Interconnection Topology Research Articles

Benchmarking Quantum Annealing Against \u201cHard\u201d Instances of the Bipartite Matching Problem

This paper experimentally investigates the behavior of analog quantum computers as commercialized by D-Wave when confronted to instances of the maximum cardinality matching problem which is specifically designed to be hard to solve by means of simulated annealing. We benchmark a D-Wave “Washington” (2X) with 1098 operational qubits on various sizes of such instances and observe that for all but the most trivially small of these it fails to obtain an optimal solution. Thus, our results suggest that quantum annealing, at least as implemented in a D-Wave device, falls in the same pitfalls as simulated annealing and hence provides additional evidences suggesting that there exist polynomial-time problems that such a machine cannot solve efficiently to optimality. Additionally, we investigate the extent to which the qubits interconnection topologies explains these latter experimental results. In particular, we provide evidences that the sparsity of these topologies which, as such, lead to QUBO problems of artificially inflated sizes can partly explain the aforementioned disappointing observations. Therefore, this paper hints that denser interconnection topologies are necessary to unleash the potential of the quantum annealing approach.

Dynamic event-triggered distributed filtering design for interval type-2 fuzzy systems over sensor networks under deception attacks

This article investigates the event-based distributed filtering design issue for interval type-2 (IT2) fuzzy systems over sensor networks under deception attacks. In sensor networks, while each sensor receives its measurement value, it can also sense neighbouring one's measurement based on the interconnected topology, thereby estimating system states. To reduce redundant transmission, a novel distributed dynamic event-triggered mechanism (DETM) is introduced to each sensor node. In particular, the proposed DETM contains an internal dynamic variable, which is a filtered version of the trigger event signal to increase the interval between two consecutive event triggers. Then, a new distributed filter error fuzzy system is well constructed under the consideration of DETM, networked-induced delay, and random deception attacks. To relax stability conditions, slack matrices with membership functions (MFs) information are used in the stability analysis. Furthermore, based on Lyapunov–Krasovskii functional approach, membership-functions-dependent sufficient criteria are obtained to ensure the established filter error fuzzy system is mean-square stability with performance. Two examples are finally shown to demonstrate the effectiveness of the filtering method.

Resilient Scheduling of Networked Microgrids Against Real-Time Failures

Integrating microgrids within distribution systems can significantly improve the power system’s reliability while reducing operating costs. However, due to the unintentional disaster conditions, sometimes distribution systems and microgrids cannot support each other, and the microgrids are forced to work in the islanded mode. Accordingly, we developed an optimal resilient scheduling scheme that guarantees networked microgrids (NMGs) reliable operation in the normal and islanding modes. To achieve this aim, the problem is decomposed into day-ahead normal operation (grid-connected) and real-time islanded examination by benders decomposition algorithm perspective. The specified scheme of NMGs in the normal operation will be scrutinized in the real-time islanded mode. According to the benders decomposition theory, the scheduling of NMGs would be revised in the next iteration if the current schedule is not feasible for possible real-time islanding conditions. The status of thermal units, charging, and discharging of energy storage systems respecting their other constraints are changed depending on the type and severity of mismatches between generation and demand. Three different interconnection topologies are tested for assessing the performance of the proposed method and the impact of transaction energy between NMGs on that. Numerical simulations illustrate the advantages of the proposed scheme and explain its merits.

Stability of cluster formations in adaptive Kuramoto networks

This paper studies stability properties of multi-cluster formations in Kuramoto networks with adaptive coupling. Sufficient conditions for the local asymptotic stability of the corresponding synchronization invariant toroidal manifold are derived and formulated in terms of the intra-cluster interconnection topology and plasticity parameters of the adaptive couplings. The proposed sufficient stability conditions qualitatively mimic certain counterpart results for Kuramoto networks with static coupling which require sufficiently strong and dense intra-cluster connections and sufficiently weak and sparse inter-cluster ones. Remarkably, the existence of cluster formations depends on the interconnection structure between nodes belonging to different clusters and does not require any coupling links between nodes that form a cluster. On the other hand, the stability properties of clusters depend on the interconnection structure inside the clusters. This dependence constitutes the main contribution of the paper. Also, a numerical example is provided to validate the proposed theoretical findings.

Large-Scale Discrete Fourier Transform on TPUs

In this work, we present two parallel algorithms for the large-scale discrete Fourier transform (DFT) on Tensor Processing Unit (TPU) clusters. The two parallel algorithms are associated with two DFT formulations: one formulation, denoted as KDFT, is based on the Kronecker product; the other is based on the famous Cooley-Tukey algorithm and phase adjustment, denoted as FFT. Both KDFT and FFT formulations take full advantage of TPU's strength in matrix multiplications. The KDFT formulation allows direct use of nonuniform inputs without additional step. In the two parallel algorithms, the same strategy of data decomposition is applied to the input data. Through the data decomposition, the dense matrix multiplications in KDFT and FFT are kept local within TPU cores, which can be performed completely in parallel. The communication among TPU cores is achieved through the one-shuffle scheme in both parallel algorithms, with which sending and receiving data takes place simultaneously between two neighboring cores and along the same direction on the interconnect network. The one-shuffle scheme is designed for the interconnect topology of TPU clusters, minimizing the time required by the communication among TPU cores. Both KDFT and FFT are implemented in TensorFlow. The three-dimensional complex DFT is performed on an example of dimension 8192 ×8192 ×8192 with a full TPU Pod: the run time of KDFT is 12.66 seconds and that of FFT is 8.3 seconds. Scaling analysis is provided to demonstrate the high parallel efficiency of the two DFT implementations on TPUs.

P-cloth

We present a novel parallel algorithm for cloth simulation that exploits multiple GPUs for fast computation and the handling of very high resolution meshes. To accelerate implicit integration, we describe new parallel algorithms for sparse matrix-vector multiplication (SpMV) and for dynamic matrix assembly on a multi-GPU workstation. Our algorithms use a novel work queue generation scheme for a fat-tree GPU interconnect topology. Furthermore, we present a novel collision handling scheme that uses spatial hashing for discrete and continuous collision detection along with a non-linear impact zone solver. Our parallel schemes can distribute the computation and storage overhead among multiple GPUs and enable us to perform almost interactive simulation on complex cloth meshes, which can hardly be handled on a single GPU due to memory limitations. We have evaluated the performance with two multi-GPU workstations (with 4 and 8 GPUs, respectively) on cloth meshes with 0.5 -- 1.65 M triangles. Our approach can reliably handle the collisions and generate vivid wrinkles and folds at 2 -- 5 fps, which is significantly faster than prior cloth simulation systems. We observe almost linear speedups with respect to the number of GPUs.

Continuous Genetic Algorithms in the Optimization of Logistic Networks: Applicability Assessment and Tuning

Globalization opens up new perspectives for handling goods distribution in logistic networks. However, establishing an efficient inventory policy is challenging by virtue of the analytical and computational complexity. In this study, the goods distribution process that was governed by the order-up-to policy, implemented in either a distributed or centralized way, was investigated in the logistic systems with complex interconnection topologies. Uncertain demand may be imposed at any node, not just at conveniently chosen contact points, with a lost-sales assumption that introduces a non-linearity into the node dynamics. In order to adjust the policy parameters, the continuous genetic algorithm (CGA) was applied, with the fitness function incorporating both the operational costs and customer satisfaction level. This study investigated how to select the parameters of the popular inventory management policy when operating in the non-trivial networked structures. Moreover, precise guidelines for the CGA tuning in the considered class of problems were provided and evaluated in extensive numerical experiments.

Аналіз захищеності інтернет-вузлів від кібератак типу «перехоплення маршруту»

Cyberattacks on global routing on the global computer network Internet (route hijack, route leak) lead to large-scale consequences with violation of data integrity, availability and confidentiality during the process of internetwork data exchange. Threats to BGP-4 routing protocol can’t be fully mitigated neither in short-term nor in long term. None of proposed and partially implemented upgrades and add-ons like Mutually Agreed Norms for Routing Security (MANRS) and Resource Public Key Infrastructure (RPKI) can not deliver reliable protection against those types of attacks.Recent information security and data protection technics are based on risk management. A new risk-oriented approach to improving the topology of network interconnections in order to increase the security of internetwork data exchange is described. The new approach is based on applying new topology-related metrics to the Internet nodes, that is autonomous systems (AS). The criterion for the effectiveness of the topology against attacks on global routing is risk assessment as a measure of information security.Assessing the risks of route hijack requires quantitative measurement of the impact of an attack e.g. the scope of routing distortion. The risk for risk owner of hijacking hist route on a particular node in the network depends on the distance between the AS. Close nodes have more trust, so the first proposed metrics is called trust metrics. A kind of node centrality or significance is considered because it affects the losses estimation. Such significance derives from the number of network prefixes (i.e subnets) which receive routing announces through this particular node. Ranking nodes by this metrics requires methods for retrieving and processing routing tables. In this paper we describe the sources, methods of processing, and examine several ASes from Ukrainian segment of the Internet on the significance metrics. Well-known Internet exchanges of Ukraine, and then all large telco operators appeared to be the most significant Internet nodes. This demonstrates the adequacy of the represented methodology. Tabl.: 1. Fig.: 3. Refs: 9 titles.

Experimental Investigation of PV Array Interconnection Topologies at Nonuniform Aging Condition for Power Maximization

In vast Photovoltaic (PV) power plant the output power production decreases significantly due to the fact of non-uniform aging of PV modules. The non-uniform aging of PV modules increases current-voltage (I-V) mismatch among the array modules and causes mismatch power loss (MPL). There are different interconnection topologies of the PV module in an array to minimize MPL and thus maximize the array output power. This paper investigates four different interconnection topologies experimentally on a 4×4 nonuniformly aged PV array. Three different patterns of PV module rearrangement are used to investigate the performance of each interconnection topology in terms of array output power and MPL. The experimental results show that the proposed interconnection topology is yields about 3.28% (average) higher output power than that of the most commonly used series-parallel array topology.
 GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 6(1), Dec 2019 P 39-45

LaScaDa: A Novel Scalable Topology for Data Center Network

The growth of cloud-based services is mainly supported by the core networking infrastructures of large-scale data centers, while the scalability of these services is influenced by the performance and dependability characteristics of data centers. Hence, the data center network must be agile and reconfigurable in order to respond quickly to the ever-changing application demands and service requirements. The network must also be able to interconnect the big number of nodes, and provide an efficient and fault-tolerant routing service to upper-layer applications. In response to these challenges, the research community began exploring novel interconnect topologies, namely: Flecube, DCell, Ficonn, HyperFlaNet and BCube. However, these topologies either scale too fast (grows exponentially in size), or too slow, and therefore suffer from performance bottlenecks. In this paper, we propose a novel data center topology called LaScaDa (Layered Scalable Data Center) as a new solution for building scalable and cost-effective data center networking infrastructures. The proposed topology organizes nodes in clusters of similar structure, then interconnect these clusters in a well-crafted pattern and system of coordinates for nodes to reduce the number of redundant connections between clusters, while maximizing connectivity. LaScaDa forwards packets between nodes using a new hierarchical row-based routing algorithm. The algorithm constructs the route to the source based on the modular difference between the source and destination coordinates. Furthermore, the proposed topology interconnects a large number of nodes using a small node degree. This strategy increases the number of directly connected clusters and avoids redundant connections. As a result, we get a good quality of nodes in terms of average path length (APL), bisection bandwidth, and aggregated bottleneck throughput. Experimental results show that LaScaDa has better performance than DCell, BCube, and HyperBcube in terms of scalability, while providing a good quality of service.

An Emerging Dynamics Approach for Synchronization of Linear Heterogeneous Agents Interconnected Over Switching Topologies

In this letter, we propose an emergent dynamics based tool to approximate the synchronized behavior in large networks of interconnected linear systems with switching interconnection topologies and linear coupling. We assume that the networks are heterogeneous, but the states of all systems are of the same dimension. The goal of this letter is to show that, in the case of sufficiently large coupling gains, the network is practically synchronized, and its' synchronized behavior can be approximated by a reduced order switching system independent of the control gains. The results are ensured for strongly connected networks under fairly mild assumptions by introducing a minimum dwell-time between two consecutive switches. Numerical simulations illustrate the theoretical results.

The Cost of Scaling a Reliable Interconnection Topology

In distributed computing, many papers try to evaluate the message complexity of a distributed system as a function of the number of nodes $n$ n . But what about the cost of building the distributed system itself? Assuming that we want to reliably connect $n$ n nodes, how does the total number of nodes of the network evolve with $n$ n ? Addressing such a question lies at the heart of achieving scalability in cloud computing. In this paper, we give the explicit description of a distributed system of which any two of the $n$ n nodes, for any $n$ n , remain connected (by a path of alive nodes and channels) with probability at least $\mu$ μ , despite the very fact that (a) every other node or channel has an independent probability $\lambda$ λ of failing, and (b) the number of channels connected to every node is physically bounded by a constant. We show however that if we also require any two of the $n$ n nodes to maintain a balanced message throughput with a constant probability, then $O(n \log ^{1+\epsilon } n)$ O ( n log 1 + e n ) additional intermediary nodes are sufficient, where $\epsilon > 0$ e > 0 is an arbitrarily small constant.

Evolving optical interconnection topology: from survivable rings to resilient meshes

Physical topologies are evolving from elementary survivable rings into complex mesh networks. Nevertheless, no topology model is known to provide an economic, systematic, and flexible interconnection paradigm for ensuring that those meshes bear resilience features. This paper argues that intrinsic resilience can be brought by twin graph topologies, as they satisfy equal length disjoint path property with minimal number of physical links. Also, they benefit from property preserving recursive methods to graciously scale up/down and merge/split topologies. An exhaustive investigation is performed across twin graph families composing networks from 4 to 17 nodes, whereas diverse real-world topologies and ring networks are used as benchmarks. First, we illustrate the growing and the merging processes, and discuss the topology diversity of twin graphs. We analyze the impact of single cable cuts between neighbouring nodes, then we stress topologies with 2, 3, and 4 simultaneous cable cuts. Improved resiliency is seen for neighbor nodes and also reduction of cut sets able to disconnect the twin topologies in comparison with real-world networks. At transport layer, we derive and validate an upper bound for additional capacity required to implement $$1+1$$ path dedicated protection. As networks grow larger, this protection cost is consistently reduced compared to benchmark topologies. We also test the suitability of our approach at optical layer regarding transponders consumption. Finally, we present as a use case the redesign of CESNET into a resilient network.

Synchronization and Multicluster Capabilities of Oscillatory Networks With Adaptive Coupling

We prove the existence of a multidimensional nontrivial invariant toroidal manifold for the Kuramoto network with adaptive coupling. The constructed invariant manifold corresponds to the multicluster behavior of the oscillators phases. Contrary to the static coupling, the adaptive coupling strengths exhibit quasiperiodic oscillations preserving zero phase-difference within clusters. The derived sufficient conditions for the existence of the invariant manifold provide a tradeoff between the natural frequencies of the oscillators, coupling plasticity parameters, and the interconnection structure of the network. Furthermore, we study the robustness of the invariant manifold with respect to the perturbations of the interconnection topology, and establish structural, and quantitative constraints on the perturbation adjacency matrix preserving the invariant manifold. Additionally, we demonstrate the application of the new results to the problem of interconnection topology design, which consists in endowing the desired multicluster behavior to the network by controlling its interconnection structure.

Parametric indicators for partial shading and fault prediction in photovoltaic arrays with various interconnection topologies

Photovoltaic arrays are mainly installed to generate maximum power and serve the load demand. However, the arrays are susceptible to various unpredictable scenarios such as partial shading and electrical faults that reduce the overall performance and result in serious power loss, hotspot formation, and severe damage to the modules. So, partial shading and fault detection algorithms are considered to be an important constituent to avoid unwanted power loss and system failures. Most of the algorithms use the voltage and current variation approach as detecting indicators for shading and faults. However, the array voltage and current can also vary due to certain other factors such as module temperature difference that result in reliability reduction due to false detection. In this paper, the sensitivity of various widely used array topologies to partial shading and electrical faults have been studied using various electrical parametric indicators. The variability of these indicators to shading and faults has been studied for determining the most relevant indicators that can be used for shade and faults detection in all array topologies. Also, the topologies have been studied using the characteristics curves, power generation, and mismatch losses to determine the most fault-tolerant topologies. The entire study has been performed in the MATLAB/Simulink environment and validated using experimental analysis. It has been found that the indicators largely varies to the shading/faults in the arrays and differs for different topologies and can be used to detect/predict faults. Also, it has been found that during minimum (10%) and maximum (90%) system shading, the parallel topology generated higher power nearly equal to 88.95% and 19.48% of the unshaded scenario respectively. However, during 90% system fault, all the topologies generated nearly equal power i.e. 11.27% of the no-fault scenario.

Approximate abstractions of control systems with an application to aggregation

Previous approaches to constructing abstractions for control systems rely on geometric conditions or, in the case of an interconnected control system, a condition on the interconnection topology. Since these conditions are not always satisfiable, we relax the restrictions on the choice of abstractions, instead opting to select ones which nearly satisfy such conditions via optimization-based approaches. To quantify the resulting effect on the error between the abstraction and concrete control system, we introduce the notions of practical simulation functions and practical storage functions. We show that our approach facilitates the procedure of aggregation, where one creates an abstraction by partitioning agents into aggregate areas. We demonstrate the results on an application where we regulate the temperature in three separate zones of a building.

When Are Cyber Blackouts in Modern Service Networks Likely?

Service liability interconnections among globally networked IT- and IoT-driven service organizations create potential channels for cascading service disruptions worth billions of dollars, due to modern cyber-crimes such as DDoS, APT, and ransomware attacks. A natural question that arises in this context is: What is the likelihood of a cyber-blackout? , where the latter term is defined as the probability that all (or a major subset of) organizations in a service chain become dysfunctional in a certain manner due to a cyber-attack at some or all points in the chain. The answer to this question has major implications to risk management businesses such as cyber-insurance when it comes to designing policies by risk-averse insurers for providing coverage to clients in the aftermath of such catastrophic network events. In this article, we investigate this question in general as a function of service chain networks and different cyber-loss distribution types. We show somewhat surprisingly (and discuss the potential practical implications) that, following a cyber-attack, the effect of (a) a network interconnection topology and (b) a wide range of loss distributions on the probability of a cyber-blackout and the increase in total service-related monetary losses across all organizations are mostly very small. The primary rationale behind these results are attributed to degrees of heterogeneity in the revenue base among organizations and the Increasing Failure Rate property of popular (i.i.d/non-i.i.d) loss distributions, i.e., log-concave cyber-loss distributions. The result will enable risk-averse cyber-risk managers to safely infer the impact of cyber-attacks in a worst-case network and distribution oblivious setting.

Inter-connected coupled lines Resonator topology for bandpass filter application

This paper presents an inter-connected side-shorted coupled-line resonator topology as a base cell. The base cell is built from two single-shorted quarter-wavelength coupled-line sections, connected in series to give a half-wavelength coupled-line that creates a single resonance of bandpass filter response. Higher-order bandpass filter is produced by adding new single-shorted coupled-line sections, cascaded in an inter-connected manner to the base cell. This new topology creates a unique arrangement that caused cross coupling effects between the resonators, resulting to the occurrence of transmission zeros that lead to the improvement of selectivity of the higher order bandpass filter response. For validation of concept, 2<sup>nd</sup> and 3<sup>rd</sup> order bandpass filters were fabricated using microstrip technology on Roger 3210 substrate with parameter of <em>Ɛr</em> = 10.2, <em>h</em> = 1.27 mm and <em>tan δ</em> = 3x10-3. The filters were measured and the results show good agreement with simulation results.

Robust containment control for a class of heterogeneous uncertain nonlinear multi-agent systems in lower triangular form

This paper studies the robust containment control problem for a class of nonlinear multi-agent systems in lower triangular form with parameter uncertainty. The agents are heterogenous with the particularity that the dynamics of the leaders are totally different from those of the followers. The interconnection topology is described by a general directed graph. Based on the distributed internal model, the robust containment control problem is first converted into the stabilisation problem for an augmented network. A distributed state feedback control is then proposed to solve the stabilisation problem of the subsequent augmented network by the block backstepping technique. Under the proposed control, all the followers' outputs will converge to the convex hull spanned by the leaders.

Stochastic Pinning Controllability of Noisy Complex Networks

Our ability to coordinate the behavior in networks of complex dynamical systems is often challenged by the presence of noise affecting the individual dynamics and the communication links. In the literature, conservative global conditions guaranteeing the almost sure convergence toward the desired trajectory of a virtual node, the pinner, have been derived. In this article, we identify the minimal conditions on the individual dynamics, interconnection topology, and noise intensities, so that the network exponentially converges onto the pinner's trajectory. Specifically, we broaden the master stability function approach to deal with networks of coupled stochastic differential equations, and provide necessary and sufficient conditions for local exponential pinning controllability of networks of stochastic systems. Interestingly, our analyses show that noise can be either beneficial or detrimental for pinning controllability, depending on how it diffuses in each node. Our analytical findings are illustrated with representative numerical examples.