Mohammed Madi

Mohammed Madi


Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
8 May 2020 in Turkish Journal of Electrical Engineering and Computer Sciences
Verified
Journal Article
Open access
MMMohammed Madi
Mohammed Madi
FJFidaa Jarghon
Fidaa Jarghon
Yousef FazeaYousef Fazea
Yousef Fazea
Omar AlmomaniOmar Almomani
Omar Almomani
ASAdeeb Saaidah
Adeeb Saaidah

1 January 2023 in AIP Conference Proceedings
Verified
Conference Paper
Open access
PDF file
Omar AlmomaniOmar Almomani
Omar Almomani
MAMohammed Almaayah
Mohammed Almaayah
MMMohammed Madi
Mohammed Madi
AAAdeeb Alsaaidah
Adeeb Alsaaidah
MAMalek Almomani
Malek Almomani
SSSami Smadi
Sami Smadi
With the advancement of Internet technologies, network security concerns are growing exponentially. One of the most difficult issues of network security is keep

1 April 2020
Verified
Conference Paper
Closed access
NMNadim Madi
Nadim Madi
MMMohammed Madi
Mohammed Madi
The steady growing trend of user demand in using various 4G mobile broadband applications obligates telecom operators to thoroughly plan a precise Quality of Service (QoS) contract with its subscribers. This directly reveals a challenge in figuring out a sophisticated behavior of radio resources (RBs) at the base station to effectively handle the oscillated loads to fulfill their QoS profiles. This paper elaborates on the above issue by analyzing the behavior of the downlink packet scheduling scheme and proposes a solution to bridge between the two major QoS indicators for Real-Time (RT) services, that are, throughput and delay. The proposed scheduling scheme emphasizes that a prior RBs planning indeed has an immense impact on the behavior of the deployed scheduling rule, particularly, when heterogeneous flows share the channel capacity. System-level simulations are performed to evaluate the proposed scheduling scheme in a comparative manner. The numerical results of throughput and delay assured that diverse QoS profiles can be satisfied in case of considering RBs planning.

1 January 2013 in International Journal of Grid and High Performance Computing
Verified
Journal Article
Closed access
PDF file
MMMohammed Madi
Mohammed Madi
YYYuhanis Yusof
Yuhanis Yusof
SHSuhaidi Hassan
Suhaidi Hassan
Data Grid is an infrastructure that manages huge amount of data files, and provides intensive computational resources across geographically distributed collaboration. To increase resource availability and to ease resource sharing in such environment, there is a need for replication services. Data replication is one of the methods used to improve the performance of data access in distributed systems by replicating multiple copies of data files in the distributed sites. Replica placement mechanism is the process of identifying where to place copies of replicated data files in a Grid system. Existing work identifies the suitable sites based on number of requests and read cost of the required file. Such approaches consume large bandwidth and increases the computational time. The authors propose a replica placement strategy (RPS) that finds the best locations to store replicas based on four criteria, namely, 1) Read Cost, 2) File Transfer Time, 3) Sites’ Workload, and 4) Replication Sites. OptorSim is used to evaluate the performance of this replica placement strategy. The simulation results show that RPS requires less execution time and consumes less network usage compared to existing approaches of Simple Optimizer and LFU (Least Frequently Used).

22 March 2021
Verified
Conference Paper
Closed access
Yousef FazeaYousef Fazea
Yousef Fazea
Fathey MohammedFathey Mohammed
Fathey Mohammed
MMMohammed Madi
Mohammed Madi
AAAmmar Ahmed Alkahtani
Ammar Ahmed Alkahtani
Network function virtualization (NFV / VNF) and information-centric networking (ICN) are two trending technologies that have attracted expert’s attention. NFV is a technique in which network functions (NF) are decoupling from commodity hardware to run on to create virtual communication services. The virtualized class nodes can bring several advantages such as reduce Operating Expenses (OPEX) and Capital Expenses (CAPEX). On the other hand, ICN is a technique that breaks the host-centric paradigm and shifts the focus to “named information” or content-centric. ICN provides highly efficient content retrieval network architecture where popular contents are cached to minimize duplicate transmissions and allow mobile users to access popular contents from caches of network gateways. This paper investigates the implementation of NFV in ICN. Besides, reviewing and discussing the weaknesses and strengths of each architecture in a critical analysis manner of both network architectures. Eventually, highlighted the current issues and future challenges of both architectures.

1 August 2015
Verified
Conference Paper
Closed access
MMMohammed Madi
Mohammed Madi
HTHatim Mohamed Tahir
Hatim Mohamed Tahir
YYYuhanis Yusof
Yuhanis Yusof
SHSuhaidi Hassan
Suhaidi Hassan
The abstract Data Grid is an infrastructure that manages huge amount of data files, and provides intensive computational resources across geographically distributed collaboration. A key concept in Data Grids is replication of data, whereby multiple copies of data are stored at different geographical locations, making access to data faster and more reliable. However, replication is also bounded by two factors: the size of storage available at different sites within the Data Grid and the bandwidth between these sites. In this paper, we proposed a dynamic replication mechanism termed as Replica Number Mechanism (RNM) that determine the optimal number of replicas to be created or deleted with the aim of minimizing the overall resource usage (network bandwidth and storage usage). OptorSim is used to evaluate the performance of the proposed mechanism. The simulation results show that RNM requires less execution time and consumes less network usage and storage usage compared to existing approaches of Simple Optimizer and LFU (Least Frequently Used).