Adaptive Routing Mechanism Research Articles

LBCapsNet: a lightweight balanced capsule framework for image classification of porcelain fragments

The image classification task of porcelain fragments is of great significance for the digital preservation of cultural heritage. However, common issues are encountered in the image processing of porcelain fragments, including the low computation speed, decreased accuracy due to the uneven distribution of sample categories, and model instability. This study proposes a novel Capsule Network model, referred to as LBCapsNet, which is suitable for the extraction of features from images of porcelain artifacts fragments. A bottleneck-like channel transformation module denoted by ChannelTrans, which resides between the convolutional layer and the PrimaryCaps layer, was first designed. This module is used to reduce the computational complexity and enhance the processing speed when dealing with intricate porcelain images. The MF-R loss function was then proposed by incorporating focal loss into the original loss function. This allows to address the issue of imbalanced distribution of ceramic shard samples and reduce the classification errors, which leads to faster convergence with smoother trend. Finally, an adaptive dynamic routing mechanism is designed with a dynamic learning rate to enhance the overall stability of the classification process. The experimental results obtained on public datasets, such as MNIST, Fashion- MNIST, CIFAR10, FMD and DTD as well as porcelain fragments dataset, demonstrate that LBCapsNet achieves high classification accuracy with faster and more stable computation compared with existing methods. Furthermore, the ability of LBCapsNet to process special textures can provide technical support for the digital preservation and restoration of cultural heritage.

Optimal order-[formula omitted] routing policy for adaptive routing in real road networks

In uncertain traffic networks, adaptive routing mechanism is essential in adapting to dynamic traffic changes and making effective routing decisions. Most previous work on adaptive routing commonly ignores the realistic requirement of drivers to select and enter a right lane before intersections, and this would lead to urgent lane changing at intersections that not only violates traffic rules but even causes traffic accidents. This paper redefines the adaptive routing problem in real road networks as an optimal order-k routing policy problem by proposing a novel order-k routing policy. It is a routing mechanism that selects the next k arcs at each decision intersection and the first m arcs are the same with the last m arcs of the k arcs selected at the last decision intersection, which are defined as an m-arc-constrained order-k link. This routing mechanism gives sufficient preparation time for lane changing. We develop a two-phase methodology to handle this problem. To address complex spatio-temporal correlations in real road networks, instead of using the random sampling method, we use a copula-based scenario generation method to generate high-quality scenarios for improving solution performances. A two-stage algorithm integrating the enumeration of m-arc-constrained order-k links and the construction of the optimal routing policy is developed to find the optimal order-k routing policy based on the scenarios generated. Extensive numerical experiments demonstrate the superiority of the optimal order-k routing policy to simultaneously obtain good performances and meet the realistic requirement of drivers’ lane changing.

APAP: An adaptive packet-reproduction and active packet-loss data collection protocol for WSNs

In lossy, large-scale wireless sensor networks (WSNs), data collection protocols face the challenge of balancing expected data transmission reliability and limited resources of sensors. Packet redundancy strategies have been widely employed to guarantee transmission reliability. However, these schemes often result in energy waste, especially in sink-neared hotspot districts. We propose the APAP to balance the two competing interests in energy-constrained WSNs. APAP mainly consists of two parts: adaptive packet-reproduction routing and active packet-loss mechanism. In the first part, we design a compensation function to compensate for packet losses and employ it in the packet-reproduction routing. Through available network parameters, such a function offers an optimized number of redundant packets. In the second part, we devise a novel distributed packet-loss mechanism to detect and intercept redundant packets in the hotspot area. Hotspot nodes record the simple traffic information in their vicinity on a local micro-table, these nodes transform their mode based on the records to reach a basic consensus with one-hop neighbors, they then collaboratively intercept excess packets from outside, thus the injection traffic can be mitigated. Such an interception area has the potential to be expanded and prolonged as the redundancy becomes more severe. Our mechanism imposes low-complexity requirements on general devices. Moreover, thorough mathematical analyses are offered for the performance of APAP. Simulation results indicate that with high reliability, the maximum node energy consumption is reduced by 44.7% to 66.3% compared to conventional protocols in one round. Besides, the network lifetime is prolonged by 91.1% to 200%.

DisAVR: Disentangled Adaptive Visual Reasoning Network for Diagram Question Answering.

Diagram Question Answering (DQA) aims to correctly answer questions about given diagrams, which demands an interplay of good diagram understanding and effective reasoning. However, the same appearance of objects in diagrams can express different semantics. This kind of visual semantic ambiguity problem makes it challenging to represent diagrams sufficiently for better understanding. Moreover, since there are questions about diagrams from different perspectives, it is also crucial to perform flexible and adaptive reasoning on content-rich diagrams. In this paper, we propose a Disentangled Adaptive Visual Reasoning Network for DQA, named DisAVR, to jointly optimize the dual-process of representation and reasoning. DisAVR mainly comprises three modules: improved region feature learning, question parsing, and disentangled adaptive reasoning. Specifically, the improved region feature learning module is designed to first learn robust diagram representation by integrating detail-aware patch features and semantically-explicit text features with region features. Subsequently, the question parsing module decomposes the question into three types of question guidance including region, spatial relation and semantic relation guidance to dynamically guide subsequent reasoning. Next, the disentangled adaptive reasoning module decomposes the whole reasoning process by employing three visual reasoning cells to construct a soft fully-connected multi-layer stacked routing space. These three cells in each layer reason over object regions, semantic and spatial relations in the diagram under the corresponding question guidance. Moreover, an adaptive routing mechanism is designed to flexibly explore more optimal reasoning paths for specific diagram-question pairs. Extensive experiments on three DQA datasets demonstrate the superiority of our DisAVR.

Design of fully adaptive routing and hybrid VC allocation in wireless NOC

Wireless network-on-chip (WiNoC) establishes a long-range single-hop wireless links on the base of the traditional planar metal interconnects network, which improve network performance in several aspects. The establishment of wireless link improves the diversity of path for packet transmitting, while simultaneously aggravates the deadlock problem, leading it to more complicated condemn. The traditional routing mechanism of wireless network on chip can avoid deadlock by sacrificing the adaptability of transmitting, which leads to unbalanced and insufficient use of limited on chip resources. In this paper, a fully adaptive routing mechanism is proposed to balance buffer utilization. At the same time, we proposed a hybrid virtual channel allocation strategy in order to make full use of buffer resources. For a large number of single-flit wired packets and wireless packets, more aggressive non-atomic allocation is adopted, and the remaining packets are arranged with atomic allocation to avoid potential deadlock. Experimental results showed that compared with the traditional deadlock solutions, the proposed scheme introduces less area and power consumption, and balances the utilization of buffer resources. Under the non-uniform Traffic Patterns, the proposed scheme has better performance in terms of delay and throughput, achieves 62.0% improvement compared to the traditional counterpart.

AMLR: An Adaptive Multi-Level Routing Algorithm for Dragonfly Network

High-radix hierarchical structures, such as the dragonfly, fat-tree, and torus, are cost-effective topologies for high-performance computer (HPC) networks. In these networks, dragonfly outperforms traditional topologies such as fat-tree and torus in cost and scalability. However, network congestion occurs due to the imbalanced traffic pattern, which can lead to degraded performance. The routing algorithm influences the performance of the dragonfly topology in many ways. Routing algorithm can be designed to avoid saturating global or local links, and to avoid deadlock in the network. In this letter, we introduce an adaptive multi-level routing (AMLR) for dragonfly networks. AMLR has three-level routes. By dividing these routes meticulously, all paths of the network can be used more effectively. Traffic between groups will be more balanced. In particular, we propose a congestion control scheme to cooperate with AMLR in the data transmission process. Furthermore, congestion detection and notification are leveraged to identify congested packet and inform the network. Evaluations show that the proposed adaptive multi-level routing and congestion control mechanism can relieve the imbalance between groups in the 100-node dragonfly topology. As a result, AMLR provides 26%, 98%, 78%, and 99% lower latencies, and 13%, 87%, 13%, and 128% higher throughputs compared to the shortest routing under uniform, adv+i, hotspot, and permutation traffic, respectively.

Efficient path planning of drone swarms over clustered human crowds in social events

PurposeIn this study, supervision and control of the possible problems among people over a large area with a limited number of drone cameras and security staff is established.Design/methodology/approachThese drones, namely unmanned aerial vehicles (UAVs) will be adaptively and automatically distributed over the crowds to control and track the communities by the proposed system. Since crowds are mobile, the design of the drone clusters will be simultaneously re-organized according to densities and distributions of people. An adaptive and dynamic distribution and routing mechanism of UAV fleets for crowds is implemented to control a specific given region. The nine popular clustering algorithms have been used and tested in the presented mechanism to gain better performance.FindingsThe nine popular clustering algorithms have been used and tested in the presented mechanism to gain better performance. An outperformed clustering performance from the aggregated model has been received when compared with a singular clustering method over five different test cases about crowds of human distributions. This study has three basic components. The first one is to divide the human crowds into clusters. The second one is to determine an optimum route of UAVs over clusters. The last one is to direct the most appropriate security personnel to the events that occurred.Originality/valueThis study has three basic components. The first one is to divide the human crowds into clusters. The second one is to determine an optimum route of UAVs over clusters. The last one is to direct the most appropriate security personnel to the events that occurred.

On the Exploration of a Low-Power Photonic Network Architecture

The photonic on-chip network is an emerging technology that can provide low power and high bandwidth. However, photonic devices such as laser sources, resonators, and waveguides have high static power consumption, reducing the energy efficiency of the system. This article proposes a low-power optical network architecture. First, a dynamic network resource supply strategy is designed, and the optical network resources are adjusted according to the runtime traffic characteristics. Second, by leveraging power-efficient routers, our network architecture minimizes power used for compensating optical signal loss. Finally, an adaptive optical routing mechanism is designed to offer the lowest latency and power by utilizing existing network resources. The experimental results show that, compared to the existing scheme, our proposed architecture can save 51 percent power consumption and 60 percent energy consumption in the PARSEC and SPLASH-2 benchmark tests.

Fastest adaptive estimation algorithms for topological structure errors in smart grid networks

Compared with traditional wired networks, wireless sensor networks(WSN) have the characteristics of low cost and rapid deployment, and also guarantee the same level of fault tolerance as wired networks. The WSN can also monitor the operating status of the power grid in real time, collect physical information such as related parameters, and provide more comprehensive and complete power grid operation data as a reference basis for smart grid operation and related management personnel, and complete the diagnosis, monitoring and power statistics of smart grid equipment The rapid construction of the data communication network has become a key technology to effectively solve the problems of difficult optimization management and high cost and economic benefits in the smart grid. This paper discusses the application of WSNs in smart grids from two aspects. Firstly, construct a WSN topology that complies with the smart grid architecture, and establish a real-time routing mechanism that meets the requirements of smart distribution network communication reliability; secondly, propose a fastest adaptive algorithm for the fault of the WSN topology in the smart grid . The proposed adaptive routing mechanism has certain advantages in node energy consumption, which reduces energy consumption by nearly 4% compared to the directional diffusion method and the LEACH algorithm. Therefore, the algorithm is more suitable for the adaptation of WSN topology, and the method can Improve the life cycle of sensor nodes and networks.

Thermal-Aware Design and Simulation Approach for Optical NoCs

For chip multiprocessors, one major challenge is to bridge the increasing speed gap between processor and the global on-chip interconnect delay. By integrating optical interconnects in network-on-chip (NoC) architectures, optical NoCs can overcome the power and bandwidth bottleneck of traditional electrical on-chip networks. However, while considering the thermal sensitivity of silicon photonic devices used in optical NoCs, optical interconnects may not have advantages in power efficiency as compared with their electrical counterparts. To tackle this problem, in this article, we propose a thermal-aware design and simulation approach for optical NoCs. Key techniques include thermal-sensitive optical power loss models from device level to network level, a thermal-aware adaptive routing mechanism, and a thermal-aware simulation platform. The thermal-aware simulation platform enables optical NoC simulation together with on-chip temperature simulation as well as optical thermal effect modeling. With the proposed thermal-aware simulation platform, we conducted a case study of an $8\times 8$ mesh-based optical NoC under a set of synthetic traffic patterns as well as real applications at typical temperature scenarios. By comparing and analyzing different temperature distributions, we can conclude that it can achieves a better optimization effect for the temperature distributions where the hot spots are scattered across the chip.

无线传感网多参数路由均衡机制研究

无线传感器网络能够实时监测覆盖区域内各种物理量的动态变化情况，在军事、环境监测等领域获得了广泛应用。由于无线链路的时变特性、网络结构的动态变化等因素，使得无线传感网的路由设计一直是研究的热点和难点。当前的路由算法主要是基于单目标的性能优化，算法性能随着应用的差异产生很大的不同。针对多参数系统在实际情况中的应用需求，以传包率、时延、抖动、吞吐量、能耗等为衡量指标，结合模糊理论，提出一种基于GRC的多参数均衡的路由机制。实验结果表明，基于GRC的方法可以有效选择最优化算法，依据评估结果动态选择最优化算法，在中等流量情况下，系统能够获得32%的整体性能增益。方法实现了算法性能的定量分析、性能排序，结果可以为无线传感网性能评估提供一定的理论依据，也可以为算法优化提供方向。 Wireless Sensor Network (WSN) is capable of measuring parameters within its coverage area. It gains wide applications in the areas such as military fields, environment monitoring for the sake of safety, efficiency as well as on-time nature. Nevertheless, factors such as time dependent nature of wireless links, dynamic topology make it different for proliferation of wireless sensor network. Routing is a key but the most difficult part in the design as well as optimization of wireless sensor networks. Specific speaking, routing in WSN is designed to improve one or at most two performance metrics, leading to its performance deterioration when the application fields change. An adaptive routing mechanism based on GRC, with five metrics considered, is proposed, targeting at multiple parameters such as packet delivery ratio, delay, jitter, throughput and energy cost evaluation, in this paper to rank the alternative protocols and thus rank them accordingly using fuzzy logics. Competing metrics are balanced and therefore our method is able to obtain the optimal routing algorithm. Simulation results show that a 32% gain may be achieved by using the proposed method in terms of middle traffic flow. Our method is able to provide a quantitative method for performance evaluation for wireless sensor network. It also aims at providing benchmark for algorithm optimization.

Development of an adaptive routing mechanism in software-defined networks

The purpose of this paper is to develop of a single mechanism of the adaptive routing of different types of traffic based on the current quality of service requirements. Software-defined networking is a technology of the future. The current development trend of communication systems constantly confirms this fact. However, to date, the use of this technology in its current form is only justified in large networks of major technology companies and service providers. Currently, a large number of dynamic routing protocols have been developed in communication networks. Our task is to create a solution that can make it possible to use the ability of each node to make a decision on the transmission of information by every possible means for each type of traffic. This task can be accomplished by solving the problem of the development of generalized metric that characterizes the communication channels between devices in the network in detail and the problem of the development of a mechanism of adaptive network logical topology reconfiguration (route control) in order to ensure the high quality of service of the whole network that meets current quality requirements for a particular type of service.

A two-hop based adaptive routing protocol for real-time wireless sensor networks.

One of the most important and challenging issues in wireless sensor networks (WSNs) is to optimally manage the limited energy of nodes without degrading the routing efficiency. In this paper, we propose an energy-efficient adaptive routing mechanism for WSNs, which saves energy of nodes by removing the much delayed packets without degrading the real-time performance of the used routing protocol. It uses the adaptive transmission power algorithm which is based on the attenuation of the wireless link to improve the energy efficiency. The proposed routing mechanism can be associated with any geographic routing protocol and its performance is evaluated by integrating with the well known two-hop based real-time routing protocol, PATH and the resulting protocol is energy-efficient adaptive routing protocol (EE-ARP). The EE-ARP performs well in terms of energy consumption, deadline miss ratio, packet drop and end-to-end delay.

A Global Hierarchical Adaptive Routing Mechanism in Many-Core Processor Network-on-Chip

A Global Hierarchical Adaptive Routing Mechanism in Many-Core Processor Network-on-Chip

Development of an Adaptive Routing Mechanism in Software-Defined Networks

The purpose of this work is to develop a unitary mechanism of adaptive routing of different kinds, basing on the current requirements on the quality of service. The software configuration of a network is the technology of the future. The trend in communication systems constantly confirms this fact. However, the application of this technology in its current form is justified only in large networks of technology giants and telecom operators. Today we have a large number of dynamic routing protocols to route big volume traffic in communication networks. Our task is to create the solution that can use the opportunities of each node to make a decision on the transmission of information by all possible means for each type of traffic. Achieving this goal is possible by solving the problem of the development of generalized metrics, which details the links between devices in the network, and the problem of establishing a framework of adaptive logical network topology (route management) to ensure the quality of the whole network in order to meet the current requirements on the quality of a particular type service.

On-the-fly adaptive routing for dragonfly interconnection networks

Adaptive deadlock-free routing mechanisms are required to handle variable traffic patterns in dragonfly networks. However, distance-based deadlock avoidance mechanisms typically employed in Dragonflies increase the router cost and complexity as a function of the maximum allowed path length. This paper presents on-the-fly adaptive routing (OFAR), a routing/flow-control scheme that decouples the routing and the deadlock avoidance mechanisms. OFAR allows for in-transit adaptive routing with local and global misrouting, without imposing dependencies between virtual channels, and relying on a deadlock-free escape subnetwork to avoid deadlock. This model lowers latency, increases throughput, and adapts faster to transient traffic than previously proposed mechanisms. The low capacity of the escape subnetwork makes it prone to congestion. A simple congestion management mechanism based on injection restriction is considered to avoid such issues. Finally, reliability is considered by introducing mechanisms to find multiple edge-disjoint Hamiltonian rings embedded on the dragonfly, allowing to use multiple escape subnetworks.

Flow-Aware Multi-Topology Adaptive Routing

Internet routing processes currently rely on protocols that were developed more than ten years ago. Today, we have far more computational power and memory at our disposal, and it is possible to take advantage of these resources in order to greatly increase the efficiency of routing protocols. Therefore, we propose a new approach to routing packets in IP-based networks: Flow-Aware Multi-Topology Adaptive Routing, or FAMTAR. FAMTAR combines flow-aware traffic management and an adaptive routing mechanism. A standard routing protocol is used to find the optimal path between two nodes in a network. FAMTAR makes it possible to automatically create additional paths when such demand occurs. Between two endpoints, the transmission may follow n different paths, where n is limited only by the topology of the network. In this letter, we compare FAMTAR to a classic routing protocol and demonstrate FAMTAR's superiority.

Mobility Tolerant Firework Routing for Improving Reachability in MANETs

In this paper, we investigate our mobility-assisted and adaptive broadcast routing mechanism, called Mobility Tolerant Firework Routing (MTFR), which utilizes the concept of potentials for routing and improves node reachability, especially in situations with high mobility, by including a broadcast mechanism. We perform detailed evaluations by simulations in a mobile environment and demonstrate the advantages of MTFR over conventional potential-based routing. In particular, we show that MTFR produces better reachability in many aspects at the expense of a small additional transmission delay and intermediate traffic overhead, making MTFR a promising routing protocol and feasible for future mobile Internet infrastructures.

Rank-Based Routing Strategy for Named Data Network

NDN (Named Data Networking) is clean-slate architecture for future networking, in which packets carry data names rather than source or destination addresses, being a sharp contrast to today IP architecture. The default routing strategy for NDN is flooding the interest packets to all the possible interfaces which could reach for the data provider or data cache container. Obviously, the default routing strategy is not best way in the actual networking for the heavy load of routing items. This article proposes an interface rank-based routing strategy (RBRS), in which the PIT and FIB structures are detailed and expanded to satisfy the Interest and Data packets transmission, and the interfaces are ranked through a cumulative algorithm for route selection. Through the simulation, RBRS has been proved an adaptive routing mechanism with better performance of network load balance, while reducing the average routing hops and the centric nodes load.

Analysis of Lightpath Re-provisioning in Green Optical Networks

The paper investigates how the level of re-provisioning of lightpaths can affect the calculation of the cost of lightpaths and consequently the result of routing decisions. The paper introduces a re-provisioning mechanism with partial re-routing capabilities to lower the Co2 emission rate while it provides the most available routes between any pair of source and destination. The paper provides a thorough analysis of adaptive green routing mechanism by establishing a partial re-provisioning environment to analyze how the re-provisioning level can affect Co2 emission level, blocking rate, and resource allocation.