Environment-Independent Online Real-Time Traffic Identification

In this paper, we present a real-time system identification method based on relay feedback testing with applications to multirotor unmanned aerial vehicles. The proposed identification method provides an alternative to the expensive lab testing of certain unmanned aerial vehicle (UAV) dynamic parameters. Moreover, it has the advantage of identifying the parameters that get changed throughout the operation of the UAV which requires onboard identification methods. The modified relay feedback test (MRFT) is used to generate stable limit cycles at frequency points that reveal the underlying UAV dynamics. The locus of the perturbed relay system (LPRS) is used to predict the exact amplitude and frequency of these limit cycles. Real-time identification is achieved by using the homogeneity properties of the MRFT and the LPRS which are proven in this paper. The proposed identification method was tested experimentally to estimate the aerodynamic parameters as well as the onboard sensor’s time delay parameters. The MRFT testing takes a few seconds to perform, and the identification computations take an average of 0.2 seconds to complete in modern embedded computers. The proposed identification method is compared against state-of-the-art alternatives. Advantages in identification accuracy and quantification of uncertainty in estimated parameters are shown.

In this paper, we propose an extension to GridFTP that optimizes its performance by dynamically adjusting the number of parallel TCP connections. GridFTP has been used as a data transfer protocol to effectively transfer a large volume of data in Grid computing. GridFTP supports a feature called parallel data transfer that improves throughput by establishing multiple TCP connections in parallel. However, for achieving high GridFTP throughput, the number of TCP connections should be optimized based on the network status. In this paper, we propose an automatic parallelism tuning mechanism called GridFTP-APT (GridFTP with Automatic Parallelism Tuning) that adjusts the number of parallel TCP connections according to information available to the Grid middleware. Through simulations, we demonstrate that GridFTP-APT significantly improves the performance of GridFTP in various network environments.

In this paper, we present a scheme that protects legitimate traffic from the large volume of attackers packets during a DDoS attack. Legitimate packets can be recognized by the tokens they carry in the IP header. Obtaining a token does not require protocol additions or changes, rather it is automatically obtained when a TCP connection is established. We believe that the Implicit Token Scheme (ITS) has numerous advantages: (1) It is totally transparent to clients. (2) No new protocols or modification of existing ones is needed to implement ITS. (3) Operations required by intermediate routers are computationally not more intensive than a couple of addition operations which could be easily done at wire-speed. (4) Does not lead to false positives. (5) Can sustain server availability even during attacks involving hundreds of thousands of attackers.

In the petroleum industry, accurately identifying downhole fluid is crucial for understanding fluid composition and estimating crude oil contamination and other properties. Near-infrared (NIR) spectrum analysis technology has achieved successful fluid identification applications due to its non-destructive nature and high efficiency. However, for real-time downhole fluid analysis, the NIR spectrometer faces challenges such as miniaturization and cost effectiveness. To address these issues, we construct a real-time downhole fluid identification system in this work. First, we propose a lightweight and deployable fluid identification model by integrating the successive projections algorithm (SPA) and a quadratic neural network (QNN). The SPA allows for spectral feature selection, and the QNN acts as an efficient identification model. Consequently, we use only four specific wavelengths with a one-hidden-layer QNN to achieve high identification accuracy. Second, we devise a hardware deployment scheme for real-time identification. We use four laser diodes to replace conventional light sources, further saving space. The QNN is then deployed to the STM32 MCU to implement real-time identification. Computational and online experiments demonstrate that our system functions well in real-time fluid identification and can further estimate the oil contamination rate with acceptable error.

Intensive correlative studies of magnetic fields and plasmas within the earth's magnetotail at geocentric radial distances of ∼23–46 RE during March-October 1974 have revealed striking new features. The instruments employed in this survey were the University of Iowa Lepedea and the Goddard Space Flight Center magnetometer. The hot tenuous plasmas within the plasma sheet were found to be in a state of almost continual flow and were threaded with northward, or closed, geomagnetic field lines. The magnetic field is referred to as ‘northward’ or ‘southward’ if the component Bz is positive or negative, respectively, regardless of the magnitudes of the other components. Proton bulk speeds were in the range 50–500 km s−1. The magnetic fields are directed northward, irrespective of whether the plasma flows are tailward or earthward. These observations show the demand for a strong persistent source of magnetic flux and hot plasmas for the plasma sheet. No characteristic proton bulk flows, e.g., strong dawn-to-dusk motions, were evident during crossings of the magnetic neutral sheet. Occasionally, the satellite encountered the region of acceleration in the magnetotail, the ‘fireball.’ This spectacular phenomenon exhibits strong jetting of plasmas in excess of 1000 km s−1, proton temperatures of ∼107 °K (kT ∼ 1 keV), disordered magnetic fields, southward magnetic fields during tailward jetting of plasmas, and northward magnetic fields for fast plasma flows toward earth. Observations of electrons are used to demonstrate that earthward plasma flows within the fireball are threaded with closed geomagnetic field lines, and open magnetic field lines are embedded in the tailward jetting plasmas. The magnetosheathlike plasmas within the boundary layers which are positioned contiguously to the plasma sheet display striking evidences of plasma heating, great changes in bulk flow velocities and acceleration of energetic electrons with E > 45 keV. Typical temperatures and bulk flow speeds within the boundary layer plasmas are ∼106 °K and ∼400 km s−1, respectively. Persistent zones of southward magnetic fields are detected, which are often positioned adjacent to the plasma sheet and within the boundary layer plasmas. Rotations of the magnetic fields from southward to northward, or vice versa, in these boundary layers are accompanied by large enhancements of energetic electron intensities, substantial heating of the low-energy electron distributions, and strong perturbations of the proton velocity distribution functions. During periods for northward directed fields the proton bulk flows decelerate to speeds of ≲200 km s−1, densities decrease, and the proton velocity distributions can be fitted with two Maxwellians with temperatures of ∼2 × 105 °K and ∼ 107 to 5 × 107 °K for specific examples. The boundary layer plasmas appear to be the primal source of hot plasmas and closed geomagnetic field lines for the plasma sheet. Qualitatively, all of the major results of the present study are consistent with macroscopic features which are expected from merging of magnetic field lines in the earth's magnetotail or, more specifically, in the magnetosheathlike boundary layer plasmas.

We deal with electromagnetically driven flows and their influence on the mass transfer through an interface between a mercury pool and a covering water layer. This experiment is devoted to simulate a refining ladle. The liquid metal pool is located in the single phase coil which may be supplied with alternating electric current with various frequencies. According to the coil current frequency, various types of flow regime may be obtained, namely : bulk flows, surface wave motions. Firstly, we review some experimental results concerning the characteristics of the turbulent flow. Secondly, we analyze the effect of various types of surface flow on the mass transfer coefficient by means of an electrochemical method, which is used to measure the instantaneous mass transfer across the liquid metal interface.

Mobile IP enables IP mobility support for mobile node (MN), but it suffers from triangular routing, packet redirecting, increase in IP header size, and the need for new infrastructure support. This paper details an alternative to enable terminal mobility support for MN. This scheme does not suffer from triangular routing effect and does not require dedicated infrastructure support such as home agent. It also does not increase the size of the IP header and does not require redirection of packets. These benefits are enabled with a tradeoff, which requires modifications on MN and its correspondent node. It uses an innovative IP-to-IP address mapping method to provide IP address transparency for applications and taps on the pervasiveness of SIP as a location service. From our analysis, we show that TMSP is much more efficient than mobile IP in terms of the number of hops as well as overhead. Our prototype implementation also shows that TMSP provides seamless communication for both TCP and UDP connections and the computational overhead for TMSP has minimal impact on packet transmission.

Although IP multicast has been rapidly evolving in the last few years, the current Internet is not fully multicast-enabled because of the lack of robust inter-domain routing and controlling protocols. In this paper, we present an alternative architecture for data distribution on Internet called PSRM that realizes semantic reliable, loose synchronized, multicast data delivery. PSRM is not based on global IP multicast, instead it uses a hybrid way to combine unicast delivery with multicast delivery. In PSRM, IP multicast is used only in local area, or multicast domain, to enhance the performance, and these multicast domains are organized into a spanning tree by TCP connections. As PSRM is based upon ALF protocol architecture, we use application-defined semantics to adapt content in a heterogeneous environment. PSRM have been implemented and demonstrated by a prototype distance learning application.

Transmission Control Protocol (TCP) is the main transport protocol that provides reliable transmission in the current Internet. However, TCP still has problems that may affect its performance on various network environments. Packet reordering, which is one of the problems on TCP, refers to the out-of-order event of packets. There are many reasons that can cause packet reordering. In this chapter, we propose RA-TCP, a novel TCP variant which modifies the retransmission occasion and the congestion response of the traditional TCP mechanism, to improve the performance on packet reordering. In particular, we replace the three duplicate ACKs with a retransmission detection timer (RDT) for the trigger of fast retransmit. Our simulation studies reveal that RA-TCP performs consistently better than existing mechanisms that try to make TCP more robust to packet reordering.

In current Internet, network API acts as a bridge between application and network and the importance of its role is growing. However, it has inherent limitation of tight-coupling which makes almost indivisible all the network environments, such as transport controls and network-specific addresses. This coupling not only makes it difficult to change one without changing another, but also prevents both sides from evolving. This work presents a novel network API, iPlug and dSocket, which not only decouples identifier and locator, but splits application-specific functions from protocol-specific. Our design enables (1) injection of information-centered applications requirements, (2) encapsulated control of underlying network mechanisms, and (3) dynamic coupling between applications and network. The proposed API is implemented as a shared library that can be easily deployed. Our evaluations on mobility environment showed that applications have the benefits of clear abstraction and easy programmability from decoupled iPlug and dSocket API.

Cables are essential elements in bridge engineering. The cable force is usually determined by the vibration method using the cable frequency. This paper proposes a real-time online identification method of cable modal frequency based on bandpass filter and Hilbert transform. A recursive form of band-pass filtering (RBF) is employed so that the original signal can be filtered for the target frequency band to obtain a single modal signal of the target order of the cable. The Recursive Hilbert transform (RHT) is then used to obtain a real-time resolved signal for real-time frequency identification, allowing for real-time identification and tracking of the time-varying modal frequencies at the cable's target order. This method is more efficient than traditional time-frequency analysis methods. According to numerical simulations and actual measurement data. The method is noise-resistant and does not necessitate prior knowledge of the order. The method allows online identification and tracking of time-varying frequency of interest at a specific order. The procedure can be applied to the real-time identification of cable incident frequencies in an online monitoring system, and can also provide a basis for further real-time identification of time-varying cable forces.

A method of network traffic identification based on RBF (Radial Basis Function) neural network is proposed by analysis of the current status of the network environment. By using the public data set and the real-time traffic for a combination of supervised learning, this method constructs a reasonable training set and testing set to experiment and implement the network traffic identification based on RBF neural. The experiments prove the identification method in the application of network traffic has the characteristics of high accuracy, low complexity and high recognition efficiency, and the practical feasibility in real-time traffic identification.

For RFID-based applications, the uniqueness of ID assigned to each RFID tag should be guaranteed. Several research/standard organizations such as EPCglobal, ISO/IEC, Ubiquitous ID Center, and so on, have developed their own Unique Item ID (UII) specifications. The existence of various UII schemes may cause interoperability problems between applications using different UII schemes when those applications are operated on future global Internet network environment. In addition, it is expected that the traffic for UII query will be increased ten-times higher than that for DNS query in the current Internet. In order to overcome these problems, this paper proposes a fast tree-based classification algorithm applicable for various UII schemes, which can make it efficient to construct global directory lookup services for RFID applications with various UII schemes. Since the proposed scheme can be operated on readers, it can not only distribute traffic loads for UII queries, but also global RFID networks.

Proper management of plant diseases requires accurate disease diagnosis and precise identification of the phytopathogens involved. Traditional and conventional methods of disease diagnosis and pathogen detection have several demerits. It takes a lot of time to diagnose a disease and to identify a pathogen accurately by traditional approaches. Moreover, results are not always conclusive because similar symptoms can be caused by different pathogens or physiological conditions and sometimes it is very difficult to distinguish closely related organisms on the basis of their morphological characters only. Thus the traditional methods normally applied for pathogen identification and disease diagnosis are less sensitive and less reliable. The need for rapid and accurate identification and diagnostic methods to identify the organisms that cause plant diseases are essential for the formulation of effective disease control strategies.

Tomicus is a globally significant forestry pest, with Yunnan Province in southwestern China experiencing particularly severe infestations. The morphological differences among Tomicus species are minimal, making accurate identification challenging. While traditional molecular identification and morphological recognition methods are reliable, they require specialized personnel and equipment and are time-consuming. For individuals with limited expertise, accurate identification becomes particularly difficult. This highlights the challenge of developing a rapid, efficient, and accurate classification model for Tomicus. This study investigates four major Tomicus species in Yunnan Province: Tomicus yunnanensis, Tomicus minor, Tomicus brevipilosus, and Tomicus armandii. We collected samples from infested pine trees and constructed a dataset comprising 6,371 high-resolution images captured using a handheld microscope. A novel Tomicus classification model, DEMNet, was proposed based on an improved ResNet50 architecture. Experimental results demonstrate that DEMNet outperforms ResNet50 across key metrics, achieving a classification accuracy of 92.8%, a parameter count of 1.6 M, and an inference speed of 0.1193 s per image. Specifically, DEMNet reduces the parameter count by 90% while improving classification accuracy by 9.5%. Its lightweight and high-precision design makes DEMNet highly suitable for deployment on embedded devices, offering significant potential for real-time Tomicus identification and pest management applications.