds.…”

Section: Cloud Computing Applicationsmentioning

confidence: 99%

On Service Level Agreement Assurance in Cloud Computing Data Centers

Zainelabden

Ibrahim

Kliazovich

et al. 2016

2016 IEEE 9th International Conference on Cloud Computing (CLOUD)

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SaaS is providing cloud applications like all the normal classes of applications of normal computing like the web applications, le applications, email applications, real-time applications, highly interactive applications, massive data analysis applications, high performance computing applications and mobile cloud applications. Cloud computing uses the internet data centers to host the applications and data storage and also the processing power in the addition to the virtualization. Clouds are a huge stack of easily and usefully virtualized services and resources (Like software, platform and hardware).These resources are used by people all over the world and dynamically congured to accommodate more and more load and scale to a huge number of users. This stack of resources and services is delivered to the customers by a pay-per-use model which veries that the services provided by the cloud providers are provided by means of service level agreements.In this master thesis, we present an assurance to the service level agreement between the cloud users and the cloud services providers by trying to assess and evaluate the cloud computing data centers services and applications provided to the cloud users. Also we introduce mathematical test models for the web, le, real time and distributed applications. We can use these test models to see the behavior of the applications over a long time.In this master thesis, we classify the cloud applications into 8 dierent classes of applications and then identify the failures and problems which aect these cloud applications.We classify also all failures types which may occur in cloud data centers like network failures, physical server failures, VM unavailability, individual failures racks and individual component failures. We got the important metrics for each class of applications and developed real scenarios for four classes. Then, we introduce dierent failures to these scenarios to see what is the impact in the most important metrics of applications. Then, we simulate these scenarios in Network Simulator 2. Finally, we solved and mitigated the failures in simulation by using two failure mitigation techniques. The rst one is the virtual machine migration and redundancy. The second technique is the forward error correction.Experimental results acquired over the course of this master's thesis give an assessment and verication of the cloud applications services provided by the cloud provider data centers. And also verify that the cloud data center provider gives their users the best services performance and high QoS, we use this verication to assure SLA response times metric and a good quality and performance of services as mentioned inside the SLA document. This verication will be given to the cloud customers.iii iv Acknowledgment "Today don't beg, don't ask, Just thank God in silence; for all the blessings in your life. " Paulo CoelhoThe road to want something is always guided by unseen strong currents of support from people who believe that you will do it what you have set...

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Section: Cloud Computing Applicationsmentioning

confidence: 99%

On Service Level Agreement Assurance in Cloud Computing Data Centers

Zainelabden

Ibrahim

Kliazovich

et al. 2016

2016 IEEE 9th International Conference on Cloud Computing (CLOUD)

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“…Autonomic computing manage applications execution in dynamically changing and unpredictable environments without any user's manual intervention [15,102,109] by regularly checking and monitoring the changing conditions automatically. Mobile computing extends the computing facilities to the smart mobile devices in order to enhance their capabilities on demand for accommodating computational-and storage-intensive applications [1,15,59,111,118].…”

Section: Immediate Extension Of Grid Resource Managementmentioning

confidence: 99%

Survey on Grid Resource Allocation Mechanisms

et al. 2014

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Grid is a distributed high performance computing paradigm that offers various types of resources (like computing, storage, communication) to resource-intensive user tasks. These tasks are scheduled to allocate available Grid resources efficiently to achieve high system throughput and to satisfy A. Y. Zomaya University of Sydney, Sydney, Australia user requirements. The task scheduling problem has become more complex with the ever increasing size of Grid systems. Even though selecting an efficient resource allocation strategy for a particular task helps in obtaining a desired level of service, researchers still face difficulties in choosing a suitable technique from a plethora of existing methods in literature. In this paper, we explore and discuss existing resource allocation mechanisms for resource allocation problems employed in Grid systems. The work comprehensively surveys Gird resource allocation mechanisms for different architectures (centralized, distributed, static or dynamic). The paper also compares these resource allocation mechanisms based on their common features such as time complexity, searching mechanism, allocation strategy, optimality, operational environment and objective function they adopt for solving computing-and data-intensive applications. The comprehensive analysis of cutting-edge research in the Grid domain presented in this work provides readers with an understanding of essential concepts of resource allocation mechanisms in Grid systems and helps them identify important and outstanding issues for further investigation. It also helps readers to choose the most appropriate mechanism for a given system/application.

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“…A lot of researches have been done on remote execution of mobile applications services on the Cloud to increase performance and save mobile power and memory resources [19] and [20]. These researches are divided into two paths:…”

Section: B Related Workmentioning

confidence: 99%

An Enhanced Version of the MCACC to Augment the Computing Capabilities of Mobile Devices Using Cloud Computing

Elgendy¹,

Shaikh²,

Moussa³

2014

SpecialIssue

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Abstract-Recently as smartphones have a wide range of capabilities a lot of heavy applications like gaming, video editing, and face recognition are now available. However, this kind of applications need intensive computational power, memory, and battery. A lot of researches solve this problem by offloading applications to run on the Cloud due to its intensive storage and computation resources. Later, some techniques chooses to offload part of the applications while leaving the rest to be processed on the smartphone based on one or two metrics like power and CPU consumption only without any consideration to other important metrics. Our previously proposed MCACC framework has introduced a new generation of offloading frameworks that handle this problem by smartly emerging a group of real-time metrics like total execution time, energy consumption, remaining battery, memory, and security into the offloading decision. In this paper, we introduce an enhanced version of the MCACC framework that can now smartly operate under low bandwidth network scenario in addition to its existing capabilities. In this framework, any mobile application is divided into a group of services, and then each of them is either executed locally on the mobile or remotely on the Cloud through a dynamic offloading decision model. The extensive simulation studies show that both heavy and light applications can benefit from the proposed framework while saving energy and improving performance compare to previous counterparts. The enhanced MCACC turns the smartphones to be smarter as the offloading decision is taken without any user interference.

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A Review on Distributed Application Processing Frameworks in Smart Mobile Devices for Mobile Cloud Computing

Cited by 264 publications

References 44 publications

On Service Level Agreement Assurance in Cloud Computing Data Centers

On Service Level Agreement Assurance in Cloud Computing Data Centers

Survey on Grid Resource Allocation Mechanisms

An Enhanced Version of the MCACC to Augment the Computing Capabilities of Mobile Devices Using Cloud Computing

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