In recent times, the applications like streaming audio-video, Internet telephony and multi-player online games are the most prevalent in the Internet world. So, it becomes a great concern to carry out these applications effectively and efficiently. These applications prefer timeliness in packet delivery to reliability. TCPs reliability through packet retransmission and abrupt rate control features are unsuitable for these applications. As a result, these applications prefer UDP as the transport layer protocol. UDP does not have any congestion control mechanism which is vital for the overall stability of the Internet. For this reason, a new transport layer protocol Datagram Congestion Control Protocol (DCCP) has been introduced which is suitable for these applications because of its exclusive characteristics. But the congestion control algorithm of DCCP seems a little bit faulty as they have some limitations. This paper describes another one congestion control algorithm for DCCP.
IndexTerms-DCCP, CCID, Real-time multimedia applications, congestion control algorithm.
I. INTRODUCTIONThe real time multimedia applications are the dominant applications in today's Internet. That's why many transport level solutions have been suggested for transferring these wide variety of applications precisely. Most of them do not use any congestion control mechanism which can be threatening for our today's Internet. As a remedy, a new transport layer protocol DCCP [1] is offered with some congestion control mechanisms for real time applications. DCCP is desirable for the applications where timing constraints exists but reliability is not expected.The application programmer do not need to provide congestion control at the application layer while using DCCP. There are two built-in congestion control mechanisms of DCCP are TCP-like (Congestion Control IDentifier 2) and TCP-friendly (Congestion Control IDentifier 3). These are useful for those applications where a steady rate of data transmission is required rather than reliable in-order delivery of packets.
Addressing the problem of spam emails in the Internet, this paper presents a comparative study on Naïve Bayes and Artificial Neural Networks (ANN) based modeling of spammer behavior. Keyword-based spam email filtering techniques fall short to model spammer behavior as the spammer constantly changes tactics to circumvent these filters. The evasive tactics that the spammer uses are themselves patterns that can be modeled to combat spam. It has been observed that both Naïve Bayes and ANN are best suitable for modeling spammer common patterns. Experimental results demonstrate that both of them achieve a promising detection rate of around 92%, which is considerably an improvement of performance compared to the keyword-based contemporary filtering approaches.
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