Packet Processing Time Research Articles

Unidirectional switch model for multiservice traffic with polymodal distribution

The modern stage of development of telecommunication networks is characterized by active improvement of routing algorithms in packet-switched networks taking into account the provision of the required quality of service. The need to transfer large amounts of information is due to the need to ensure the normal functioning of modern multimedia applications, in particular such as IP telephony, video and radio broadcasting, interactive distance learning, which determines the multiservice nature of traffic, which is heterogeneous, and its statistical properties in most cases are of a complex polymodal nature. Taking into account the fact that traditional Poisson models providing FIFO servicing of network traffic for solving modern telecommunication problems lead to overly optimistic results in terms of delays, there is a need to develop a new mathematical model of a unidirectional switch providing FIFO servicing of multiservice traffic with polymodal distribution taking into account the provision of the required quality of subscriber service and an algorithm for estimating its main parameters. Development of a mathematical model of a unidirectional switch FIFO-service of multiservice traffic with polymodal distribution taking into account the provision of the required quality of subscriber service and an algorithm for estimating its main parameters. A new mathematical model of a unidirectional switch implementing FIFO-service of multiservice traffic with polymodal distribution has been developed, allowing one to estimate the probabilities that packets arriving at the switch input will not be processed due to overflow of its buffer memory and exceeding the maximum packet processing time. The model takes into account the delays introduced by the channel and channel equipment during the distribution and processing of packets from the source to the switch in question. Recommendations for modeling traffic processing to ensure the specified accuracy of the results are presented.

Enhancing Network Security through Advanced Authentication and Key Management Mechanisms

This paper introduces the SEAKS-PKMv2 protocol, a robust security mechanism aimed at addressing vulnerabilities within the PKMv2 framework, particularly focusing on mutual authentication, key management, and encryption in mobile WiMAX networks. By integrating RSA-based and EAP-based authentication methods, SEAKS-PKMv2 establishes a secure environment that mitigates risks such as replay, man-in-the-middle and interleaving attacks. The protocol adopts a distributed authentication and localized key management approach, facilitating efficient and secure network access and data transmission. Through simulation, we evaluate the SEAKS-PKMv2 protocol’s performance in terms of packet delivery ratio, overhead, processing time, and resilience against rogue relay station attacks. The findings demonstrate significant improvements in network security and efficiency, confirming the effectiveness of SEAKS-PKMv2 in enhancing the integrity and confidentiality of communications in distributed network settings.

CSVRF: A CAM‐based popularity‐aware egress group‐caching scheme for SVRF‐based packet forward engines

AbstractAs a key component of high‐performance switches and routers, the packet forwarding engine (PFE) is mainly responsible for selecting the appropriate output port for tens of thousands of packets within an extremely short time frame. However, the performance of PFE is determined by the selected group membership algorithm. This paper puts forth a hybrid strategy–caching scalar‐pair and vectors routing and forwarding (CSVRF), consisting of virtual output port bitmap caching (VOPBC) and fractional‐N SVRF to address major multicast forwarding issues such as scalability by using content addressable memory. In CSVRF, a virtual output port bitmap cache is introduced, which includes the most popular combinations of output port bitmap and divides the big scalar‐pair into N sub‐groups to achieve parallel compute and the reusability of less bit‐length prime. The results demonstrate that the memory space and the forwarding latency are effectively reduced compared with previous work. In space efficiency, it only required 10% memory space compared with the original SVRF/fractional‐N SVRF, decreased 10% memory usage compared with pure VOPBC and nearly improved 1 to 4 orders of magnitude of packet processing time compared with the original SVRF and the fractional‐N SVRF respectively.

Access Control Management System for Edge Computing Environment Using Tag‐Based Matching and Cache Injection

With increasing attention to the secondary use of data, privacy protection laws such as the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) have come into force to protect residents from unauthorized exploitation of personal data. Flow management is an effective method to track the distribution of user data in a multi‐domain network environment. Transparency in the relationship between data and service providers is essential to track the status of data provision. Vendor and Consumer Relationship Management (VCRM) manages this relationship by regulating relevant flow information. VCRM is expected to collaborate with the edge‐computing environment in the management of regional unit flow, wherein all access to personal user data should be restricted in accordance with the stakeholders' requests. Accordingly, this study proposes a packet processing function that collaborates with VCRM to manage the access control of flows passing through a regional network. Moreover, this paper proposes methods to reduce packet processing time on the switch, and requests to the switch controller. Using tag‐based matching and cache injection methods, the number of requests to the controller decreased to 33.4% of the original figure. Our proposed method also reduces the total processing time on flow management switches in the network environment in the analysis of encrypted TCP streams such as HTTP over TLS and MQTT over TLS. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Deterministic Model of Information Queries Batch Processing in a Multithreaded Server

The analytical model of processing a batch of similar requests in a multithreaded server is considered. The model is based on the high determinism of the duration of individual stages of request processing and the moments of events leading to the switching of the processor from one processing program thread to another. Unlike other deterministic models based on the theory of schedules, in this case the goal is not to find the optimal distribution of work across processors, but to study the dependence of the main characteristics of the software server (packet processing time, marginal performance) on the characteristics of the request and the size of the batch. The model concerns the situa­tion when distributed system with intensive flows of information queries is developed and special measures to ensure the required performance must be taken. One of these measures is the introduction of batch query processing tools, allowing an array of similar information queries to be processed in a single service call. The introduction of such tools usually allows you to repeatedly increase the rate of processing queries in the system and very often becomes a real «lifesaver» for customers who issue, for example, hundreds of thousands of queries per day or more. It is quite likely that a sequence of ordinary single queries cannot provide a solution, and batch processing simply has no alternative

Cable: A framework for accelerating 5G UPF based on eBPF

An increasing number of 5G core network modules are being implemented in the X86 cloud environment. Improving the modules’ packet processing ability can accelerate the 5G data plane. EBPF is a promising way to reduce the packet processing consumption in the Linux kernel. In this paper, we propose Cable, a framework to accelerate the 5G data plane by using eBPF. Cable can not only reduce the packet processing time in a single UPF, but also schedule PDU sessions to suitable UPFs by the monitoring information. We implemented Cable in the open source 5G core project Free5GC and made it publicly available. Evaluation in a simulation environment shows that Cable can reduce packet processing time in a single UPF by over 30% and improve the whole system’s UPF usage by 25%.

Real-Time Encrypted Traffic Classification with Deep Learning

Confidentiality requirements of individuals and companies led to the dominance of encrypted payloads in the overall Internet traffic. Hence, traffic classification on a network became increasingly difficult as it must rely on only the packet headers. Many vital tasks such as differential pricing, providing a safe Internet for children, and eliminating malicious connections require traffic classification, even if the payload contents are encrypted. Encrypted traffic is harder to classify as packet content becomes unreadable. In this work, we aim to provide an insight into traffic classification using encrypted packets in terms of both accuracy and packet processing time. LSTM (Long Short-Term Memory) architecture is a good candidate for this problem as it can handle sequences. Each flow can be modeled as a sequence and patterns of the sequences can provide valuable information. We compare the performance of LSTM with other methods in both real-time and offline experiments. Compared to a machine learning method both online and offline LSTM excelled with precision and recall differences up to 50%. Average accuracy with LSTM was measured as 97.77% offline and 91.7% in real-time. Average packet processing time in real-time was recorded as 0.593 msec which is 5 times faster than a recent work that uses LSTM method.

PPTMon: Real-Time and Fine-Grained Packet Processing Time Monitoring in Virtual Network Functions

By softwarizing the legacy network functions, Network Function Virtualization (NFV) allows rapid development and deployment of network services as well as simplicity and flexibility in network operations and management. Monitoring the performance characteristics of Virtual Network Functions (VNFs), particularly packet processing time, is important to ensure that VNFs are operating correctly with desired performance. This is especially crucial for low-latency network services. In this paper, we present Packet Processing Time Monitoring (PPTMon), a real-time, fine-grained, and end-to-end solution for VNF packet processing time monitoring. PPTMon can provide per-hop monitoring for a single VNF as well as end-to-end monitoring for multiple VNFs in a service function chain. PPTMon allows monitoring in both sampling and continuous fashions. Continuously monitoring every packet may greatly degrade the performance of the VNFs and generate a huge amount of monitoring data. PPTMon’s event-filtering algorithm effectively filters out non-important data and reduces the performance overhead. PPTMon processes packets in-stack by embedding timestamp information directly into the packets, thus further reducing the effect on the VNF performance. PPTMon is implemented on top of extended Berkeley Packet Filter (eBPF) – a Linux framework that allows high-speed packet processing. Our experiment results shows that PPTMon can monitor VNF packet processing time with high accuracy and low impact on performance.

Edge Intelligent Agent Assisted Hybrid Hierarchical Blockchain for continuous healthcare monitoring & recommendation system in 5G WBAN-IoT

Wireless Body Area Network (WBAN) is an emerging technology that faces many challenges for monitoring patient health state information and early diagnosis of any disease (e.g. COVID-19). In addition, WBAN has many issues such as high energy consumption, overhead and latency due to the scarcity in resources, for that we bring edge assisted 5G environment in WBAN. The patient information is sensitive and easily traced by the attackers due to insecurity, for that, we proposed the EiA-H2B model (Edge intelligent Agent Hybrid Hierarchical Blockchain) which includes five phases. Firstly we proposed Biological PUF based sensor authentication, which is a strong credential that provides high security. All the sensors are authenticated by the virtual authenticator that is deployed by a blockchain ledger. Due to the mobility of WBAN, we focused on handover that is done by Bi-Partite One to N matching theory. Secondly, we proposed high voting based virtual clustering, in this phase high voting sensor is elected as a super node and that is used to create a virtual cluster. Thirdly, we proposed duty cycle MAC scheduling protocol is used to predict the original state of the sensors which is done by Attention Matrix based Gated Recurrent Unit (AM-GRU), and then the timeslots are allocated for avoiding packet loss and retransmission. Fourth, we perform relay selection and routing that is done by Global Optimization based Artificial Electric Field Algorithm (AEFA). And finally, we predict emergency data and generate an alert in EiA using Human Learning aided State Action Reward State Action (SARSA) algorithm that finds the current state and predicts the corresponding action. Based on that current state information SARSA provides an efficient recommendation to the patients. Experiments are conducted by OMNeT ++ network simulator and evaluate the performance of the proposed EiA-H2B model in terms of energy consumption, success rate, network throughput, end to end delay, packet loss rate, authentication time and processing time.

Анализ очереди в системе G/G/1 на основе гиперэкспоненциальных распределений

For real-time applications, the change in packet delay, which is usually called delay jitter, is one of the most important parameters of quality of service in modern infocommunication networks when processing multimedia streams, along with the delay and the probability of packet loss. This article discusses approaches to assessing jitter in modern infocommunication networks when processing non-Poissonian traffic in the G/G/1 system. To approximate the system of an arbitrary queue G/G/1, a model based on hyperexponential distributions of the type H2/H2/1 was used. As a processed stream, the implementation of IP network traffic with the absence of mutual correlations between the time intervals between packets and the times of packet processing is used. An important task in this case is to determine the parameters of hyperexponential distributions for the time intervals between packets and packet processing times. The paper presents two methods for determining the parameters of hyperexponential distributions: using the method of moments and using the EM-algorithm. The paper analyzes the influence of the network load factor on the jitter value when using two models for determining the parameters of hyperexponential distributions. This analysis showed a slight increase in jitter with increasing network load both in the case of using the method of moments and in the case of the EM algorithm. It has been determined that the estimates of the jitter values in the case of applying the method of moments and the EM algorithm are quite close in value. The main result of the work is to obtain simple calculation formulas for the analysis of jitter in the G/G/1 system using hyperexponential distributions.

Методика получения обобщенных статистических характеристик сетевого оборудования для создания имитационных моделей

The research is devoted to the problem of the development models of network equipment that precisely reproduce the operation of real equipment by the time characteristics. Aim. This research is aimed at developing a methodology that allows you to quickly obtain models that statistically coincide in the behavior of the selected parameters with real measured equipment on existing open modeling systems. Methods. To obtain the performance parameters and time characteristics of the real equipment, an approach was proposed, which includes experiment planning to compute the characteristics for a wide range of input traffic intensities. In addition, the approach describes the connection scheme and equipment configuration including external switch control to test the effect of various settings on the performance and packet processing times. It also includes the scripts to automate the creation of traffic test sets with the required parameters of time distribution between the packets as well as the scheme of connection through the container services and receiving traffic dumps. The approach does not include the testing of the output queues operation because the goal was to investigate and transfer into the model processes, which occur before the frames are placed in the outgoing interface queues. An open-source Omnet++ software was used as a modeling environment. Results. We studied the structure of its existing switch model and identified disadvantages that affect the accuracy and reliability of the results. In addition, we proposed an approach for implementing model delay lines based on the interpolation of time parameter tables obtained from real data for the required combination of traffic parameters and inbound interfaces. To test the developed approaches, a test bench on real equipment was assembled, and an experimental research plan was developed. Finally, an automated testing script was implemented according to a given plan. Testing was carried out in the conventional frame switching mode as well as in the switching mode based on OpenFlow tables. In addition, the time characteristics of the intermediate equipment were also obtained in order to take into account their influence on the experimental results. Based on them, a table of parameters was computed for the processing delay line in the model, and the experiment was conducted on the model in Omnet++. Since the obtained samples in the statistical analysis showed the types of distributions that are different from the 3 normal and exponential, the statistical Mann–Whitney U-test was used to compare the mean values. Conclusion. The results obtained at a significance level of 0.05 confirmed the efficiency of this approach for models that more accurately describe the temporal characteristics of the traffic processing in network equipment.

Collaborative Packet Header Parsing in NetFPGA-Based High Speed Switches

Packet parsing is an important task performed by network elements, that involves traversal of a complex parser graph. At very high link bandwidths, the parsing time has to be reduced significantly. This letter proposes a collaborative approach, where the ingress switch parses the header stack and passes an unique parser code (UPC) to downstream routers, that use this UPC to compute the header offsets without parsing. This approach was implemented on a Xilinx NetFPGA based programmable data plane switch, and was shown to reduce packet processing time by nearly 8%.

An Incrementally-Deployable P4-Enabled Architecture for Network-Wide Heavy-Hitter Detection

The advent of Software-Defined Networking with OpenFlow first, and subsequently the emergence of programmable data planes, has boosted lots of research around many networking aspects: monitoring, security, traffic engineering. In the context of monitoring, most of the proposed solutions show the benefits of data plane programmability by simplifying the network complexity with a one big-switch abstraction. Only few papers look at network-wide solutions, but consider the network only composed by programmable devices. In this paper, we argue that the primary challenge for a successful adoption of those solutions is the deployment problem: how to compose and monitor a network consisting of both legacy and programmable switches? We propose an approach for incrementally deploy programmable devices in an ISP network with the goal of monitoring as many distinct network flows as possible. While assessing the benefits of our solution, we realized that proposed network-wide monitoring algorithms might not be optimized for a partial deployment scenario. We then also developed and implemented in P4 a novel strategy capable of detecting network-wide heavy flows: results show that it can achieve better accuracy than state-of-the-art solutions while relying on less information from the data plane and leading to only marginal additional packet processing time.

IPsec for high speed network links: Performance analysis and enhancements

Network packets security has always been significantly important and well researched topic but the network throughput and latency are not optimal on high speed network links, when using existing IPsec solutions. Network packet processing in Linux kernel is significantly slow (especially for 10-G/40-G link speed) due to context switching associated with system calls, and transitional copy operations in packet traversal through all network layers. Control plane layered packet processing involve copy operation per layer, which increases the packet processing time and consequently decreases the throughput of the network. In contrast to the kernel networking, data plane solutions like DPDK (Data Plane Development Kit) provide direct access to packets (from NIC) in user-space bypassing kernel stack, with zero intermediate copy operations and no context switching. For the normal packets, Intel DPDK claims 10x improvement in the throughput over kernel networking. Being inspired by that remarkable efficiency, we have done empirical evaluation of IPsec performance in data plane. Towards this goal, primarily we have analyzed the performance effect by individual bottleneck modules of strongSwan (an IPsec implementation); by redesigning them with data plane equivalent modules. Secondarily, we have proposed an efficient solution for strongSwan using DPDK API; which eliminates all previously identified bottleneck modules. In the proposed design, multi-cores design has been incorporated in the crypto module and performance is analyzed in terms of throughput and latency. There is an improvement of up to 3.54x in throughput and 2.54x improvement in latency as compared to existing control plane design. With AES128GCM as encryption scheme, a maximum throughput of 4.795 Gbps is achieved, while using only two cores.

P4 to FPGA-A Fast Approach for Generating Efficient Network Processors

This paper presents a framework for converting P4 programs to VHDL and then implementing them on Field-Programmable Gate Array (FPGA) platforms. In this framework, a match-action-based hardware architecture is introduced with clearly designed components, which correspond to the described functionalities in the P4 programs. A pre-built template library is used for the compilation that includes optimized VHDL templates corresponding to specific clearly designed components. From the output of a standard frontend P4 compiler, the proposed compiler extracts parameters and relationships within the functions being employed, maps them to corresponding templates by calling, configuring, optimizing and instantiating them, and finally generates the appropriate FPGA code. A pre-built evaluation library is also proposed that helps the compiler to optimize the implementation during the mapping phase. A prototype of this framework is also implemented and evaluated; in this process, it is found that the generated processors use few resources and have high throughput and low latency. Compared with a state-of-the-art solution, the packet processing time is halved. In addition, the generated processors are able to operate at a line rate of nearly 100 Gigabits per second for a basic layer-3 forwarding application.

A Cost-Efficient Software Based Router and Traffic Generator for Simulation and Testing of IP Network

The development was carried out using the Qt5.2 integrated development environment, which uses the programming language C++. The main advantage of this environment is that the code written in it can be compiled to different platforms (for example, Windows, Linux, Mac OS). A software router based on a modular architecture has been developed. It uses the socket technology, which allows forming a program-oriented packet network with any topology, including full-coupled topology. A network traffic generator to test the developed software router has been designed. We proposed a scheme to measure the packet processing time of a router using a specialized packet-capture network interface cards (NIC 1 and NIC 2) and a novel traffic generator installed on PC. Based on an experimental test bed we confirmed that our software router provides a cost-efficient alternative to the expensive, special hardware router CISCO 2801.

OPTIMAL ROUTE DEFINITION IN THE RAILWAY INFORMATION NETWORK USING NEURAL-FUZZY MODELS

Purpose. Modern algorithms for choosing the shortest route, for example, the Bellman-Ford and Dijkstra algorithms, which are currently widely used in existing routing protocols (RIP, OSPF), do not always lead to an effective result. Therefore, there is a need to study the possibility of organizing routing in in the railway network of information and telecommunication system (ITS) using the methods of artificial intelligence. Methodology. On the basis of the simulation model created in the OPNET modeling system a fragment of the ITS railway network was considered and the following samples were formed: training, testing, and control one. For modeling a neural-fuzzy network (hybrid system) in the the MatLAB system the following parameters are input: packet length (three term sets), traffic intensity (five term sets), and the number of intermediate routers that make up the route (four term sets). As the resulting characteristic, the time spent by the packet in the routers along its route in the ITS network (four term sets) was taken. On the basis of a certain time of packet residence in the routers and queue delays on the routers making up different paths (with the same number of the routers) the optimal route was determined. Findings. For the railway ITS fragment under consideration, a forecast was made of the packet residence time in the routers along its route based on the neural-fuzzy network created in the MatLAB system. The authors conducted the study of the average error of the neural-fuzzy network`s training with various membership functions and according to the different methods of training optimization. It was found that the smallest value of the average learning error is provided by the neuro-fuzzy network configuration 3–12–60–60–1 when using the symmetric Gaussian membership function according to the hybrid optimization method. Originality. According to the RIP and OSPF scenarios, the following characteristics were obtained on the simulation model created in the OPNET simulation system: average server load, average packet processing time by the router, average waiting time for packets in the queue, average number of lost packets, and network convergence time. It was determined that the best results are achieved by the simulation network model according to the OSPF scenario. The proposed integrated routing system in the ITS network of railway transport, which is based on the neural-fuzzy networks created, determines the optimal route in the network faster than the existing OSPF routing protocol. Practical value. An integrated routing system in the ITS system of railway transport will make it possible to determine the optimal route in the network with the same number of the routers that make up the packet path in real time.

Secure And Efficient Cluster Based Routing Model For Wireless Sensor Network

recently wireless sensor network has be adopted across wide range of application such as Internet of Things (IoT) based healthcare, military domain etc. due to its low cost availability and ease of deployment. For such application efficient secure and energy efficient design is needed. For improving energy efficiency exiting model adopted cluster based routing model. However, it incurs energy overhead among cluster head. Therefore, efficient cluster selection algorithm is needed. This work present an energy efficient cluster selection algorithm using multi-objective function using enhanced Imperialist Competitive Algorithm. Further, for providing secure communication the existing model are designed using asymmetric cryptography such as RSA, and Diffe-Hellman etc. As a result, incurs communication overhead and increase packet processing delay. For overcoming research challenges this work present symmetric Elliptical curve cryptography (ECC model. The proposed secure and efficient symmetric based ECC (SESECC) attained significant performance in terms of communication overhead, packet processing time and lifetime.

Packet Clustering Introduced by Routers

In this article, we investigate a router’s inherent variation on packet processing time and its effect on interpacket delay and packet clustering. We propose a simple pipeline model incorporating the inherent variation, and two metrics—one to measure packet clustering and one to quantify inherent variation. To isolate the effect of the inherent variation, we begin our analysis with no cross traffic and step through setups where the input streams have different data rates, packet size, and go through a different number of hops. We show that a homogeneous input stream with a sufficiently large interpacket gap will emerge at the router’s output with interpacket delays that are negative correlated with adjacent values and have symmetrical distributions. We show that for smaller interpacket gaps, the change in packet clustering is smaller. It is also shown that the degree of packet clustering could in fact decrease for a clustered input. We generalize our results by adding cross traffic. All the results predicted by the model are validated with experiments with real routers. We also investigated several factors that can affect the inherent variation as well as some potential applications of this study.

Maximizing Service Reward for Queues With Deadlines

In this paper, we consider a real-time queuing system with rewards and deadlines. We assume that the packet processing time is known upon arrival, as is the case in communication networks. This assumption allows us to demonstrate that the well-known earliest-deadline-first policy performance can be improved. We then propose a scheduling policy that provides excellent results for packets with rewards and deadlines. We prove that the policy is optimal under deterministic service time and binomial reward distribution. In the more general case, we prove that the policy processes the maximal number of packets while collecting rewards higher than the expected reward. We present simulation results that show its high performance in more generic cases compared to the most commonly used scheduling policies.