Enhanced Network performance measure for priority inhibited Networks using information theory Supervised By: Prof. Bassem M.Mokhtar Mohamed Wagdy Nomeir Faculty of Engineering, Alexandria University bmokhtar@alexu.edu.eg, es-mohamed.nomeir1318@alexu.edu.eg Abstract Methodology & System Setup Our setup is the simplest priority network environment, static priority, however the measure used before couldn’t give the accurate performance measure needed. We will use 3 nodes y1, y2 and y3. Each node is independent and has a different priority; y2 has the highest priority then y1 then y3, they are Bernoulli random variables where 1 means that they have message to send. A central controller (scheduler) that decides which node to send the data in the network given the network information. We extend information theory, rate distortion measures for measuring the network performance. We consider the network information as our information source and the minimum required information to achieve a given performance. Let X= [ y1, y2 , y3] be the complete network information and be the estimated network information in the controller due to transmission error probabilities. is the distortion measure used before which resembles the cost of not using the complete information. In this poster we investigate a well known network performance measure and detect some network properties and parameters that it doesn’t satisfy or grasp. We propose an extra factor that will help in enhancing the measuring of network performance. Introduction Network performance can be quantified by many measures such as throughput, latency, link capacity, and data error rate. Also available network information is a key factor in determining network performance. Network information can be any information concerning traffic information, channel state or the topology of the network. In ideal case scenario as the information increases the performance increases, but in many real networks it might not be the case where there might be an inverse relation; Consider a network with small capacity and large demand for network information, if we increase the information in a low capacity network the overall performance decreases. Real networks that should be studied must have capacity threshold, transition error probability also one important factor is the priority constraints in the network. Priority inside the network should be considered in its performance measure to fully define the performance of the network. Priority can be static, dynamic (stochastic) or location dependent. In this poster we apply a well known performance measure in a priority constrained network and show its defects by simulation results using MATLAB then we introduce an extra weighting factor in order to grasp this property in the measure without the need for a new one. Results The measure matrix doesn’t show any cost for priority property. This indifference gives non accurate results as shown in the figures. We should add an extra weighting: System Parameters D is the accepted distortion threshold. denotes the network performance function. is the priority of the chosen node. is the priority of the node that should be chosen with full network information. is the lowest priority (highest magnitude) in the network. Conclusions The measure gives non accurate results. The results can be modified by extra weighting to grasp the priority property in the network. For different type of priority constraint, stochastic or location, N won’t be constant. If there are many priorities in the network and the weighting factor is not used, the errors will be more apparent and the measure won’t be useful. References J. Hong, V. O. Li, Impact of information on network performance-an information-theoretic perspective, in: Global Telecommunications Conference, 2009. S. M. Ross, Introduction to probability models, Academic press, 2014. T. M. Cover, J. A. Thomas, Elements of information theory, John Wiley & Sons, 2012. Biography Bassem M. Mokhtar is assistant professor in the Department of the Electrical Engineering in Faculty of Engineering, University of Alexandria, Egypt. He received his BS and MS degrees in Electrical Engineering from Alexandria University, Egypt, in 2004 and 2008, respectively. He received PhD in Computer Engineering from Virginia Tech, USA in 2014. Mohamed Wagdy Nomeir is a 3rd year student in the Department of the Electrical Engineering in Faculty of Engineering, University of Alexandria, Egypt. 33rd NATIONAL RADIO SCIENCE CONFERENCE (NRSC 2016), www.nrsc2016.aast.edu