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In future generation networks, data protection is a crucial necessity particularly when information is sent on a system. Network protection has three objectives known as discretion, reliability and accessibility. The most common procedure exploited to attain this ambition is encryption. The Generalized Multi Protocol Label Switched (GMPLS) optical networks are designed to survive Internet Protocol's (IPʹs) unreliable delivery. In this paper, GMPLS network is proposed with random users and then the data protection algorithms have been analyzed on proposed GMPLS optical network. The various algorithms involve Rivest Shamir Adleman (RSA) algorithm and Advanced Encryption Standard (AES) algorithm. The considered algorithms are very popular but have not been implemented on GMPLS optical networks in the literature which shows the novelty of the presented work. The network performance is compared for these algorithms in terms of various parameters like blocking probability and latency. The results reveal that RSA reduces the blocking probability < 0.005 and latency < 0.007 ms. This shows that RSA gives better performance than AES algorithm and enhance the quality of service considering blocking probability, latency and overheads in GMPLS optical networks leading to enhanced data protection. [ABSTRACT FROM AUTHOR]

This research problem discusses the occurrence during the MPLS service tunneling process which often looping during the data transmission process, especially in Layer 2-OSI, where data packets will be sent back to the recipient so that data packets do not reach their destination or because of problems with the traffic of sending data. Looping Prevention is one of the proposed methods in this research that occur in tunnel service causes looping. This method is applied by analyzing traffic based on MAC addresses obtained from service verification results so that the cause of looping is known. The results of looping protection methods get an average throughput and delay, when the process of uploading traffic of 16 MB gets 119.3 bps for throughput and delay of 5.9 ms, and when downloading gets throughput of 185.33 bps and delay 6.5 ms. Then, the process of uploading traffic of 32 MB get upload throughput of 129 bps and delay 5.2 ms, and when downloading gets a throughput of 232.66 bps and gets a delay of 4.13 ms. All values obtained are in the category very well based on the standard category TIPHON. [ABSTRACT FROM AUTHOR]

The magnon propagation length (MPL) is one of the crucial factors to govern spin transport in a magnetic material. Here, we determine MPL ($\xi$) in compensated ferrimagnetic Gd3Fe5O12 (GdIG) thin films at room temperature by investigating longitudinal spin Seebeck effect (LSSE) in Gd3Ga5O12 (GGG)/GdIG($t$)/Pt (5 nm) heterostructures with different thicknesses ($t$) of the GdIG film. All films possess in-plane (IP) magnetic easy axis, and the compensation temperature shifts down to lower temperature with decreasing GdIG thickness. At room temperature, the LSSE signal is rather constant with thickness between $t = 221$ and 89 nm, but drops significantly below $t = 50$ nm. By fitting the thickness dependence of the LSSE voltage to a modified atomistic spin model considering the influence of saturation magnetization, we obtain $\xi $ = 45 nm ± 8 nm for GdIG thin films at room temperature. The MPL of GdIG is much shorter than that of Y3Fe5O12 films ($\xi $ ~90–140 nm), but higher than that of Fe3O4 films ($\xi $ ~20 nm). The obtained value of $\xi $ explains the drop in the LSSE voltage in GdIG films when the film thickness is reduced below 50 nm, knowledge of which is also essential to the design of spincaloritronic devices based on GdIG films. [ABSTRACT FROM AUTHOR]

Summary: This paper proposes a solution to the problem of switching between different network paths. We choose to switch between multiprotocol label switching (MPLS) and software‐defined wide area networking (SD‐WAN) connections specifically as they are the mainstream currently. The solution should maintain a service license agreement (SLA) while choosing SD‐WAN as long as possible to save cost. Therefore, a deep reinforcement learning solution is proposed that predicts when to switch based on bandwidth availability and quality of service (QoS) parameters like jitter and delay. Results show that double deep Q learning in combination with these parameters are suitable to make a sophisticated decision on link switching between MPLS and SD‐WAN. [ABSTRACT FROM AUTHOR]

Compositional Optimization (CompOpt) was recently proposed for optimization of discrete-event systems of systems. A modular optimization model allows CompOpt to divide the optimization into separate sub-problems, mitigating the state space explosion problem. This paper presents the Modular Optimization Learner (MOL), a method that interacts with a simulation of a system to automatically learn these modular optimization models. MOL uses a modular learning that takes as input a hypothesis structure of the system and uses the provided structural information to split the acquired learning into a set of modules, and to prune parts of the search space. Experiments show that modular learning reduces the state space by many orders of magnitude compared to a monolithic learning, which enables learning of much larger systems. Furthermore, an integrated greedy search heuristic allows MOL to remove many sub-optimal paths in the individual modules, speeding up the subsequent optimization. Note to Practitioners—Automation systems are becoming increasingly large and complex and the automation of more and more advanced tasks often requires the coordination of multiple subsystems. Optimization can have a great impact on the efficiency of these systems in terms of cost and operation speed. Finding optimal solutions is, however, a difficult task. As the number of tasks and subsystems of the automation system increases, the search space of the optimization problems tends to grow exponentially. Compositional Optimization (CompOpt) is a method specifically designed for the optimization of large-scale automation systems. A challenge with the application of CompOpt is that it takes as input a specific type of optimization model that divides the system into subsystems; like machines, vehicles, etc. Formulating these models requires a high level of expertise and system knowledge. This paper addresses this challenge with an algorithm that learns these models from a simulation of the system. The simulation can be implemented in any software as long as a suitable interface exists or can be constructed. To divide the learning into subsystems, the algorithm uses an initial plant structure hypothesis (PSH). This can be viewed as a meta-model that includes known structural information, such as the number of subsystems and which actions that affect each subsystem. The more structural information that is added to PSH, the more efficient the learning and subsequent optimization will be. The purpose of this is to reduce the level of expertise and system knowledge needed in the application of optimization, to simplify the transition to Industry 4.0. [ABSTRACT FROM AUTHOR]

Coverage performance is very important for operators when commercializing NR networks due to its direct impact on service quality as well as CAPEX and OPEX. Compared to LTE, NR systems may operate at higher frequency bands, resulting in larger path loss and worse coverage performance. In this article, potential coverage issues for NR networks are discussed. Through link budget analysis, the gaps between baseline and target performance for typical NR physical channels are described; then the bottleneck channels are identified, including PUSCH, PUCCH, and PRACH. This article mainly focuses on PUSCH coverage enhancement, and potential solutions are discussed in a comprehensive manner. On top of the potential solutions, four joint schemes, which take feasibility as well as specification impact into consideration, are proposed for VoIP and eMBB services to further improve the coverage performance. [ABSTRACT FROM AUTHOR]

Recently, there has been an increasing need for new applications and services such as big data, blockchains, vehicle-to-everything (V2X), the Internet of things, 5G, and beyond. Therefore, to maintain quality of service (QoS), accurate network resource planning and forecasting are essential steps for resource allocation. This study proposes a reliable hybrid dynamic bandwidth slice forecasting framework that combines the long short-term memory (LSTM) neural network and local smoothing methods to improve the network forecasting model. Moreover, the proposed framework can dynamically react to all the changes occurring in the data series. Backbone traffic was used to validate the proposed method. As a result, the forecasting accuracy improved significantly with the proposed framework and with minimal data loss from the smoothing process. The results showed that the hybrid moving average LSTM (MLSTM) achieved the most remarkable improvement in the training and testing forecasts, with 28% and 24% for long-term evolution (LTE) time series and with 35% and 32% for the multiprotocol label switching (MPLS) time series, respectively, while robust locally weighted scatter plot smoothing and LSTM (RLWLSTM) achieved the most significant improvement for upstream traffic with 45%; moreover, the dynamic learning framework achieved improvement percentages that can reach up to 100%. [ABSTRACT FROM AUTHOR]

Network operators cannot change their foot-print to upgrade the entire network to support SDN from scratch. Hence, network operators adapted the original SDN concept into a hybrid SDN approach to have a pragmatic, evolutionary, and economically viable solution. This article tests an SDN architecture based on a hierarchical structure of a Software-Defined Transport Networking (SDTN) controller, which deals with the end-to-end service provision and topology collection on top of a set of SDN controllers for each technological domain. The authors demonstrate L3/L2 VPN service deployment using an underlay multi-domain IP/Optical network in a field trial. The approach allows a service provider to migrate brownfield scenarios into SDN domains using programmatic interfaces. [ABSTRACT FROM AUTHOR]

This article presents an active ball joint mechanism (ABENICS) enhanced by interactions of spherical gears. The gear-based joint drives three rotational degrees of freedom (RDoF) without slippage. The capabilities were inspired by the unique interactions between two different innovative gears [the cross spherical gear (CS-gear) and monopole gear (MP-gear)] and the superimposition of those interactions by the CS-gear's quadrature spherical tooth structure. One MP-gear constrains two of the three RDoF of the CS-gear. The driving module which drives the MP-gear converts this “constraint” into a “drive” and drives the CS-gear with two RDoF. The CS-gear orthogonally superimposes the interactions caused by two MP-gears to achieve three RDoF driving forces. The principle was revealed by analyzing an equivalent linkage modeled on the mechanism of ABENICS. The linkage also led to the kinematics and torque equations. The theory and physical characteristics of ABENICS were verified in comprehensive and continuous positioning experiments on manufactured prototypes. The flexibility of the actuator placement was also verified in different configurations of the driving modules. The active ball joint, ABENICS can transmit high torque and reliable positioning in three RDoF without an orientation sensor, which applies to robot joints and orientation control mechanisms. [ABSTRACT FROM AUTHOR]

The hardcore model on a graph $G$ with parameter $\lambda > 0$ is a probability measure on the collection of all independent sets of $G$ , that assigns to each independent set $I$ a probability proportional to $\lambda ^{|I|}$. In this paper we consider the problem of estimating the parameter $\lambda $ given a single sample from the hardcore model on a graph $G$. To bypass the computational intractability of the maximum likelihood method, we use the maximum pseudo-likelihood (MPL) estimator, which for the hardcore model has a surprisingly simple closed form expression. We show that for any sequence of graphs $\{G_{N}\}_{N \geq 1}$ , where $G_{N}$ is a graph on $N$ vertices, the MPL estimate of $\lambda $ is $\sqrt {N}$ -consistent (that is, it converges to the true parameter at rate $1/\sqrt {N}$), whenever the graph sequence has uniformly bounded average degree. We then extend our methods to obtain estimates for the vector of activity parameters in general $H$ -coloring models, in which restrictions between adjacent colors are encoded by a constraint graph $H$. These constitute an important class of Markov random fields that includes all hard-constraint models, which arise in a broad array of fields including combinatorics, statistical physics, and communication networks. Given a single sample from an $H$ -coloring model, we derive sufficient conditions under which the MPL estimate is $\sqrt {N}$ -consistent. Moreover, we verify the sufficient conditions for $H$ -coloring models for which there is at least one ‘unconstrained’ color (that is, there exists at least one vertex in the constraint graph $H$ that is connected to all vertices), as long as the graph sequence has uniformly bounded average degree. This applies to many $H$ -coloring examples such as the Widom-Rowlinson and multi-state hard-core models. On the other hand, for the $q$ -coloring model, which falls outside this class, we show that the condition can fail and consistent estimation may be impossible even for graphs with bounded average degree. Nevertheless, we show that the MPL estimate is $\sqrt {N}$ -consistent in the $q$ -coloring model when $\{G_{N}\}_{N \geq 1}$ has bounded average double neighborhood. The presence of hard constraints, as opposed to soft constraints, leads to new challenges, and our proofs entail applications of the method of exchangeable pairs as well as combinatorial arguments that employ the probabilistic method. [ABSTRACT FROM AUTHOR]

Video prediction is challenging, due to the pixel-level precision requirement and the difficulty in capturing scene dynamics. Most approaches tackle the problems by pixel-level reconstruction objectives and two decomposed branches, which still suffer from blurry generations or dramatic degradations in long-term prediction. In this paper, we propose a Motion-Aware Feature Enhancement (MAFE) network for video prediction to produce realistic future frames and achieve relatively long-term predictions. First, a Channel-wise and Spatial Attention (CSA) module is designed to extract motion-aware features, which enhances the contribution of important motion details during encoding, and subsequently improves the discriminability of attention map for the frame refinement. Second, a Motion Perceptual Loss (MPL) is proposed to guide the learning of temporal cues, which benefits to robust long-term video prediction. Extensive experiments on three human activity video datasets: KTH, Human3.6M, and PennAction demonstrate the effectiveness of the proposed video prediction model compared with the state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

Rectangular grid graph (RGG) and diagonal grid graph (DGG) are induced subgraphs of a rectangular or diagonal grid, respectively. Their $k$ -coloring problem has direct applications in printing contact/via layouts by multipatterning lithography (MPL). However, the problem in general is computationally difficult for $k>2$ , while it remains an open question on grid graphs due to their regularity and sparsity. On the other hand, directed self-assembly (DSA) technique can work with MPL to optimize the graph by grouping neighboring vertices such that $k$ can be reduced, but the problem of deploying the grouping for coloring is even more intractable. In this paper, we study both of the $k$ -coloring problems, with and without DSA grouping, on RGG and DGG. Without grouping, a complete $k$ -coloring analysis is conducted and particularly the NP-completeness of 3-coloring on a diagonal grid is proved. When considering grouping, we present a 3-coloring solution and prove the NP-completeness to solve the problem of $k=2$. [ABSTRACT FROM AUTHOR]

Featured with simple topology and easy realization of zero-voltage-switching, the Class E dc–dc converter is preferable for very high-frequency application. In this article, a multipower-level (MPL) hysteresis control is proposed for the Class E dc–dc converter, in which, multiple switching frequencies are selected for obtaining multiple input power levels, and the two adjacent input powers closest to the load power are chosen to synthesize the load power. Compared with the on–off control, which has only two input power levels, i.e., the input power in on mode and zero power in off mode, the MPL hysteresis control reduces the modulation frequency, and thus reducing the mode transition losses. Meanwhile, the conduction losses are also reduced. As a result, the efficiency of the converter is greatly improved. The parameters design and the switching frequencies selection for the Class E dc–dc converter with MPL hysteresis control are presented. Finally, a prototype of 10-W Class E dc–dc converter with 9–18 V input is fabricated and tested in the lab, and the experimental results are provided to verify the effectiveness of the proposed MPL hysteresis control scheme. [ABSTRACT FROM AUTHOR]

We show nonparametric identification of the parameters in the dynamic stochastic block model as recently introduced by Matias and Miele (2017) in the case of binary, finitely weighted, and general edge states. We formulate conditions on the true parameters, which guarantee actual point identification instead of mere generic identification, and which also lead to novel conclusions in the static case. In particular, our results justify in terms of the identification of the applications by Matias and Miele to finitely weighted edges with three edge states. We also give numerical illustrations via the variational EM algorithm in simulation settings covered by our identification analysis. [ABSTRACT FROM AUTHOR]

A microwave photonic link with flexible suppression of the even-order and third-order distortions is proposed by using a single integrated polarization-multiplexing dual parallel Mach-Zehnder modulator (PM-DPMZM). A 180° electric hybrid is applied to introduce a phase shift of 180° between the even and odder modulation sidebands of the radio frequency (RF) signal. One DC bias voltage of the PM-DPMZM is adjusted to implement not only the optimal suppression of the even-order or third-order distortions but also a simultaneous suppression of these two distortions. The experimental system is carried out. In the best suppression points for the second or third intermodulation distortions (IMD2 or IMD3), the spurious-free dynamic range (SFDR) of IMD2 and IMD3 is improved by 17.1 and 17.7 dB, comparing with the conventional MZM based MPL. In the case of the simultaneous suppression, the SFDR values of IMD2 and IMD3 are enhanced by 10.6 and 6.4 dB. The proposed link has great flexibility, simple structure, and convenient operation, and it can be applied in both the single-octave and multi-octave communication systems. [ABSTRACT FROM AUTHOR]

Highlights • Multi-protocol label switching networks is optimized based on reliability and costs. • Decoupled the problem into two sub-problems: the cost and the reliability problems. • Working and backup paths are the first K+1 paths regardless of rank of back path. • An algorithm is proposed to reduce the searching space for working and backup paths. Abstract The multi-protocol label switching (MPLS) networks have been widely applied in the backbone network in recent years with offering better Quality-of -Service (QoS). The reliability of MPLS networks is of great importance. In this paper, we consider optimal design for MPLS networks, where working and backup paths are optimally selected to minimize networks' constructing costs under reliability constraints. As both the networks' constructing costs and the network reliability are related to the lengths of the selected paths, the optimal network design problem is decoupled into two sub-problems: the cost related and the reliability related problems, where the cost related problem has been solved by Sohn et al.. Considering the reliability related problem, we proposed a reliability related algorithm to optimally search for the working and backup paths by greatly reducing the searching space. Both the cost related and the reliability related problems can be solved using the same searching criteria, so the optimal set of the working and backup paths of the proposed problem can be derived by comparing the results obtained from the cost related and reliability related problems. Numerical examples are also provided to verify the reliability related algorithm and the whole multi-path transmission design approach. [ABSTRACT FROM AUTHOR]

Abstract: The usage of mobile nodes is increasing very rapidly and so it is very essential to have an efficient channel allocation procedure for the next generation cellular networks. It is very expensive to increase the existing available spectrum. Hence, it is always better to utilize the existing spectrum in an effective way. In view of this, this paper proposes a channel allocation algorithm for next generation cellular networks which is based on deep learning. The system is made learned deeply to determine the number of channels that each base station can acquire and also dynamically varying based on the time. The originating and handoff calls are two different types of calls being considered in this paper. The number of channels that be exclusively used for originating calls and handoff calls is determined using deep learning. STWQ—Non-LA and STWQ—LAR are used to compare with the proposed work. The results show that the proposed algorithm, DLCA outperforms in terms of blocking and dropping probability. [ABSTRACT FROM AUTHOR]

Multiprotocol Label Switching (MPLS) is effective in managing and utilizing available network bandwidth. It has advanced security features and a lower time delay. The existing literature has covered the performance of MPLS-based networks in relation to conventional Internet Protocol (IP) networks. But, too few literatures exist on the performance of MPLS-based Virtual Private Networks (VPN) in relation to traditional VPN networks. In this paper, a comparison is made between the effectiveness of the MPLSVPN network and a classic VPN network using simulation studies done on OPNET®. The performance metrics used to carry out the comparison include; End to End Delay, Voice Packet Sent/Received and Label Switched Path's Traffic. The simulation study was carried out with Voice over Internet Protocol (VoIP) as the test bed. The result of the study showed that MPLS-based VPN networks outperform classic VPN networks. [ABSTRACT FROM AUTHOR]

This paper presents the modeling and analysis of a proposed label-quality of service (QoS) switching protocol for heterogeneous robot in a swarm. Establishing the data communication and network in multirobot task allocation is an important aspect in robot collaboration. Instead of passing the data through the cloud network, each robot can be configured as a node in its swarm for intercommunication. This research was conducted to model and propose aggregation and classification methods in a swarm robot network inspired from multiprotocol label switching, namely, label-QoS switching protocol. Each packet of data is forwarded with a proposed 2-side label values that are concerned with addressing and QoS. This proposed protocol was applied in each of the node's routing, and it was set up with forwarding information table. The simulation and analysis were conducted in 2 situations: (1) with a constant n-label switch mobile robot and a number of packet data increasing with time and (2) with a constant number of packet and varying n-label switch mobile robot by time. With reference to the network parameter performances, it shows that the anomaly treatment by the proposed protocol is able to prioritize the data forwarding between the robots at the edge of the swarm with class of service although the robot community at the center is increasing or getting crowded. [ABSTRACT FROM AUTHOR]

Multi-Protocol Label Switching for Traffic Engineering (MPLS-TE) technology is an intelligent and advanced tool for handling traffic through the core networks and implementing new services based on virtual transport. Since MPLS-TE combines channel and network layer mechanisms, network administrators can optimally integrate and allocate the traffic loads while maintaining the speed of technologies such as Asynchronous Transfer Mode (ATM) technology. In this paper, the problem of the developed algorithm of multi-path routing which allows us to determine the optimum number of independent shortest paths is theoretically solved. In details, the article proposes a way for finding the set of shortest paths using Dijkstra's algorithm, and then determination of the maximum flow for each of the shortest paths based on the mathematical concepts and finally, introducing the solution of the multi-criteria optimization problem for a set of shortest paths. According to our approach, optimizing the use of resources in the core networks is possible with using the MPLS-TE technology. [ABSTRACT FROM AUTHOR]

Near-Infrared (NIR) Spectroscopy was used for the non-destructive assessment of physico-chemical quality parameters in olive oil. At the same time, the influence of the sample presentation mode (spinning versus static cup) was evaluated using two spectrophotometers with similar optical characteristics. A total of 478 olive oil samples were used to develop calibration models, testing various spectral signal pre-treatments. The models obtained by applying MPLS regression to spectroscopic data yielded promising results for olive oil quality measurements, particularly for acidity, the peroxide index and alkyl and ethyl ester content. The results obtained indicate that this non-invasive technology can be used successfully by the olive oil sector to categorize olive oils, to detect potential fraud and to provide consumers with more reliable information. Although both sample presentation modes yielded comparable results, equations constructed with samples scanned using the spinning mode provided greater predictive capacity. [ABSTRACT FROM AUTHOR]

High reliability, efficient I/O performance and flexible consistency provided with low storage cost are all desirable properties of cloud storage systems. Due to the inherent conflicts, however, simultaneously achieving optimum on all these properties is impractical. N-way Replication and Erasure Coding, two extensively-applied storage schemes with high reliability, adopt opposite and unbalanced strategies on the tradeoff among these properties, thus considerably restraining their effectiveness on wide range of workloads. To address the aforementioned obstacle, we propose a novel storage scheme called ASSER, an ASSembling chain of Erasure coding and Replication. ASSER stores each object in two parts: a full copy and a certain amount of erasure-coded segments. We establish dedicated read/write protocols for ASSER leveraging the unique structural advantages. On the basis of elementary protocols, we implement sequential and PRAM (Pipeline-RAM) consistency to make ASSER feasible for various services with different performance/consistency requirements. Evaluation results demonstrate that under the same fault tolerance and consistency level, ASSER outperforms N-way replication and pure erasure coding in I/O throughput under diverse system and workload configurations with superior performance stability. More importantly, ASSER delivers stably efficient I/O performance at much lower storage cost than the other comparatives. [ABSTRACT FROM PUBLISHER]

This paper presents an efficient method for rerouting traffic in the Multiprotocol Label Switching (MPLS) network, when a fault occurs in the working link. The method has been designed to handle both single and multiple faults based on the protection switching and rerouting techniques. The proposed method leads to less packets loss, has better Packet Delivery Ratio (PDR), good throughput and eliminates packet disorder. The proposed method has been simulated using the Network Simulator (NS2) version 2.34 and the simulation results have shown that the proposed method significantly improves the network performance in comparison to similar existing methods. [ABSTRACT FROM AUTHOR]

With the widespread use of real-time applications (VoIP, IPTV, Video conference, etc.) in Internet, protection and resource optimization become increasingly desired. Network protection aims to decrease the interruption time of communications by precomputing backup paths capable to receive and route traffics of affected primary paths upon failures. Resource optimization is achieved by improving data routing and resource sharing: data routing is often optimized by following the shortest paths whereas resource sharing is applied between the backup paths protecting against different failure risks. Two strategies of resource sharing are defined in literature: (1) backup sharing which limits the resource sharing to the backup paths and (2) global sharing which extends the resource sharing to the primary and backup paths. In this paper, we compared the effects of resource sharing strategies on the resource utilization when the primary paths correspond to the shortest ones according to a static metric. With the single failure assumption, we show formally that the resource sharing between primary and backup paths is limited to some few links which cannot form a backup path. Thus, independently of the amount of resources (for instance: bandwidth) that can be shared between the primary and backup paths, the maximum number of backup paths is bounded. In our simulation, we comfort our formal result by showing that the two strategies have close acceptance rates of backup paths and protection bandwidth utilizations. [ABSTRACT FROM AUTHOR]

A multiobjective routing model for multiprotocol label switching networks with multiple service types and path protection is presented in this article. The routing problem is formulated as a biobjective integer program, where the considered objectives are formulated according to a network-wide optimization approach,i.e.the objective functions of the route optimization problem depend explicitly on all traffic flows in the network. A disjoint path pair is considered for each traffic trunk, which guarantees protection to the associated connection. A link-path formulation is proposed for the problem, in which a set of possible pairs of paths is devised in advance for each traffic trunk. An exact method (based on the classical constraint method for solving multiobjective problems) is developed for solving the formulated problem. An extensive experimental study, with results on network performance measures in various randomly generated networks, is also presented and discussed. [ABSTRACT FROM AUTHOR]

The suboptimal distribution of the traffic load over the high-speed optical network channels results in poor overall channel utilization and leads to the increased energy consumption. This means that configuration of the network management system including traffic engineering protocols and traffic management mechanisms may have indirect but significant impact on the overall energy efficiency of the particular optical transport network setup. Therefore, we aim in this paper to estimate how energy efficiency of the optical transport network depends on the configuration of the management protocols and mechanisms deployed into the GMPLS and OBS technologies. In addition, we analyze particular configurations of specific mechanisms those allow to increase energy efficiency of the optical transport network without compromising the parameters of the quality of service (QoS). [ABSTRACT FROM AUTHOR]

The evolution of software defined networking (SDN) has played a significant role in the development of next-generation networks (NGN). SDN as a programmable network having 'service provisioning on the fly' has induced a keen interest both in academic world and industry. In this article, a comprehensive survey is presented on SDN advancement over conventional network. The paper covers historical evolution in relation to SDN, functional architecture of the SDN and its related technologies, and OpenFlow standards/protocols, including the basic concept of interfacing of OpenFlow with network elements (NEs) such as optical switches. In addition a selective architecture survey has been conducted. Our proposed architecture on software defined heterogeneous network, points towards new technology enabling the opening of new vistas in the domain of network technology, which will facilitate in handling of huge internet traffic and helps infrastructure and service providers to customize their resources dynamically. Besides, current research projects and various activities as being carried out to standardize SDN as NGN by different standard development organizations (SODs) have been duly elaborated to judge how this technology moves towards standardization. [ABSTRACT FROM AUTHOR]

Traffic engineering in the Internet is responsible for the optimization and evaluation of the performance of IP networks to avoid congestion. One of the most accepted proposals is MPLS (Multiprotocol Label Switching), which provides an efficient paradigm for traffic optimization. Other proposals include the adjustment of link weights of interior gateway protocols (IGPs), the LISP protocol (Locator/ID Separation Protocol), and segment routing (SR). Currently, work is still being done on the topic and updates to existing recommendations are being proposed. [Extracted from the article]

Bidirectional multicast mechanisms are used to support multi-point to multi-point (MP2MP) traffic such as video-conferencing. These mechanisms are deployed today in multi-protocol label switching (MPLS) networks using the connectionless mode in which traffic engineering (TE) features such as bandwidth reservation and fast reroute in case of link and/or node failure are not defined. Indeed, TE procedures are defined in MPLS for unicast and multicast point-to-multipoint (P2MP) traffic only. Hence, MP2MP traffic that requires TE procedures is carried out using a full mesh of P2P or P2MP paths. Similarly, a full mesh of P2P and P2MP backup paths should be predefined in order to fast reroute traffic in case of a node failure. This leads to a major scalability problem since MPLS TE paths incur heavy overhead burden on MPLS nodes (CPU and memory). In this paper, we emphasize on fast reroute procedures using MP2MP TE paths. In particular, we define the control plane procedures that should be established. In addition, we present a simulation study that demonstrates the scalability amelioration when using MP2MP TE paths for fast rerouting instead of full mesh P2P and/or P2MP paths. [ABSTRACT FROM AUTHOR]

Background: Hierarchical Multi-Label Classification is a classification task where the classes to be predicted are hierarchically organized. Each instance can be assigned to classes belonging to more than one path in the hierarchy. This scenario is typically found in protein function prediction, considering that each protein may perform many functions, which can be further specialized into sub-functions. We present a new hierarchical multi-label classification method based on multiple neural networks for the task of protein function prediction. A set of neural networks are incrementally training, each being responsible for the prediction of the classes belonging to a given level. Results: The method proposed here is an extension of our previous work. Here we use the neural network output of a level to complement the feature vectors used as input to train the neural network in the next level. We experimentally compare this novel method with several other reduction strategies, showing that it obtains the best predictive performance. Empirical results also show that the proposed method achieves better or comparable predictive performance when compared with state-of-the-art methods for hierarchical multi-label classification in the context of protein function prediction. Conclusions: The experiments showed that using the output in one level as input to the next level contributed to better classification results. We believe the method was able to learn the relationships between the protein functions during training, and this information was useful for classification. We also identified in which functional classes our method performed better. [ABSTRACT FROM AUTHOR]

Bandwidth Allocation Models (BAMs) are resource allocation methods used for networks in general. BAMs are currently applied for handling resources such as bandwidth allocation in MPLS DS-TE networks (LSP setup). In general, BAMs define resource restrictions by 'class' and allocate the available resources on demand. This is frequently necessary to manage large and complex systems like routing networks. G-BAM is a new generalized BAM that, by configuration, incorporates the 'behavior' of existing BAMs (MAM, RDM, G-RDM and AllocTC-Sharing). In effect, any current available BAM 'behavior' is reproduced by G-BAM by simply adjusting its configuration parameters. This paper focuses on investigating the applicability of using autonomy together with BAMs for improve performance and facilitating the management of MPLS DS-TE networks. It is investigated the applicability of 'BAM switching' using a framework with autonomic characteristics. In brief, it is investigated the switching among 'BAM behaviors' and BAM's reconfiguration with distinct network traffic scenarios by using G-BAM. Simulation results suggest that the autonomic switching of 'BAM behaviors' based on high-level management rules (Service Level Agreements, Quality of Service (QoS) or other police) may result in improving overall network management and operational parameters such as link utilization and preemption. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The convergent communication network will play an important role as a single platform to unify heterogeneous networks and integrate emerging technologies and existing legacy networks. Although there have been proposed many feasible solutions, they could not become convergent frameworks since they mainly focused on converting functions between various protocols and interfaces in edge networks, and handling functions for multiple services in core networks, e.g., the Multi-protocol Label Switching (MPLS) technique. Software-defined networking (SDN), on the other hand, is expected to be the ideal future for the convergent network since it can provide a controllable, dynamic, and cost-effective network. However, SDN has an original structural vulnerability behind a lot of advantages, which is the centralized control plane. As the brains of the network, a controller manages the whole network, which is attractive to attackers. In this context, we proposes a novel solution called adaptive suspicious prevention (ASP) mechanism to protect the controller from the Denial of Service (DoS) attacks that could incapacitate an SDN. The ASP is integrated with OpenFlow protocol to detect and prevent DoS attacks effectively. Our comprehensive experimental results show that the ASP enhances the resilience of an SDN network against DoS attacks by up to 38%. [ABSTRACT FROM AUTHOR]

Network-wide local unambiguous failure localization (NL-UFL) has been demonstrated as an interesting scenario of monitoring trails (m-trails). It attempts to enable every node to autonomously localize any failure event in the network in a distributed and all-optical manner by inspecting a set of m-trails traversing through the node. This paper investigates the m-trail allocation problem under the NL-UFL scenario by taking each link and node failure event into consideration. Bound analysis is performed using combinatorial group testing (CGT) theory and this is followed by the introduction of a novel heuristic on general topologies. Extensive simulation is conducted to examine the proposed heuristic in terms of the required cover length and the number of m-trails to achieve NL-UFL. [ABSTRACT FROM AUTHOR]

To date, NTT has been providing high-quality dedicated services such as analog and high-speed digital services on its time division multiplexing network. NTT has also been shifting its relay networks to packet transport networks in conjunction with the shift to the Next Generation Network. This article introduces a new packet transport multiplexing adapter for dedicated service provisioning on packet transport networks using circuit emulation technologies. [ABSTRACT FROM AUTHOR]

Looking in to the modern technology, we see new inventions and innovations which are unique. As an example, during the past years, new technologies have been created in computer networks like metropolitan area network (MAN) that has had a noticeable advance in urban communication. Therefore the aim of this article is to provide and compile information regarding MAN technology and MPLS. Utilizing Ethernet in urban networks needs a developing potential and strength that only exists in MPLS and IP levels. Two layer and three joint networks are the solutions that join simplicity and economy of Ethernet at IP/MPLS scale. Different transfer technologies have been used in MAN so metropolitan services should be given on a mixture of optic and data switches, MPLS have been developed for this work and using generalized-MPLS makes MPLS deployments possible even on none-IP-aware switches. At first, theories about using MAN technology to produce urban networks are explained. Then a set of problems regarding the management of resources and provisioning barriers are introduced following the solutions by means of IP/MPLS network which have been implemented and validated in eSNP simulator. [ABSTRACT FROM AUTHOR]

This article presents analysis and possible reactions of MPLS network on unauthorized access and on device's failure. Five Cisco routers joined into a core network were used to conduct the project. The devices were connected into a classic reliability model with envelope shape. The key aspects of the research were incidents' simulation in line with previously prepared scenarios as well as diagnosis of network's reactions to a particular type of a device failure. These effects were modelled using special devices such as analysers and generators of data traffic. Additionally, the range of the project included measuring convergence time of the routing protocols acting inside the network combined with analysis of reactions to forced changes of route. [ABSTRACT FROM AUTHOR]

Multi Protocol Label Switching (MPLS) has been used to provide traffic engineering and high speed networking. MPLS is an evolving network technology. MPLS is a framework which is introduced by IETF. It is a differentiated and scalable framework. MPLS delivers end-to-end IP services with the use of simple configuration and management. Fault tolerance is an important Quality Of Service factor. Fault tolerance needs to be considered to maintain network survivability. Fault tolerance is very important in every network system because it provides the facility to operate the network if any one or more parts of the system are damaged. The network devices are enabled by MPLS to specify path based on quality of service and bandwidth. The main use of MPLS technology is to speed up the network flow with the use of labels. [ABSTRACT FROM AUTHOR]

The emergence of new kinds of applications and technologies (e.g., data-intensive applications, server virtualization, and big data technology) has led to a higher utilization of network resources. These services imply increased bandwidth consumption and unexpected congestions, especially in backbones. In this article, a novel proposal is studied with the aim of improving the performance of prioritized forwarding equivalence classes in congested Multiprotocol Label Switching Transport Profile (MPLS-TP) domains. The congestion impact on those QoS-aware services that require high reliability and low delay is analyzed. A new policy has been implemented on MPLS-TP, which is a technology that provides QoS by means of flow differentiation in the Internet backbones. The proposal is known as Gossip-based local recovery policy and is offered as an operation, administration, and management function to allow local recovery of lost traffic for MPLS-TP privileged forwarding equivalence classes. In order to fulfill the requirements for implementation on MPLS-TP, a minimum set of extensions to resource reservation protocol traffic engineering has also been proposed to provide self-management capable routes. Finally, we have carried out a performance improvement measurement by means of an analytical model and simulations. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]