Abstract
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.
Highlights
The design and portability of mobile devices make them minuscule, which is mandatory for them to be movable and accessible in order to carry them anywhere [1]
With the intention of minimize the average response time and key constrained Service 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
Mobile devices are capable of sustaining a wide range of applications, a lot of demand increasing the requirements in key areas such as computation and communication [2]
Summary
The design and portability of mobile devices make them minuscule, which is mandatory for them to be movable and accessible in order to carry them anywhere [1]. Mobile devices are capable of sustaining a wide range of applications, a lot of demand increasing the requirements in key areas such as computation and communication [2]. These pretenses a challenge because the mobile phone is resource-constrained device with limited processing power, memory, storage, and battery energy. The cloud is usually located remotely and far away from its mobile users (MUs), and the Service Delay (Network and Process delay) incurred by transferring data between MUs and the cloud can be very costly. Due to the size of the network in GDN, a given the mobile user (MU) could be a significant number of network edges away from the nearest cloudlet, the Service Delay.
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