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Energy Aware Task Assignment with Cost Optimization in Mobile Cloud Computing

International Journal of Communications, Network and System Sciences 2018年第8期11卷 175-185页

作者： Irfan Ali Jamali abdullah Lakhan abdul rasheed mahesar Dileep Kumar Sajnani Department of Computer Science in Southeast University Nanjing China

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.

关键词： Mobile Cloud Computing Energy-Efficient Task Offloading EETS Mobile Offloading

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Latency Aware and Service Delay with Task Scheduling in Mobile Edge Computing

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Communications and Network 2018年第4期10卷 127-141页

作者： Dileep Kumar Sajnani abdul rasheed mahesar abdullah Lakhan Irfan Ali Jamali Department of Computer Science and Engineering Southeast University Nanjing China

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.

关键词： MLAWAS Multilayer Latency Aware Workload Assignment Strategy MCC Mobile Cloud Computing MEC Mobile Edge Computing Service Delay Latency

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Simultaneous Quantification of Ibuprofen and Paracetamol in Tablet Formulations Using Transmission Fourier Transform Infrared Spectroscopy

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American Journal of Analytical Chemistry 2012年第8期3卷 503-511页

作者： Muhammad Ali Mallah Syed Tufail Hussain Sherazi Sarfaraz Ahmed mahesar abdul Rauf Khaskheli National Center of Excellence in Analytical Chemistry University of Sindh Jamshoro Pakistan

A very simple, non-destructive, inexpensive and green strategy was applied for the simultaneous determination of ibu-profen (IBP) and paracetamol (PC) using transmission Fourier Transform Infrared (FTIR) spectroscopy in tablet formulations for routine quality control laboratories. For the determination of the active pharmaceutical ingredients (API), KBr pellets containing known amount of standards and samples were used for acquisition of the FTIR spectra. The partial least squares (PLS) calibration model was developed using the spectral region from 1781 - 1683 cm-1 for IBP and 1630 - 1530 cm-1 for PC. The excellent coefficients of determination (R2), 0.9999 and 0.9998 were achieved for IBP and PC, respectively. The accuracy of calibration model was also verified through root mean square error of cross validation (RMSECV) which was found to be 0.064. This work clearly shows the capability of transmission FTIR spectroscopy for assessment of exact quantity of API to control the quality of finished products as well as during processing in pharmaceutical industries without involvement of any solvent.

关键词： Transmission FTIR Pharmaceutical Formulation Ibuprofen Paracetamol Simultaneous Determination Quantitative Analysis

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