Incoming Packets Research Articles

TupleMerge: Fast Software Packet Processing for Online Packet Classification

Packet classification is an important part of many networking devices, such as routers and firewalls. Software-defined networking (SDN) heavily relies on online packet classification which must efficiently process two different streams: incoming packets to classify and rules to update. This rules out many offline packet classification algorithms that do not support fast updates. We propose a novel online classification algorithm, TupleMerge (TM), derived from tuple space search (TSS), the packet classifier used by Open vSwitch (OVS). TM improves upon TSS by combining hash tables which contain rules with similar characteristics. This greatly reduces classification time preserving similar performance in updates. We validate the effectiveness of TM using both simulation and deployment in a full-fledged software router, specifically within the vector packet processor (VPP). In our simulation results, which focus solely on the efficiency of the classification algorithm, we demonstrate that TM outperforms all other state of the art methods, including TSS, PartitionSort (PS), and SAX-PAC. For example, TM is 34% faster at classifying packets and 30% faster at updating rules than PS. We then experimentally evaluate TM deployed within the VPP framework comparing TM against linear search and TSS, and also against TSS within the OVS framework. This validation of deployed implementations is important as SDN frameworks have several optimizations such as caches that may minimize the influence of a classification algorithm. Our experimental results clearly validate the effectiveness of TM. VPP TM classifies packets nearly two orders of magnitude faster than VPP TSS and at least one order of magnitude faster than OVS TSS.

Voltage- and temperature-controllable quantum-data processing across three-terminal superconducting nanodevices

Quantum entanglement is among the main fundamental resources for quantum information processing tasks like quantum communication, quantum computation, etc. The states with such kind of a nonlocal correlation can easily be obtained from a single-mode wave packet using a passive linear beam splitter. Taking into account scalable arguments and thus the need to implement quantum technologies in a solid-state platform, we study transmission of quantum data encoded in quasiparticles charges across a nanoscale three-arm beam splitter made by different BCS superconducting wires with a node size less than the smallest coherence length. It is calculated as to how a quasiparticle wave packet injected into one of the device leads is divided between two others. We show that an appropriate choice of the incoming wave packet permits to control the ratio of the two outgoing charges by comparatively small voltages of the order of the superconducting energy gap. The response of the device is analyzed as a function of the applied voltage biases and an asymmetry parameter, the ratio of the energy gaps in the two outward leads. We discuss two possible ways of the coherent wave-packet injection, specific pulses of voltages at ultra-low temperatures and those of current biases at temperatures comparable with the critical temperature of a superconducting emitter. Finally, we argue that voltages applied to outward leads as well as the temperature of an inward lead can serve as a control parameter for the charges delivered within a quantum network.

Traveling distance estimation for dispersive Lamb waves through sparse Bayesian learning strategy

Lamb wave is a promising tool for the nondestructive testing and structural health monitoring (SHM) of plate-like structures. The dispersive effect is an intrinsic property of guided waves, making the energy of the incoming wave packets spreading out in time domain so that wave packets are easily overlapped, which causes the traveling distances of the wave packets hard to be estimated and thus degrades the resolution of imaging. Traveling distance estimation is the basis of damage localization in Lamb wave based SHM. To deal with these problems, a sparse Bayesian learning (SBL) strategy based method is proposed to sparsely estimate the traveling distance of each dispersive wave packet. To establish a spare representation model, an overcomplete dictionary with each atom corresponding to a dispersive Lamb wave is designed to decompose the measured dispersive signal in frequency domain. The sparse representation model is based on a prior knowledge that the number of wave packets in the measured signal is sparse comparing with the number of atoms of the designed dictionary. Then the distance spectrum, the amplitude coefficients in distance domain, can be sparsely recovered via the SBL strategy. Dispersion compensated signal can also be achieved using the distance spectrum and another designed non-dispersive dictionary. Results from simulations and experiments on a plate both demonstrate the effectiveness of the proposed method.

APPLICATION OF ACCESS CONTROL LIST FOR NETWORK SECURITY AT CISCO ROUTER AS A FIREWALL

The provision limiting access to network users is one of the defensive action system from cyber attacks that can occur through a network connected to the user. Installation ACL device the router can be a firewall, where each incoming and outgoing packets will be matched with a list of existing entries, and then will proceed preconfigured actions.

Trust Based Routing Algorithm to Improve Quality of Service in DSR Protocol

Wireless sensor networks involve low power fixed and mobile nodes with limited energy resources. Lack of resources such as energy and bandwidth, could reduce cooperation between nodes that may lead to lower quality of service parameters. Lack of cooperation would result in not forwarding incoming packets by each node to save its remaining energy. Also, due to inherent characteristics of wireless sensor networks, they are vulnerable to be attacked by malicious or selfish nodes. Trust management methods can be used to deal with such problems by designing a routing protocol that is based on trust and can improve quality of service parameters. In this paper, we utilize a trust management system and provide a method to reduce energy consumption and improve quality of service parameters. We improved packet delivery ratio and the amount of remaining energy in Dynamic Source Routing protocol, while maintaining the end to end delay.

Counter-propagating wave packets in the quantum transition state approach to reactive scattering.

The quantum transition state concept provides an intuitive and numerically efficient framework for the description of quantum state-resolved reactive scattering and thermal reaction processes. Combining multiconfigurational time-dependent Hartree wave packet dynamics calculations with a flux correlation function based analysis, rigorous full-dimensional calculations of initial state-selected and state-to-state reaction probabilities for six atom reactions are feasible. In these calculations, a set of wave packets is generated in the transition state region, propagated into the asymptotic area, and analyzed. In the present work, an alternative approach which employs counter-propagating sets of wave packets is introduced. Outgoing wave packets started in the transition state region are matched with incoming wave packets generated in the reactant (or product) asymptotic area. Studying the H + CH4 → H2 + CH3 reaction as a prototypical example, one finds that the incoming wave packets can be propagated closely up to the transition state region with minor numerical effort. Employing cross correlation functions of incoming and outgoing wavefunctions, the propagation times required for the outgoing wave packet and thus the numerical costs of the entire calculation can be reduced significantly. Detailed full-dimensional calculations studying initial state-selected reaction probabilities for the H + CH4 → H2 + CH3 reaction are presented to illustrate the new approach. It is found that converged results can be obtained using shorter propagation times of the outgoing wave packets and less single-particle functions.

Prospects for Bioinspired Single-Photon Detection Using Nanotube-Chromophore Hybrids

The human eye is an exquisite photodetection system with the ability to detect single photons. The process of vision is initiated by single-photon absorption in the molecule retinal, triggering a cascade of complex chemical processes that eventually lead to the generation of an electrical impulse. Here, we analyze the single-photon detection prospects for an architecture inspired by the human eye: field-effect transistors employing carbon nanotubes functionalized with chromophores. We employ non-equilibrium quantum transport simulations of realistic devices to reveal device response upon absorption of a single photon. We establish the parameters that determine the strength of the response such as the magnitude and orientation of molecular dipole(s), as well as the arrangements of chromophores on carbon nanotubes. Moreover, we show that functionalization of a single nanotube with multiple chromophores allows for number resolution, whereby the number of photons in an incoming light packet can be determined. Finally, we assess the performance prospects by calculating the dark count rate, and we identify the most promising architectures and regimes of operation.

Fuzzy Logic‐based Efficient Interest Forwarding (FLEIF) in Named Data Networking

AbstractContent centric or Named Data Networking (NDN) is expected to replace IP‐based communication in the future Internet architecture. Here, connections are established based on data instead of host addresses. This flexibility helps in decreasing the end‐to‐end delay, as the requested data may be available in any intermediate router's cache. In NDN, a small Interest packet sent on a link results in large sized incoming Data packets on the same link. Therefore, sending multiple Interest packets on a single outgoing face may cause congestion on the returning path. Hence, regulation of Interest packets based on link characteristics is important to avoid congestion. In this paper, an intelligent mechanism based on Neuro‐Fuzzy Logic is proposed for calculating outgoing link prices of each intermediate node. The class of each outgoing link on a router is determined for Interest forwarding in order to avoid congestion. Comparison results show that the proposed method effectively improves throughput by decreasing packet loss ratio.

Cooperative Authentication in Underwater Acoustic Sensor Networks

With the growing use of underwater acoustic communications (UWAC) for both industrial and military operations, there is a need to ensure communication security. A particular challenge is represented by underwater acoustic networks (UWANs), which are often left unattended over long periods of time. Currently, due to the physical and performance limitations, the UWAC packets rarely include encryption, leaving the UWAN exposed to external attacks faking legitimate messages. In this paper, we propose a new algorithm for message authentication in a UWAN setting. We begin by observing that, due to the strong spatial dependency of the underwater acoustic channel, an attacker can attempt to mimic the channel associated with the legitimate transmitter only for a small set of receivers, typically just for a single one. Taking this into account, our scheme relies on trusted nodes that independently help a sink node in the authentication process. For each incoming packet, the sink fuses beliefs evaluated by the trusted nodes to reach an authentication decision. These beliefs are based on the estimated statistics of the channel parameters, which are chosen to be the most sensitive to the transmitter-receiver displacement. Our simulation results show accurate identification of an attacker's packet. We also report results from a sea experiment demonstrating the effectiveness of our approach.

Electron-electron interaction in graphene at finite Fermi energy

Using the Bethe-Salpeter equation in the leading approximation, we derive the wave equation describing the interaction of two electrons in graphene at arbitrary value of the Fermi energy EF. For the solutions of this equation, we have found the explicit forms of the density and the current which obey the continuity equation. We have traced the evolution of the wave packet during a scattering process. It is shown that the long-living localized quasi-stationary peak may appear at EF < 0. Then this peak decays into a set of wave packets following each other. At t → ∞ a total norm of all outgoing wave packets equals to that of incoming wave packet. At EF = 0 the localized state does not appear. For EF < 0 there is an infinite set of the localized solutions with the finite norms. We clearly demonstrate the qualitative difference of the results obtained on the bases of the Bethe-Salpeter equation and the results following from the wave equation where the Hamiltonian is a sum of the one-particle Hamiltonians and the electron-electron interaction potential.

Segment Routing in Software Defined Networks: A Survey

Segment routing (SR) has emerged as a promising source-routing methodology to overcome the challenges in the current routing schemes. It has received noticeable attention both in industry and academia, due to its flexibility, scalability, and applicability, especially in software defined networks. The emerging cloud services require strict service level agreements such as packet loss, delay, and jitter. Studies have shown that traditional network architectures lack the essential flexibility and scalability to offer these services. To combat this, a more flexible and agile routing paradigm of SR enables a source node to steer an incoming packet along a performance engineered path represented as an ordered list of instructions called segment list. This is encoded as a multiprotocol label switching label stack or an IPv6 address list in the packet header. This paper provides a comprehensive review of the novel SR technology by describing its architecture, operations, and key applications to date. SR paradigm can be effectively applied to a wide range of network applications, such as traffic engineering, network resiliency, network monitoring, and service function chaining, to achieve efficient network solutions. Furthermore, this paper identifies an interesting set of future research directions and open issues that can help realize the full potential of the emergent SR paradigm.

USING SENSITIVITY FUNCTION FOR CONGESTION CONTROL IN TELECOMMUNICATION NETWORK

The scheme of control of congestion with the use of feedback on the sign of the sensitivity function of productivity of the telecommunication network is considered. The performance sensitivity sign (target function) provides the optimal direction for adjusting the speed of the data source. The most common scheme for controlling binary feedback feedback messages about possible network congestion is to detect and set the congestion bit based on the length of the incoming packet queue. The main advantage of a queue-based scheme is its low complexity: the length of the queue can be controlled by a single counter. However, this method can create large queues in network nodes. Detecting the created mash should be delayed for some time to create the queue. Similarly, the detection of a congestion solution is also delayed by the time required to process the queue. To determine the sensitivity function of the network performance, it is proposed to use a simple neural network model of the dynamic system. The developed optimal control algorithm provides the formation of a control signal in such a way that the output of the system is as close as possible to the pre-established characteristics of the network. The model for the backtroque prediction of the queue state is proposed. The results of the simulation of the performance of the proposed scheme show that the scheme based on sensitivity has better performance compared with the usual scheme of choosing the threshold. A sensitivity-based circuit gives smaller variations in queue size and source speeds. Moreover, fluctuations are not significantly different, even if there are large changes in the service speeds of bottlenecks in the telecommunication network or its fragments.

Wireless Scheduling for Information Freshness and Synchrony: Drift-Based Design and Heavy-Traffic Analysis

We consider the problem of scheduling in wireless networks with the aim of maintaining up-to-date and synchronized (also called, aligned ) information at the receiver across multiple flows. This is in contrast to the more conventional approach of scheduling for optimizing long-term performance metrics such as throughput, fairness, or average delay. Maintaining the age of information at a low and roughly equal level is particularly important for distributed cyber-physical systems, in which the effectiveness of the control decisions depends critically on the freshness and synchrony of information from multiple sources/sensors. In this paper, we first expose the weakness of several popular MaxWeight scheduling solutions that utilize queue-length, delay, and age information as their weights. Then, we develop a novel age-based scheduler that combines age with the interarrival times of incoming packets in its decisions, which yields significant gains in the information freshness at the receiver. We characterize the performance of our strategy through a heavy-traffic analysis that establishes upper and lower bounds on the freshness of system information.

Enhancing Replacement Policy of Content-Centric Networking to Support Reaction toward Natural Disaster

Replacement policy in Content-Centric Networking (CCN) is a necessary and current, function as an important part in Interest packet caching. Pending Interest Table (PIT) is the main and core cache tables in CCN and plays a significant role for recording the information of Interest packets that are forwarded but are still waiting for matching with incoming Data packets. However, PIT management is more fundamental with regard to CCN operations for better memory efficiency. The PIT size determination of the forwarding system is a difficult problem in PIT management. Due to the limited PIT sizing, PIT replacement is utilized to remove the current entry from PIT and constructing a new space for the incoming entry to it. In a disaster area, this problem is due to the massive Interest packet that generating by survivors from the disaster and rescuers. The PIT overflow could be subjected due to use of long Interest lifetimes that would simultaneously increase the number of entries in the PIT. Thus particularly when there is no flexible replacement policy, hence affecting PIT performance. Therefore, the ultimate aim of this paper is to develop the replacement policy that can deal with this problem. The proposed policy is a PIT management based on CCN PIT replacement policy for managing the PIT during a natural disaster, which can lead to mitigating PIT overflowing. The results showed the overall scenarios, the proposed policy better PIT memory usage as well as decreasing the Interest drop, delay time, Interest lifetime and Interest retransmission. A positive significance influence in this work would be to presents a formulate a rule as a function which can decrease the delay and thus be leading to increasing PIT utilization, which will be very much useful for survivors, emergency rescue teams as well as emergency operation centers.

Detection and differentiation of application layer DDoS attack from flash events using fuzzy‐GA computation

Distributed Denial-of-Service (DDoS) attacks are serious threats in the data center application, mainly affecting the web server. Even though there are various techniques to detect and mitigate such attacks so far they fail to meet in the case of application layer attack and Flash Events (FE). In the paper, we aim at detecting application layer DDoS attacks and distinguish it from FE. We have considered a DDoS attack model and selected the parameters in the incoming packets that correspond in causing the attack. Based on the attack model we have analysed the statistical parameters of the incoming packets such as inter-arrival time, the probability of uniqueness of an IP address in given time frame and the unavailability of HTTP (Hyper Text Transfer Protocol) GET acknowledgment bit in the header field. These parameters are the input to the Fuzzy classification model. We have used Genetic Algorithm (GA) to provide an optimised value range for the input parameters. The optimised values are now applied to Fuzzy logic to identify whether the web accessing clients shows the behavior of attack, normal or FE. The experimental results show that Fuzzy-GA model provides an accuracy of 98.4% in detecting DDoS attack and 97.3% in detecting FE..

Minimum Cost Hypothesis Testing for Utility-Based Sleep-Mode

This letter considers designing a utility-based sleep-mode for the system with a traffic source of Markov-modulated Poisson process. Our design framework makes use of the minimum cost hypothesis testing to detect the state of the traffic source. More specifically, observing a packet arrival for a finite time interval, the system decides to enter sleep-mode with the hypothesis that the traffic source should be in the state with the lowest packet arrival rate. In designing the hypothesis testing, we consider two sleep-modes, such as $V$ -policy and $N$ -policy, and show how long the system should observe an incoming packet and when to wake up under two sleep-modes in conjunction with discontinuous reception mechanism.

Integrated Packet Classification to Support Multiple Security Policies for Robust and Low Delay V2X Services

One of the key applications in the 5G system is Vehicle-to-Everything (V2X). Ultra-low delay communication is essential for the safety of users and pedestrians in V2X. However, as sophisticated and various cyberattacks are increasing, it becomes hard to satisfy low delay constraints. To protect networks from such attacks, even single network security equipment provides multiple security functions, resulting in the inevitable additive delay in packet processing. In this paper, we suggest a new packet classification paradigm to resolve this issue. The proposed algorithm integrates multiple policy rule-sets into a single rule-set and classifies incoming packets using the integrated rule-set. Thus, it has a unique feature providing high classification performance regardless of the number of security policies. Through extensive performance evaluations, we confirm that the performance improvement is also increased with the total rule-set number increasing without the significant overhead of memory cost. We expect that it will mitigate the delay issue of existing network equipment for upcoming services such as V2X.

소프트웨어 정의 무선 메쉬 네트워크에서 마스터 컨트롤러 선택방법

소프트웨어 정의 무선 메쉬 네트워크에서 새로운 패킷에 실시간으로 잘 대응하기 위해선 가장 낮은 지연시간을 갖는 Flow Setup이 필요하다. 본 논문은 서포트 백터 머신(SVM)으로 영구적 링크 끊김을 예측하고 이를 바탕으로 미리 Flow Setup을 준비하여 기존 방법보다 끊김없이 낮은 지연시간을 갖는 마스터 컨트롤러 선택방법 RCM을 제안한다. In Software-Defined Wireless Mesh Network, a Flow Setup with the lowest delay is needed to adequately cope with new incoming packet in real time. Therefore, Master Controller Selection Method RCM that prepares Flow Setup in advance for more seamless and lower Flow Setup delay than existing methods is proposed by using SVM that predicts permanent link failure.

Optimal route path sustainability in military information system with reduced interference effect

The main purpose of this work is to exploit MANET environment in military environment to broadcast the data through efficient data transmission rate. This eventually results in different security issues like conflict and collision. These complexities could minimize the distribution of the packet ratio. Constant position node environment has been used in prevailing system, with interference-aware routing based on its nearby nodes. The previous researches could not handle the interference effects that occur in run time, and as a result, the performance of the system might get affected. In order to handle these issues, interference effect is evaluated in the proposed work to eliminate the packet loss. A novelty based on interference avoidance using coefficient of restitution measure approach has been proposed. This will obtain the incoming packets from more than one node, and it will calculate the “restitution” collision of the considered node. Improved route establishment is attained with minimum interference effect by making use of this measure. Genetic algorithm is utilized in this work to choose the most effective path from the available paths. The simulation results show that the proposed work provides significant results as compared to the existing techniques.

An Accurate and Efficient Modeling Framework for the Performance Evaluation of DPDK-Based Virtual Switches

Data plane development kit (DPDK) works as a specialized library that enables virtual switches to accelerate the processing of incoming packets by, among other things, balancing the incoming flow of packets over all the CPU cores and processing packets by batches to make a better use of the CPU cache. Although DPDK has become a de facto standard, the performance modeling of a DPDK-based vSwitch remains a challenging problem. In this paper, we present an analytical queueing model to evaluate the performance of a DPDK-based vSwitch. Such a virtual equipment is represented by a complex polling system in which packets are processed by batches, i.e., a given CPU core processes several packets of one of its attached input queues before switching to the next one. To reduce the complexity of the associated model, we develop a general framework that consists in decoupling the polling system into several queueing subsystems, each one corresponding to a given CPU core. We resort to servers with vacation to capture the interactions between subsystems. Our proposed solution is conceptually simple, easy to implement and computationally efficient. Tens of comparisons against a discrete-event simulator show that our models typically deliver accurate estimates of the performance parameters of interest (e.g., attained throughput, packet latency or loss rate). We illustrate how our models can help in determining an adequate setting of the vSwitch parameters using several real-life case studies.