Abstract TCP variants are significant as they are crucial in IP supporting networks. Hence, research is directed towards the management of TCP variants in network management and functioing. TCP provides a trustworthy end to end data transfer under changeable wired networks. The unreliability of IP network is a major problem where TCP is deployed to address the issue. Network management now... TCP variants are significant as they are crucial in IP supporting networks. Hence, research is directed towards the management of TCP variants in network management and functioing. TCP provides a trustworthy end to end data transfer under changeable wired networks. The unreliability of IP network is a major problem where TCP is deployed to address the issue. Network management now heavily relies on MPLS over Internet to transfer data, to have edge over the traditional transferring strategies. While studying the protocol networks, it is found that the TCP show varying behavior. The current study is an extension of the work we did for TCP variants under IP and MPLS networks by focusing Tahoe, Reno, New Reno, Sack and Vegas under File Transfer Protocol (FTP). Read More Read Less

Abstract In Association Rule Mining (ARM) rules are the core which determine the mining process and its effectiveness. In the ARM, a central issue is the sensitivity which is either ignored or not addressed by the researchers in data mining. It is important to avoid senstive information disclosure in ARM. We propose to use Bayesian Network which is dependent on PPDM... In Association Rule Mining (ARM) rules are the core which determine the mining process and its effectiveness. In the ARM, a central issue is the sensitivity which is either ignored or not addressed by the researchers in data mining. It is important to avoid senstive information disclosure in ARM. We propose to use Bayesian Network which is dependent on PPDM model and can reliably hide away sensitive rules in ARM. Additionally we advoate that the XML domain of PPDM can be reinforced with the use of sensitivity. We document clearly the efficacy of PPDM model with empirical validity in the current study. We also expect that the future research will address more issues of ARM based on PPDM model Read More Read Less

Abstract Sets may be ordered, unordered, or partially ordered. Amongst partially ordered sets (posets), if the relation between the ordered elements is one of > then this is a standard poset, but if the relation between the ordered elements is one of >then this is called a strict poset. It is the author’s contention that many strict posets exist implicitly: for... Sets may be ordered, unordered, or partially ordered. Amongst partially ordered sets (posets), if the relation between the ordered elements is one of > then this is a standard poset, but if the relation between the ordered elements is one of >then this is called a strict poset. It is the author’s contention that many strict posets exist implicitly: for example, most examples of preference ordering are actually only partial orders, since one may easily rank one’s most-favorite and least-favorite of anything, but of all that is inbetween, there has probably not been formed a complete total ordering. Furthermore, even if there was a complete total ordering, the solicitation of the preference order information often results in only a partial order being known: for example, it is easier to ask “which of these two do you like better” than it is to ask “please rank all of these from most favorite to least favorite” for large sets. Additionally, preferences change over time, and as a result, finding and identifying which piece of ordering information is now invalid is a challenge for a variety of reasons. This paper seeks to identify some initial possibilities for remedying and meeting that challenge. Read More Read Less

Abstract To design adaptive protocols for MANET, techniques from the field of artificial intelligence have been adopted. It is evidnet that the efficiency feature is incremental as the bandwidth and energy are scarce resources in MANETs. Moreover, adaptivity is crucial to achieve the routing task correctly in presence of varying network conditions in terms of mobility, links quality and traffic load.... To design adaptive protocols for MANET, techniques from the field of artificial intelligence have been adopted. It is evidnet that the efficiency feature is incremental as the bandwidth and energy are scarce resources in MANETs. Moreover, adaptivity is crucial to achieve the routing task correctly in presence of varying network conditions in terms of mobility, links quality and traffic load. In our study we have used the extended application of Reinforcement Learning (RL) technique to achieve adaptive routing in MANETs Read More Read Less

Abstract The routing simulations over ad hoc networks indicate that network capacity is poorly utilized in terms of throughput and packet delay when the 802.11 MAC protocol is integrated with routing algorithms. Also, since wireless network access point is open to anyone, problem of security is inherent in wireless scenario. In this paper we aim to study the characteristics & performance... The routing simulations over ad hoc networks indicate that network capacity is poorly utilized in terms of throughput and packet delay when the 802.11 MAC protocol is integrated with routing algorithms. Also, since wireless network access point is open to anyone, problem of security is inherent in wireless scenario. In this paper we aim to study the characteristics & performance of MAC Layer with regard to IEEE 802.11 MAC protocol and IEEE 802.3 MAC protocol from the point of view of Campus Area Network. We conducted some simulation for the same using NS-2 and concluded an adaptive performance model best suited for University Campus Area for networking in terms of throughput and fairness. We created a performance model of Wireless local area network to show what happens when large number of mobile nodes take part, move and communicate with one another in a WLAN and simulated our model taking varying slot time from 20 to 15, 12 & 10 micro sec. for getting optimum key point for such WLANs Read More Read Less