MODELING RADIO RESOURCE MANAGEMENT IN COGNITIVE RADIO SYSTEM BASED ON OFDMA USING COLORED PETRI NET

Cognitive Radio(CR) system based on Orthogonal Frequency Division Multiple Access(OFDMA),such as Wireless Regional Area Networks(WRAN) and Worldwide Interoperability for Microwave Access(WiMAX),often attempt to improve performance via dynamic radio resource management,which is characterized as concurrent processing of different traffic and nondeterministic system capacity.It is essential to design and evaluate such complex system using proper modeling and analysis tools.In the previous work,most of the communication systems were modeled as Markov Chain(MC) and Stochastic Petri Nets(SPN),which have the explicit limitation in evaluating adaptive OFDMA CR system with wide area traffic.In this paper,we develop an executable top-down hier-archical Colored Petri Net(CPN) model for adaptive OFDMA CR system,and analyze its performance using CPN tools.The results demonstrate that the CPN can model different radio resource manage-ment algorithms in CR Systems,and the CPN tools require less computational effort than Markov model using Matlab,with its flexibility and adaptability to the traffics which arrival interval and processing time are not exponentially distributed.

Fault Aware Dynamic Resource Manager for Fault Recognition and Avoidance in Cloud

Fault tolerance(FT)schemes are intended to work on a minimized and static amount of physical resources.When a host failure occurs,the conventional FT frequently proceeds with the execution on the accessible working hosts.This methodology saves the execution state and applications to complete without disruption.However,the dynamicity of open cloud assets is not seen when taking scheduling choices.Existing optimization techniques are intended in dealing with resource scheduling.This method will be utilized for distributing the approaching tasks to the VMs.However,the dynamic scheduling for this procedure doesn’t accomplish the objective of adaptation of internal failure.The scheme prefers jobs in the activity list with the most elevated execution time on resources that can execute in a shorter timeframe,but it suffers with higher makespan;poor resource usage and unbalance load concerns.To overcome the above mentioned issue,Fault Aware Dynamic Resource Manager(FADRM)is proposed that enhances the mechanism to Multi-stage Resilience Manager at an application-level FT arrangement.Proposed FADRM method gives FT a Multi-stage Resilience Manager(MRM)in the client and application layers,and simultaneously decreases the over-head and degradations.It additionally provides safety to the application execution considering the clients,application and framework necessities.Based on experimental evaluations,Proposed Fault Aware Dynamic Resource Manager(FADRM)method 157.5 MakeSpan(MS)time,0.38 Fault Rate(FR),0.25 Failure Delay(FD)and improves 5.5 Performance Improvement Ratio(PIR)for 25,50,75 and 100 tasks and 475 MakeSpan(MS)time,0.40 Fault Rate(FR),1.30 Failure Delay(FD)and improves 6.75 improves Performance Improvement Ratio(PER)for 100,200,300 and 500 Tasks compare than existing methodologies.