Search

In recent times, there has been a noticeable surge in the inclination towards the implementation of network automation solutions. This trend is driven by the objective of optimizing network availability within the context of hybrid data center networks, which are becoming increasingly prevalent. Reliability, performance, scalability, and minimal resource overhead are crucial solution design characteristics that significantly impact the decisionmaking process regarding adoption. Recent research has shown that 90% of network outages happen because of human factors and 69% of respondents manage their network with manual method. That high human error of up to 90%, occurs when configuring network devices using manual method. These problems had a negative impact on the functioning of the organization and were harmful to the user. In this research, we investigate solutions to reduce network outage that caused human error using network automation using the Python programming language and multi-threading method. This network automation will reduce configuration time, eliminate human error, and significantly increase efficiency. The aim of this research is to investigate the efficacy of network automation using Python and multi-threading to reduce network outages.The method used in this research is a parallel or multi-tread execution process method using GNS3 as network simulator. Based on experimental results, the multithread automation approach is significantly faster than both the serial automation method (67 seconds) and the manual method (248 seconds), this method requiring only 41 seconds to configure all Cisco router devices. If you're looking for speed, look no farther than the multithread automation approach, which is 6 times quicker than the manual method and 3.7 times quicker than the serial automation approach. The findings of this study have substantial and immediate implications for the ability of network engineers to speed up the configuration of networks and lower the rate of human error in doing so. [ABSTRACT FROM AUTHOR]

Batteries are classically used as backup in case of power outages in telecommunications networks to keep the services always active. Recently, network operators use the batteries as a demand response lever, so as to reduce the energy costs and to generate revenues in the energy market. In this work, we study how the telecommunications operator can optimize the use of a battery over a given horizon to reduce energy costs and to perform load curtailments efficiently, as long as the safety usage rules are respected. First, we formulate the related optimization problem as a mixed integer program taking into account the telecommunication engineering and battery operation constraints, as well as the market rules. Second, we give two practical variants of the problem that can be solved to optimality in polynomial time thanks to a graph-oriented algorithm we propose. We also use this algorithm as a heuristic to solve efficiently the main problem. Finally, simulations based on real data from the French telecommunications operator Orange show the relevance of the model and of the graph-oriented algorithm: these prove to be computationally efficient in solving large scale instances, and significant savings and revenues can be generated through our optimized battery management policies. [ABSTRACT FROM AUTHOR]

Energy consumed by the sensor nodes are more sporadic in a sensor networks. A skilled way to bring down energy consumption and extend maximum life-time of any sensor present can be of evenly and unevenly distributed random area networks. Cluster heads are more responsible for the links between the source and destination. Energy consumption are much compare to member nodes of the network. Re-clustering will take place if the connectivity in the distributed network failure occurs in between the cluster networks that will affects redundancy in the network efficiency. Hence, we propose pragmatic distribution based routing cluster lifetime using fitness function (PDBRC) prototype is better than the existing protocol using MATLAB 2021a simulation tool. [ABSTRACT FROM AUTHOR]

The increase in the number of cases of failure of information and telecommunication networks due to cyber attacks determines the need to protect them from this type of attacks. The issue of increasing cyber security in the conditions of conducting operations by groups of troops (forces) is very important. Due to the armed conflict in the East of Ukraine, the military-political instability in the Middle East, the struggle for influence on world financial and energy flows, the global military-political instability is intensifying. This is due to an increase in the number of communication devices in information and telecommunication networks, as well as an increase in the number of possible attacks that can be used to disrupt the operation of an information and telecommunication network. Considering the above, the object of research is a special purpose information and telecommunication system. The subject of research is cyber security of a special purpose information and telecommunication system. Classical methods of scientific knowledge, namely analysis and synthesis, were used during the research. The research identifies factors that affect cyber security in a special purpose information and telecommunications system. All this must be taken into account while planning and deploying a special purpose information and telecommunication system. The analysis of the consequences of the impact on the information and telecommunications system of special purpose of modern devices of defeat and the impact of devices of radio-electronic suppression and other factors was carried out. A typical special purpose information and telecommunication system does not fully meet the requirements for constant readiness to ensure the management of troops (forces), stability, mobility and throughput. A formalized description of the task of improving cyber security in a special purpose information and telecommunications network is provided. The components that affect the level of cyber security of the special purpose information and telecommunication network during the group’s operations have been established. The impact of the specified conditions and factors must be reflected: in the planning documents during the planning of the deployment and operation of the group’s information and telecommunications system; in the software, during operational management. [ABSTRACT FROM AUTHOR]

Objective: The objective of the study was to review the evidence on interventions to improve obstetric emergency referral decision making, communication and feedback between health facilities in sub‐Saharan Africa (SSA). Methods: A systematic search of PubMed, Embase, Cochrane Register and CINAHL Plus was conducted to identify studies on obstetric emergency referral in SSA. Studies were included based on pre‐defined eligibility criteria. Details of reported referral interventions were extracted and categorised. The Joanna Biggs Institute Critical Appraisal checklists were used for quality assessment of included studies. A formal narrative synthesis approach was used to summarise findings guided by the WHO's referral system flow. Results: A total of 14 studies were included, with seven deemed high quality. Overall, 7 studies reported referral decision‐making interventions including training programmes for health facility and community health workers, use of a triage checklist and focused obstetric ultrasound, which resulted in improved knowledge and practice of recognising danger signs for referral. 9 studies reported on referral communication using mobile phones and referral letters/notes, resulting in increased communication between facilities despite telecommunication network failures. Referral decision making and communication interventions achieved a perceived reduction in maternal mortality. 2 studies focused on referral feedback, which improved collaboration between health facilities. Conclusion: There is limited evidence on how well referral interventions work in sub‐Saharan Africa, and limited consensus regarding the framework underpinning the expected change. This review has led to the proposition of a logic model that can serve as the base for future evaluations which robustly expose the (in)efficiency of referral interventions. [ABSTRACT FROM AUTHOR]

As industrialization accelerates, the industrial sensor network environment becomes more complex. Hierarchical multi-cluster wireless sensing network topology is generally used due to large-scale industrial environments, harsh environments, and data overload impact. In industrial wireless sensor networks, the overload of some nodes may lead to the failure of the whole network, which is called cascading failure. This phenomenon has incalculable impact on industrial production. However, cascading failure models have mainly been studied for planar structures, and there is no cascading failure model for hierarchical topologies in industrial environments. Therefore, this paper built a cascading failure model for hierarchical industrial wireless sensor networks (IWSNs) for realistic industrial network topologies. By establishing an evaluation mechanism considering the efficiency of the network and the viability of nodes, the network communication efficiency that is not considered in the traditional evaluation mechanism is solved. In addition, aiming at the problem of network topology changes caused by node failure, dynamic load distribution methods (ADD, SLD) are used to improve network invulnerability. Theoretical analysis and experimental results show that the traditional allocation method (SMLD) does not apply in hierarchical topologies; when the general cluster head node capacity is moderate, increasing the capacity of single-hop cluster head nodes can prevent cascading failures more effectively. [ABSTRACT FROM AUTHOR]

Nowadays, networks (systems) appear in many areas of science and technology. One of the most important strategies to reduce the likelihood of the failure of an operating network is preventive maintenance (PM). In this article, we propose some optimal PM models for a network consisting of n, n ≥ 1, links (components). The criteria of interest are the "cost function" of renewing the network and "stationary availability" of the network during its mission. In the first part of the article, we consider the case that the network is formed of identical components while in the second part, we deal with the case that the network is built up from several nonidentical groups of components. In both parts, we utilize the PM under some partial information about the status of the network at a time t. The results of the article are developed using the notions of signature and survival signature. To interpret the proposed models, the results are illustrated numerically and graphically for two networks. [ABSTRACT FROM AUTHOR]

Unbalanced voltage drops can lead to non-sinusoidal current injections and power oscillations at twice the fundamental frequency of the grid in photovoltaic parks connected to the electrical system. These oscillations can damage the inverter DC link capacitor, which is one of the components that most limits the life of the inverter. Proper controls of these converters can address this problem efficiently. In those solutions, the reference current calculation is one of the most important problems to be addressed for reliable operation of converters under unbalanced grid faults. This article presents a comparison of the reference current generation schemes, during a single-phase fault in the network..It provides an evaluation of the performance of different techniques and being able to help in the selection of the appropriate control during major network failures. [ABSTRACT FROM AUTHOR]

Hard-and-software integrated systems such as command and control systems (C4ISR systems) are typical systems that are comprised of both software and hardware, the failures of such devices result from complicated common cause failures and common (or shared) signals that make classical reliability analysis methods will be not applicable. To this end, this paper applies the Goal-Oriented (GO) methodology to detailed analyze the reliability of a C4ISR system. The reliability as well as the failure probability of the C4ISR system, are reached based on the GO model constructed. At the component level, the reliability of units of the C4ISR system is computed. Importance analysis of failures of such a system is completed by the qualitative analysis capability of the GO model, by which critical failures of hardware failures like communication module failures and motherboard module failures as well as software failures like network module application software failures and decompression module software failures are ascertained. This method of this paper contributes to the reliability analysis of all hard-and-software integrated systems. [ABSTRACT FROM AUTHOR]

Large-scale distributed computing infrastructures ensure the operation and maintenance of scientific experiments at the LHC: more than 160 computing centers all over the world execute tens of millions of computing jobs per day. ATLAS — the largest experiment at the LHC — creates an enormous flow of data which has to be recorded and analyzed by a complex heterogeneous and distributed computing environment. Statistically, about 10–12% of computing jobs end with a failure: network faults, service failures, authorization failures, and other error conditions trigger error messages which provide detailed information about the issue, which can be used for diagnosis and proactive fault handling. However, this analysis is complicated by the sheer scale of textual log data, and often exacerbated by the lack of a well-defined structure: human experts have to interpret the detected messages and create parsing rules manually, which is time-consuming and does not allow identifying previously unknown error conditions without further human intervention. This paper is dedicated to the description of a pipeline of methods for the unsupervised clustering of multi-source error messages. The pipeline is data-driven, based on machine learning algorithms, and executed fully automatically, allowing categorizing error messages according to textual patterns and meaning. [ABSTRACT FROM AUTHOR]

This work shows a methodology known as the S Transform for time-frequency analysis of different distortions in electric power systems, which mostly are non-stationary and short-duration events, due to the contribution of network impedances and loads types connected by the users. The ability to identify all types of power quality distortions encrypted in the current and voltage signals is very important for failures and malfunctions analysis of monitoring equipment, protection, and control of electrical networks. An important feature of the S Transform is that it combines a frequency dependent resolution of time-frequency space, with information fully connected to the local phase. This allows defining the term of local phase spectrum. Additionally, it shows that amplitude response is invariant from frequency, in contrast to Wavelet and Short Time Fourier Transforms. The following study cases will be simulated by means of PSCAD software: motors starting up and shutting down, line-ground fault, zero-sequence harmonics in a balanced three-phase load, unbalanced three-phase load, a signal with high frequency components and notches presence. [ABSTRACT FROM AUTHOR]

Copyright of Scientific Bulletin of National Mining University is the property of National Mining University, State Higher Educational Institution and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this work, cascading transmission line failures are studied through a dynamical model of the power system operating under fixed conditions. The power grid is modeled as a stochastic dynamical system where first-principles electromechanical dynamics are excited by small Gaussian disturbances in demand and generation around a specified operating point. In this context, a single line failure is interpreted in a large deviation context as a first escape event across a surface in phase space defined by line security constraints. The resulting system of stochastic differential equations admits a transverse decomposition of the drift, which leads to considerable simplification in evaluating the quasipotential (rate function) and, consequently, computation of exit rates. Tractable expressions for the rate of transmission line failure in a restricted network are derived from large deviation theory arguments and validated against numerical simulations. Extensions to realistic settings are considered, and individual line failure models are aggregated into a Markov model of cascading failure inspired by chemical kinetics. Cascades are generated by traversing a graph composed of weighted edges representing transitions to degraded network topologies. Numerical results indicate that the Markov model can produce cascades with qualitative power law properties similar to those observed in empirical cascades. [ABSTRACT FROM AUTHOR]

The availability of network communication services is an important evaluation standard to measure the ability of the network to meet the user's business needs. The current related research mostly focuses on the evaluation of network reliability, which cannot reflect the logical relationship between failure/maintenance and network performance parameters. Mobile Ad Hoc Network is a multi-hop, centerless and energy-constrained distributed system. Due to the dynamic change of communication environment and the instability of wireless link, Ad Hoc Network is facing great challenges in service availability. In this thesis, a fault-based quantitative evaluation model of traffic availability in Ad Hoc networks is proposed. By studying the multi-state Markov fault model of communication networks and the performance analysis of delay index based on CSMA∖CA protocol, the quantitative evaluation of traffic availability in Ad Hoc networks is realized. And the availability of tactical unit network under different typical network configuration conditions is analyzed through experiments. [ABSTRACT FROM AUTHOR]

Hyper-convergence is a new innovation in data center technology, it changes the way clouds manage and maintain enterprise IT infrastructure. Hyper-convergence is more efficient and basically agile technology environment. Cloud computing is a latest technology due to provision of latest cloud services over the internet. The cloud service providers cannot promise accurate reliability of their services i.e. problem in provisioning of software or hardware failure etc. Reliability of cloud computing services depends on the ability of fault tolerance during the execution of services. There are so many factors can cause faults, such as network failure, browser crash, request time out or hacker attacks. When users are facing these types of faults, they usually resubmit their requests. However, if there is any key element involved in faults or errors, additional action may be needed to deal with system logs. If there is anomaly behavior occurred in faulted virtual machine, these VMs may need extra attention from cloud system protection and security point of view. In this paper, provision of reliability management in hyper-convergence cloud infrastructure is proposed and self-healing techniques in software as a service on the basis of failure in cloud services. Intelligent cloud service reliability framework will increase the reliability during execution of cloud service. [ABSTRACT FROM AUTHOR]

Studies in technological innovation systems (TIS) have made significant progress in explaining the dynamics of industry formation for emerging technologies, recognizing that learning is an interactive process. Recent literature suggests that knowledge development and diffusion among different sectors can play a role in the establishment of a TIS. However, we lack an understanding of how the characteristics of different sectors involved in a TIS influence inter-sectoral learning, i.e. purposive learning-by-interacting between different sectors involved in a TIS. To address this gap, we examine how patterns of inter-sectoral learning vary across three TISs – solar photovoltaic systems, wind turbines, and lithium-ion batteries. Using concepts from the literature on sectoral systems of innovation, we show that the characteristics of the different sectors involved in the TIS influence patterns of inter-sectoral learning. Thus, we provide a systematic way of explaining differences in the importance of learning-by-interacting between different technologies observed in the empirical literature, helping policymakers anticipate potential failures in inter-sectoral learning, and we suggest measures to address them. We also demonstrate the value of explicitly analyzing the sectoral configuration in future TIS analyses, and hence contribute to more closely integrating the literatures on TIS and sectoral systems of innovation. • We examine patterns of inter-sectoral learning in technological innovation systems. • Sectoral characteristics determine need for inter-sectoral learning in a TIS. • Complexity and specificity of sectoral knowledge bases are important determinants. • Innovation policy should consider sectoral characteristics to avoid network failures. [ABSTRACT FROM AUTHOR]

In this paper, we consider an M/M/ queue with catastrophes. We study the model and obtain the time dependent solution by using continued fraction techniques. The corresponding steady state probabilities are also deduced. Further, we have obtained some important measures of the studied model. At the end, we provide some numerical examples to visualize the applicability of the model in practical situations. [ABSTRACT FROM AUTHOR]

For better describing the network cascading failure caused by random attacks such as traffic accidents, this paper introduces the ORNL-PSerc-Alaska (OPA) model to analyze the urban regional traffic network vulnerability. Firstly, the double-layer network model is built for analyzing the complex characteristics of the regional traffic network. Secondly, the cascading failure model is built to better describe the process of the network cascading failure under random attacks. Finally, by simulating the network failure process, the vulnerability of the traffic network will be pointed out, which provides the theoretical basis for avoiding the network cascading failure under random attacks. [ABSTRACT FROM AUTHOR]

In a distributed computing environment, real-time tasks communicate via a network infrastructure whose stability significantly impacts timing predictability. Network stability includes two aspects. First, the network has to guarantee the deadline requirements of real-time message transmissions in the absence of network failures. Second, the network needs to support dynamic recovery when network failures occur. This paper generalizes previous static routing approaches, which address the first aspect of the network stability, by developing a dynamic failure recovery policy and a protocol to address the second aspect of the network stability. We derive new real-time forwarding paths without compromising the capability of network devices to guarantee deadlines of concurrent real-time transmissions. We implement this mechanism on a network simulation platform and evaluate it on real hardware in a local cluster to demonstrate its feasibility and effectiveness. Experiments confirm the ability to bound recovery delays based on the network parameters. [ABSTRACT FROM AUTHOR]

Content caching at mobile user devices (UDs) utilizing device-to-device (D2D) communications is a promising technology to enhance the performance of mobile networks in terms of latency, throughput, and energy consumption. In this paper, a novel method of content delivery using multiple devices to single device (MDSD) communications through D2D links is presented. In this method, the Zipf distribution with an exponent shape parameter is adopted to model the content caching popularity for the analysis of the achievable signal-to-interference-plus-noise ratio. In order to investigate the advantage of the proposed MDSD method, first, a closed-form expression of the outage probability is theoretically derived for a single D2D communication to evaluate the success of content delivery to a reference UD. Second, the expression of the outage probability for MDSD communication is derived, where the outage probability is modeled as a function of content caching popularity, the density of UDs, and the size of cooperative area. The research work is further extended to address the frequency reuse among different UDs in one cell, where a frequency band factor is introduced, and the optimal radius of the cooperative area is introduced and analyzed. The analytical results, validated by the simulation results, show that the outage probability decreases drastically when the popularity of the content increases or the radius of the cooperative area increases. Using the derived closed-form expression of the outage probability, the area spectral efficiency (ASE) of the system is presented. Furthermore, the results show that as the frequency band factor increases, the outage probability decreases, and also the ASE decreases. Finally, it is shown that the MDSD outperforms the single-D2D-based method. [ABSTRACT FROM AUTHOR]

Network failures are undesirable but inevitable occurrences for most modern communication and computing networks. A good network design must be robust enough to handle sudden failures, maintain traffic flow, and restore failed parts of the network within a permissible time frame, at the lowest cost achievable and with as little extra complexity in the network as possible. Emerging next-generation (xG) communication and computing networks such as fifth-generation networks, software-defined networks, and internet-of-things networks have promises of fast speeds, impressive data rates, and remarkable reliability. To achieve these promises, these complex and dynamic xG networks must be built with low failure possibilities, high network restoration capacity, and quick failure recovery capabilities. Hence, improved network restoration models have to be developed and incorporated in their design. In this paper, a comprehensive study on network restoration mechanisms that are being developed for addressing network failures in current and emerging xG networks is carried out. Open-ended problems are identified, while invaluable ideas for better adaptation of network restoration to evolving xG communication and computing paradigms are discussed. [ABSTRACT FROM AUTHOR]

Existing trust evaluation models for wireless sensor networks can accurately and objectively evaluate trust value of nodes, but the nodes' energy saving problem was ignored. Especially when there are a few malicious nodes in a network, the overall trust value calculation for all nodes would waste lots of energy. Beside that, the network failure caused by nodes death was also not considered. In this paper, we proposed a method for avoiding energy hole which applied trust evaluation models and a trust evaluation method based on information entropy, so as to achieve the purpose of improving nodes utilization. Simulation results show that the proposed method can effectively improve nodes utilization, and it has reasonable detection rate and lower false alert rate compared to other classical methods. [ABSTRACT FROM AUTHOR]

Predicting failures on networks and systems is critical in order to maintain high uptime rates. Online failure prediction (OFP) techniques use machine learning and predictive analytics to generate failure models that can be applied to computer network data. These techniques can be provisioned on state-of-the-art stream processing systems, such as Spark Streaming, in order to cope with the scalability challenges from the base data. A big challenge with OFP is selecting the right information to process, as well as the appropriate features in order to achieve high accuracy in predicting failures on complex, interconnected systems. In this article we describe an OFP system built over Apache Spark that takes a repository of network management events, trains a Random Forest model, and uses this model to predict the appearance of future events in near real time. We show through our experiments the usefulness of network management events for accurate predictions, and the advantages of the proposed system in terms of predictive quality, cost, and ease of deployment. [ABSTRACT FROM PUBLISHER]

We present a novel study of reliable broadcast in interdependent networks, in which the failures in one network may cascade to another network. In particular, we focus on the interdependency between a communication network and a power grid network, where the power grid depends on the communication network for control and the communication network depends on the grid for power. In this paper, we propose a best effort broadcast algorithm to handle crash failures in the communication network that may cause cascading failures. We guarantee that all the correct nodes, which operate correctly according to the protocol and do not experience any software or hardware or network failures, eventually deliver the message if the sender is correct. We provide a centralized algorithm and a fully distributed algorithm for nodes to analyze and handle cascading failures. At the core of our work is the fully distributed algorithm which enjoys great performance and scalability. Our evaluation results show that the algorithm handles cascading failures with low overhead. [ABSTRACT FROM AUTHOR]

The design of optical networks decomposes into different tasks, where the engineers must basically organize the way the main system’s resources are used, minimizing the design and operation costs and respecting critical performance constraints. More specifically, network operators face the challenge of solving routing and wavelength dimensioning problems while aiming to simultaneously minimize the network cost and to ensure that the network performance meets the level established in the Service Level Agreement (SLA). We call this the Routing and Wavelength Dimensioning (R&WD) problem. Another important problem to be solved is how to deal with failures of links when the network is operating. When at least one link fails, a high rate of data loss may occur. To avoid it, the network must be designed in such a manner that upon one or multiple failures, the affected connections can still communicate using alternative routes, a mechanism known as Fault Tolerance (FT). When the mechanism allows to deal with an arbitrary number of faults, we speak about Multiple Fault Tolerance (MFT). The different tasks before mentioned are usually solved separately, or in some cases by pairs, leading to solutions that are not necessarily close to optimal ones. This paper proposes a novel method to simultaneously solve all of them, that is, the Routing, the Wavelength Dimensioning, and the Multiple Fault Tolerance problems. The method allows to obtain: a) all the primary routes by which each connection normally transmits its information, b) the additional routes, called secondary routes, used to keep each user connected in cases where one or more simultaneous failures occur, and c) the number of wavelengths available at each link of the network, calculated such that the blocking probability of each connection is lower than a pre-determined threshold (which is a network design parameter), despite the occurrence of simultaneous link failures. The solution obtained by the new algorithm is significantly more efficient than current methods, its implementation is notably simple and its on-line operation is very fast. In the paper, different examples illustrate the results provided by the proposed technique. [ABSTRACT FROM AUTHOR]

We investigate the system performance of a nonorthogonal multiple access (NOMA) based downlink amplify-and-forward relay network over Nakagami-$m$ fading channels with imperfect channel state information, where the base station and all users are provided with multiple antennas, while the relay is equipped with a single antenna. Two special conditions of interest (e.g., Nakagami-1, i.e., Rayleigh and Nakagami-2) are analyzed, and closed-form expression for the system outage probability is derived. Moreover, tight lower and upper bounds of the outage probability, and the outage probability in the high signal-to-interference-and-noise ratio regime, i.e., in the presence of error floor, which exists due to the channel estimation errors, are obtained. Finally, computer simulations are conducted to verify the accuracy of the numerical analysis and to confirm the superiority of the antenna selection and NOMA scheme. [ABSTRACT FROM PUBLISHER]

We propose a novel artificial noise (AN) injection scheme for wireless systems over quasi-static fading channels, in which a single-antenna transmitter sends confidential messages to a half-duplex receiver in the presence of an eavesdropper. Different from classical AN injection schemes, which rely on a multiantenna transmitter or external helpers, our proposed scheme is applicable to the scenario, where the legitimate transceivers are very simple. We analyze the performance of the proposed scheme and optimize the design of the transmission. Our results highlight that perfect secrecy is always achievable by properly designing the AN injection scheme. [ABSTRACT FROM PUBLISHER]

This paper studies the optimal frequency reuse for the transmission of multimedia scalable sources, such as embedded images or scalable video, which need unequal error protection or unequal transmission rates in the bitstream. First, we analyze the crossover of the outage probabilities for full and partial frequency reuse cases in terms of the data rate. We prove that we can find a crossover of the outage probability curves for a data rate lower than a given threshold, which is a function of the parameters such as the partial frequency reuse factor and the user location in the cell. Moreover, the crossover point in the signal-to-noise ratio (SNR) is a strictly increasing function of the data rate. On the other hand, for a data rate higher than or equal to the threshold, there is no crossover; for all SNRs, the outage probability of full-frequency reuse is lower than that of partial-frequency reuse. The results are proven for the arbitrary location of a user in a cell, and for an arbitrary partial frequency reuse factor. Furthermore, the results hold, regardless of the numbers of transmit and receive antennas in the multiple-input multiple-output systems of orthogonal space-time block codes, and of the vertical Bell Labs space-time architecture with a zero-forcing linear receiver. Based on the analysis, we propose unequal-frequency reuse for the optimal transmission of scalable sources. The numerical results show that the peak-SNR performance improves when a sequence of scalable packets is transmitted at the subbands governed by unequal-frequency reuse in cellular networks. [ABSTRACT FROM AUTHOR]

Root cause analysis includes the methods to identify the sources of errors in a network. Most techniques rely on knowledge models of the system, which are usually built by using network operators' expertise. This presents problems related to knowledge extraction, scalability, and understandability. We propose an offline method based on machine learning techniques for the automatic identification of dependencies between system events, enhanced with summarization, operations on graphs, and visualization that help network operators identify the root causes of errors. We illustrate it with examples from a corporate network. [ABSTRACT FROM PUBLISHER]

Because the Internet of Things is embedded in the physical system, the network failure leads to the loss of money or life. The dependent failure or the common cause failure completely destroys the redundancy for improving the reliability, so it severely impacts on the system reliability. Incorporating the common cause failure, we analyze the exact time-dependent all-terminal reliability of the wireless networks with dependent failures, which provides a more realistic assessment of the reliability. We consider both hardware failure and channel fading in the static environment. First, by incorporating the common cause failures into the time-dependent reliability polynomials, we derive the exact time-dependent reliability polynomials of the regular wireless networks of which each node connects other nodes via four point-to-point radio modules. Second, we derive the polynomials of the wireless networks including the random mesh network where each node connects other nodes through the redundant radio-broadcast modules. Finally, we calculate the exact instantaneous failure rates. Surprisingly, we have found that the torus network comprised of the node holding four redundant radio-broadcast modules is compatible with the complete network that is known as the most reliable network. [ABSTRACT FROM AUTHOR]

We consider shielding critical links to enhance the robustness of a network, in which shielded links are resilient to failures. We first study the problem of increasing network connectivity by shielding links that belong to small cuts of a network, which improves the network reliability under random link failures. We then focus on the problem of shielding links to guarantee network connectivity under geographical and general failure models. We develop a mixed integer linear program (MILP) to obtain the minimum cost shielding to guarantee the connectivity of a single source–destination pair under a general failure model, and exploit geometric properties to decompose the shielding problem under a geographical failure model. We extend our MILP formulation to guarantee the connectivity of the entire network, and use Benders decomposition to significantly reduce the running time. We also apply simulated annealing to obtain near-optimal solutions in much shorter time. Finally, we extend the algorithms to guarantee partial network connectivity, and observe significant reduction in the shielding cost, especially when the geographical failure region is small. [ABSTRACT FROM AUTHOR]

In this paper, we study using Destination Artificial Noise (DAN) besides Source Artificial Noise (SAN) to enhance physical layer secrecy with an outage probability based approach. It is assumed that all nodes in the network (i.e. source, destination and eavesdropper) are equipped with multiple antennas. In addition, the eavesdropper is passive and its channel state and location are unknown at the source and destination. In our proposed scheme, by optimized allocation of power to the SAN, DAN and data signal, a minimum value for the outage probability is guaranteed at the eavesdropper, and at the same time a certain level of signal to noise ratio at the destination is ensured. Our simulation results show that using DAN along with SAN brings a significant enhancement in power consumption compared to methods that merely adopt SAN to achieve the same outage probability at the eavesdropper. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks are prone to link/node failures due to various environmental hazards such as interference and internal faults in deployed sensor nodes. Such failures can result in a disconnection in part of the network and the sensed data being unable to obtain a route to the sink(s), i.e. a network failure. Network failures potentially degrade the Quality of Service (QoS) of Wireless Sensor Networks (WSNs). It is very difficult to monitor network failures using a manual operator in a harsh or hostile environment. In such environments, communication links can easy fail because of node unequal energy depletion and hardware failure or invasion. Thus it is desirable that deployed sensor nodes are capable of overcoming network failures. In this paper, we consider the problem of tolerating network failures seen by deployed sensor nodes in a WSN. We first propose a novel clustering algorithm for WSNs, termed Distributed Energy Efficient Heterogeneous Clustering (DEEHC) that selects cluster heads according to the residual energy of deployed sensor nodes with the aid of a secondary timer. During the clustering phase, each sensor node finds k -vertex disjoint paths to cluster heads depending on the energy level of its neighbor sensor nodes. We then present a k -Vertex Disjoint Path Routing (kVDPR) algorithm where each cluster head finds k -vertex disjoint paths to the base station and relays their aggregate data to the base station. Furthermore, we also propose a novel Route Maintenance Mechanism (RMM) that can repair k -vertex disjoint paths throughout the monitoring session. The resulting WSNs become tolerant to k -1 failures in the worst case. The proposed scheme has been extensively tested using various network scenarios and compared to the existing state of the art approaches to show the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Electronic Business Management is the property of National Tsing Hua University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)