Routing Network Research Articles

Analysis of computer virus propagation behaviors over complex networks: a case study of Oregon routing network

This paper mainly aims to explore the propagation behaviors of computer virus over complex networks under the combined effects of network topology and removable storage media. To this end, a dynamical model is established and analyzed theoretically, including the outbreak threshold, equilibria and their global dynamics. It is found from the systematic analysis that the virus will die out or persist in the network depending on the outbreak threshold, which is associated with the network topology and removable storage media. Moreover, a set of well-designed experiments are performed over the Oregon routing network to verify the proposed model and its theoretical analysis results. Experimental results show that the predicted results of the model are in good agreement with the simulation results over the above network, and the removable storage media have a great effect on viral spread. To this regard, some preventive measures against virus infection are recommended.

Software defined network emulation with OpenFlow protocol

In software defined network the network infrastructure layer where the entire network devices, like switches and routers reside is connected with the separate controller layer with the help of standard called OpenFlow. The open flow standard enables different vendor devices like juniper, cisco and Huawei switch to connect to the controller or a software program. The software program controls and manages the network devices. Therefore, software defined network architecture makes the network flexible, cost effective and manageable, enables dynamic provisioning of bandwidth, dynamic scale out and dynamic scale in compared to the traditional network. In this study, the architectures and principles of software defined network is explored by emulating the software defined network employing a mininet.

IoT 홈 허브 및 장치에서 무선 공유기 네트워크 설정을 위한 반응형 웹 사용자 인터페이스 서비스 제공 방법

사물 인터넷 (Internet of Things: IoT) 장치는 인터넷에 연결되어 서버와 통신을 하게 된다. 사물에 부착된 센서로부터 정보를 얻기 위해 고사양의 와이파이, 하드웨어와 소프트웨어로 구성된 라즈베리 플랫폼을 사용하는 것이 일반적이다. 본 논문에서는 가격이 저렴하고 대중적인 WiFi system on chip (SoC)에서 사용자가 손쉽게 IoT 장치를 공유기에 접속하는데 hypertext markup language version 5 (HTML5), IoT oriented representational state transfer (REST) protocol, Inline JavaScript, document object model (DOM) 및 Inline cascading style sheets (CSS)를 이용한 반응형 웹 사용자 인터페이스 서비스 제공 방법을 제안한다. 이 방법은 IoT 시스템을 구성하는데 있어 최소 비용으로 사용자 편의 인터페이스 제공하는 장점이 있으며, artificial intelligence (AI) IoT 서비스를 위한 제어기와 센서에 최적의 장치 설계 방법이 될 수 있다.

Optimized evolutionary algorithm and supervised ACO mechanism to mitigate attacks and improve performance of adhoc network

Optimization is the procedure of discovering optimal solution or results under particular circumstances. Typically, optimization is utilized for maximization or minimization of values of functions; it can be local or global optima. Discovering exact solutions to the issues is NP-hard. This type of complicated issue needs exponential quantities of computation power as well as item and quantity of decision parameters rise. For overcoming the issues, research scholars have suggested Evolutionary Algorithm (EA) protocols as a way for searching near-optimal solutions. In this work, Ant Colony Optimization (ACO) is used combined with the power of faith on effective factors in distance of trustworthy optimum routing in WSN. ACO has its basis in the foraging behavior of ants who look for the shortest route between then nest and the food source. The energy efficient node random trust based on routing network is designed in a safe and random routing mode that reveals all fingerprints and useful load distribution. The details are combined with confidence choices, using a modified ACO algorithm. The ACO application, makes this method a stronger and faster with a metaheuristic algorithm compared with the other routing methodologies. Modified ACO method, exercise as a parameter for calculating the energy levels of terminals used fitness route planning its organization. Proposed work shows improvement in the network performance under Dos and DDoS attack in terms of amount of data loss, data delay.

Influential Nodes Identification in Complex Networks via Information Entropy.

Identifying a set of influential nodes is an important topic in complex networks which plays a crucial role in many applications, such as market advertising, rumor controlling, and predicting valuable scientific publications. In regard to this, researchers have developed algorithms from simple degree methods to all kinds of sophisticated approaches. However, a more robust and practical algorithm is required for the task. In this paper, we propose the EnRenew algorithm aimed to identify a set of influential nodes via information entropy. Firstly, the information entropy of each node is calculated as initial spreading ability. Then, select the node with the largest information entropy and renovate its l-length reachable nodes’ spreading ability by an attenuation factor, repeat this process until specific number of influential nodes are selected. Compared with the best state-of-the-art benchmark methods, the performance of proposed algorithm improved by 21.1%, 7.0%, 30.0%, 5.0%, 2.5%, and 9.0% in final affected scale on CEnew, Email, Hamster, Router, Condmat, and Amazon network, respectively, under the Susceptible-Infected-Recovered (SIR) simulation model. The proposed algorithm measures the importance of nodes based on information entropy and selects a group of important nodes through dynamic update strategy. The impressive results on the SIR simulation model shed light on new method of node mining in complex networks for information spreading and epidemic prevention.

Employing a Machine Learning Approach to Detect Combined Internet of Things Attacks against Two Objective Functions Using a Novel Dataset

One of the important features of routing protocol for low-power and lossy networks (RPLs) is objective function (OF). OF influences an IoT network in terms of routing strategies and network topology. On the contrary, detecting a combination of attacks against OFs is a cutting-edge technology that will become a necessity as next generation low-power wireless networks continue to be exploited as they grow rapidly. However, current literature lacks study on vulnerability analysis of OFs particularly in terms of combined attacks. Furthermore, machine learning is a promising solution for the global networks of IoT devices in terms of analysing their ever-growing generated data and predicting cyberattacks against such devices. Therefore, in this paper, we study the vulnerability analysis of two popular OFs of RPL to detect combined attacks against them using machine learning algorithms through different simulated scenarios. For this, we created a novel IoT dataset based on power and network metrics, which is deployed as part of an RPL IDS/IPS solution to enhance information security. Addressing the captured results, our machine learning approach is successful in detecting combined attacks against two popular OFs of RPL based on the power and network metrics in which MLP and RF algorithms are the most successful classifier deployment for single and ensemble models.

On weak Pareto optimality of nonatomic routing networks

This paper establishes several sufficient conditions for the weak Pareto optimality of Nash equilibria in nonatomic routing games on single- and multi-commodity networks, where a Nash equilibrium (NE) is weakly Pareto optimal (WPO) if under it no deviation of all players could make everybody better off. The results provide theoretical and technical bases for characterizing graphical structures for nonatomic routing games to admit WPO NEs. We prove that the NE of every nonatomic routing game on a single or multi-commodity network is WPO (regardless of the choices of nonnegative, continuous, nondecreasing latency functions on network links) if the network does not have two links x, y and three paths each of which goes from some origin to some destination such that the intersections of the three paths with $$\{x,y\}$$ are $$\{x\},\{y\}$$ and $$\{x,y\}$$, respectively. This sufficient condition leads to an alternative proof of the recent result that the NE of every 2-commodity nonatomic routing game on any undirected cycle is WPO. We verify a general property satisfied by all feasible 2-commodity routings (not necessarily controlled by selfish players) on undirected cycles, which roughly says that no feasible routing can “dominate” another in some sense. The property is crucial for proving the weak Pareto optimality associated to the building blocks of undirected graphs on which all NEs w.r.t. two commodities are WPO.

Abstract P6-11-12: Access to certified breast cancer centers in the mainly rural state of Bavaria, Germany: A structural health geographical analysis

Abstract Background: In Germany, evidence- and consensus-based recommendations for the treatment of breast cancer patients are available from the national guideline. To ensure implementation of these standards in clinical routine care, two different certification programs for breast cancer exist in Germany: 1) accreditation ‘Organ Cancer Center’ of the German Cancer Society (“Deutsche Krebsgesellschaft” DKG); 2) Disease Management Program (DMP) developed by Health Insurance Companies. For our analysis we focused on Bavaria due to its mainly rural character, which can lead to challenges in patients’ medical supply with long travel distances. We aimed to investigate the accessibility of certified Breast Cancer Centers (cBCC) in rural and urban areas of Bavaria and to estimate how many inhabitants and potentially breast cancer patients might be affected. Methods: Accessibility of cBCC was defined according to travel time by car (or taxi) within 30 minutes. Addresses of cBCCs were identified through the homepages of the DKG, the Bavarian Association of Statutory Health Insurance Physicians (KVB), and a health insurance company. Data collection took place between August and December 2018. Only cBCC located in Bavaria with valid certification at point of search were eligible. Using ArcGIS, a routing network was created to identify clear catchment areas for each facility. The modeled speeds on which the traffic is based are street specific and consider the average regional traffic situations. The latter was then combined with the disaggregated 100 × 100 meters population data for the Census 2011, which allowed analyzing absolute population on a fine spatial resolution. Aggregated data on incident and prevalent breast cancer rates (women only) were obtained from the Epidemiological Bavarian Cancer Registry and merged on district level. As only aggregated data from the Bavarian Cancer Registry were utilized, a formal ethics committee (EC) review was not required. A declaration of no objection by the EC of the University of Würzburg is available (#2019042402). Results: A total of 58 cBCC (both DKG/DMP: n=44, DMP only: n=14) were identified and included in our analysis. The predefined accessibility coverage comprises 76% of Bavaria. Focusing on all Bavarian administrative areas (n=96) we identified following categories: n=38 had full access, n=56 partial access and n=2 no access. On population level, n=5,533,166 (87.5%) females reach a cBCC within 30min travel time. Whereas about 800.000 (12.5%) women have hampered access with about 3/4 living in rural regions. Data from the Bavarian Cancer Registry reveal that non-accessibility might affect ca. 5.000 prevalent and ca. 1.500 newly-diagnosed female breast cancer patients - based on a hypothetical stable age-standardized (EU) incidence and 5-yrs prevalence rate. Conclusion: Our analysis revealed that there is no Bavaria-wide accessibility to cBCC and that disparities between rural and urban areas exist. Integrating GIS methods to health care service research allows 1) identifying regions with limited access to evidence-based structures (e.g. cBCC) and 2) planning of structures needed from a public health point of view. Our findings can be used to inform policy makers about injustice regarding health care accessibility. Furthermore, results can serve for developing and evaluating telemedical strategies to deliver high quality health care to all inhabitants regardless of residence. Citation Format: Stephanie Stangl, Sebastian Rauch, Jürgen Rauh, Martin Meyer, Jacqueline Müller-Nordhorn, Manfred Wildner, Peter U. Heuschmann, Achim Wöckel. Access to certified breast cancer centers in the mainly rural state of Bavaria, Germany: A structural health geographical analysis [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-11-12.

A hybrid link protection scheme for ensuring network service availability in link-state routing networks

The internet is playing an increasingly crucial role in both personal and business activities. In addition, with the emergence of real-time, delay sensitive and mission-critical applications, stringent network availability requirement is put forward for internet service providers (ISPs). However, commonly deployed intradomain link-state routing protocols react to link failures by globally exchanging link state advertisements and recalculating routing table, inevitably causing significant forwarding discontinuity after a failure. Therefore, the loop-free criterion (LFC) approach has been widely deployed by many ISPs for coping with the single network component failure scenario in large internet backbones. The success of LFC lies in its inherent simplicity, but this comes at the expense of letting certain failure scenarios go unprotected. To achieve full failure coverage with LFC without incurring significant extra overhead, we propose a novel link protection scheme, hybrid link protection (HLP), to achieve failure resilient routing. Compared to previous schemes, HLP ensures high network availability in a more efficient way. HLP is implemented in two stages. Stage one provides an efficient LFC based method (MNP-e). The complexity of the algorithm is less than that of Dijkstra's algorithm and can provide the similar network availability with LFC. Stage two provides backup path protection (BPP) based on MNP-e, where only a minimum number of links need to be protected, using special paths and packet headers, to meet the network availability requirement. We evaluate these algorithms in a wide spread of relevant topologies, both real and synthetic, and the results reveal that HLP can achieve high network availability without introducing conspicuous overhead. HLP not only needs around 10% time of that of full protection, but also provides full protection capabilities that full protection provide.

Development of an Efficient Router Based on Network on Chip Network

A reconfigurable VLSI architecture for router is the main solution for communication interface quality of service go flexibility of network, cost of chip .The proposed architecture dynamically configure itself with respect to hardware modules such as packet based switch, router and data packet size by changing the conditions of communication and it's requirement at run time .In network on chip were using extended XY algorithm to improve performance of communication. The proposed design work avoids the dead lock and data loss in the path with the help of this design we can achieve high Data through put and low latency .in this paper we are receiving the previous method and approaches of dynamic reconfigurable router in network on chip

Design of Priority Based Reconfigurable Router in Network on Chip

Network on Chip (NoC) is an advanced integration design for communication networks and used as modules in System on Chip (SoC) designs. It provides the solution to the problem of traditional bus based SoC. A router is a key component which is considered as backbone of communication in NoC .The objective is to design a priority based reconfigurable router. Initially a 4x4 VLSI router is designed and synthesised, then the channels inside the router are modified to achieve reconfiguration in order to improve the efficiency of the router. In 4x4 Reconfigurable Router the slots are well utilized but prioritization was not considered. Since routers are associatedwith switches to take data transfer decisions and results in high power consumption. In order to overcome this problem, new priority based reconfigurable router is designed. The design entry for router is done using Verilog HDL, The design is synthesized and simulated using Xilinx ISE Design Suite 14.3 & ModelSim -Altera 6.5b software respectively and the corresponding results in terms of power and delay are analysed.

Hose-model network virtualization in flexgrid optical networks

Network virtualization, which can flexibly and efficiently embed multiple client networks to a substrate network, is one of the most promising technologies to address the ossification problem of Internet infrastructure. This work focuses on studying the problem of hose-model network virtualization in general topology flexgrid optical networks. A mathematical model for this problem is presented, which integrates hose-model traffic routing and virtual network mapping into a unified integer linear programming (ILP) formulation. Considering the computational difficulty of an ILP algorithm, four heuristic algorithms are presented. They first optimize and allocate link bandwidths to transport hose-model traffic in the virtual network; second, the derived virtual network is mapped in a substrate flexgrid optical network, in which a virtual link is mapped to one or multiple optical connections with or without grooming being allowed. The performance of the mapping success rate and time-average revenue for these algorithms is assessed by extensive simulation.

Congestion-Aware and Energy-Aware Virtual Network Embedding

Network virtualization is an inherent component of future internet architectures. Network resources are virtualized from the underlying substrate and elastically provisioned and offered to customers on-demand. Optimal allocation of network resources in terms of utilization, quality of service, and energy consumption has been a challenge. Existing solutions consider congestion control in a single-objective virtual network embedding (VNE) problem. This paper defines a multiple-objective VNE problem called the congestion-aware, energy-aware VNE (CEVNE). The aim is to seek a solution that saves cost, saves energy and avoids network congestion simultaneously. CEVNE modelling techniques and solution approaches apply both the weighting method and the constraint method to search for pareto-optimal solutions that produce the best compromised solutions for all three objectives. Solving VNE problem is, however, NP-hard. A heuristic solution is proposed involving a two-stage coordinated CEVNE. The node-mapping algorithm searches for the sub-optimal solutions for three objectives. The link mapping process is an SDN-based heuristic algorithm that deploys a path service and a resource monitoring application on an SDN controller. The solution is realized using SDN, Segment Routing, and open network operating system platform (ONOS) technologies. The energy minimization is implemented with a registry that keeps track of active nodes and sets inactive nodes to sleep mode. The evaluation results showed that the multiple-objective CEVNE approach is feasible and achieves its goals of optimizing the resource allocation, improving the runtime, saving the energy consumption and controlling the network congestion.

Uncertainty in Multicommodity Routing Networks: When Does It Help?

We study the equilibrium behavior in a multi-commodity selfish routing game with many types of uncertain users where each user over- or under-estimates their congestion costs by a multiplicative factor. Surprisingly, we find that uncertainties in different directions have qualitatively distinct impacts on equilibria. Namely, contrary to the usual notion that uncertainty increases inefficiencies, network congestion actually decreases when users over-estimate their costs. On the other hand, under-estimation of costs leads to increased congestion. We apply these results to urban transportation networks, where drivers have different estimates about the cost of congestion. In light of the dynamic pricing policies aimed at tackling congestion, our results indicate that users' perception of these prices can significantly impact the policy's efficacy, and "caution in the face of uncertainty" leads to favorable network conditions.

Design and Implementation of Arduino-Based Weather Monitoring System in Rural

The Weather Monitoring System is an instrument that measures and records meteorological parameters using sensors. This sensor serves as a measuring instrument to measure every change in weather. Output data from sensors will be sent to the web server so that it can be accessed by users or people who need weather data. Weather data obtained from temperature sensors, air humidity, wind direction and speed, and air pressure are processed by the microcontroller and sent to the web server via cellular networks. The data displayed on the web server is a graph according to the value sent by the sensor. This study began a literature study on Arduino Uno, Ethernet shield, BMP180 sensor sensor, DHT11 sensor, wind direction and speed kit, Wifi Router, 3G network modem, equipment that will be realized starting with designing and making hardware and software. Tests carried out in the telecommunications system laboratory include testing air pressure with the BMP180 Sensor, testing temperature and humidity with the DHT11 Sensor, testing kits for wind speed and direction, testing data delivery with the Wifi Router and 3G network modem, and testing all devices. From the system design and testing concluded that the Arduino-based Automatic Weather Monitoring Device on 3G Cellular Networks has good flexibility and precision because the devices can be placed in various places, especially in rural areas. Data Output from sensors can be monitored through the Thingspeak.com website, so users do not need to directly monitor where the device is placed.

ANCAMAN KEAMANAN JARINGAN PADA SERVER UNTUK MEMBATASI WEBSITE TERTENTU MENGGUNAKAN MIKROTIK

<p><em>Mikrotik RouterOs ™ is an operating system and software that can be used to make a computer a reliable network router, designed to provide convenience for its users, the administration can be done through Windows application (Winbox), The server is a computer system that provides certain types of services (services) in a computer network, the server is supported by a processor that is scalable and a large ram is also equipped with a special operating system, called a (network operating system). The internet provides a lot of useful content if the user uses the internet well, besides that the<strong> </strong>internet can also have a negative impact on its users if the internet is used for negative things which will affect the young generation who will embrace this country to be the successor of this nation. outside the prevailing norms. Today the internet has many different types of social networking sites that have been used by many people, the goal or One of the solutions is that internet users do not access the negative or self-detrimental effects, using the Scientific of Inquiry method by limiting access to websites Specifically for prevention efforts in accessing negative internet sites in this case containing pornographic content is by blocking these negative sites permanently using a web proxy that serves to block some websites that cannot be accessed by clients through a browser on the Mikrotik Faculty of Engineering routers Ibn Khaldun Universit</em></p>

Optimal Distribution of Spiking Neurons Over Multicore Neuromorphic Processors

In a multicore neuromorphic processor embedding a learning algorithm, a presynaptic neuron is occasionally located in a different core from the cores of its postsynaptic neurons, which needs neuron-to-target core communication for inference through a network router. The more neuron-to-target core connections, the more workload is imposed on the network router, which the more likely causes event routing congestion. Another significant challenge arising from a large number of neuron-to-core connections is data duplication in multiple cores for the learning algorithm to access the full data to evaluate weight update. This data duplication consumes a considerable amount of on-chip memory while the memory capacity per core is strictly limited. The optimal distribution of neurons over cores is categorized as an optimization problem with constraints, which may allow the discrete Lagrangian multiplier method (LMM) to optimize the distribution. Proof-of-concept demonstrations were made on the distribution of neurons over cores in a neuromorphic processor embedding a learning algorithm. The choice of the learning algorithm was twofold: a simple spike timing-dependent plasticity learning rule and event-driven random backpropagation algorithm, which are categorized as a two- and three-factor learning rule, respectively. As a result, the discrete LMM significantly reduced the number of neuron-to-core connections for both algorithms by approximately 55% in comparison with the number for random distribution cases, implying a 55% reduction in the workload on the network router and a 52.8% reduction in data duplication. The code is available on-line (https://github.com/guhyunkim/Optimize-neuron-distribution).

An Energy Balanced Routing Hole and Network Partitioning Mitigation Model for Homogeneous Hierarchical Wireless Sensor Networks

This article addresses the challenges of routing hole and network partitioning often experienced in hierarchical wireless sensor networks (WSNs). This developed model classifies network nodes into sets for effective energy management and formulates two cluster networks namely: switching and non-switching networks. Both networks are considered homogeneous and static WSNs and adopted approaches of residual energy, multi-hop and minimal distance as routing decision parameters. The switching network in addition introduces an energy switching factor as a major decision parameter for the switching of cluster head roles amongst cluster nodes. Network simulation was done using Truetime 2.0 and energy dissipation of the respective nodes and cluster heads was observed against a threshold. Results showed the introduction of the energy switching factor gave a significant energy balancing effect as nodes exhibited uniform energy dissipation. Furthermore, the residual energies for most nodes were above the threshold eliminating the possibility of the presence of routing hole and network partitioning.

A Fine-Grained Source-Throttling Method for Mesh Architectures

Source-throttling algorithms aim at adjusting network load appropriately so that high network throughput can be maintained and latency can be decreased efficiently. One challenge of designing a source-throttling algorithm is how to precisely evaluate network congestion status. State-of-the-art source-throttling algorithms for mesh-connected network-on-chip usually evaluate congestion status of the whole network or only that of neighbor routers. They usually appear empirical or locally-greedy. To avoid such problems, we propose a fine-grained source-throttling algorithm. Our main contributions are: 1, we can quantify the impact of throttling action on network routers; 2, we can monitor network traffic more intelligently compared with previous work, only the routers that are most affected by the source's throttling action are used to evaluate congestion status of the RSD network. Based on such measures, most throttling parameters shall not be empirically set but be precisely figured out by a smarter searching algorithm of finding anchor routers as the throttling baseline. Thus, it can solve over-throttling and under-throttling problems more precisely. Time complexity of proposed method is only O(M * N) (M*N is the scale of 2D mesh network). Simulation results show that it has higher throughput, lower fluctuation and lower latency than source-throttling algorithms with empirical parameters such as INC and self-tuned technologies under different network scenarios.

A Re-Ranking Algorithm for Identifying Influential Nodes in Complex Networks

Influential nodes in complex networks play more significant role than other nodes in many applications such as viral marketing. Identification of the most influential nodes and ranking them based on their spreading ability is a hot topic in the field of complex networks. However, when selecting a set of influential nodes, we need to consider the mutual influence between the nodes, rather than simply selecting nodes with strong influence. And how to select the initial node set to maximize the spreading scale after the propagation process has become a challenging issue. In this paper, based on node ranking methods, a novel re-ranking algorithm Re-rank by Information Spreading Function (RINF) is proposed to identify a set of influential nodes in complex networks. For each step in the proposed algorithm, select the node with the highest score, and then update scores of nodes based on local paths of the selected node with the help of information spreading probability function INF. The effectiveness of proposed algorithm is evaluated by Susceptible-Infected-Recovered (SIR) model. Compared with original methods, the performance of re-ranked versions of corresponding methods has increased from 3.1% to 61.1%. Compared with the best result of all benchmark methods, the performance of PageRank_INF (PageRank after re-ranking) improved by 2.9%, 1.4%, 1.5%, 3.6%, 3.2%, and 3.4% on BA, Jazz, PGP, Sex, USAir and Router network, respectively. Experimental results show that the proposed algorithm can well identify influential nodes in complex networks.