Latency Aware Optimal Workload Assignment in Mobile Edge Cloud Offloading Network

• Published in: 2018 IEEE 4th International Conference on Computer and Communications (ICCC) pp. 658 - 662
• Main Authors: Sajnani, Dileep Kumar, Mahesar, Abdul Rasheed, Lakhan, Abdullah, Jamali, Irfan Ali, Lodhi, Rakhshanda, Aamir, Muhammad
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2018
• Subjects: A A; benc mar a lications; Cloud computing; Containers; Delays; Mobile handsets; offloading; Performance evaluation; rocess delay; Servers; Time factors; transmission delay; ybrid r n time en ironments
• DOI: 10.1109/CompComm.2018.8780954

Mobile Edge Cloud Architecture (MECA) facilitates mobile devices to perform computational intensive applications in a collaborative manner with cloud computing. The offloading system in MECA is a technique in which application can be divided into local execution and cloud execution. However, existing MECA does not stable due to a longer delay for interactive and real time applications which have to execute within a given deadline. Since, current offloading systems do not consider communication and cloud process delay, they have just focused on mobile execution time. In this paper, we are minimizing the hybrid delay (i.e., mobile process delay, communication delay, cloud process delay) in order to minimize average response time of application. To cope with the above challenges we have proposed Latency Aware Task Assignment Algorithm (LATA), which aim is to minimize the response time of interactive application. Simulation results show that our proposed LATA has reduced response time of application as compared to baseline approaches.