Flexible Flow Control Research Articles

A large-scale traffic signal control algorithm based on multi-layer graph deep reinforcement learning

Due to its capability in handling complex urban intersection environments, deep reinforcement learning (DRL) has been widely applied in Adaptive Traffic Signal Control (ATSC). However, most existing algorithms are designed for specific road networks or traffic conditions, making it difficult to transfer them to new environments. Moreover, current graph-based algorithms do not fully capture the geometric and spatial features of intersections, leading to incomplete embedding of the agent's environment depiction. Additionally, the actions adopted by these algorithms are inherently based on fixed-cycle phases, limiting the flexibility of traffic signal control. To address the aforementioned issues, this paper proposes a Multi-layer Graph Mask Q-Learning (MGMQ) algorithm for multi-intersection ATSC to optimize traffic and reduce delay. Unlike previous graph-based algorithms, this paper introduces a method for computing multi-layer graphs, dividing the traffic environment into upper-level traffic network-layer graphs and lower-level intersection-layer graphs, and employs the graph attention algorithm and an improved GraphSAGE algorithm for computation. This method not only enables the generation of embedded state for intersections that include geometric and spatial features, but also allows the algorithm to adapt to different traffic conditions and road networks. Additionally, we introduce an action masking mechanism, allowing this algorithm can be adapted to different action spaces. As a result, the algorithm uses arbitrary signal phases as actions to achieve flexible traffic flow control, and can be directly applied to intersections with arbitrary geometry. The final test results demonstrate that a model trained solely on synthetic road networks can be directly transferred to other synthetic network configurations or real-world urban road networks, outperforming current state-of-the-art algorithms.

Arbitrary Wireless Energy Distribution within an Epsilon Near‐zero Environment

AbstractEfficient power distribution to multiple receivers with controlled amounts is critical for wireless communication and sensing systems. Previous efforts have attempted to improve power transfer efficiency through strong coupling and parity‐time (PT) symmetry, providing attractive opportunities for flexible energy flow control. In this study, a novel method for achieving arbitrary power distribution is proposed and numerically demonstrated by leveraging the unique properties inside an epsilon near‐zero (ENZ) environment. Specifically, it shows that the power from a single source can be transferred to multiple receivers inside an ENZ medium with negligible loss by modifying optical properties of receivers rather than introducing sophisticated active control modules. Importantly, full power transfer is independent of the size and shape of the ENZ medium, as well as the positions of the receivers and source. A realizable system is further designed with effective zero index at microwave frequencies to confirm the high efficiency of energy transfer. The innovative approach, employing photonic doping for advanced and efficient wireless power transfer, may shed light on the new generation of energy efficient communication/sensing systems with versatile control functionalities.

Collaborative passenger flow control optimization of urban rail transit network based on sliding window mechanism

In order to enhance the operational performance of urban rail transit networks under overloaded conditions, this study proposes a novel network-level collaborative passenger flow strategy based on a sliding window mechanism. The main idea is to categorize arriving passengers at stations into different groups using variable-length windows and allocate them to specific trains. With the aim of minimizing the total passenger extra waiting time under cost budget, we establish a mixed integer programming model with sliding window constraints, flow distribution constraints, and node flow constraints to build the optimal matching relation between passenger flow demands and transportation resources. Specifically, the model incorporates precise quantity constraints related to transfers, facilitating the accurate quantification of both internal and external demands of network passenger flow. Then we use logical constraint transformation and linearization techniques to enable the model to be solved directly by commercial optimization solvers. For large-scale problems, we adopt a rolling horizon approach to improve computing efficiency. To validate the effectiveness of the sliding-window based passenger control method, we conduct case studies including a small designed example and real-world research on the Beijing Subway network. The experimental results demonstrate that our proposed model assists managers in developing flexible and accurate network-level collaborative passenger flow control schemes.

Distributed Cross-Domain Optimization for Software Defined Industrial Internet of Things

As a promising paradigm, the Industrial Internet of Things (IIoT) provides a wide range of intelligent services through the interconnection and interaction of heterogeneous networks. The quality of these services depends on how the bandwidth is shared among different flows. Hence, it is critical to design a flexible flow control strategy in multi-region management scenarios. In this paper, we establish a flow optimization model based on the IIoT networks managed by multiple Software-Defined Networking (SDN) controllers. Specifically, it jointly optimizes the real-time delivery, route selection, and constrained resource allocation to maximize the total utilities of domains. Since the topology and resources within each domain are kept secret, the problem model belongs to a multi-block problem with coupling constraints, which is difficult to be solved directly. To this end, we first decompose the problem into several intra-domain subproblems, which can be solved in parallel. By considering the inter-domain communication problem, we then introduce the slack variables to implement the interaction among domains. Finally, we design a distributed Proximal Symmetric Alternating Direction Method of Multipliers (Prox-SADMM) algorithm to solve the above joint optimization problem. Through numerical simulations, we investigate the impact of data timeliness, multi-path routing, and resource constraints on the rate utility. The performance analysis confirms that the Prox-SADMM algorithm can be well applied to large-scale networks and provides guidance to set appropriate parameter values according to the realistic requirements of IIoT networks.

Development of Paper Microfluidics with 3D-Printed PDMS Barriers for Flow Control.

Paper microfluidics has been extensively exploited as a powerful tool for environmental and medical detection applications. Both flow delay and compatibility with either polar or non-polar reagents are indispensable for the automation of detections requiring multiple reaction steps. This article reports the systematic studies of a 3D-printing protocol, characterization, and application of both the partially and fully penetrated polydimethylsiloxane (PDMS) barriers for flexible flow control in paper microfluidics. The physical parameters of PDMS barriers printed using a simple liquid dispenser were found related to the printing pressure, speed, diffusion time after printing, baking temperature, and PDMS viscosity. The capability of PDMS barriers to confine the flow of non-polar solvents was demonstrated using oil flow in both wax- and PDMS-surrounded channels. It was identified that the minimum width of channels to prevent leakage was 470 ± 54 μm, which was as narrow as that fabricated using stamps from lithography. Both the partially penetrated barriers (PPBs) and constriction channels were of the capability to delay flow in paper microfluidics. Additionally, an in silico investigation led to the further understanding that the reduction of channel cross-section resulting from PPBs was the primary reason for flow delay. Our results suggest that increasing the penetration depth of the barriers is more efficient in delaying flow than increasing the PPB length. Finally, devices with four inlet channels and 0-6 PPBs across each channel were successfully applied in flow delay for sequential fluid delivery. These results improve the understanding of the major factors, affecting the 3D PDMS barrier fabrication and the resulting flow control in paper microfluidics, providing practical implications for applications in various fields.

HybridFlow: Achieving Load Balancing in Software-Defined WANs With Scalable Routing

The scalability issue hinders the deployment of Software-Defined Networking (SDN) in the Wide Area Networks (WANs). Existing solutions have two issues: (1) network performance relies on complicated controller synchronization, which increases the complexity of network control; (2) fine-grained flow processing enables flexible flow control at the cost of high processing load on the controllers and high flow table occupancy on switches. In this paper, we propose a scalable routing solution named HybridFlow, which achieves a good load balancing performance using a single controller with low control overhead (i.e., flow routing and rerouting overhead). HybridFlow mainly employs two techniques: hybrid routing and crucial flow rerouting. Hybrid routing enabled by commercial SDN switches gives us opportunities to reduce the processing load of the controller by routing flows with the hybrid OpenFlow/OSPF mode. Thus, the majority of flows can be routed by OSPF without involving the controller. Crucial flow rerouting realizes load balancing by dynamically identifying crucial flows based on a new metric called Variation Slope and rerouting these flows with the hybrid OpenFlow/OSPF mode. The simulation based on the real traffic traces and network typologies shows that compared with the optimal solution, HybridFlow can achieve 87% of the optimal load balancing performance by rerouting 36% less flows on average.

PipeCache: High Hit Rate Rule-Caching Scheme Based on Multi-Stage Cache Tables

OpenFlow switches hardware cannot store all the OpenFlow rules due to a limited resource. The rule-caching scheme is one of the best solutions to solve the hardware size limitation. In OpenFlow switches, Multiple Flow Tables (MFTs) provide more flexible flow control than a single table. Exact match and wildcard match are two typical matching methods. The exact match applies to a single flow table and multiple flow tables, but the performance is low under frequently changing traffic. Many commodity switches use Ternary Content Addressable Memory (TCAM) to support fast wildcard lookups. Earlier works on wildcard-match rule-caching focus on the dependency problem caused by the overlaps of match fields. Their designs cannot handle the rule-caching problem of MFTs because they are based on a single flow table, instead of the widely used MFTs structure. So, we propose a new design named PipeCache that solves the problem of MFTs rule-caching scheme based on wildcard-match. In our design, we logically split the TCAM resources, and assign them to each flow table according to the size of each flow table. Each flow table will cache the selected rules into their assigned TCAM resources and be updated in time by our algorithms to make the most use of the limited TCAM resources. We compare our structure with the exact-match scheme and the wildcard-match scheme based on a single flow table under different cache sizes and traffic localities. Experiment results show that our design PipeCache improves cache hit rate by up to 18.2% compared to the exact-match scheme and by up to 21.2% compared to the wildcard-match scheme based on a single flow table.

Deploying a Fast Detection and Eviction Mechanism of Invalid Connection-Oriented Flow-Entries in SDNs: A Scalability Approach

As a new paradigm of network architecture, Software Defined Networking (SDN) has been used in a large number of scenarios because it realizes flexible and efficient fine-grained flow control of the network, and promotes the evolution of the network to a programmable and scalable direction. However, the transition of the traditional networking model to SDN architectures poses scalability issues due to the limitation of the flow-table in size. Facing the traffic explosion on future networks with resource-constrained architectures, the storage space of the flow-table is not enough to bear so many flow-entries so that it not only causes performance degradation in data delivery but also results in scalability and cost-efficiency issues. To address this issue, in this article, we propose a solution to expedited evict the invalid flow-entries by detecting the disconnect messages of connection-oriented protocols such as Transmission Control Protocol (TCP) and Stream Control Transmission Protocol (SCTP) based on SDN controller and OpenFlow or programming protocol-independent packet processors (P4) switches. The behavior of detection is achieved by adding a specific SDN ruleset within the transport-layer in between the controller and switches. Different from the original timeout solutions, our scheme can delete invalid flow-entries in time according to the transmission layer disconnection instead of relying on the original timeout mechanism. Through a series of simulation results. we also demonstrate the superiority of our proposed solution in reducing the flow-entries occupancy and control overhead on controller, and improving the table-miss rate.

Control of flow structures around a cylinder in deep water employing a passive control element

This study aimed to experimentally investigate the swirling flow characteristic in the periphery of a cylinder located vertically in a deep water channel using a particle image velocity measurement method (PIV). In addition to the PIV method, paint visualization experiments were performed to observe the structures of vortical flow qualitatively. Based on the cylinder diameter, Reynolds numbers were changed incrementally as 2.5 × 103, 5 × 103, and 7.5 × 103, while the length of the control element, L = 180 mm was kept constant. The flexible splitter plate made of a plastic material was easily deformed under the influence of vortical flow. In the horizontal plane, taken from the middleheight of the cylinder, instantaneous flow data was measured first. Along these measurements, the distributions and magnitude of the velocity vectors, 〈V〉, vorticity concentrations, 〈ω〉, patterns of streamlines, 〈ψ〉, root mean square of velocity component such as 〈urms〉 and 〈vrms〉, correlations of shear stresses, 〈u′u′〉, 〈v′v′〉 and 〈u′v′〉, turbulent kinetic energy, TKE, and spectral analysis is conducted to define the frequency, f of vortex formations. The presence of a flexible flow control element located along the central axis line of the cylinder significantly affects the vortex formations. The existence of the flexible flow control element can significantly influence the wake flow region. Furthermore, many of the value of flow characteristics decreased as mentioned with respect to the bare case.

Circuit‐based logical layer 2 bridging in software‐defined data center networking

SummaryWith the expansion of the size of data centers, software‐defined networking (SDN) is becoming a trend for simplifying the data center network management with central and flexible flow control. To achieve L2 abstractions in a multitenant cloud, Open vSwitch (OVS) is commonly used to build overlay tunnels (eg, Virtual eXtensible Local Area Network [VXLAN]) on top of existing underlying networks. However, the poor VXLAN performance of OVS is of huge concern. Instead of solving the performance issues of OVS, in this paper, we proposed a circuit‐based logical layer 2 bridging mechanism (CBL2), which builds label‐switched circuits and performs data‐plane multicasting in a software‐defined leaf‐spine fabric to achieve scalable L2 without overlay tunneling. Our evaluations indicate that direct transmission in OVS improves throughput performance by 58% compared with VXLAN tunneling, and data‐plane multicasting for ARP reduces address resolution latency from 149 to 0.5 ms, compared with control‐plane broadcast forwarding. The evaluation results also show that CBL2 provides 0.6, 0.4, and 11‐ms protection switching time, respectively, in the presence of switch failure, link failure, and port shutdown in practical deployment.

A (21150, 19050) GC-LDPC Decoder for NAND Flash Applications

In this paper, a (21150, 19050) globally-coupled low-density parity check (GC-LDPC) code designed for NAND flash memories is presented. The proposed LDPC code comprises three disjoint subcodes which can be decoded independently. This highly structural parity check matrix contributes to efficient decoder implementation and flexible decoding flow control. Moreover, a two-phase local/global decoding procedure optimized for the proposed GC-LDPC code is introduced. Scenarios of collaborative decoding that leverages the special code structures are discussed. In the proposed decoder architecture, the pipelined processing elements with scheduling are employed to reduce the critical path and decoding latency as well. Implemented in UMC 65 nm process, the post-layout simulation shows a maximum decoding throughput of 4.32 Gb/s with the chip area 3.376 mm2.

Adaptive Wildcard Rule Cache Management for Software-Defined Networks

Software-Defined Networking enables flexible flow control by caching rules at OpenFlow switches. Wildcard rule caching enables management of traffic aggregates, reduces flow setup queries, and simplifies policy management. However, to guarantee correct packet matching, some rules that depend on the requested rule need to be cached as well, which leads to unnecessary flow table bloat and potential overflow. We have proposed a scheme called CAching rules in Buckets (CAB) to mitigate the dependency issue by partitioning the field space into buckets and caching rules associated with the requested buckets. In this paper, we propose the Adaptive Cache ManagEment (ACME) for CAB, which dynamically adjusts the sizes and shapes of buckets according to incoming traffic to achieve more efficient flow table utilization. The improvement also includes preloading rules that span a wide field space to reduce bandwidth usage in the control channel. We formalize the caching policies for CAB-ACME to guarantee the semantic correctness of packet classification. We evaluate the performance of CAB-ACME through software-based simulations and a prototype built with the OpenDaylight controller and hardware switches from multiple vendors. The results show that, compared with other rule caching schemes, CAB-ACME reduces the cache miss rate by one order of magnitude and the control channel bandwidth usage by a half. ACME also helps maintain a steadier performance under dynamic traffic changes compared with the baseline CAB design.

The Application of SNiPER to the JUNO Simulation

The JUNO (Jiangmen Underground Neutrino Observatory) is a multipurpose neutrino experiment which is designed to determine neutrino mass hierarchy and precisely measure oscillation parameters. As one of the important systems, the JUNO offline software is being developed using the SNiPER software. In this proceeding, we focus on the requirements of JUNO simulation and present the working solution based on the SNiPER.The JUNO simulation framework is in charge of managing event data, detector geometries and materials, physics processes, simulation truth information etc. It glues physics generator, detector simulation and electronics simulation modules together to achieve a full simulation chain. In the implementation of the framework, many attractive characteristics of the SNiPER have been used, such as dynamic loading, flexible flow control, multiple event management and Python binding. Furthermore, additional efforts have been made to make both detector and electronics simulation flexible enough to accommodate and optimize different detector designs.For the Geant4-based detector simulation, each sub-detector component is implemented as a SNiPER tool which is a dynamically loadable and configurable plugin. So it is possible to select the detector configuration at runtime. The framework provides the event loop to drive the detector simulation and interacts with the Geant4 which is implemented as a passive service. All levels of user actions are wrapped into different customizable tools, so that user functions can be easily extended by just adding new tools. The electronics simulation has been implemented by following an event driven scheme. The SNiPER task component is used to simulate data processing steps in the electronics modules. The electronics and trigger are synchronized by triggered events containing possible physics signals.The JUNO simulation software has been released and is being used by the JUNO collaboration to do detector design optimization, event reconstruction algorithm development and physics sensitivity studies.

Ion transport and selection through DCGC-based electroosmosis in a conducting nanofluidic channel

Compared to conventional electroosmosis over a non-polarizable insulating surface with fixed surface charge (or zeta potential), induced-charge electroosmosis occurs over an electrically polarizable surface with the ability of surface charge modulation (both magnitude and sign) under externally applied electric fields. Here, for the first time we propose to extend the induced-charge electroosmosis to nanofluidic channels with conducting (ideally polarizable) walls. Furthermore, we present a numerical model to describe the electrokinetic transport in such conducting nanofluidic channels. The analysis of numerical results shows new applications of induced-charge electroosmosis for actively tunable ion selection and flexible flow control in nanofluidics. This is achieved through the direct contact gate control (DCGC) of surface charge in induced-charge electroosmosis by applying very low voltages directly on conducting walls of nanochannels.

Solvability and solutions for bus-type extended load flow

In traditional load flow calculation, only three types of buses, PQ, PV, and Vθ, are generally specified. To accommodate the integration of new kinds of power equipment and flexible load flow control facilities, extra bus types are needed in load flow model. The load flow model incorporated with all possible bus types is named as bus-type extended load flow (BELF) for short in this paper. Both Newton–Raphson and decoupled BELF solutions are developed. An important problem for BELF is its solvability, which is carefully studied and topology-based criteria are proposed to ascertain BELF’s solvability. Numerical tests are carried out to verify the convergence of the BELF solution and the correctness of the proposed solvability criteria.

Plasmon flow control at gap waveguide junctions using square ring resonators

A compact add-drop coupler with square ring resonator (SRR) in gap plasmon waveguide is studied. It is shown that there exist both travelling-wave and standing-wave resonant modes in the resonator due to the influence of the four corners in the square ring. Based on SRR, a new type of two-dimensional plasmonic L-shaped bend is proposed. The compact geometry and high add-drop efficiency of the proposed structure enable the realization of flexible flow control at waveguide junctions, e.g. T-splitter and waveguide cross intersections, in nano scale. The optical field propagation patterns in the gap waveguide junctions equipped with SRRs are investigated by the finite-difference time-domain method.

Hydrodynamic gating for sample introduction on a microfluidic chip

We present a microfluidic sample introduction approach based on a novel flow control mechanism, hydrodynamic gated injection. It has the advantages of easy and flexible flow control, similar to its analog, electrokinetic gated injection, but exhibits the unique properties of strong driving force and good biocompatibility, ideal for applications involving live biological samples. Theories for hydrodynamic gating were proposed and validated by both numerical simulations and flow visualization experiments. An investigation with fluorescein revealed that pico-liter samples can be injected with high repeatability (RSD <1.9%). Selective injections of GFP-transfected nematode eggs were demonstrated with a survival rate of >95%. We expect the developed method to be potentially useful for microfluidic cell and organism analysis, either as a sample introduction module or a stand-alone analyzer.