The increasing complexity of smartphone applications and services necessitate high battery consumption but the growth of smartphones' battery capacity is not keeping pace with these increasing power demands. To overcome this problem, researchers gave birth to the Mobile Cloud Computing (MCC) research area. In this paper we advance on previous ideas, by proposing and implementing the first known Near Field Communication (NFC)-based computation offloading framework. This research is motivated by the advantages of NFC's short distance communication, with its better security, and its low battery consumption. We design a new NFC communication protocol that overcomes the limitations of the default protocol; removing the need for constant user interaction, the one-way communication restraint, and the limit on low data size transfer. We present experimental results of the energy consumption and the time duration of two computationally intensive representative applications: (i) RSA key generation and encryption, and (ii) gaming puzzles. We show that when the helper device is more powerful than the device offloading the computations, the execution time of the tasks is reduced. Finally, we show that devices that offload application parts considerably reduce their energy consumption due to the low-power NFC interface and the benefits of offloading.
However, the current state of their project is quite preliminary and does not present any real implementation. Furthermore, the design is quite limited, due to the fact that it requires the user to constantly tap on the device: once when offloading the security computation and another tap when receiving the result. Conversely, in this work we have redesigned the NFC communication protocol to eliminate the need for user intervention, which enables a convenient and automated offloading process. NFC-based computation offloading does not need to consider most of the problems that traditional offloading frameworks face. For example, the low--range communication capabilities of NFC eliminate the need for data encryption, which of course is an overhead that current frameworks have to deal with @cite_4 . Moreover, our architecture allows the mobile devices to automatically connect with the powerful offloadee entities, since they will be in close NFC proximity, eliminating the need for long registration process as presented in @cite_18 or intentionally neglected as in other works.
@cite_18 @cite_4
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Smartphones have exploded in popularity in recent years, becoming ever more sophisticated and capable. As a result, developers worldwide are building increasingly complex applications that require ever increasing amounts of computational power and energy. In this paper we propose ThinkAir, a framework that makes it simple for developers to migrate their smartphone applications to the cloud. ThinkAir exploits the concept of smartphone virtualization in the cloud and provides method-level computation offloading. Advancing on previous work, it focuses on the elasticity and scalability of the cloud and enhances the power of mobile cloud computing by parallelizing method execution using multiple virtual machine (VM) images. We implement ThinkAir and evaluate it with a range of benchmarks starting from simple micro-benchmarks to more complex applications. First, we show that the execution time and energy consumption decrease two orders of magnitude for a N-queens puzzle application and one order of magnitude for a face detection and a virus scan application. We then show that a parallelizable application can invoke multiple VMs to execute in the cloud in a seamless and on-demand manner such as to achieve greater reduction on execution time and energy consumption. We finally use a memory-hungry image combiner tool to demonstrate that applications can dynamically request VMs with more computational power in order to meet their computational requirements. Despite their steadily increasing capabilities, mobile end-user devices such as smart phones often suffer from reduced processing and storage resources. Cloud-based mobile augmentation (CMA) has recently emerged as a potential solution to this problem. CMA combines concepts of cloud computing and surrogate computing in order to offload resource-intensive tasks to external resources. During the past years, different CMA frameworks have been introduced that enable the development and usage of CMA-based applications. Unfortunately, these frameworks have usually not been designed with security in mind but instead mainly focus on efficient offloading and reintegration mechanisms. Hence, reliance on CMA concepts in security-critical fields of application is currently not advisable. To address this problem, this paper surveys currently available CMA frameworks and assesses their suitability and applicability in security-critical fields of application. For this purpose, relevant security requirements are identified and mapped to the surveyed CMA frameworks. Results obtained from this assessment show that none of the surveyed CMA framework is currently able to meet all relevant security requirements. By identifying security limitations of currently available CMA frameworks, this paper represents a first important step towards development of a secure CMA framework and hence paves the way for a use of CMA-based applications in security-critical fields of application.