4 resultados para LARGE-MAGELLANIC-CLOUD
em CORA - Cork Open Research Archive - University College Cork - Ireland
Resumo:
The increasing penetration rate of feature rich mobile devices such as smartphones and tablets in the global population has resulted in a large number of applications and services being created or modified to support mobile devices. Mobile cloud computing is a proposed paradigm to address the resource scarcity of mobile devices in the face of demand for more computing intensive tasks. Several approaches have been proposed to confront the challenges of mobile cloud computing, but none has used the user experience as the primary focus point. In this paper we evaluate these approaches in respect of the user experience, propose what future research directions in this area require to provide for this crucial aspect, and introduce our own solution.
Resumo:
Nearly one billion smart mobile devices are now used for a growing number of tasks, such as browsing the web and accessing online services. In many communities, such devices are becoming the platform of choice for tasks traditionally carried out on a personal computer. However, despite the advances, these devices are still lacking in resources compared to their traditional desktop counterparts. Mobile cloud computing is seen as a new paradigm that can address the resource shortcomings in these devices with the plentiful computing resources of the cloud. This can enable the mobile device to be used for a large range of new applications hosted in the cloud that are too resource demanding to run locally. Bringing these two technologies together presents various difficulties. In this paper, we examine the advantages of the mobile cloud and the new approaches to applications it enables. We present our own solution to create a positive user experience for such applications and describe how it enables these applications.
Resumo:
The mobile cloud computing model promises to address the resource limitations of mobile devices, but effectively implementing this model is difficult. Previous work on mobile cloud computing has required the user to have a continuous, high-quality connection to the cloud infrastructure. This is undesirable and possibly infeasible, as the energy required on the mobile device to maintain a connection, and transfer sizeable amounts of data is large; the bandwidth tends to be quite variable, and low on cellular networks. The cloud deployment itself needs to efficiently allocate scalable resources to the user as well. In this paper, we formulate the best practices for efficiently managing the resources required for the mobile cloud model, namely energy, bandwidth and cloud computing resources. These practices can be realised with our mobile cloud middleware project, featuring the Cloud Personal Assistant (CPA). We compare this with the other approaches in the area, to highlight the importance of minimising the usage of these resources, and therefore ensure successful adoption of the model by end users. Based on results from experiments performed with mobile devices, we develop a no-overhead decision model for task and data offloading to the CPA of a user, which provides efficient management of mobile cloud resources.
Resumo:
Mobile Cloud Computing promises to overcome the physical limitations of mobile devices by executing demanding mobile applications on cloud infrastructure. In practice, implementing this paradigm is difficult; network disconnection often occurs, bandwidth may be limited, and a large power draw is required from the battery, resulting in a poor user experience. This thesis presents a mobile cloud middleware solution, Context Aware Mobile Cloud Services (CAMCS), which provides cloudbased services to mobile devices, in a disconnected fashion. An integrated user experience is delivered by designing for anticipated network disconnection, and low data transfer requirements. CAMCS achieves this by means of the Cloud Personal Assistant (CPA); each user of CAMCS is assigned their own CPA, which can complete user-assigned tasks, received as descriptions from the mobile device, by using existing cloud services. Service execution is personalised to the user's situation with contextual data, and task execution results are stored with the CPA until the user can connect with his/her mobile device to obtain the results. Requirements for an integrated user experience are outlined, along with the design and implementation of CAMCS. The operation of CAMCS and CPAs with cloud-based services is presented, specifically in terms of service description, discovery, and task execution. The use of contextual awareness to personalise service discovery and service consumption to the user's situation is also presented. Resource management by CAMCS is also studied, and compared with existing solutions. Additional application models that can be provided by CAMCS are also presented. Evaluation is performed with CAMCS deployed on the Amazon EC2 cloud. The resource usage of the CAMCS Client, running on Android-based mobile devices, is also evaluated. A user study with volunteers using CAMCS on their own mobile devices is also presented. Results show that CAMCS meets the requirements outlined for an integrated user experience.