Internet Routing Research Articles

Compatibility issues of wireless sensor network routing in internet of things applications

Compatibility issues of wireless sensor network routing in internet of things applications

Compatibility issues of wireless sensor network routing in internet of things applications

Compatibility issues of wireless sensor network routing in internet of things applications

An Optimal Homogenous Stability-Based Disturbance Observer and Sliding Mode Control for Secure Communication System

To prevent the loss of data or distortion of the real sent data in the secure communication, the disturbance and uncertainty rejection is very important technique. Especially, the secure communication of the chaotic system, where the master and slave systems are used to encrypt and decrypt the signal. These systems are should be a chaotic. The chaotic system is unpredictable and unstable. The security is obtained if the master and slave systems are synchronizing. Therefore, this paper proposes a new disturbance observer (DO) for estimating attacked signals on public channels and uncertain values of the secure communication system (SCS). First, a new condition of the reaching law was proposed via a homogenous stability condition, which was used to construct the disturbance observer and synchronization controller. Second, the proposed stability is applied to design a new DO for estimating the attacked signals on the public channels and the variations of the parameters of all master and slave systems (MSSs). Third, the MSSs were synchronized by the sliding mode control (SMC) with the same reaching law with the proposed DO. The calculations of controller and observer designs were based on the Takagi-Sugeno fuzzy (TSF) system, where the MSSs were taken into account as the fuzzy system. However, the TSF was used for calculation only. The original chaotic of MSSs were used to keep the characteristics of the chaos phenomenon. Final, the mathematically proven was provided to show the corrections of the proposed methods. To show the superior powers of the proposed method, the simulation of MATLAB software and experiment of local network via the internet router were used to conduct the logical analysis. The tested disturbances and uncertainties were mostly compensated by the proposed DO.

Performance analysis of an internet router using the Markovian quasi birth and death process

Performance analysis of an internet router using the Markovian quasi birth and death process

Performance analysis of an internet router using the Markovian quasi birth and death process

Performance analysis of an internet router using the Markovian quasi birth and death process

Improvisation of Node Mobility Using Cluster Routing-based Group Adaptive in MANET

In today's Internet routing infrastructure, designers have addressed scaling concerns in routing constrained multiobjective optimization problems examining latency and mobility concerns as a secondary constrain. In tactical Mobile Ad-hoc Network (MANET), hubs can function based on the work plan in various social affairs and the internally connected hubs are almost having the related moving standards where the topology between one and the other are tightly coupled in steady support by considering the touchstone of hubs such as a self-sorted out, self-mending and self-administration. Clustering in the routing process is one of the key aspects to increase MANET performance by coordinating the pathways using multiple criteria and analytics. We present a Group Adaptive Hybrid Routing Algorithm (GAHRA) for gathering portability, which pursues table-driven directing methodology in stable accumulations and on-request steering strategy for versatile situations. Based on this aspect, the research demonstrates an adjustable framework for commuting between the table-driven approach and the on-request approach, with the objectives of enhancing the output of MANET routing computation in each hub. Simulation analysis and replication results reveal that the proposed method is promising than a single well-known existing routing approach and is well-suited for sensitive MANET applications.

BiCAM-based automated scoring system for digital logic circuit diagrams

Abstract In online education, it is critical for the quality of education to evaluate and grade the assignments or examinations that students upload to the system. However, it is time-consuming to determine how well the circuit drawings prepared for the digital logic course, which is a fundamental course in computer engineering and similar disciplines, are not only correct but also compatible with the truth table. Content-addressable memory (CAM), also known as associative memory, is a data storage and retrieval unit. Typically, it is used instead of the conventional memories in fast-paced and time-sensitive applications such as address lookup in Internet routers, databases, and pattern recognition. CAMs implement the search process by comparing the content itself with a key instead of finding the address like the conventional memories. To see the effect of using binary content-addressable memory-based memory on the time spent scoring hand or digital-drawn logic circuits, it is compared with various data structures commonly used in logic simulation programs. I found a significant relationship (O(1)), indicating that the proposed architecture reduces the time complexity in the search process. This expression is the same as time complexity in hash tables.

Maximizing Flow Rates in Multihop Two-Tier IoT Networks With Ambient Backscattering Tags

This article considers routing and link scheduling in a two-tier wireless Internet of Things (IoT) network. The first tier consists of routers that communicate via active radio-frequency (RF) transmissions. The second tier consists of passive tags that backscatter ambient RF signals from routers. Our objective is to maximize the network throughput at both tiers. To this end, we outline a mixed-integer linear program (MILP) that jointly optimizes the active time of RF links and backscatter links, and traffic over links. We also present a heuristic called the algorithm-transmission set generator (ALGO-TSG) to compute transmission sets. Moreover, we also outline a heuristic called centralized max-flow (CMF) to maximize network throughput by jointly considering routing and link scheduling. The results show that: 1) the network throughput achieved by ALGO-TSG at both tiers is 29.80% higher as compared to the case without backscattering and 2) the throughput of CMF is on average 21.36% lower than the throughput computed by MILP.

Design an Optimal Fractional Order PI Controller for Congestion Avoidance in Internet Routers

The main problem that degrade data transition in communication networks is the congestion, to achieve stable TCP network, an active queue management (AQM) is used for controlling congestion and saving regular queue length .In this paper, a robust Fractional Order PI (FOPI) controller is suggested to control the AQM system, Gray Wolf Optimization Algorithm (GWO) is used for tuning of the controller gains and the Integral Time Absolute Error (ITAE) is adopted as a fitness function for monitoring system response by minimizing its error value until reach an efficient and robust response. The transient analysis is used for comparing the suggested controller with two conventional controllers (PI & PID) to show the efficient behavior of suggested controller, then a robustness analysis is applied by adding disturbances positive and negative signals with value 150 packets at different time(15 sec, 30 sec) to the system also varying the queue size after each 40 sec to see the system response , the controller overcomes the disturbances signals with less than 3.5 sec and faces the queue size varying values and returning the system response to its desired value efficiently.

BGP2Vec: Unveiling the Latent Characteristics of Autonomous Systems

BGP announcements hold latent information about the Internet Autonomous Systems (ASes) and their functional position within the Internet eco-system. This information can aid us in understanding the Internet structure and also in solving many practical problems. In this paper, we present BGP2Vec, a novel approach to revealing the latent characteristics of ASes using neural-network-based embedding. We show that our embedding indeed captures important characteristics of ASes, and then show how the embedding can be used to solve two problems: ASN business-type classification and AS Type of Relationships (ToRs) inference. ToRs inference has been heavily studied in the past two decades and is important for studying Internet routing and identifying IP hijack attacks. We use the BGP2Vec vectors as an input to artificial neural networks and achieve excellent results: an accuracy of 95.8% for ToR classification and an accuracy of 79.2% for AS classification.

Dingo Optimization Based Cluster Based Routing in Internet of Things.

The Wireless Sensor Network (WSN) is a collection of distinct, geographically distributed, Internet-connected sensors, which is capable of processing, analyzing, storing, and exchanging collected information. However, the Internet of Things (IoT) devices in the network are equipped with limited resources and minimal computing capability, resulting in energy conservation problems. Although clustering is an efficient method for energy saving in network nodes, the existing clustering algorithms are not effective due to the short lifespan of a network, an unbalanced load among the network nodes, and increased end-to-end delays. Hence, this paper proposes a novel cluster-based approach for IoT using a Self-Adaptive Dingo Optimizer with Brownian Motion (SDO-BM) technique to choose the optimal cluster head (CH) considering the various constraints such as energy, distance, delay, overhead, trust, Quality of Service (QoS), and security (high risk, low risk, and medium risk). If the chosen optimal CH is defective, then fault tolerance and energy hole mitigation techniques are used to stabilize the network. Eventually, analysis is done to ensure the progression of the SADO-BM model. The proposed model provides optimal results compared to existing models.

Access Convergence for Heavy Load Markov Ethernet Bursty Traffic Using Two-level Statistical Multiplexing

A method for modeling aggregated heavy Markov bursty Ethernet traffic from different sources is proposed in this paper, particularly that prevailing between gateway services and internet routing devices, with the aim of achieving rate accommodation. In other words, to accommodate different rates while filtering out delays in the queue, to achieve access network convergence. Although gateway functions can be used to achieve this by adapting service rates, as many gateways as services are required. Instead of considering the distributed gateway services method, statistical multiplexing is chosen for this study for cost efficiency in network resources. Unfortunately, statistical multiplexing exhibits greater packet variation (jitter) and transfer delay. These delays, basically resulting from positive correlations or time dependency in the queue system, are addressed through infinitesimal queue modeling, based on the diffusion process approximated by Ornstein-Uhlenbeck, which deals with infinitesimal changes in the Markov queue. The related analysis has resulted in an exponential queueing model for univariate and/or multivariate servers obtained through Markov Gaussian approximation. An experiment based on two different voice algorithms shows rate accommodation, and a fluid solution, which is dynamically outputted according to the transmission link availability during each transition time, without any significant delay. Hence, better transfer delay and rate control is obtained through the proposed two multiplexing levels within an Ethernet LAN

Designing and developing IoT based security system for smart home

This paper represents Internet of Things (IoT) based security system for smart home. As technology has progressed and the use of IoT has grown, digital door locks have become increasingly common. Door Security System application uses ESP8266 and IoT technology to monitor the status of the door. Blynk is a communication protocol that allows a smartphone to communicate with a door lock system. The Door Security System is available on Android and iOS. With this automation system, users may utilize an IR (Infrared remote) remote to manage their home security system from afar. We attempted to connect door security system in our home. Obviously, we will be able to solve that problem in the future. WiFi modules connect to our home internet router and link to our IoT server. Our Android and Web applications communicate with the server as well. This program allows users to check the current state of their home appliances and control them from anywhere. Also MQ3 indicates higher overall performance than the MQ2 in phrases of distance and reaction time.

Edge-Based Optimal Routing in SDN-Enabled Industrial Internet of Things

The efficiency of communication between devices in any network depends on the network architecture and the routing algorithms. This efficiency vastly affects the productivity of the Internet of Things (IoT) nodes when utilized in an industrial environment. The conundrum of using the conventional network architecture in an industry/factory connected by IoT devices has paved the way for the development of software-defined networking (SDN). Traditional network architectures lack network programmability and hinder the testing and performance evaluation of new communication protocols. The use of vendor-specific hardware is a major hindrance to create a network where the control is centralized for the deployment of different policies over the network. This article aims to find an optimal path for efficient communication between the nodes present in a programmable Industrial IoT (IIoT) network. A programmable IIoT network is created and end-user routing algorithms are designed to find the optimal path for communication. We integrate an SDN framework with IIoT nodes for the creation of a centralized programmable network architecture and deploy custom routing algorithms over it for evaluation. To further reduce the communication latency, we incorporate edge computing servers (ECSs) in the network. Three routing algorithms: 1) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -means-based optimal path algorithm; 2) cluster-based optimal path algorithm; and 3) minimum interval-based optimal path algorithm, that can be deployed over an SDN are proposed in this article. Experimental results reveal that the proposed algorithms are more efficient than the existing algorithms.

Improved random early detection congestion control algorithm for internet routers

In the internet, router plays a strategic role in the transmission of data packets. Active queue management (AQM) aimed at managing congestion by keeping a reduced average buffer occupancy and hence a minimal delay. The novel random early detection (RED) algorithm suffers from large average buffer occupancy and delay shortcomings. This problem is due in part to the existence of a distinctive linear packet drop function it deploys. In this paper, we present a new version of RED, called improved RED (IMRED). An important strategy of IM-RED is to deploy two dropping functions: i) nonlinear (i.e. quadratic) to deal with both light-and moderatenetwork traffic load conditions, and ii) linear to deal with heavy traffic load condition. Simulation experiments conducted using open-source ns-3 software to evaluate and compare the functionality of the proposed IM-RED with other two previous AQM algorithms confirmed that IM-RED reduces the average buffer occupancy and obtained an improved delay performance especially at heavy network traffic load scenario. Very fortunately, since RED algorithm is known to appear as a built-in model in ns-3 and even Linux kernel, its implementation can therefore be leveraged to obtain IMRED while only adjusting the packet dropping probability profile and holding on to its other attributes.

RouteChain: Towards Blockchain-based secure and efficient BGP routing

Routing on the Internet is defined among autonomous systems (ASes) based on a weak trust model where it is assumed that ASes are honest. While this trust model strengthens the connectivity among ASes, it also results in an attack surface that can be exploited to hijack the routing paths. One such attack is known as the BGP prefix hijacking, in which a malicious AS broadcasts IP prefixes that belong to a target AS, thereby hijacking its traffic. In this paper, we propose RouteChain: a blockchain-based secure BGP routing system that counters BGP hijacking and maintains a consistent view of the Internet routing paths. Towards that, we leverage provenance assurance and tamper-proof properties of blockchains to augment trust among ASes. We group ASes based on their geographical (network) proximity and construct a bi-hierarchical blockchain model that detects false prefixes prior to their spread over the Internet. We evaluate RouteChain using three different consensus protocols and show its effectiveness by drawing a case study with the Youtube hijacking of 2008. Our results show that RouteChain can efficiently detect false prefix announcements and prevent BGP attacks over the Internet.

Visualizing connections: University campus and social infrastructure

As a social infrastructure, the material substrates of a campus intertwine with the sociabilities it supports. Intending to identify the integration potential between a Brazilian public university campus and its surrounding neighborhoods, we mapped the campus’ social infrastructures and identified through diagrammatic studies its morphological dimensions. Internet routers distributed on the university campus provided georeferenced data of the human dynamics on campus. Counting user connections in groups of access points, we obtained the population density of the potential social infrastructure use. Afterward, associating Wi-Fi data and typological information, we traced itineraries that connect these infrastructures. The results encompass a systemic view that highlights the campus’ potential to develop sociability within a complex service network. Furthermore, through new readings of the social infrastructures, we suggest alternative potential uses. These results highlight the hybrid methodologies that associate objective characteristics of the built environment with data-driven methodologies, such as Wi-Fi-generated datasets.

TSN-based routing and scheduling scheme for Industrial Internet of Things in underground mining

Recently, there has been a growing interest in Time-Sensitive Networking (TSN) research in the Industrial Internet of Things(IIoT). The research on real-time and reliable IIoT transmission technology based on TSN has received extensive attention. Especially in some industrial scenarios, such as the safety monitoring of the underground construction environment, the real-time and reliability of data transmission is very important due to the long tunnel and complex structure in underground mining. It is a huge challenge to ensure that the data collected by the sensor has a slight end-to-end delay to the receiving end. A routing scheduling method is proposed based on TSN for IIoT applications in underground mining. Firstly, according to the characteristics of large-scale and distributed hybrid topology in mines and the delay constraints of TSN, the multi-hop routing cooperative scheduling problem S is defined. It is proved that the problem is NP-Hard. Secondly, two algorithms are proposed for problem S: (1) greedy algorithm based on local shortest delay; (2) heuristic algorithm based on an ant colony. Finally, a comparative experimental analysis of the proposed algorithm is carried out, proving that this paper’s algorithm performs better in terms of delay and jitter.

Trust and Mobility-Based Protocol for Secure Routing in Internet of Things.

In the Internet of Things (IoT), the de facto Routing Protocol for Low Power and Lossy Networks (RPL) is susceptible to several disruptive attacks based on its functionalities and features. Among various RPL security solutions, a trust-based security is easy to adapt for resource-constrained IoT environments. In the existing trust-based security for RPL routing attacks, nodes’ mobility is not considered or limited to only the sender nodes. Similarly, these trust-based protocols are not evaluated for mobile IoT environments, particularly regarding RPL attacks. Hence, a trust and mobility-based secure routing protocol is proposed, termed as SMTrust, by critically analysing the trust metrics involving the mobility-based metrics in IoT. SMTrust intends to provide security against RPL Rank and Blackhole attacks. The proposed protocol is evaluated in three different scenarios, including static and mobile nodes in an IoT network. SMTrust is compared with the default RPL objective function, Minimum Rank with Hysteresis Objective Function (MRHOF), SecTrust, DCTM, and MRTS. The evaluation results indicate that the proposed protocol outperforms with respect to packet loss rate, throughput, and topology stability. Moreover, SMTrust is validated using routing protocol requirements analysis to ensure that it fulfils the consistency, optimality, and loop-freeness.

Fast Conflict Detection for Multi-Dimensional Packet Filters

To support advanced network services, Internet routers must perform packet classification based on a set of rules called packet filters. If two or more filters overlap, a filter conflict will occur and lead to ambiguity in packet classification. Further, it may affect network security or even the correctness of packet routing. Hence, it is necessary to detect conflicts to avoid the above problems. In recent years, many conflict detection algorithms have been proposed, but most of them detect conflicts for only prefix fields (i.e., source/destination IP address fields) of filters. For greater practicality, conflict detection must include non-prefix fields such as source/destination IP port fields and the protocol field. In this study, we propose an efficient conflict detection algorithm for five-dimensional filters, which include both prefix and non-prefix fields. In the proposed algorithm, a tiny lookup table is created for quickly filtering out a large portion of non-conflicting filter pairs, thereby reducing the overall conflict detection time. Experimental results show that our algorithm reduces the detection time by 10% to 28% compared with other conflict detection algorithms for 20 K filter databases. More importantly, our algorithm can be used to extend any existing conflict detection algorithms for two-dimensional filters to support fast conflict detection for five-dimensional filters.