-In terms of network security, software-defined networks (SDN) offer researchers unprecedented control over network infrastructure and define a single point of control over the data flows routing of all network infrastructure. OpenFlow protocol is an embodiment of the software-defined networking paradigm. OpenFlow network security applications can implement more complex logic processing flows than their permission or prohibition. Such applications can implement logic to provide complex quarantine procedures, or redirect malicious network flows for their special treatment. Security detection and intrusion prevention algorithms can be implemented as OpenFlow security applications, however, their implementation is often more concise and effective. In this paper we considered the algorithm of the information security management system based on soft computing, and implemented a prototype of the intrusion detection system (IDS) for software-defined network, which consisting of statistic collection and processing module and decision-making module. These modules were implemented in the form of application for the Beacon controller in Java. Evaluation of the system was carried out on one of the main problems of network security -identification of hosts engaged in malicious network scanning. For evaluation of the modules work we used mininet environment, which provides rapid prototyping for OpenFlow network. The proposed algorithm combined with the decision making based on fuzzy rules has shown better results than the security algorithms used separately. In addition the number of code lines decreased by 20-30%, as well as the opportunity to easily integrate the various external modules and libraries, thus greatly simplifies the implementation of the algorithms and decision-making system.

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In this paper, we present an Openflow-SDN based network visualization and performance evaluation model that helps in network designing and planning to examine how networks' performance will be affected as the traffic loads and network utilization change. To achieve the aimed goal, as a research method, we used AnyLogic Multimethod simulation tool. This is a first of its kind where SDN performance evaluation is based on queuing model simulation to monitor change of average packet processing time for various network parameters. Using presented in this work SDN model, network administrators and planners can better predict likely performance changes arising from traffic variation. This allows them to make prompt decisions to prevent seemingly small issues from becoming major bottlenecks.

Vehicular ad hoc networks (VANETs) are a recent class of peer-to-peer wireless networks that are used to organize the communication and interaction between cars (V2V), between cars and infrastructure (V2I), and between cars and other types of nodes (V2X). These networks are based on the dedicated short-range communication (DSRC) IEEE 802.11 standards and are mainly intended to organize the exchange of various types of messages, mainly emergency ones, to prevent road accidents, alert when a road accident occurs, or control the priority of the roadway. Initially, it was assumed that cars would only interact with each other, but later, with the advent of the concept of the Internet of things (IoT), interactions with surrounding devices became a demand. However, there are many challenges associated with the interaction of vehicles and the interaction with the road infrastructure. Among the main challenge is the high density and the dramatic increase of the vehicles’ traffic. To this end, this work provides a novel system based on mobile edge computing (MEC) to solve the problem of high traffic density and provides and offloading path to vehicle’s traffic. The proposed system also reduces the total latency of data communicated between vehicles and stationary roadside units (RSUs). Moreover, a latency-aware offloading algorithm is developed for managing and controlling data offloading from vehicles to edge servers. The system was simulated over a reliable environment for performance evaluation, and a real experiment was conducted to validate the proposed system and the developed offloading method.

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