Papers by palash gourshettiwar
International Journal on Recent and Innovation Trends in Computing and Communication, Apr 30, 2016
This paper gives a review of the Data mining handle. After the investigation of the way of data m... more This paper gives a review of the Data mining handle. After the investigation of the way of data mining and its significance in information warehousing is included. It depicts the CRISP-DM standard now being utilized as a part of industry as the standard for an innovation impartial data mining prepare display. The paper finishes up with a noteworthy delineation of the data mining handle system and the unsolved issues that offer open doors for research. The approach is both reasonable and theoretically stable to be valuable to both scholastics and experts.
Transport Control Protocol (TCP) incast congestion happens when number of senders work in paralle... more Transport Control Protocol (TCP) incast congestion happens when number of senders work in parallel with the same receiver where the high bandwidth and low latency network problem occurs. For many data center network application such as search, the heavy traffic is present on such server. Incast congestion degrades the performance as the packets are lost at server side due to buffer overflow and hence the response time will be more. To improve the performance this report is focusing on the TCP throughput, RTT, receive window. Our method is to adjust the TCP receive window proactively active before packet loss occurs. Our aim is to avoid the wastage of bandwidth by adjusting its size as per the number of packets. To avoid the packet loss the ICTCP algorithm has been implemented. The algorithm has been implemented in the data center network which is ToR.
International Journal on Recent and Innovation Trends in Computing and Communication, 2015
Semantic Data Mining alludes to the information mining assignments that deliberately consolidate ... more Semantic Data Mining alludes to the information mining assignments that deliberately consolidate area learning, particularly formal semantics, into the procedure. Numerous exploration endeavors have validated the advantages of fusing area learning in information mining and in the meantime, the expansion of information building has enhanced the group of space learning, particularly formal semantics and Semantic Web ontology. Ontology is an explicit specification of conceptualization and a formal approach to characterize the semantics of information and data. The formal structure of ontology makes it a nature approach to encode area information for the information mining utilization. Here in Semantic information mining ontology can possibly help semantic information mining and how formal semantics in ontologies can be joined into the data mining procedure.
International Journal on Recent and Innovation Trends in Computing and Communication, 2015
– The use of the disks of the nodes of a cluster as worldwide stockpiling framework is a reasonab... more – The use of the disks of the nodes of a cluster as worldwide stockpiling framework is a reasonable answer for a cloud situation. The requirement for the accessible of data from anyplace is expanding; this speaks to an issue for some clients who use applicati ons, for example, databases, media, individual document, records, and so forth. The I/O information requests of these applications get higher as they get bigger. So as to enhance execution of these applications can utilize parallel document frameworks. PVFS2 is a free parallel record framework grew by a multi-organization group of parallel I/O, systems administration and capacity specialists. In this overview of the configuration of an execution for cloud environment for ready to store and move down information by utilizing remote servers that can be gotten to through the Internet. The execution expects to expand the accessibility of information and lessen in loss of data.
This report addresses the issue of routing in mobile ad hoc networks (MANETs) using directional a... more This report addresses the issue of routing in mobile ad hoc networks (MANETs) using directional antennas. Existing directional routing schemes either assume a complete network topology or simply use omni-directional routing schemes to forward packets in underlying directional environment. In this report a Directional Routing Protocol (DRP) for MANETs is proposed. DRP is an on-demand directional routing protocol which assumes a cross layer interaction between routing and MAC layer and is inspired by Dynamic Source Routing (DSR) protocol. The main features of DRP include an efficient route discovery mechanism, establishment and maintenance of directional routing and directional neighbor tables and novel directional route recovery mechanisms. Implementation of DRP on top of MDA, a MAC protocol for directional antennas and have compared its performance with the DSR protocol over both omni-directional and directional antenna models. DRP considerably improves the packet delivery ratio, de...
International Journal of Recent Trends in Engineering and Research, Jun 13, 2017
Data Mining alludes to the information mining assignments that deliberately consolidate area lear... more Data Mining alludes to the information mining assignments that deliberately consolidate area learning, particularly formal semantics, into the procedure. Numerous exploration endeavors have validated the advantages of fusing area learning in information mining and in the meantime, the expansion of information building has enhanced the group of space learning, particularly formal semantics and Semantic Web ontology. Ontology is an explicit specification of conceptualization and a formal approach to characterize the semantics of information and data. The formal structure of ontology makes it a nature approach to encode area information for the information mining utilization. Keywords-information mining; ontology; data mining I. INTRODUCTION Data mining, otherwise called knowledge discovery from database (KDD), is the methodology of nontrivial extraction of verifiable, beforehand obscure, and possibly valuable data from information [1]. With the recent advances in data mining strategies lead to numerous momentous upsets in information investigation and big data. Data mining likewise joins methods from insights, computerized reasoning, machine learning, database framework, and numerous different controls to examine substantial information sets. Semantic Data Mining alludes to data mining errands that deliberately fuse space learning, particularly formal semantics, into the methodology. Past semantic data mining exploration has bore witness to the positive impact of space learning on data mining. Amid the seeking and pattern generating procedure, area learning can function as an arrangement of former information of requirements to help decrease hunt space and aide the inquiry way [2], [3].
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Papers by palash gourshettiwar