Identification of the Use of Unauthorized Apps in the O2O Service by Combining Online Events and Offline Conditions

A model for detecting unauthorized Apps use events by combined analysis of situation information in an offline service and user behavior in an online environment is proposed. The detection and response to abnormal behavior in the O2O service environment can be focused on providers, whose decisions change dynamically based on the offline market status and conditions. However, the method for identifying the user’s tools and detecting the usage pattern of the service user were developed in the existing online service environment. Thus, in order to identify abnormal behavior in the O2O service environment, we conducted an experiment to identify the abnormal behavior of providers of smart mobility services, a representative O2O service. In the experiment, the range of normal behavior of a taxi drivers was identified, which was prepared on the basis of the test result directly executed by an expert. The optimal features were selected in order to effectively detect abnormal behavior from the event data relating to the service call acceptance behavior. In addition, by processing the collected data based on the selected features by using various machine-learning classification algorithms, we derived a detection and prediction model that is 98.28% accurate with a prediction result of more than 74% based on the F1 score. Based on these results, we expect to be able to respond to abnormal behavior that may occur in various types of O2O services.

A Novel Call Admission Control Algorithm for Next Generation Wireless Mobile Communication

Wireless communication technology is progressing very vastly. With this change in technology customer services for multimedia and non-multimedia are increasing day by day. But due to limited resources of the wireless network, we need to design an efficient CAC algorithm to enhance QoS levels for end users. The Quality of service (QoS) enhancement in the wireless network is related to making an efficient use of current network resources and the optimization of the users. Call acceptance in CAC is one of the challenge in mobile cellular networks to ensure that the acceptance of a new call into a resource limited wireless network should not deviate the service level Agreement (SLAs) at the time of conversations. In the next generation wireless network, CAC has the direct impact on QoS for user calls & overall system performance. To handle handoff calls and new calls in cellular network channel reservation scheme have been already proposed to reserve system bandwidth for higher priority call for CAC. This earlier proposed scheme is not as per the required level of satisfaction because the available reversed bandwidth is not allocated properly in case of least handoff rate. In this, the authors like to present a new channel borrowing scheme where new non real time (NRT) calls can make use of reserved channels. It can borrow this reserved channel on a temporary basis and after this immediately if any handoff call enters the current cell and no any other channels are available, then it will pre-empt the channel from an earlier borrowed NRT user if exists. This pre-empted NRT call is kept in the priority queue to consider its service when any channel becomes free. The number of NRT calls in the queue should not be large to avoid delayed service. The fundamental objective of the proposed scheme to design of the system for evaluating the results and comparing with the results of the existing system. From the results of current research work, it is observed that proposed scheme decreases call dropping probability which increase slightly in call blocking rate over high-density handoff call rate.