Mobile Cloud computing is a technology of delivering services, such as software, hardware (virtual as well) and bandwidth over the Internet. Mobile devices are enabled in order to explore, especially Smart phones. The mobile cloud computing technology is growing rapidly among the customers and many companies such as Apple, Google, Facebook and Amazon with rich users. Users can access their data at any time, at any place, even with any device including mobile devices by using the cloud storage services, although these properties offer flexibility and scalability in controlling data, however, at the same time it reminds us with new security threats. These security issues can be resolved by proper handling of data. The cloud server provider can secure the data by applying the encryption and decryption techniques while storing the data over the cloud. In this paper, we proposed some encryption and decryption methods for securing the data over the cloud so that an unauthorized person or machine cannot access the confidential data owing to encrypted form.

Nowadays, the usage of mobile devices is progressively increased. Until, delay sensitive applications (Augmented Reality, Online Banking and 3D Game) are required lower delay while executed in the mobile device. Mobile Cloud Computing provides a rich resource environment to the constrained-resource mobility to run above mentioned applications, but due to long distance between mobile user application and cloud server introduces hybrid delay (i.e., network delay and process delay). To cope with the hybrid delay in mobile cloud computing for delay sensitive applications, we have proposed novel hybrid delay task assignment (HDWA) algorithm. The preliminary objective of the HDWA is to run the application on the cloud server in an efficient way that minimizes the response time of the application. Simulation results show that proposed HDWA has better performance as compared to baseline approaches.

In a traditional Mobile Cloud Computing (MCC), a stream of data produced by mobile users (MUs) is uploaded to the remote cloud for additional processing throughout the Internet. Though, due to long WAN distance it causes high End to End latency. With the intention of minimize the average response time and key constrained Service Delay (network and cloudlet Delay) for mobile users (MUs), offload their workloads to the geographically distributed cloudlets network, we propose the Multi-layer Latency Aware Workload Assignment Strategy (MLAWAS) to allocate MUs workloads into optimal cloudlets, Simulation results demonstrate that MLAWAS earns the minimum average response time as compared with two other existing strategies.

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In this paper, we are investigating the power consumption of mobile device while performing offloading system. The offloading system is way in which mobile application can be divided into local and remote execution in order to alleviate the CPU energy consumption. However, existing offloading systems do not consider data transfer communication energy while performing mobile offloading system. They have just focused on mobile CPU energy consumption. In this paper, we are investigating the energy consumption mobile CPU and communication energy collaboratively while performing mobile offloading for complex application. To cope up with the above problem, we have proposed Energy Efficient Task Scheduler (EETS) algorithm, whose aim is to determine optimal tasks execution in offloading system in order to minimize mobile CPU and communication energy. Simulation results show that EETS outperforms as compared to baseline approaches.