Mohammad Shojafar

In society today, mobile communication and mobile computing have a significant role in every aspect of our lives, both personal and public communication. However, the growth in mobile computing usage can be enhanced by integrating mobile computing into cloud computing. This will result in emerging a new model called Mobile Cloud Computing (MCC) that has recently attracted much attention in the academic sector. In this work, the main challenges and issues related to MCC are outlined. We also present the recent work and countermeasure solutions that are proposed by researchers to counter the challenges and lastly, crucial open research and issues that direct future research is highlighted.

Mobile Cloud Computing

10.1109/dese.2017.21

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Citations (54)

TEL: Low-Latency Failover Traffic Engineering in Data Plane

arXiv (Cornell University) (2020)

Habib Mostafaei Mohammad Shojafar Mauro Conti

Modern network applications demand low-latency traffic engineering in the presence of network failure while preserving the quality of service constraints like delay and capacity. Fast Re-Route (FRR) mechanisms are widely used for traffic re-routing purposes in failure scenarios. Control plane FRR typically computes the backup forwarding rules to detour the traffic in the data plane when the failure occurs. This mechanism could be computed in the data plane with the emergence of programmable data planes. In this paper, we propose a system (called TEL) that contains two FRR mechanisms, namely, TEL-C and TEL-D. The first one computes backup forwarding rules in the control plane, satisfying max-min fair allocation. The second mechanism provides FRR in the data plane. Both algorithms require minimal memory on programmable data planes and are well-suited with modern line rate match-action forwarding architectures (e.g., PISA). We implement both mechanisms on P4 programmable software switches (e.g., BMv2 and Tofino) and measure their performance on various topologies. The obtained results from a datacenter topology show that our FRR mechanism can improve the flow completion time up to 4.6x$-$7.3x (i.e., small flows) and 3.1x$-$12x (i.e., large flows) compared to recirculation-based mechanisms, such as F10, respectively.

Forwarding plane

Failover

10.48550/arxiv.2009.13640

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OVRP_ICA: An Imperialist-Based Optimization Algorithm for the Open Vehicle Routing Problem

Lecture notes in computer science (2015)

Shahab Shamshirband Mohammad Shojafar Ali Asghar Rahmani Hosseinabadi Ajith Abraham

Vehicle Routing Problem

Imperialist competitive algorithm

10.1007/978-3-319-19644-2_19

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