Showing papers on "Network topology published in 2015"

Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks

Abstract: A Long Short-Term Memory (LSTM) network is a type of recurrent neural network architecture which has recently obtained strong results on a variety of sequence modeling tasks. The only underlying LSTM structure that has been explored so far is a linear chain. However, natural language exhibits syntactic properties that would naturally combine words to phrases. We introduce the Tree-LSTM, a generalization of LSTMs to tree-structured network topologies. TreeLSTMs outperform all existing systems and strong LSTM baselines on two tasks: predicting the semantic relatedness of two sentences (SemEval 2014, Task 1) and sentiment classification (Stanford Sentiment Treebank).

Jupiter Rising: A Decade of Clos Topologies and Centralized Control in Google's Datacenter Network

Abstract: We present our approach for overcoming the cost, operational complexity, and limited scale endemic to datacenter networks a decade ago. Three themes unify the five generations of datacenter networks detailed in this paper. First, multi-stage Clos topologies built from commodity switch silicon can support cost-effective deployment of building-scale networks. Second, much of the general, but complex, decentralized network routing and management protocols supporting arbitrary deployment scenarios were overkill for single-operator, pre-planned datacenter networks. We built a centralized control mechanism based on a global configuration pushed to all datacenter switches. Third, modular hardware design coupled with simple, robust software allowed our design to also support inter-cluster and wide-area networks. Our datacenter networks run at dozens of sites across the planet, scaling in capacity by 100x over ten years to more than 1Pbps of bisection bandwidth.

A Survey of In-Band Full-Duplex Transmission: From the Perspective of PHY and MAC Layers

Abstract: In-band full-duplex (IBFD) transmission represents an attractive option for increasing the throughput of wireless communication systems A key challenge for IBFD transmission is reducing self-interference Fortunately, the power associated with residual self-interference can be effectively canceled for feasible IBFD transmission with combinations of various advanced passive, analog, and digital self-interference cancellation schemes In this survey paper, we first review the basic concepts of IBFD transmission with shared and separated antennas and advanced self-interference cancellation schemes Furthermore, we also discuss the effects of IBFD transmission on system performance in various networks such as bidirectional, relay, and cellular topology networks This survey covers a wide array of technologies that have been proposed in the literature as feasible for IBFD transmission and evaluates the performance of the IBFD systems compared to conventional half-duplex transmission in connection with theoretical aspects such as the achievable sum rate, network capacity, system reliability, and so on We also discuss the research challenges and opportunities associated with the design and analysis of IBFD systems in a variety of network topologies This work also explores the development of MAC protocols for an IBFD system in both infrastructure-based and ad hoc networks Finally, we conclude our survey by reviewing the advantages of IBFD transmission when applied for different purposes, such as spectrum sensing, network secrecy, and wireless power transfer

Distributed Consensus Strategy for Platooning of Vehicles in the Presence of Time-Varying Heterogeneous Communication Delays

Abstract: We analyze and solve the platooning problem by treating it as the problem of achieving consensus in a network of dynamical systems affected by time-varying heterogeneous delays due to wireless communication among vehicles Specifically, a platoon is modeled as a dynamical network where: 1) each vehicle, with its own dynamics, is a node; 2) the presence of communication links between neighboring vehicles is represented by edges; and 3) the structure of the intervehicle communication is encoded in the network topology A distributed control protocol, which acts on every vehicle in the platoon, is derived It is composed of two terms: a local action depending on the state variables of the vehicle itself (measured onboard) and an action depending on the information received from neighboring vehicles through the communication network The stability of the platoon is proven by using Lyapunov–Razumikhin theorem Numerical results are included to confirm and illustrate the theoretical derivation

SPHINX: Detecting Security Attacks in Software-Defined Networks.

Abstract: Software-defined networks (SDNs) allow greater control over network entities by centralizing the control plane, but place great burden on the administrator to manually ensure security and correct functioning of the entire network. We list several attacks on SDN controllers that violate network topology and data plane forwarding, and can be mounted by compromised network entities, such as end hosts and soft switches. We further demonstrate their feasibility on four popular SDN controllers. We propose SPHINX to detect both known and potentially unknown attacks on network topology and data plane forwarding originating within an SDN. SPHINX leverages the novel abstraction of flow graphs, which closely approximate the actual network operations, to enable incremental validation of all network updates and constraints. SPHINX dynamically learns new network behavior and raises alerts when it detects suspicious changes to existing network control plane behavior. Our evaluation shows that SPHINX is capable of detecting attacks in SDNs in realtime with low performance overheads, and requires no changes to the controllers for deployment.

Heuristic Approaches to the Controller Placement Problem in Large Scale SDN Networks

Abstract: Software Defined Networking (SDN) marks a paradigm shift towards an externalized and logically centralized network control plane. A particularly important task in SDN architectures is that of controller placement, i.e., the positioning of a limited number of resources within a network to meet various requirements. These requirements range from latency constraints to failure tolerance and load balancing. In most scenarios, at least some of these objectives are competing, thus no single best placement is available and decision makers need to find a balanced trade-off. This work presents POCO, a framework for Pareto-based Optimal COntroller placement that provides operators with Pareto optimal placements with respect to different performance metrics. In its default configuration, POCO performs an exhaustive evaluation of all possible placements. While this is practically feasible for small and medium sized networks, realistic time and resource constraints call for an alternative in the context of large scale networks or dynamic networks whose properties change over time. For these scenarios, the POCO toolset is extended by a heuristic approach that is less accurate, but yields faster computation times. An evaluation of this heuristic is performed on a collection of real world network topologies from the Internet Topology Zoo. Utilizing a measure for quantifying the error introduced by the heuristic approach allows an analysis of the resulting trade-off between time and accuracy. Additionally, the proposed methods can be extended to solve similar virtual functions placement problems which appear in the context of Network Functions Virtualization (NFV).

Virtual network functions placement and routing optimization

Abstract: Network Functions Virtualization (NFV) is incrementally deployed by Internet Service Providers (ISPs) in their carrier networks, by means of Virtual Network Function (VNF) chains, to address customers' demands. The motivation is the increasing manageability, reliability and performance of NFV systems, the gains in energy and space granted by virtualization, at a cost that becomes competitive with respect to legacy physical network function nodes. From a network optimization perspective, the routing of VNF chains across a carrier network implies key novelties making the VNF chain routing problem unique with respect to the state of the art: the bitrate of each demand flow can change along a VNF chain, the VNF processing latency and computing load can be a function of the demands traffic, VNFs can be shared among demands, etc. In this paper, we provide an NFV network model suitable for ISP operations. We define the generic VNF chain routing optimization problem and devise a mixed integer linear programming formulation. By extensive simulation on realistic ISP topologies, we draw conclusions on the trade-offs achievable between legacy Traffic Engineering (TE) ISP goals and novel combined TE-NFV goals.

An Optimal and Distributed Method for Voltage Regulation in Power Distribution Systems

Abstract: This paper addresses the problem of voltage regulation in power distribution networks with deep-penetration of distributed energy resources, e.g., renewable-based generation, and storage-capable loads such as plug-in hybrid electric vehicles. We cast the problem as an optimization program, where the objective is to minimize the losses in the network subject to constraints on bus voltage magnitudes, limits on active and reactive power injections, transmission line thermal limits and losses. We provide sufficient conditions under which the optimization problem can be solved via its convex relaxation. Using data from existing networks, we show that these sufficient conditions are expected to be satisfied by most networks. We also provide an efficient distributed algorithm to solve the problem. The algorithm adheres to a communication topology described by a graph that is the same as the graph that describes the electrical network topology. We illustrate the operation of the algorithm, including its robustness against communication link failures, through several case studies involving 5-, 34-, and 123-bus power distribution systems.

Impedance-Source Networks for Electric Power Conversion Part II: Review of Control and Modulation Techniques

Abstract: Impedance-source networks cover the entire spectrum of electric power conversion applications (dc-dc, dc-ac, ac-dc, ac-ac) controlled and modulated by different modulation strategies to generate the desired dc or ac voltage and current at the output. A comprehensive review of various impedance-source-network-based power converters has been covered in a previous paper and main topologies were discussed from an application point of view. Now Part II provides a comprehensive review of the most popular control and modulation strategies for impedance-source network-based power converters/inverters. These methods are compared in terms of theoretical complexity and performance, when applied to the respective switching topologies. Further, this paper provides as a guide and quick reference for researchers and practicing engineers in deciding which control and modulation method to consider for an application in a given topology at a certain power level, switching frequency and demanded dynamic response.

On orchestrating virtual network functions

Abstract: Middleboxes or network appliances like firewalls, proxies, and WAN optimizers have become an integral part of today's ISP and enterprise networks. Middlebox functionalities are usually deployed on expensive and proprietary hardware that require trained personnel for deployment and maintenance. Middleboxes contribute significantly to a network's capital and operational costs. In addition, organizations often require their traffic to pass through a specific sequence of middleboxes for compliance with security and performance policies. This makes the middlebox deployment and maintenance tasks even more complicated. Network Function Virtualization (NFV) is an emerging and promising technology that is envisioned to overcome these challenges. It proposes to move packet processing from dedicated hardware middleboxes to software running on commodity servers. In NFV terminology, software middleboxes are referred to as Virtual Network Functions (VNFs). It is a challenging problem to determine the required number and placement of VNFs that optimize network operational costs and utilization, without violating service level agreements. We call this the VNF Orchestration Problem (VNF-OP) and provide an Integer Linear Programming (ILP) formulation with implementation in CPLEX. We also provide a dynamic programming based heuristic to solve larger instances of VNF-OP. Trace driven simulations on real-world network topologies demonstrate that the heuristic can provide solutions that are within 1.3 times of the optimal solution. Our experiments suggest that a VNF based approach can provide more than 4 χ reduction in the operational cost of a network.

Convex Relaxation for Optimal Power Flow Problem: Mesh Networks

Abstract: This paper is concerned with the optimal power flow (OPF) problem. We have recently shown that a convex relaxation based on semidefinite programming (SDP) is able to find a global solution of OPF for IEEE benchmark systems, and moreover this technique is guaranteed to work over acyclic (distribution) networks. The present work studies the potential of the SDP relaxation for OPF over mesh (transmission) networks. First, we consider a simple class of cyclic systems, namely weakly-cyclic networks with cycles of size 3. We show that the success of the SDP relaxation depends on how the line capacities are modeled mathematically. More precisely, the SDP relaxation is proven to succeed if the capacity of each line is modeled in terms of bus voltage difference, as opposed to line active power, apparent power or angle difference. This result elucidates the role of the problem formulation. Our second contribution is to relate the rank of the minimum-rank solution of the SDP relaxation to the network topology. The goal is to understand how the computational complexity of OPF is related to the underlying topology of the power network. To this end, an upper bound is derived on the rank of the SDP solution, which is expected to be small in practice. A penalization method is then applied to the SDP relaxation to enforce the rank of its solution to become 1, leading to a near-optimal solution for OPF with a guaranteed optimality degree. The remarkable performance of this technique is demonstrated on IEEE systems with more than 7000 different cost functions.

Presto: Edge-based Load Balancing for Fast Datacenter Networks

Abstract: Datacenter networks deal with a variety of workloads, ranging from latency-sensitive small flows to bandwidth-hungry large flows. Load balancing schemes based on flow hashing, e.g., ECMP, cause congestion when hash collisions occur and can perform poorly in asymmetric topologies. Recent proposals to load balance the network require centralized traffic engineering, multipath-aware transport, or expensive specialized hardware. We propose a mechanism that avoids these limitations by (i) pushing load-balancing functionality into the soft network edge (e.g., virtual switches) such that no changes are required in the transport layer, customer VMs, or networking hardware, and (ii) load balancing on fine-grained, near-uniform units of data (flowcells) that fit within end-host segment offload optimizations used to support fast networking speeds. We design and implement such a soft-edge load balancing scheme, called Presto, and evaluate it on a 10 Gbps physical testbed. We demonstrate the computational impact of packet reordering on receivers and propose a mechanism to handle reordering in the TCP receive offload functionality. Presto's performance closely tracks that of a single, non-blocking switch over many workloads and is adaptive to failures and topology asymmetry.

Pinning Synchronization of Directed Networks With Switching Topologies: A Multiple Lyapunov Functions Approach

Abstract: This paper studies the global pinning synchronization problem for a class of complex networks with switching directed topologies. The common assumption in the existing related literature that each possible network topology contains a directed spanning tree is removed in this paper. Using tools from $M$ -matrix theory and stability analysis of the switched nonlinear systems, a new kind of network topology-dependent multiple Lyapunov functions is proposed for analyzing the synchronization behavior of the whole network. It is theoretically shown that the global pinning synchronization in switched complex networks can be ensured if some nodes are appropriately pinned and the coupling is carefully selected. Interesting issues of how many and which nodes should be pinned for possibly realizing global synchronization are further addressed. Finally, some numerical simulations on coupled neural networks are provided to verify the theoretical results.

Interference-Based Topology Control Algorithm for Delay-Constrained Mobile Ad Hoc Networks

Abstract: As the foundation of routing, topology control should minimize the interference among nodes, and increase the network capacity. With the development of mobile ad hoc networks (MANETs), there is a growing requirement of quality of service (QoS) in terms of delay. In order to meet the delay requirement, it is important to consider topology control in delay constrained environment, which is contradictory to the objective of minimizing interference. In this paper, we focus on the delay-constrained topology control problem, and take into account delay and interference jointly. We propose a cross-layer distributed algorithm called interference-based topology control algorithm for delay-constrained (ITCD) MANETs with considering both the interference constraint and the delay constraint, which is different from the previous work. The transmission delay, contention delay and the queuing delay are taken into account in the proposed algorithm. Moreover, the impact of node mobility on the interference-based topology control algorithm is investigated and the unstable links are removed from the topology. The simulation results show that ITCD can reduce the delay and improve the performance effectively in delay-constrained mobile ad hoc networks.

Synchronization of Nonlinear Coupled Networks via Aperiodically Intermittent Pinning Control

Abstract: In this paper, pinning synchronization problem for nonlinear coupled networks is investigated, which can be recurrently connected neural networks, cellular neural networks, Hodgkin–Huxley models, Lorenz chaotic oscillators, and so on. Nodes in the network are assumed to be identical and nodes’ dynamical behaviors are described by continuous-time equations. The network topology is undirected and static. At first, the scope of accepted nonlinear coupling functions is defined, and the effect of nonlinear coupling functions on synchronization is carefully discussed. Then, the pinning control technique is used for synchronization, especially the control type is aperiodically intermittent. Some sufficient conditions to guarantee global synchronization are presented. Furthermore, the adaptive approach is also applied on the pinning control, and a centralized adaptive algorithm is designed and its validity is also proved. Finally, several numerical simulations are given to verify the obtained theoretical results.

Physarum Optimization: A Biology-Inspired Algorithm for the Steiner Tree Problem in Networks

Abstract: Using insights from biological processes could help to design new optimization techniques for long-standing computational problems. This paper exploits a cellular computing model in the slime mold physarum polycephalum to solve the Steiner tree problem which is an important NP-hard problem in various applications, especially in network design. Inspired by the path-finding and network formation capability of physarum, we develop a new optimization algorithm, named as the physarum optimization, with low complexity and high parallelism. To validate and evaluate our proposed models and algorithm, we further apply the physarum optimization to the minimal exposure problem which is a fundamental problem corresponding to the worst-case coverage in wireless sensor networks. Complexity analysis and simulation results show that our proposed algorithm could achieve good performance with low complexity. Moreover, the core mechanism of our physarum optimization also may provide a useful starting point to develop some practical distributed algorithms for network design.

Revealing the Hidden Language of Complex Networks

Abstract: Sophisticated methods for analysing complex networks promise to be of great benefit to almost all scientific disciplines, yet they elude us In this work, we make fundamental methodological advances to rectify this We discover that the interaction between a small number of roles, played by nodes in a network, can characterize a network’s structure and also provide a clear real-world interpretation Given this insight, we develop a framework for analysing and comparing networks, which outperforms all existing ones We demonstrate its strength by uncovering novel relationships between seemingly unrelated networks, such as Facebook, metabolic, and protein structure networks We also use it to track the dynamics of the world trade network, showing that a country’s role of a broker between non-trading countries indicates economic prosperity, whereas peripheral roles are associated with poverty This result, though intuitive, has escaped all existing frameworks Finally, our approach translates network topology into everyday language, bringing network analysis closer to domain scientists

Expansion Model for the Controller Placement Problem in Software Defined Networks

Abstract: In this letter, we propose a mathematical model for the controller placement problem in Software Defined Networks (SDN). More precisely, given a set of switches that must be managed by the controller(s), the model simultaneously determines the optimal number, location, and type of controller(s) as well as the interconnections between all the network elements. The goal of the model is to minimize the cost of the network while considering different constraints. The simulation results show that the model can be used to plan small scale SDN. When trying to solve larger instances of the problem, the solver is taking too much time and also running out of memory. The proposed model could be used by various enterprises and cloud-based networks to start integrating SDN or plan a new SDN.

Dynamic fluctuations in global brain network topology characterize functional states during rest and behavior

Abstract: Higher brain function relies upon the ability to flexibly integrate information across specialized communities of macroscopic brain regions, but it is unclear how this mechanism manifests over time. Here we characterized patterns of time-resolved functional connectivity using resting state and task fMRI data from a large cohort of unrelated subjects. Our results demonstrate that dynamic fluctuations in network structure during the resting state reflect transitions between states of integrated and segregated network topology. These patterns were altered during task performance, demonstrating a higher level of network integration that tracked with the complexity of the task and correlated with effective behavioral performance. Replication analysis demonstrated that these results were reproducible across sessions, sample populations and datasets. Together these results provide insight into the brain's coordination between integration and segregation and highlight key principles underlying the reorganization of the network architecture of the brain during both rest and behavior.

The Relative Ineffectiveness of Criminal Network Disruption

Abstract: Researchers, policymakers and law enforcement agencies across the globe struggle to find effective strategies to control criminal networks. The effectiveness of disruption strategies is known to depend on both network topology and network resilience. However, as these criminal networks operate in secrecy, data-driven knowledge concerning the effectiveness of different criminal network disruption strategies is very limited. By combining computational modeling and social network analysis with unique criminal network intelligence data from the Dutch Police, we discovered, in contrast to common belief, that criminal networks might even become ‘stronger’, after targeted attacks. On the other hand increased efficiency within criminal networks decreases its internal security, thus offering opportunities for law enforcement agencies to target these networks more deliberately. Our results emphasize the importance of criminal network interventions at an early stage, before the network gets a chance to (re-)organize to maximum resilience. In the end disruption strategies force criminal networks to become more exposed, which causes successful network disruption to become a long-term effort.

Distributed Energy Trading: The Multiple-Microgrid Case

Abstract: In this paper, a distributed convex optimization framework is developed for energy trading between islanded microgrids. More specifically, the problem consists of several islanded microgrids that exchange energy flows by means of an arbitrary topology. Due to scalability issues and in order to safeguard local information on cost functions, a subgradient-based cost minimization algorithm that converges to the optimal solution in a practical number of iterations and with limited communication overhead is proposed. Furthermore, this approach allows for a very intuitive economics interpretation that explains the algorithm iterations in terms of a “supply–demand model” and “market clearing.” Numerical results are given in terms of the convergence rate of the algorithm and the attained costs for different network topologies.

An Improved Control System for Modular Multilevel Converters with New Modulation Strategy and Voltage Balancing Control

Abstract: Modular multilevel converter (MMC) has become one of the most promising converter topologies for future high-power applications. A challenging issue of the MMC is the voltage balancing among arm capacitors. A good overall control system is also vital for the MMC, which should be based on sound mathematical model, readily adaptable for different applications, and capable of high performance. This paper presents a general control structure for MMC inverters, which is suitable for both voltage-based and energy-based control methods, and includes voltage balancing between the upper and lower arms. A new method for voltage balancing among arm capacitors, which is based on an improved pulse-width modulation, is also presented. The proposed method avoids some major disadvantages found in present voltage balancing methods, such as dependence on computation-intensive voltage sorting algorithms, extra switching actions, interference with output voltage, etc. Furthermore, all switching actions are evenly distributed among power devices. The proposed control system as a whole can serve as a promising solution for practical applications, especially when the number of submodules is fairly high. Simulation and experimental results verify the effectiveness of the proposed methods.

Modeling of Local False Data Injection Attacks With Reduced Network Information

Abstract: Modern power grids are becoming more prone to cyberattacks. Even worse, an attacker without the full topology and parameter information of a power grid can still execute a false data injection attack without being detected by the state estimator. This paper proposes an efficient strategy for determining the optimal attacking region that requires reduced network information. The effectiveness of the proposed algorithm is verified through extensive simulations. This paper introduces a new front in the study of smart grid cyber security: determination of a feasible attacking region by obtaining less network information. This paper is also essential and significant for finding effective protection strategies against false data injection attacks based on the deep understanding of the mechanisms and strategies of the attacks.

Optimizing User Association and Spectrum Allocation in HetNets: A Utility Perspective

Abstract: The joint user association and spectrum allocation problem is studied for multi-tier heterogeneous networks (HetNets) in both downlink and uplink in the interference-limited regime. Users are associated with base-stations (BSs) based on the biased downlink received power. Spectrum is either shared or orthogonally partitioned among the tiers. This paper models the placement of BSs in different tiers as spatial point processes and adopts stochastic geometry to derive the theoretical mean proportionally fair utility of the network based on the coverage rate. By formulating and solving the network utility maximization problem, the optimal user association bias factors and spectrum partition ratios are analytically obtained for the multi-tier network. The resulting analysis reveals that the downlink and uplink user associations do not have to be symmetric. For uplink under spectrum sharing, if all tiers have the same target signal-to-interference ratio (SIR), distance-based user association is shown to be optimal under a variety of path loss and power control settings. For both downlink and uplink, under orthogonal spectrum partition, it is shown that the optimal proportion of spectrum allocated to each tier should match the proportion of users associated with that tier. Simulations validate the analytical results. Under typical system parameters, simulation results suggest that spectrum partition performs better for downlink in terms of utility, while spectrum sharing performs better for uplink with power control.

Smart Meter Data Analytics for Distribution Network Connectivity Verification

Abstract: Many utilities have the data quality problem with the geographical information system (GIS) records at distribution level This affects many business functions of a utility, including asset management, outage response, and workforce safety For correcting connectivity errors in the GIS representation of the distribution network topology, BC Hydro has developed an in-house algorithm The algorithm leverages smart meter interval measurements and identifies the neighboring meters by voltage profile correlation analysis It also predicts customers’ upstream and downstream location relationship by voltage magnitude comparisons The output of the algorithm is then compared with the existing GIS records to correct any errors in it This paper presents in detail the algorithm and the promising testing results within the practical BC Hydro system Challenges for underground services are demonstrated The algorithm’s potential use for phase detection by collectively leveraging smart meter and feeder meter data is explored It shows encouraging results when applied in a downstream section of a large feeder