Mohammad Shojafar
Mohammad Shojafar (S'13-M'17-SM'19) is Senior Lecturer (Associate professor) in the Network Security, an Intel Innovator, a Senior IEEE member, working in the 5G Innovation Centre (5GIC) at the University of Surrey, UK. Before joining 5GIC, he was a Senior Researcher and a Marie Curie Fellow in the SPRITZ Security and Privacy Research group at the University of Padua (UNIPD), Italy. He was a Senior Researcher working in a network security project jointly with Ryerson University & Telus Communications Inc (TELUS) in Toronto, Canada, in 2019. Also, he was CNIT Senior Researcher at the University of Rome Tor Vergata contributed to 5G PPP European H2020 SUPERFLUIDITY; project. Mohammad was a PI of the PRISENODE project, a 275,000 euro Horizon 2020 Marie Curie project in the areas of network security collaborating at UNIPD, Italy. He also was a PI on an Italian SDN security and privacy (60,000 euro) supported by the UNIPD. He is Associate Editor in IEEE TCE.
Supervisors: Ali Miri, Mauro Conti, Mukesh Singhal, Rajmukar Buyya, Enzo Baccarelli, and Jemal Abawajy
Address: Department of Mathematics and Computer Science,
University of Padua,
Via Trieste, 63,
35131, Padua, Italy.
Supervisors: Ali Miri, Mauro Conti, Mukesh Singhal, Rajmukar Buyya, Enzo Baccarelli, and Jemal Abawajy
Address: Department of Mathematics and Computer Science,
University of Padua,
Via Trieste, 63,
35131, Padua, Italy.
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Papers by Mohammad Shojafar
available for users, and they only pay for used resources The most important issues in cloud computing are scheduling and energy consumption which many researchers worked on them. In these systems a scheduling mechanism has two phases: task prioritization and processor selection. Di fferent priorities may cause to di fferent makespan and for each processor which assigned to the task, the energy consumption is di fferent. So
a good scheduling algorithm must assign priority to each task and select the best processor for them, in such a way that makespan and energy consumption be minimized. In this paper, we proposed a two phase's algorithm for scheduling, named TETS, the first phase is task prioritization and the second phase is processor assignment.We use three prioritization methods for prioritize the tasks and produce optimized initial chromosomes and assign the tasks to processors which is an energy-aware model. Simulation results indicate that our algorithm is better than previous algorithms in terms of energy consumption and makespan. It can improve
the energy consumption by 20% and makespan by 4%.
components of mobile applications. The ultimate goal of RSA is to reduce execution time and energy consumption of resource-intensive mobile applications which contributes to successful MCC adoption. Role of RSA is critical in efficiently executing resource-intensive mobile applications in the cloud. Although several aspects of MCC have been extensively reviewed, analysis of RSAs in MCC is overlooked.Therefore, it is important
to provide a comprehensive review of RSA to complement existing literature in MCC. In this paper, we conduct a survey to
review the state-of-the-art RSA approaches in MCC and present
the taxonomy of existing RSA approaches. We present a brief
tutorial on resource scheduling in MCC followed by a critical
review of some of the most credible approaches to highlight
their advantages and disadvantages. We then discuss the open
challenges in this area and point out future research directions.
available for users, and they only pay for used resources The most important issues in cloud computing are scheduling and energy consumption which many researchers worked on them. In these systems a scheduling mechanism has two phases: task prioritization and processor selection. Di fferent priorities may cause to di fferent makespan and for each processor which assigned to the task, the energy consumption is di fferent. So
a good scheduling algorithm must assign priority to each task and select the best processor for them, in such a way that makespan and energy consumption be minimized. In this paper, we proposed a two phase's algorithm for scheduling, named TETS, the first phase is task prioritization and the second phase is processor assignment.We use three prioritization methods for prioritize the tasks and produce optimized initial chromosomes and assign the tasks to processors which is an energy-aware model. Simulation results indicate that our algorithm is better than previous algorithms in terms of energy consumption and makespan. It can improve
the energy consumption by 20% and makespan by 4%.
components of mobile applications. The ultimate goal of RSA is to reduce execution time and energy consumption of resource-intensive mobile applications which contributes to successful MCC adoption. Role of RSA is critical in efficiently executing resource-intensive mobile applications in the cloud. Although several aspects of MCC have been extensively reviewed, analysis of RSAs in MCC is overlooked.Therefore, it is important
to provide a comprehensive review of RSA to complement existing literature in MCC. In this paper, we conduct a survey to
review the state-of-the-art RSA approaches in MCC and present
the taxonomy of existing RSA approaches. We present a brief
tutorial on resource scheduling in MCC followed by a critical
review of some of the most credible approaches to highlight
their advantages and disadvantages. We then discuss the open
challenges in this area and point out future research directions.
efficient dynamic resource provisioning scheduler which applied in Networked Data Centers (NetDCs). This method is connected to (possibly, mobile) clients through TCP/IP-based vehicular backbones The salient features of this algorithm is that: i) It is adaptive and admit distributed scalable implementation; ii) It is capable to provide hard QoS guarantees, in terms of minimum/maximum instantaneous rate of the traffic delivered to the client, instantaneous goodput and total processing delay; and, iii) It explicitly accounts for the dynamic interaction between computing and networking resources, in order to maximize the resulting energy efficiency. Actual performance of the proposed scheduler in the presence of :i) client mobility; ii)wireless fading; iii)reconfiguration and two-thresholds consolidation costs of the underlying networked computing platform; and, iv)abrupt changes of the transport quality of the available TCP/IP mobile connection, is numerically tested and compared against the corresponding ones of some state-of-the-art static schedulers, under both synthetically generated and measured real-world workload traces.