A Context-Aware Architecture Supporting Service Availability in Mobile Cloud Computing

Guerrero-Contreras, Gabriel; Garrido, José Luis García; Balderas-Díaz, Sara; Rodríguez-Domínguez, Carlos

doi:10.1109/tsc.2016.2540629

Cited by 32 publications

(15 citation statements)

References 34 publications

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“…One traditional approach is to request the cloud directly for any resource while another is to make a distributed cloud of mobile devices connected through a stable internet connection sharing resources through a pool [15]. There is a third hybrid approach in which a mobile device is connected to the cloud as well as to the pool of local mobile devices [3].…”

Section: Related Workmentioning

confidence: 99%

“…The proposed solution is only suitable for small and medium size network because as the network size increases, the factor of efficiency decreases. In the proposed architecture [3], there are four basic components i.e. communication middleware, monitoring subsystem, context manager service, replica manager service.…”

Section: Service Availability Through Replicationmentioning

confidence: 99%

See 1 more Smart Citation

A Context Aware Mechanism for Mobile Devices to Efficiently Acquire Resources Remotely

Tasneem¹,

Siddiqui²,

Liaquat³

2019

IJCA

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Mobile devices are becoming very popular due to their portability and small size, but they are still not comparable to that of PC. Computational and network intensive applications cannot run efficiently on mobile devices due to their limited batteries and energy deficient systems. Recent works to improve mobile device efficiency include mobile cloud computing, mobile edge computing, and device to device communication. Shifting the computations on the cloud will reduce the burden of mobile device but at the same time, this implementation presents many challenges. In this paper, an algorithm is proposed which can deal with the resource acquisition from different sources by using a context aware system. Implementation of that algorithm is left for future work.

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Section: Related Workmentioning

confidence: 99%

Section: Service Availability Through Replicationmentioning

confidence: 99%

A Context Aware Mechanism for Mobile Devices to Efficiently Acquire Resources Remotely

Tasneem¹,

Siddiqui²,

Liaquat³

2019

IJCA

View full text Add to dashboard Cite

show abstract

“…In fact, the selected works focus on the recommendation (or selection) of services from different cloud platforms in MCC that are affected by user preferences [104], the current context of mobile devices [105][106][107], and social networks [7,108,109]. That means that there are multiple sources of information that are used to understand the real users' needs, and at the same time, they make the recommendation effectiveness relative, since the nature of these data is unstable and relative.…”

Section: Cloud Service Recommendationmentioning

confidence: 99%

Multi-Criteria Decision Analysis Methods in the Mobile Cloud Offloading Paradigm

Bangui

Bühnová

et al. 2017

JSAN

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Abstract:Mobile cloud computing (MCC) is becoming a popular mobile technology that aims to augment local resources of mobile devices, such as energy, computing, and storage, by using available cloud services and functionalities. The offloading process is one of the techniques used in MCC to enhance the capabilities of mobile devices by moving mobile data and computation-intensive operations to cloud platforms. Several techniques have been proposed to perform and improve the efficiency and effectiveness of the offloading process, such as multi-criteria decision analysis (MCDA). MCDA is a well-known concept that aims to select the best solution among several alternatives by evaluating multiple conflicting criteria, explicitly in decision making. However, as there are a variety of platforms and technologies in mobile cloud computing, it is still challenging for the offloading process to reach a satisfactory quality of service from the perspective of customers' computational service requests. Thus, in this paper, we conduct a literature review that leads to a better understanding of the usability of the MCDA methods in the offloading operation that is strongly reliant on the mobile environment, network operators, and cloud services. Furthermore, we discuss the challenges and opportunities of these MCDA techniques for offloading research in mobile cloud computing. Finally, we recommend a set of future research directions in MCDA used for the mobile cloud offloading process.

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“…This is of key interest in case of disasters in remote areas, where typically the common network infrastructures are not accessible and the government agencies need to apply certain action protocols to support victim search, rescue and identification. [1]. Nevertheless, the Local Mobile Cloud approach is typically supported by a Mobile Ad-Hoc NETwork (MANET), which poses new challenges [12] such as battery problems, dynamic topology among others, that must be appropriately addressed to ensure the dependability of the Mobile Cloud.…”

Section: Introductionmentioning

confidence: 99%

Push and Update Model for Supporting Service Availability in a Local Mobile Cloud

Oladeji¹,

Omotosho²

2019

IJCA

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Mobile cloud computing (MCC) is the blend of cloud computing, mobile computing and wireless network to solve resource limitations of mobile devices by providing virtualized computing resources and services in a shared and scalable environment through network on a pay per use model to mobile clients. The availability of these active servicesstorage, google mail etc-in the mobile cloud keep the mobile cloud active and relevant. Research reveals that battery plays a major role in the provisioning of a service in a mobile cloud. However, Mobile Ad-hoc Network (MANET) as a platform that support local mobile cloud exhibits battery problems that pose greater challenges to the availability of a service as users move from one node to the other. Hence, this work aims at reducing the energy requirement of the monitoring service system in a local mobile network using a push and update technique.A push and update service monitoring model was developed and simulated on ns-3 to monitor service availability and necessary device status parameters such as energy level, processing power and storage capacity of mobile devices (nodes) in MANET. The push and update table was used to hold necessary device information by the service monitoring system which enables it to rest (come up at set time intervals) and alternate between two modes (Hibernation and Activation), and by so doing it saves computing resource and energy for other computation tasks. The model was evaluated by comparing it with the existing framework using service availability and battery consumption.The simulation results revealed on average 96.86% and 676.73mAh, of service availability and battery consumption respectively, for the developed PUP model, against 95.93% and 895.43mAh of average service availability and battery consumption respectively, for the existing framework.

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A Context-Aware Architecture Supporting Service Availability in Mobile Cloud Computing

Cited by 32 publications

References 34 publications

A Context Aware Mechanism for Mobile Devices to Efficiently Acquire Resources Remotely

A Context Aware Mechanism for Mobile Devices to Efficiently Acquire Resources Remotely

Multi-Criteria Decision Analysis Methods in the Mobile Cloud Offloading Paradigm

Push and Update Model for Supporting Service Availability in a Local Mobile Cloud

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