Minimum Network Research Articles

Hybrid fat-tree: Extending fat-tree to exploit optical switch transparency with WDM

Abstract Data center networks are the underlying infrastructure supporting the exponential growth of cloud services. Several data center network architectures based on electronic switches or on a combination of electronic and optical switches have been suggested in order to cope with ever-increasing demands. However, a common analytic model describing the network architectures in terms of servers, switches, transceivers, and fibers is lacking. Hence, a true comparison of the scaling in power consumption and cost between different topologies is difficult. This work presents a mathematical framework defining electronic and hybrid topologies under the same model parameters. It explores how the introduction of wavelength-division multiplexing (WDM) and optical switches in Fat-Tree like topologies impact their scaling. We find that these technologies reduce the required number of switches by 45%, transceivers by 60%, and fibers by 50% in the minimum hybrid networks. In such networks, our real case scenario study based on 25G technologies available at present predicts power savings of at least 55% and cost savings of at least 48%. On top of that, larger savings are foreseen when increased port-density transceivers become available.

A new procedure using network analysis and kernel density estimations to evaluate the effect of urban configurations on pedestrian mobility. The case study of Vitoria –Gasteiz

Walking as a stand-alone transport mode has recently been the focus of attention by researchers, urban planners and the public. The reasons are multiple and involve health, economic, social and environmental issues. City planners are implementing new urban configurations aimed at providing global solutions for environmental and mobility challenges by improving the availability and quality of the public space for walking. The aim of this paper is to provide a procedure to evaluate the impact of obstacles to pedestrian mobility and walkability —understanding obstacles as street crossings where pedestrians must wait to continue their route. The procedure combines the calculation of travel time on minimum cost routes and network kernel density estimations. The implementation of a new urban configuration in a medium sized city in northern Spain —the superblocks model in Vitoria-Gasteiz city— serves as a case study. The main results show that the implementation of the superblocks reduces pedestrian travel times by approximately 4–5%, and that the greatest improvements in pedestrian mobility due to the reduction of obstacles are found in areas in the city centre or in streets linking important residential areas with the centre. The procedure has been demonstrated to be useful for urban and transport planners to identify priority areas of action and to evaluate pedestrian movements and walkability under new urban configurations.

Zero-queue ethernet congestion control protocol based on available bandwidth estimation

Router's switch fabric has strict characteristics in terms of packet loss, latency, fairness and head-of-line (HOL) blocking. Network manufacturers address these requirements using specialized, proprietary and highly expensive switches. Simultaneously, IEEE introduces Data Center Bridging (DCB) as an enhancement to existing Ethernet bridge specifications which include technological enhancements addressing packet loss, HOL blocking and latency issues. Motivated by DCB enhancements, we investigate the possibility of using Ethernet commodity switches as a switch fabric for routers. Thereby, we present Ethernet Congestion Control Protocol (ECCP) that uses Ethernet commodity switches to achieves flexible and cost-efficient switch fabric, and fulfills the strict router characteristics. Furthermore, we present a mathematical model of ECCP using Delay Differential Equations (DDEs), and analyze its stability using the phase plane method. We deduced the sufficient conditions of the stability of ECCP that could be used for parameter setting properly. We also discovered that the stability of ECCP is mainly ensured by the sliding mode motion, causing ECCP to keep cross traffic close to the maximum link capacity and queue length close to zero. Extensive simulation scenarios are driven to validate the analytical results of ECCP behavior. Our analysis shows that ECCP is practical in avoiding congestion and achieving minimum network latency. Moreover, to verify the performance of ECCP in real networks, we conducted a testbed implementation for ECCP using Linux machines and a 10-Gbps switch.

Entropy Applications to Water Monitoring Network Design: A Review

Having reliable water monitoring networks is an essential component of water resources and environmental management. A standardized process for the design of water monitoring networks does not exist with the exception of the World Meteorological Organization (WMO) general guidelines about the minimum network density. While one of the major challenges in the design of optimal hydrometric networks has been establishing design objectives, information theory has been successfully adopted to network design problems by providing measures of the information content that can be deliverable from a station or a network. This review firstly summarizes the common entropy terms that have been used in water monitoring network designs. Then, this paper deals with the recent applications of the entropy concept for water monitoring network designs, which are categorized into (1) precipitation; (2) streamflow and water level; (3) water quality; and (4) soil moisture and groundwater networks. The integrated design method for multivariate monitoring networks is also covered. Despite several issues, entropy theory has been well suited to water monitoring network design. However, further work is still required to provide design standards and guidelines for operational use.

Effects of autapse and ion channel block on the collective firing activity of Newman–Watts small-world neuronal networks

An autapse is a special kind of synapse established between the axon and dendrites of the same neuron. In the present study, we have investigated the cooperative effects of autapse and ion channel block on the collective firing regularity of Newman–Watts small-world networks of stochastic Hodgkin–Huxley neurons. We obtain autaptic time delay induced multi-coherence resonance (MCR) phenomenon in the absence of ion channel block. When the ion channel block is considered, we find that this autaptic delay induced MCR phenomenon enhances with the increasing of potassium channel block, whereas it weakens with the increasing of sodium channel block at weak and intermediate autaptic conductance regimes. However, at strong autaptic conductance regime neither sodium nor potassium channel block have a significant effect on the collective firing regularity of the network. Besides, we investigate the effects of the coupling strength, the network randomness and the cell size on the regularity. We obtain an optimal coupling strength value and an optimal cell size leading to a more prominent MCR effect. We also show that the MCR phenomenon increases with the increasing of network randomness in potassium channel block, but it needs to a minimum network randomness for its appearing in case of sodium channel block.

Traffic modelling of the video-on-demand service through NS-3

La principal característica del servicio de video bajo demanda a través de la tecnología de video streaming es el consumo de grandes anchos de banda, por lo que los planificadores de redes deben considerar este servicio en el momento de dimensionar dichas redes. Para alcanzar esta meta, una de las herramientas es la ingeniería de tráfico y sus modelos asociados. Así, este artículo presenta un modelo de tráfico basado en la simulación por eventos discretos y desarrollado a través del software de código abierto y de investigación en redes, denominado ns-3. Se describen las abstracciones de los elementos de red, y el proceso de construcción de diferentes escenarios de evaluación, independiente de las características del servicio que se desee analizar, y la recolección y visualización gráfica de estadísticas. Finalmente se presentan los análisis de los parámetros de desempeño que permiten obtener las características mínimas de red para soportar el servicio.

Improved phantom cell deployment for capacity enhancement

Vastly increasing capacity and coverage demand in communication networks accompanied by energy efficiency challenge is getting attraction in research topics of this area. In this paper, an improved structure of Phantom cell heterogeneous networks is proposed to fulfill these requirements in the next generation cellular networks. It will be shown that the proposed orthogonal frequency-division multiple access (OFDMA) based structure can be employed in both indoor and outdoor environments by applying two individual frequency bands. Furthermore, the resource allocation problem of the proposed structure is investigated in downlink path. To this aim, a proper algorithm is presented in order to maximize the total throughput of all phantom cell users’ equipments with regard to the protected minimum network capacity of the existing macrocell. To fulfill the objective goal, an iterative approach is employed in which OFDM subchannels and power transmitted by base stations are sequentially assigned and optimized at each step for every single frequency band. It is showed that the overall joint subchannel and power allocation algorithm converges to local maximum of the original designed problem. Performance improvement of the proposed algorithm is confirmed in both indoor and outdoor environments by numerical results.

Analytical Model of Deployment Methods for Application of Sensors in Non-hostile Environment

Wireless Sensor Networks (WSNs) has become one the promising research theme due to the availability of wide range of applications useful for almost each and every area of society. One fundamental application of WSNs is event detection in a Region of Interest (RoI). A set of sensors are deployed to monitor any events inside RoI. In such monitoring applications, both the quality of detection as well as resource requirement in terms of sensors must be optimized while satisfying a certain level of detection guaranty. Therefore, carrying out an optimal sensor deployment is a challenging task for achieving a certain coverage quality with minimum energy consumption and network cost. This paper proposes analytical models for critically analyzing the performance of different deployment techniques to provide insight on the design parameters and system behaviors. Mathematical formulations have been derived to measure the quality of coverage, energy consumption and network cost of geometrical deployment patterns in terms of different metrics; namely, size of RoI, number of sensors and their sensing range. The deployment patterns are modeled by using different shapes of mathematical geometry such square, tri-tilling-hexagon and hexagon. Simulations are carried out using MATLAB considering realistic parameter setting and results are comparatively analyzed for deployment techniques. Analysis of results attests the superiority of Tri Hexagon Tiling (THT) deployment in terms of 2-coverage, energy consumption and network cost to the square and hexagon deployments. In terms of 3-coverage and 4-coverage, hexagon deployment is better as compared to THT and square deployments.

Optimal Network Design with End-to-End Service Requirements

Long-term planning for transportation, telecommunications, and other service operations entails designing networks that are both cost effective and responsive. Because infrastructure networks are expensive and the network’s design determines its service capabilities, planners must address complex trade-offs between minimizing the total cost of the network while meeting end-to-end service requirements such as limits on transit time, latency, and transshipments. To address this problem, we study a minimum cost multicommodity network design model to select arcs and route the required flows along these arcs so that each origin-to-destination route satisfies limits on various service metrics. To effectively solve this service network design problem, we focus on a polyhedral approach to strengthen its arc flow formulation. We develop several classes of strong cuts, with appropriate separation procedures, and propose an optimization-based heuristic method. We characterize the dimension of the problem’s feasible region and show that two classes of inequalities are facet-defining under appropriate conditions. Our computational results demonstrate that our Composite method, incorporating the valid inequalities and heuristic algorithm, significantly reduces computational time and generates near-optimal solutions. The model and methods developed in this paper provide a valuable planning tool for service providers in transportation, telecommunication, and other sectors. The online appendix is available at https://doi.org/10.1287/opre.2016.1579 .

Energy Minimization With Network Coding via Latin Hypercubes

Network coding is mostly used to achieve the capacity of communication networks. In this paper, motivated by the nanoscale communications where the energy cost for the channel symbols is asymmetric due to the widely employed on–off keying modulation, we design energy-minimizing network codes. We develop the best mapping between the input and output symbols at the network coding node that minimizes the average codeword energy using Latin squares, which we call the minimum energy network code (MENC). We define the class of networks composed of coding nodes with N incoming and 1 outgoing symbols as in-N networks. First, we derive the condition on the network code to minimize the average energy in in-two networks and propose two linear MENCs. Later, we investigate the MENCs for in-N networks using the Latin hypercubes and propose a low-energy network code (LENC) to reduce the average energy with network coding. We compare MENC with the classical XOR and random network codes for in-two networks. The performance comparison between LENC and random network codes for in-N networks shows that the proposed network codes provide significant energy gains.

Optimal Qos-aware network reconfiguration in software defined cloud data centers

Software-defined networking (SDN) as a new paradigm for networking provides efficient resource reallocation platform in emerging cloud data center networks. The dynamic nature of cloud data center network's traffic, as well as the existence of big flows make it necessary to periodically reprogram the network through the SDN controller. Therefore, it is critical for network researchers to minimize the side-effects of network reconfiguration. In this way, the most challenging issue is the number of rerouted flows that affect the network stability and QoS parameters. As a result, dynamic reconfiguration of the network with minimum overhead (i.e. minimum flow rerouting) is an interesting problem in SDN-based resource reallocation. In this paper, we mathematically formulated the resource reallocation problem as an optimization problem with minimum network reconfiguration overhead subject to QoS requirements of the applications’ flows. In order to reduce the time complexity of solving the optimization problem, a forwarding table compression technique is devised making the proposed scheme an efficient resource reallocation method which can be used as an application on top of the SDN controller. Our Experimental results show that the proposed scheme decreases the network reconfiguration overhead dramatically while meeting the QoS constraints. Since the reconfiguration overhead of the proposed scheme is low, the controller can reallocate the resources more frequently based on the network condition. We also studied the impact of the proposed network reconfiguration scheme on packet loss and delay in the network. The results show that the proposed approach outperform the conventional methods.

Throughput Gains From Adaptive Transceivers in Nonlinear Elastic Optical Networks

In this paper, we link the throughput gains, due to transceiver adaptation, in a point-to-point transmission link to the expected gains in a mesh network. We calculate the maximum network throughput for a given topology as we vary the length scale. We show that the expected gain in the network throughput due to transceiver adaptation is equivalent to the gain in a point-to-point link with a length equal to the mean length of the optical paths across the minimum network cut. We also consider upper and lower bounds on the variation of the gain in the network throughput due to transceiver adaptation, where integer-constrained channel bandwidth assignment and quantized adaptations are considered. This bounds the variability of results that can be expected and indicates why some networks can give apparently optimistic or pessimistic results. We confirm the results of previous authors that show finer quantization steps in the adaptive control lead to an increase in the throughput since the mean loss of throughput per transceiver is reduced. Finally, we consider the likely network advantage of digital nonlinear mitigation and show that a significant tradeoff occurs between the increase in the signal-to-noise ratio for larger mitigation bandwidths and the loss of throughput when routing fewer large-bandwidth superchannels.

Extra-Mediterranean glacial refugia in a Mediterranean faunal element: the phylogeography of the chalk-hill blue Polyommatus coridon (Lepidoptera, Lycaenidae)

Most warm-adapted Central European species are thought to have survived ice ages exclusively in Mediterranean refugia. During recent years, this point of view has been questioned. Therefore, we tested the hypothesis that extra-Mediterranean refugia also played a role in warm-adapted insect species and selected the chalk-hill blue, Polyommatus coridon. We sequenced two mitochondrial loci (COI, CR) in 150 individuals from 30 populations covering nearly the complete range. Minimum spanning networks and other statistical analyses concordantly revealed four genetic lineages with strong phylogeographic signal: a western group in Italy, France and western/central Germany, an eastern lineage in the Balkan Peninsula, the Carpathian Basin and eastern Central Europe, an Alpine group with populations in the Alps and southern Germany and a Pyrenean group. Our results are generally consistent with previous analyses for P. coridon based on allozymes and DNA sequences, but provide additional insights. We propose that these four lineages have evolved during allopatry in different glacial refugia, two in typical Mediterranean refugia (Apennines and Balkan Peninsulas), but two in extra-Mediterranean areas south of the Alps and Pyrenees. This supports survival of warm-adapted organisms in these regions in close geographic proximity to the refugia of high mountain species.

Approximating the Generalized Minimum Manhattan Network Problem

We consider the generalized minimum Manhattan network problem (GMMN). The input to this problem is a set R of n pairs of terminals, which are points in ℝ2. The goal is to find a minimum-length rectilinear network that connects every pair in R by a Manhattan path, that is, a path of axis-parallel line segments whose total length equals the pair’s Manhattan distance. This problem is a natural generalization of the extensively studied minimum Manhattan network problem (MMN) in which R consists of all possible pairs of terminals. Another important special case is the well-known rectilinear Steiner arborescence problem (RSA). As a generalization of these problems, GMMN is NP-hard. No approximation algorithms are known for general GMMN. We obtain an O(logn)-approximation algorithm for GMMN. Our solution is based on a stabbing technique, a novel way of attacking Manhattan network problems. Some parts of our algorithm generalize to higher dimensions, yielding a simple O(log d + 1 n)-approximation algorithm for the problem in arbitrary fixed dimension d. As a corollary, we obtain an exponential improvement upon the previously best O(n e )-ratio for MMN in d dimensions [ESA’11]. En route, we show that an existing O(logn)-approximation algorithm for 2D-RSA generalizes to higher dimensions.

Heuristic‐based link quality preservation for reliable data delivery

SummaryDuring the link failure conditions in Voice over Internet Protocol applications, the backup of routing information is an important requirement to offer the reliable data delivery to the destination. But the maintenance of multiple paths is the difficult and time consuming for the dynamic environment. But the hops reduction between the source and destination and the interference occurrence causes the transmission in multiple times and that leads to minimum network lifetime. Hence, the preservation of link between the multiple hops is the necessary task to improve the performance. This paper validates the link quality with the 4 measures as received signal strength indicator, bandwidth, node mobility, and the number of connections. The link quality factor (LQF) measurement considers the signal and noise level in 5 operating conditions to allow the automatic identification of closest neighbors and their location. The integration of tabu list and the heuristic‐based fitness search algorithm constructs the routing path and updates the path to identify the link failure. The LQF estimation and the dynamic update provide an efficient data delivery path with less number of iterations. The comparative analysis between the proposed hybrid tabu‐heuristic–based LQF with the existing protocols such as Adhoc On‐Demand Vector (AODV), Optimized Link State Routing (OLSR), and the Interference‐based Topology Control algorithm for Delay‐constrained (ITCD) proves the effectiveness of tabu‐heuristic–based LQF regarding the throughput, energy, packet delivery ratio with the minimum delay, and rebroadcasting probabilities.

Competitive Swarm Optimizer Based Gateway Deployment Algorithm in Cyber-Physical Systems.

Wireless sensor network topology optimization is a highly important issue, and topology control through node selection can improve the efficiency of data forwarding, while saving energy and prolonging lifetime of the network. To address the problem of connecting a wireless sensor network to the Internet in cyber-physical systems, here we propose a geometric gateway deployment based on a competitive swarm optimizer algorithm. The particle swarm optimization (PSO) algorithm has a continuous search feature in the solution space, which makes it suitable for finding the geometric center of gateway deployment; however, its search mechanism is limited to the individual optimum (pbest) and the population optimum (gbest); thus, it easily falls into local optima. In order to improve the particle search mechanism and enhance the search efficiency of the algorithm, we introduce a new competitive swarm optimizer (CSO) algorithm. The CSO search algorithm is based on an inter-particle competition mechanism and can effectively avoid trapping of the population falling into a local optimum. With the improvement of an adaptive opposition-based search and its ability to dynamically parameter adjustments, this algorithm can maintain the diversity of the entire swarm to solve geometric K-center gateway deployment problems. The simulation results show that this CSO algorithm has a good global explorative ability as well as convergence speed and can improve the network quality of service (QoS) level of cyber-physical systems by obtaining a minimum network coverage radius. We also find that the CSO algorithm is more stable, robust and effective in solving the problem of geometric gateway deployment as compared to the PSO or Kmedoids algorithms.

A hybrid protection approaches for denial of service (DoS) attacks in wireless sensor networks

ABSTRACTWireless sensor network (WSN) contains the distributed autonomous devices with the sensing capability of physical and environmental conditions. During the clustering operation, the consumption of more energy causes the draining in battery power that leads to minimum network lifetime. Hence, the WSN devices are initially operated on low-power sleep mode to maximise the lifetime. But, the attacks arrival cause the disruption in low-power operating called denial of service (DoS) attacks. The conventional intrusion detection (ID) approaches such as rule-based and anomaly-based methods effectively detect the DoS attacks. But, the energy consumption and false detection rate are more. The absence of attack information and broadcast of its impact to the other cluster head (CH) leads to easy DoS attacks arrival. This article combines the isolation and routing tables to detect the attack in the specific cluster and broadcasts the information to other CH. The intercommunication between the CHs prevents the DoS attacks effectively. In addition, the swarm-based defence approach is proposed to migrate the fault channel to normal operating channel through frequency hop approaches. The comparative analysis between the proposed table-based intrusion detection systems (IDSs) and swarm-based defence approaches with the traditional IDS regarding the parameters of transmission overhead/efficiency, energy consumption, and false positive/negative rates proves the capability of DoS prediction/prevention in WSN.

Distributed Multicast Tree Construction in Wireless Sensor Networks

Multicast tree is a key structure for data dissemination from one source to multiple receivers in wireless networks. Minimum length multica modeled as the Steiner tree problem, and is proven to be NP-hard. In this paper, we explore how to efficiently generate minimum length multi wireless sensor networks (WSNs), where only limited knowledge of network topology is available at each node. We design and analyze a simple algorithm, which we call toward source tree (TST), to build multicast trees in WSNs. We show three metrics of TST algorithm, i.e., running and energy efficiency. We prove that its running time is $O(\sqrt {n\log n})$ , the best among all existing solutions to our best knowledge. We prove that TST tree length is in the same order as Steiner tree, which give a theoretical upper bound and use simulations to show the ratio be only 1.114 when nodes are uniformly distributed. We evaluate energy efficiency in terms of message complexity and the number of forwarding prove that they are both order-optimal. We give an efficient way to construct multicast tree in support of transmission of voluminous data.

配电网中分布式源-荷协同运行多目标优化的机会约束二阶锥规划模型

在双馈风电机组和光伏发电站等多种类型的分布式电源以及电动汽车接入配电网系统的情况下，考虑配电网电源出力和负荷的随机性，建立了含不确定性DG与EV的配电网优化模型。该模型以高置信水平的最小经济运行成本和最小有功网络损耗为目标，同时加入节点电压期望值最大偏差为惩罚函数，用全牛顿步不可行内点法进行求解。对IEEE33节点系统进行仿真计算并对比其他规划及锥规划的其他算法，证明了本文所提出的优化模型计算法的有效性。 In the case of distributed power supply (DG) and electric vehicle (EV) connected to distribution network system such as double-fed wind turbine and photovoltaic power station, considering the randomness of power distribution and load of distribution network, the optimization model of distribution network with DG and EV is established. In the model, the minimum economic operating cost and the minimum active network loss are taken as goals, and the maximum deviation of the expected value of the node voltage is added as the penalty function. Full Newton step infeasible interior point algorithm is used to solve the model. The simulation of the IEEE 33-node system is carried out and compared with other algorithms of other programming, which proves the validity of the optimization model proposed in this paper.

Bilevel Traffic Evacuation Model and Algorithm Design for Large-Scale Activities

This paper establishes a bilevel planning model with one master and multiple slaves to solve traffic evacuation problems. The minimum evacuation network saturation and shortest evacuation time are used as the objective functions for the upper- and lower-level models, respectively. The optimizing conditions of this model are also analyzed. An improved particle swarm optimization (PSO) method is proposed by introducing an electromagnetism-like mechanism to solve the bilevel model and enhance its convergence efficiency. A case study is carried out using the Nanjing Olympic Sports Center. The results indicate that, for large-scale activities, the average evacuation time of the classic model is shorter but the road saturation distribution is more uneven. Thus, the overall evacuation efficiency of the network is not high. For induced emergencies, the evacuation time of the bilevel planning model is shortened. When the audience arrival rate is increased from 50% to 100%, the evacuation time is shortened from 22% to 35%, indicating that the optimization effect of the bilevel planning model is more effective compared to the classic model. Therefore, the model and algorithm presented in this paper can provide a theoretical basis for the traffic-induced evacuation decision making of large-scale activities.