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Monitoring and measurement of network traffic flows in SDN is key requirement for maintaining the integrity of our data in network. It plays a vital role in management task of SDN controller for controlling the traffic. Anomaly detection considered as one of the important issues while monitoring the traffic. More efficiently we detect the anomalies, easier it will be for us, to manage the traffic. However we have to consider the workload, response time and overhead on network while applying the network monitoring policies, so that our network perform with similar efficiency. To reduce the overhead, it is required to perform analysis on certain portion of traffic instead of analyzing each and every packet in the network. This paper presents an adaptive mechanism for dynamically updating the policies for aggregation of flow entries and anomaly detection, so that monitoring overhead can be reduced and anomalies can be detected with greater accuracy. In previous work, rules for expansion and contraction of aggregation policies according to adaptive behavior are defined. This paper represents a work towards reducing the complexity of dynamic algorithm for updating policies of flow counting rules for anomaly detection.

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Abstract-The ever increasing demand of wireless communication systems has led to search of suitable spectrum bands for transmission of data. The research in the past has revealed that radio spectrum is under-utilized in most of the scenarios. This prompted the scientist to seek a solution to utilize the spectrum efficiently. Cognitive Radios provided an answer to the problem by sensing the idle (licensed) bands and allowing (secondary) users to transmit in these idle spaces. Spectrum sensing forms the main block of cognition cycle.This paper reviews the current trends in research in the domain of spectrum sensing. The author describes the type of channel being modelled, diversity combining schemes used, optimal algorithms applied at fusion centre, spectrum sensing techniques employed. Further, the research challenges are discussed. It is presented that various attributes like sensing time, throughput, rate reliability, optimum cooperative users, sensing frequency etc. needs to be addressed. A trade-off needs to be established to optimize two opposing parameters like sensing and throughput.