Yahia Abdalla

Followers

Following

Public Views

Jonathan Zittrain

Harvard University

Beat Signer

Vrije Universiteit Brussel

Julita Vassileva

University of Saskatchewan

John F Dooley

Knox College

Antoine Meyer

Université Gustave Eiffel

Roshan Chitrakar

Nepal College of Information Technology

Lev Manovich

Graduate Center of the City University of New York

Dr. Shadab Alam

Jazan University

PALIMOTE JUSTICE

RIVERS STATE POLYTECHNIC

Ferhat Bozkurt

Ataturk University

Interests

Uploads

Papers by Yahia Abdalla

Cooperative Spectrum Sensing with Distributed Detection Threshold

2010 Second International Conference on Network Applications, Protocols and Services, 2010

This paper proposes a cooperative spectrum sensing algorithm based on distributed fusion strategy... more This paper proposes a cooperative spectrum sensing algorithm based on distributed fusion strategy and maintained probability of false alarm for cognitive radio. It further introduces a reporting strategy that discusses how cooperative sensing in distributed manner can select among possible candidate nodes in order to reduce bandwidth requirement. We adopted a dynamic distributed architecture for cooperative sensing based on the link quality of the candidate nodes and found condition on the channel quality for cooperation to be beneficial. Using probability of detection, and Bit Error Rate (BER) as performance metrics we evaluated the performance improvement of distributed cooperation over direct cooperation and non-cooperative sensing. We used analytical formulation with possible candidate selection criteria to investigate and maximize the distributed cooperation gain. By employing such distribution and selection technique, the reporting error due to the fading channel is reduced based on number of candidate nodes. Results show that the method effectively improve performance of sensing, it increase the probability of detection up to 0.9 at <;0.1 probability of false alarm. Sensitivity requirement is reduced with network scale and the node number to participate in decision fusion is reduced about 42% at probability of false alarm 0.1. Receiver operation characteristic (ROC) curve has obvious improvement compared with existing methods.

الحساب اآللي لطول الصف بغرض تقليل التأخير على الموجهات

The delay experienced by packets on routers, has become a problem and it the first cause, which r... more The delay experienced by packets on routers, has become a problem and it the first cause, which reduces the effective functioning of the Internet, this delay is due to the significant increase in the length of the queues on routers, the increase in buffer size by manufacturing in order to prevent the packets drops, forgetting that prevent the packet dropping lead to increase the delay, and the drop of the packets itself is important for the TCP protocol, in this paper we developed a new algorithm called the automatic calculation of the length of the queues (auto), the main work for this algorithm is to modify the length of the queue B automatically, according to the equation , where that C is the channel capacity and RTT is the time to send a packet and return Ack, and n is the number of connections probably estimated and not retain any information relating to connections, the difference between this algorithm and Controlling Queue Delay (Codel), is that the Codel algorithm deal wit...

Review of Artificial Immune System Research

Artificial immune system (AIS) is a metaphorical computational intelligence system developed usin... more Artificial immune system (AIS) is a metaphorical computational intelligence system developed using ideas and theories extracted from biological immune system. It is a growing area of research attempts to bridge the divide between immunology and engineering, it exploits the mechanisms of the natural immune system including functions, principles and models in order to develop problem solving techniques. AIS is offering great diversity of problem solving algorithms and techniques. It is one of the attracting fields, which notably succeed in convincing researchers to start investigating and developing real-world models to non-linear engineering problems applied to different applications such as anomaly detection, classification, machine learning, clustering etc. In spite of those great properties of AIS, researchers continue arguing that AIS research does not yet reach the quality and importance of the other computational intelligence techniques like neural networks, DNA computation, ev...

Download

الحساب الآلي لطول الصف بغرض تقليل التأخير على الموجهات

Distributed Cooperative Spectrum Sensing in Cognitive Radio Networks with Adaptive Detection Threshold

This paper proposes a cooperative sensing algorithm based on distributed fusion strategy and main... more This paper proposes a cooperative sensing algorithm based on distributed fusion strategy and maintained probability of false alarm for cognitive radio. It further introduces a reporting strategy that discusses how cooperative sensing in distributed manner can select among possible candidates in order to reduce bandwidth requirement. We adopted a dynamic distributed architecture for cooperative sensing based on the link quality and found condition on the channel quality for cooperation to be beneficial. Using probability of detection, and BER metrics we evaluated the performance improvement of distributed cooperation over direct cooperation and noncooperative sensing. We used analytical formulation with possible candidate selection criteria to investigate and maximize the cooperation gain. By employing such distribution and selection technique, the reporting error due to the fading channel is reduced. Results show that the method effectively improve performance of sensing, it increase the probability of detection up to 0.9 at <0.1 probability of false alarm. Sensitivity requirement is reduced with network scale and the number of nodes participate in decision fusion is reduced about 42% at probability of false alarm 0.1. ROC curve has obvious improvement compared with existing methods.

Download

A Novel Multilayer Artificial Immune System for Network Defense

Artificial Immune System is a promising computational intelligence system inspired by human immun... more Artificial Immune System is a promising computational intelligence system inspired by human immune system which acts as a natural resistance to diseases using sophisticated mechanisms intended to protect our bodies from invaders which are facing a number of layers of defense, i.e. physical, physiological, innate and adaptive layers. Recently we proposed a multilayer network defense artificial immune system inspired by innate immunity in humans, the outcome of that work showed encouraging results from the innate layer. This paper describes a framework of a multilayered network defense system composed of two main layers, innate and adaptive layers, both layers are described, the innate layer as a first layer of defense which is designed and implemented using fuzzy logic expert system, and adaptive layer as a second layer and shows detailed results from the whole system. The innate layer shows very encouraging results since it has already dealt with 77% of the whole traffic with false ...

Cooperative Spectrum Sensing with Distributed Detection Threshold

2010 Second International Conference on Network Applications, Protocols and Services, 2010

الحساب اآللي لطول الصف بغرض تقليل التأخير على الموجهات

Review of Artificial Immune System Research

Download

الحساب الآلي لطول الصف بغرض تقليل التأخير على الموجهات

Distributed Cooperative Spectrum Sensing in Cognitive Radio Networks with Adaptive Detection Threshold

Download

A Novel Multilayer Artificial Immune System for Network Defense

Yahia Abdalla

Related Authors

Uploads

Papers by Yahia Abdalla

Log In