Precise Marketing Strategy Optimization of E-Commerce Platform Based on KNN Clustering

With the development of computer technology and the arrival of the era of artificial intelligence, the analysis of user demand bias is of great significance to the operation optimization of e-commerce platforms. Combined with CS domain signaling data, IP packet data of PS domain, and customer CRM data provided by operators, this research studies each dimension index of operator user portrait, after that the operator user portrait platform is divided into some individual subunits, and then the corresponding data mining technology is carried out to study the implementation scheme of each subunit. The system can process and mine multidimensional data of operators’ users and form user portraits on the basis of user data aggregation. Finally, based on the operator user portrait platform studied in this paper, the operator user data are analyzed from both the user’s mobile phone use behavior and user consumption behavior. Furthermore, the application value of this research in the precision marketing and personalized service of operators is illustrated.

Scalable Balanced Pipelined IPv6 Lookup Algorithm

One of the most critical router’s functions is the IP lookup. For each incoming IP packet, IP lookup determines the output port to which the packet should be forwarded. IPv6 addresses are envisioned to replace IPv4 addresses because the IPv4 address space is exhausted. Therefore, modern IP routers need to support IPv6 lookup. Most of the existing IP lookup algorithms are adjusted for the IPv4 lookup, but not for the IPv6 lookup. Scalability represents the main problem in the existing IP lookup algorithms because the IPv6 address space is much larger than the IPv4 address space due to longer IPv6 addresses. In this paper, we propose a novel IPv6 lookup algorithm that supports very large IPv6 lookup tables and achieves high IP lookup throughput.

Limited domains considered useful

Limited domains were defined conceptually in RFC 8799 to cater to requirements and behaviours that extend the dominant view of IP packet delivery in the Internet. This paper argues not only that limited domains have been with us from the very beginning of the Internet but also that they have been shaping innovation of Internet technologies ever since, and will continue to do so. In order to build limited domains that successfully interoperate with the existing Internet, we propose an architectural framework as a blueprint. We discuss the role of the IETF in ensuring continued innovation in Internet technologies by embracing the wider research community's work on limited domain technology, leading to our key insight that Limited Domains are not only considered useful but a must to sustain innovation.

Feasibility of Longest Prefix Matching using Learned Index Structures

This paper revisits longest prefix matching in IP packet forwarding because an emerging data structure, learned index, is recently presented. A learned index uses machine learning to associate key-value pairs in a key-value store. The fundamental idea to apply a learned index to an FIB is to simplify the complex longest prefix matching operation to a nearest address search operation. The size of the proposed FIB is less than half of an existing trie-based FIB while it achieves the computation speed nearly equal to the trie-based FIB. Moreover, the computation speed of the proposal is independent of the length of IP prefixes, unlike trie-based FIBs.

On the Identification and Prediction of Stalling Events to Improve QoE in Video Streaming

Monitoring the Quality of user Experience is a challenge for video streaming services. Models for Quality of User Experience (QoE) evaluation such as the ITU-T Rec. P.1203 are very promising. Among the input data that they require are the occurrence and duration of stalling events. A stalling even5 is an interruption in the playback of multimedia content, and its negative impact on QoE is immense. Given the idiosyncrasy of this type of event, to count it and its duration is a complex task to be automated, i.e., without the participation of the user who visualizes the events or without direct access to the final device. In this work, we propose two methods to overcome these limitations in video streaming using the DASH framework. The first method is intended to detect stalling events. For simplicity, it is based on the behavior of the transport layer data and is able to classify an IP packet as belonging (or not) to a stalling event. The second method aims to predict if the next IP packet of a multimedia stream will belong to a stalling event (or not), using a recurrent neural network with a variant of the Long Short–Term Memory (LSTM). Our results show that the detection model is able to spot the occurrence of a stalling event before being experienced by the user, and the prediction model is able to forecast if the next packet will belong to a stalling event with an error rate of 10.83%, achieving an F1 score of 0.923.

Implementation of Site to Site IPsec VPN Tunnel between Routers

Today, security is very important in the communication system over through the Internet. The Transmission control protocol and Internet protocol (TCP/IP) protocol suite is used in the Internet communication that it includes five layers in which it is construct IPSec VPN Tunnel between two routers at the network layer. IPsec have two protocols that it is authentication header and encapsulation security payload (ESP) in which two protocols is shown simulation and then it is give encryption, authentication and confidentiality in which for packets at the IPSec layer within network layer and adds new IP header at the network layer. IPSec is designed to provide security at the network layer that it protects the entire IP packets. It takes an IP packet and then it includes the header, applies IPSec security methods to the entire packet and adds a new IP header. The system purpose is known use router devices at the network layer and then this layer is built IPSec VPN tunnel between routers that when it is known how does command line. IPsec VPN tunnel is built based on ACL (access list), crypto isakmp (internet security association and key management protocol) policy, transform set and crypto map and then the system is aimed to know it facts configuration and then to know used routers at the network layer and is built IPSec VPN tunnel between two routers. This system is simulated using packets tracer software 7.1.

NAT++: An Efficient Micro-NAT Architecture for Solving IP-Spoofing Attacks in a Corporate Network

The Internet Protocol (IP) version 4 (IPv4) has several known vulnerabilities. One of the important vulnerabilities is that the protocol does not validate the correctness of the source address carried in an IP packet. Users with malicious intentions may take advantage of this vulnerability and launch various attacks against a target host or a network. These attacks are popularly known as IP Address Spoofing attacks. One of the classical IP-spoofing attacks that cost several million dollars worldwide is the DNS-amplification attack. Currently, the availability of solutions is limited, proprietary, expensive, and requires expertise. The Internet is subjected to several other forms of amplification attacks happening every day. Even though IP-Spoofing is one of the well-researched areas since 2005, there is no holistic solution available to solve this problem from the gross-root. Also, every solution assumes that the attackers are always from outside networks. In this paper, we provide an efficient and scalable solution to solve the IP-Spoofing problem that arises from malicious or compromised inside hosts. We use a modified form of Network Address Translation (NAT) to build our solution framework. We call our framework as NAT++. The proposed infrastructure is robust, crypto-free, and easy to implement. Our simulation results have shown that the proposed NAT++ infrastructure does not consume more than the resources required by a simple NAT.

Design of a Low Latency and High Throughput Packet Classification Module on FPGA Platform

The Packet classification method plays a significant role in most of the Network systems. These systems categories the incoming packets in various flows and takes suitable action based on the requirements. If the size of the network is vast and complexity will arise to perform the different operations, which affects the network performance and other constraints also. So there is the demand for high-speed packet classifiers to reduce the network complexity and improve the network performance. In this article, The Bit vector Packet classifier (BV-PC) Module is designed to improve the network system performance and overcome the existing limitation of Packet classification approaches on FPGA. The BV-PC Module contains Packet generation Unit (PGU) to receive the valid incoming packets, Memory Unit (MU) to store valid packets, Header Extractor Unit (HEU) extracts the IP Header address information from the Valid packets, The BV-Based Source and Destination Address (BV-SA, BV-DA) unit receives the IP packet header Information and Process with BV based rule set and aggregates the BV-SA and BV-DA outputs, Priority Encoder encodes the Highest priority BV Rule for the generation of Classified output. The BV-PC utilizes <2% Chip area (slices), works at 509.38MHz, and consumed Less 0.103 W of total Power on Artix-7 FPGA. The BV-PC operates with a latency of 5 clock cycles and works at 815.03Mpps throughput. The BV-PC is compared with existing approaches and provides Better improvements in Hardware constraints.

ANALYSIS OF MATHEMATICAL APPARATUS FOR MANAGING CHANNEL AND NETWORK RESOURCES OF MILITARY RADIO COMMUNICATION SYSTEMS

The experience of carrying out the Operation of the United Nations (antiterrorist operation) on the territory of Donetsk and Luhansk oblasts shows that the existing procedure for managing the channel and network resources of military radiocommunication systems does not meet the modern requirements, which are put forward for them. The choice of a route in special purpose networks with the ability to self-organize on the basis of specific parameters is the main problem for managing the channel and network resources of special-purpose networks, as well as the difficult task of climbing the network. In this article, the authors analyzed the existing mathematical apparatus for controlling channel and network resources of military radiocommunication systems. During the research, the authors of the article used the classical methods of scientific knowledge, namely, the methods of analysis and synthesis, the basic provisions of the theory of communication, methods of modeling of communication networks, the theory of artificial intelligence, and others. It is established that the existing methods of controlling the channel and network resources of military radiocommunication systems take into account only certain factors influencing the quality of the use of channel and network resources of military radiocommunication systems. Therefore, it is the most expedient to choose a route for information transmission on many parameters based on fuzzy logic and a modified method of the ant colony system, through which searches and maintenance of the path of the packet passing between two points between the node from which the IP packet and the destination node are sent. To find a route, the following parameters must be considered: the energy component, the data rate, the time delay of the IP packet from the node that sends the packet to the destination node and the reliability of the delivery of the IP packet. These parameters should be taken into account while creating mathematical models, methods and techniques for managing channel and network resources of military radio communication systems.