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Abstract-Vehicular Ad hoc Networks (VANET) play an important role in future on road Vehicle-to-Vehicle communication systems and related applications like self-organizing, acquiring traffic information using sensors and disseminating it to the nearby vehicles, which are based on broadcast/geocast transmission schemes. It is a challenging task to manage networks in a dynamic environment due to the characteristic of high mobility rate, high relative speed, different driver behaviors and unpredictable link failure occurrences. One of the main criteria in VANETs that has attracted the researchers' consideration is congestion control. Congestion is a major problem all over world, resulting in wastage of valuable time and money. In this paper, we propose multi agent based congestion control scheme, which intelligently acquires the status of the neighboring node information and decides the congestion free path for the safe delivery of packets. Multi agent scheme consists of set of static and mobile agents. Proposed approach guarantees the reliability and timely delivery of messages. Multi agent based scheme exhibits better bandwidth usage and packet delivery ratio and minimizes the latency Index Terms-VANETs, multi agent, latency, bandwidth, congestion control.

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The global data center market is growing as more and more enterprises are increasingly adopting cloud computing services and applications. Data centers are evolving towards highly virtualized architectures where transformation to software defined network (SDN) based solutions provides benefits in terms of network programmability, automation, and flow visibility. With the benefits, the need for securing network becomes essential as many critical applications are hosted on to such networking platforms. Anomaly detection is a continuous process of monitoring the traffic pattern and alerting the user about the anomalies if detected. For such real time analysis NoSQL and relational databases are less efficient. This paper proposes a framework for anomaly detection and alerting system using Elasticsearch database for SDN. Traffic patterns generated from SDN devices are continuously monitored and predefined actions are taken immediately if an anomaly is detected. The proof of concept is implemented in NOKIAs Nuage Networks Laboratory and the results showed a real time anomaly detection and took relevant actions within minimum time.

Abstract-Vehicular