Transfer Control Protocol Research Articles

TCP Congestion Management Using Deep Reinforcement Trained Agent for RED

ABSTRACTIncreasing data transmission volumes are causing more frequent and more severe network congestion. In order to handle spikes in network traffic, a substantially bigger buffer has been included into the system. Bufferbloat, which happens when a bigger buffer is implemented, exacerbates network congestion. Using the transfer control protocol (TCP) congestion management strategy with active queue management (AQM) can fix this issue. As congestion increases, it becomes increasingly difficult to forecast and fine‐tune dynamic AQM/TCP systems in order to achieve acceptable performance. To shed new light on the AQM system, we plan to use deep reinforcement learning (DRL) techniques. It is possible that AQM can learn about the appropriate drop policy the same way people do when using a model‐free technique like DRL‐AQM. After training in a simple network scenario, DRL‐AQM is able to recognize complex patterns in the data traffic model and apply them to improve performance in a wide variety of scenarios. Offline training precedes deployment in our approach. In many cases, the model does not require any further parameter tweaks after training. Even in the most complicated networks, AQM algorithms have proven to be effective, regardless of the network's complexity. Minimizing buffer capacity use is an important goal of DRL‐AQM. It automatically and continually adjusts to changes in network connectivity.

Effective IoT Congestion Control Algorithm

The Internet of Things (IoT) connects devices via the Internet. Network congestion is one of the key problems that has been identified by researchers in the IoT field. When there is a huge number of IoT devices connected to the internet, this creates network congestion. Transfer control protocol is a transport layer protocol that provides a reliable end-to-end connection between two devices. Many Congestion Control Algorithms have been proposed to solve network congestion. However, there is no perfect solution to this problem. This paper proposes an effective loss-based Congestion Control Algorithm to effectively adapt the congestion window in the IoT environment. It uses simple experiment scenarios to test the algorithm for wired and wireless channels and observes important performance metrics: link utilization, inter-protocol fairness, intra-protocol fairness and throughput. The results are impressive, and the proposed algorithm is shown to outperform other standard algorithms.

Application Analysis of 5G Intelligent Communication Technologies in the Field of Sports Distance Education.

China has entered a new fifth-generation (5G) technological period, college students are relatively fast to absorb new things, and conventional teaching methods are incapable of properly stimulating students' interest in sporting activities. As a result, the 5G integrated teaching paradigm, which is based on communication technology, is an unavoidable reform of sports remote education. For a long time, technology and sports have been inextricably linked. However, new possibilities on the Internet are fast developing, resulting in massive volumes of data. In this paper, we propose a novel 5G framework for efficient sports distance education. Initially, the sports dataset is preprocessed using normalization, and the features are extracted using Principal Component Analysis (PCA). Following feature selection, a Hierarchical Multiscale Convolutional Neural Network (HM-CNN) is used to categorize and initialize the 5G utilizing the Enhanced Transfer Control Protocol (E-TCP) for efficient data transmission. The Elevated Ant Colony Optimization Algorithm improves the performance of the suggested system even more (EACO). The experimental results indicate that 5G integrated education reform based on communication technology may successfully enhance the number of college students' sports population.

Hybrid Approach for Botnet Detection Using K-Means and K-Medoids with Hopfield Neural Network

In the last few years, a number of attacks and malicious activities have been attributed to common channels between users. A botnet is considered as an important carrier of malicious and undesirable briskness. In this paper, we propose a support vector machine to classify botnet activities according to k-means, k-medoids, and neural network clusters. The proposed approach is based on the features of transfer control protocol packets. System performance and accuracy are evaluated using a predefined data set. Results show the ability of the proposed approach to detect botnet activities with high accuracy and performance in a short execution time. The proposed system provides 95.7% accuracy rate with a false positive rate less than or equal to 3%.

Deep Learning Based Intrusion Detection in Cloud Services for Resilience Management

In the global scenario one of the important goals for sustainable development in industrial field is innovate new technology, and invest in building infrastructure. All the developed and developing countries focus on building resilient infrastructure and promote sustainable developments by fostering innovation. At this juncture the cloud computing has become an important information and communication technologies model influencing sustainable development of the industries in the developing countries. As part of the innovations happening in the industrial sector, a new concept termed as ‘smart manufacturing’ has emerged, which employs the benefits of emerging technologies like internet of things and cloud computing. Cloud services deliver an on-demand access to computing, storage, and infrastructural platforms for the industrial users through Internet. In the recent era of information technology the number of business and individual users of cloud services have been increased and larger volumes of data is being processed and stored in it. As a consequence, the data breaches in the cloud services are also increasing day by day. Due to various security vulnerabilities in the cloud architecture; as a result the cloud environment has become non-resilient. To restore the normal behavior of the cloud, detect the deviations, and achieve higher resilience, anomaly detection becomes essential. The deep learning architectures-based anomaly detection mechanisms uses various monitoring metrics characterize the normal behavior of cloud services and identify the abnormal events. This paper focuses on designing an intelligent deep learning based approach for detecting cloud anomalies in real time to make it more resilient. The deep learning models are trained using features extracted from the system level and network level performance metrics observed in the Transfer Control Protocol (TCP) traces of the simulation. The experimental results of the proposed approach demonstrate a superior performance in terms of higher detection rate and lower false alarm rate when compared to the Support Vector Machine (SVM).

Research on TCP Performance Model and Transport Agent Architecture in Broadband Wireless Network

The problems of Internet stability, heterogeneity, fairness of bandwidth sharing among streams, efficiency of use and congestion control have been solved in this article. This paper proposes an improved scheme of TCP proxy acknowledgement based on Automatic Repeat Request (ARQ), which improves throughput, reduces delay and saves uplink bandwidth of wireless link, and is more suitable for future asymmetric networks. The substantial improvement is observed during the experimentation as processing efficiency of protocol. The observed results revealed that overall processing time for each packet is approximately equals to one fourth of the transfer control protocol and the reduction of 59% is also observed in the utility of resources. The protocol also incorporates various simple techniques for the recovery of loss to improve the throughput in noisy wireless conditions. The results show that the adoption of the average diversity combining technology is helpful to improve the throughput and effective factor performance, and can reduce the requirement of radio link protocol (RLP) maximum retransmission times. As nearly 90% of uplink acknowledgement frames are filtered, the uplink bandwidth utilization rate is significantly improved. Decomposing large data frames into small data frames is also helpful to improve system performance.

Useful Traffic Loss Rate Estimation Based on Network Layer Measurement

The current network is information asymmetric, about what happens in the network, and end users know much less than the Internet service provider. Especially, in a non-neutral network, for commercial interests, the operator’s behavior of adjusting network configuration and controlling data transmission priority will seriously infringe the vital interests of end users. In order to rebalance such information asymmetry to empower users, researchers have been committed to the study of end-user network performance measurements. In this paper, we contribute to the ongoing efforts to empower users by defining and estimating the useful traffic loss rate (UTLR) experienced by a Transfer Control Protocol connection. The work presented in this paper is inspired by our empirical observation that what the operator’s behavior ultimately affects is the link quality, and therefore, a good characterization of the impact of link quality changes on user’s quality of experience (QoE) is the prerequisite for empowering users. To this end, the metric UTLR is first defined in this paper to better characterize the impact of link quality changes on user’s QoE, and then, we construct a series of heuristic rules with the receiver network layer information to estimate UTLR. To improve the estimation accuracy, the effects of insufficient duplicate ACKs, static round trip time, enlarged loss period, repeated packet losses, and identification field cyclic reuse are also considered. Finally, the gradual and rigorous experiments show that the proposed method achieves a stable and precise estimation for UTLR over the entire measured parameter space.

Enhanced a TCP security protocol by using optional fields in TCP header

The Transfer Control Protocol (TCP) itself does not guarantee the security of data that it transmits. However, under some circumstances, the security of TCP communication is required, e.g. the client-server communication in banking systems. Nowadays, the source socket layer (SSL) protocol is widely used; however, SSL is based on RSA (a public-key cryptographic algorithm) algorithm, which would require more computational resource. Therefore, an alternative faster solution utilizing symmetrical algorithm (AES) are proposed to achieve these goals: bidirectional authentication, encrypted data transmission and Integrity check. Moreover, use the optional fields in TCP header for carrying related information and introduced a new device SAM (Secure access module) which provides security-related functionalities: encryption, decryption, key-diversification etc

A Study on High Rate Shrew DDOS Attack

Denial of Service attacks is frequently presenting an increasing threat to the global inter-networking infrastructure in networking area and scenario. The algorithm for Transfer Control Protocol (TCP) congestion control is highly efficient for the various networking areas and operations as well its internal assumption of end-system cooperation results is well prone to attack by high-rate flows. A Shrew attack uses the concept of a low-rate burst which is carefully designed to use the TCP’s retransmission timeout mechanism in an unfair way and can affect the bandwidth of a TCP flow in a smooth manner without coming into appearance as an intruder. A Shrew attack has further classifications such as a low rate shrew attack or a high rate shrew attack. A high rated shrew attack uses the concept of timely sending high rate packet stream in low frequency. Such attack can affect the performance of a network to a large extent.

Implementing Monitoring Systems in Mobile Applications – a Case Study

During the last years, the evolution of mobile applications allowed the developers to become more and more creative. In this way, we can imagine many applications models with a real impact in the real life. In this article we are trying to present a case study for a monitoring system using the Android platform and the benefits of computer networks. We use the power of mobile sockets and mobile threads, integrating them in a complex architecture in order to obtain a real monitoring system. As an immediate application, we propose a baby monitoring systems so that the children could be remotely supervised by their parents. The case study is based on an Android mobile client-server architecture and also uses the capabilities offered by the phone's speaker and microphone. We intend to have a robust application and that's why we initially preferred Network Service Discovery and Android P2P, but these functionalities are implemented starting with Android 4.1. So, we emulated all these functionalities by using a model based on sockets and server sockets.Keywords: Mobile Monitoring Systems, Android Implementation, Mobile Sockets, Mobile Architectures(ProQuest: ... denotes formulae omitted.)1IntroductionIn this article we present a case study of a mobile monitoring application made on Android platform. Our goal is to implement an application which can be used by parents in order to supervise their children; this vision could be used to also improve the proposals about the intelligent tutoring systems described by [1] or to implement innovative systems described by [2]. We propose the following scenario: the baby is in a room and the parent is in other room; in both rooms they have smart-phones with our application. Without using the GSM provider, the parent can hear the activity of the baby. Eventually, if the baby cries, the system will warn the parent about the situation.The application is designed to run in some conditions and rules:* the application does not use the GSM capabilities and it can also run on a tablet;* the minimum required platform is Android 2.0;* the application uses only a Wi-Fi connection and doesn't need any external remote server;* the application uses the speakers and the microphones of the involved smartphones.Initially, we intended to use Network Service Discovery [3] and Android P2P, but these functionalities are implemented starting with Android 4.1. For these reasons, we preferred to emulate these capabilities by using the socket's technology. As a conclusion, the only restrictions are the following: smart-phones with a Wi-Fi connection, speaker and microphone. As we know, these resources are already available on almost all the smartphones, so the proposed application could be installed on a significant number of mobile devices. Although the new HTML5 standard could represent a solid enterprise mobile computing foundation and a feasible path towards the proliferation of the applications as described in [4], we consider that it is extremely important that an application could be used by a large number of clients with normal smart-phones. We are also conscious that, according to [5], Mobile Application Development is a popular topic these days, when tons of mobile apps are released and available tools and resources are expanding.Nowadays, the wireless networks have many sensors and protocols used to capture and transmit data [6], but one of the oldest methods of network communication provided by Java is by using Transfer Control Protocol (TCP) sockets. For this, we use two classes: Socket and Server Socket, the latter being the one to trace the connections that are made. For the audio streaming, it is used the device's microphone which is operated by Android through the objects of type Audio Recorder. The information received by the microphone is encoded (using Audio Format class) through predefined constants (ENCODING PCM16BIT) and it is allocated abroadcast channel (in our case CHANNELINMONO). …

Multilevel bandwidth measurements and capacity exploitation in gigabit passive optical networks

The authors report an experimental investigation on the measurement of the available bandwidth for the users in gigabit passive optical networks (GPON) and the limitations caused by the Internet protocols, and transfer control protocol (TCP) in particular. We point out that the huge capacity offered by the GPON highlights the enormous differences that can be showed among the available and actually exploitable bandwidth. In fact, while the physical layer capacity can reach value of 100 Mb/s and more, the bandwidth at disposal of the user (i.e. either throughput at transport layer or goodput at application layer) can be much lower when applications and services based on TCP protocol are considered. In the context of service level agreements (SLA) verification, we show how to simultaneously measure throughput and line capacity by offering a method to verify multilayer SLA. We also show how it is possible to better exploit the physical layer capacity by adopting multiple TCP connections avoiding the bottleneck of a single connection.

SCTP performance improvement based on virtual receiver window

This article puts forward one algorithm for stream control transfer protocol (SCTP) improvement with limited receiver buffer (RBUF). As is well known, SCTP is one of the most important transfer control protocol, but most researches focus on the situations without the RBUF limit. In this study, we analyze the impact of the RBUF size on the performance. Computer simulations show that the network utility is low in reliable transfer, when the RBUF size is smaller than bandwidth delay product. By studying the transmission sequence number (TSN) transfer progress, we find that the peer receiver window (PEER_RWND), which lags behind the true receiver window (RWND), leads to the poor network utility. To improve SCTP performance with limited RBUF, the virtual receiver window (VIRTUAL_RWND) is introduced. Based on the VIRTUAL_RWND, one algorithm is proposed to increase the sending rate. Computer simulations have evaluated an excellent performance of the proposed algorithm at both ideal link without lost packet and nonideal link with lost packet.

Evaluación de algoritmos para la estimación del Round-Trip Delay Time y una propuesta de mejora

Several algorithms have been proposed for the estimation of the Round-Trip Delay Time (RTT). They aim at achieving better performance than the estimation algorithm adopted by the Transfer Control Protocol (TCP) standard proposed in the late eighties. In general, the algorithms in the literature are assessed qualitatively, observing the estimation errors for a single connection scenario or via simulations. There are no works considering a quantitative evaluation metric, comparing the performance achieved by different algorithms. This motivates the present work in which several RTT estimation algorithms are compared using a common performance metric, and common experimental scenarios. As a second contribution, we propose an adaptive algorithm to estimate RTT, which is able to react quickly against sudden changes in the signal and, simultaneously, is less sensitive to noise interference than alternatives in the literature.

Stability and throughput of FAST transfer control protocol traffic in bi-directional connections

FAST TCP is a promising new transfer control protocol developed for high-speed long-latency networks, whose performance has previously only been studied for data traffic sent in one direction. In this study, the authors propose a mathematical model for bi-directional connections using the FAST TCP protocol, which captures the asymmetric bandwidth dynamics in duplex dumbbell networks, prevalent in ADSL, satellite and other high-speed technologies. Using this model, the authors obtain a powerful result that the queue delays observed by opposite FAST TCP flows only have a time difference in a dumbbell network. Furthermore, the authors establish the conditions under which the bi-directional FAST TCP flows achieve stability, and on this basis the throughput rates of the forward and backward flows at steady-state are deduced. The authors find that, in the case of bandwidth asymmetry and one flow in each direction, in equilibrium the throughput of the bi-directional FAST TCP flows can only achieve the smaller link capacity of the duplex links, and the link with larger capacity is not fully occupied. These theoretical findings are corroborated by NS2 simulations.

Remote Video Management for Intraoperative Consultation and Surgical Telepresence

Telemedicine applications can connect surgeons from one operating room (OR) to a distant consultant. The additional capacity of telepresence provides remote consultants the ability to control their own view of the surgical field using robotic management of a network camera. The goal of this study was to compare access to surgical field by robotic camera versus image controlled by the surgeon using a camera mounted to the table. A Stryker laparoscopic camera was attached to the OR table using a Mediflex arm, and video image was transmitted with a Polycom Transfer Control Protocol (TCP)/Internet Protocol (IP) connection. A network Sony camera was mounted on a tripod, connected over the Internet using a parallel TCP/IP connection. A Web interface allowed control of the camera angle and zoom. In 22 consultations effective bandwidth was 800 Kbps for the network camera and 1024 Kbps for the Stryker camera. The operation was thyroidectomy and the consultant was either in Moscow, Russia, or Bucharest, Romania. The quality of the image in both methods was indiscernible. The ability to identify critical surgical anatomy was also indiscernible. No transmission session failed or had an interruption. The robotic camera can be a powerful tool for surgical collaboration.

Application layer QoS for videotelephony

Home broadband bandwidth will be a variable commodity as customers run multiple applications through their home hubs simultaneously. The reaction of some of these applications (e.g. Web browsing or e-mail) to congestion or packet loss will be governed by the control mechanisms within the transfer control protocol (TCP/IP). Retransmissions and rate control will slow down TCP applications when in a congested state, but data will, in general, be reliably transmitted. However, applications which are more sensitive to delay, such as voice over IP and videotelephony, are generally sent for delay considerations using the real time protocol (RTP) and the underlying unreliable user datagram protocol (UDP/IP). These protocols deliver timely data but with the downside that any congestion will lead to packet losses which will propagate up to, and need to be managed by, the application layer. This paper reports on efforts to define an application layer quality-of-service framework for the video component of videotelephony over RTP/UDP leading to an initial reference design for specifying videotelephony products. The error resilience features of the latest video-coding standard, H.264, are examined, as are modifications to existing RTP Internet recommendations to allow effective feedback-based repair for this new codec. Results using RTP early feedback and H.264 reference picture selection in a multi-reference configuration will also be presented.

Study and enhancement on buffer management for smooth handover in MIPv6

For improving Transfer Control Protocol (TCP) performance in mobile environment, smooth handover with buffer management has been proposed to realize seamless handovers. However in our simulation, even if smooth handover in Mobile IPv6 (MIPv6) is implemented, TCP can not always achieve better performance due to packets forwarding burst. Based on the study of buffer management for smooth handover, this paper proposes an enhanced buffer management scheme for smooth handover to improve TCP performance. In this scheme, a packet-pair probing technology is adopted to estimate the available bandwidth of the new path from Previous router (Prtr) to Mobile Node (MN), which will be used by Prtr to control the buffered packets forwarding. The simulation results demonstrate that smooth handover with this scheme can achieve better TCP performance than the original scheme.

Bayesian inference of network loss and delay characteristics with applications to TCP performance prediction

In large-scale dynamic communication networks, end systems cannot rely on the network itself to cooperate in characterizing its own behavior. This has prompted research activities on methods for inferring internal network behavior based on the external end-to-end network measurements. In particular, knowledge of the link losses and link delays inside the network is important for network management. However, it is impractical to directly measure packet losses or delays at every router. On the other hand, measuring end-to-end (from sources to destinations) losses or delays is relatively easy. We formulate the problems of link and delay estimation in a network based on end-to-end measurements as Bayesian inference problems and develop several Markov chain Monte Carlo (MCMC) algorithms to solve them. We show how these link loss and delay estimates can be used to predict point-to-point transfer control protocol (TCP) throughput in the network. We apply the proposed link loss and delay estimation algorithms, as well as the TCP throughput estimation algorithms, to data generated by the network simulator (ns-2) software and obtain good agreements between the theoretical results and the actual measurements.