Forwarding Mechanism Research Articles

X-Education: Education of All Things with AI and Edge Computing—One Case Study for EFL Learning

Education usually only focuses on how to educate human beings with pedagogical or technical support. However, with artificial intelligence (AI) and edge computing, education can be extended and considered not only to educate human beings but also all things, such as physical or digital things. In this study, all things are given the opportunity to learn more about themselves and build their knowledge through interactions with other things, people, and AI agents. Thus, the X-Education framework is proposed in this study for educating all things, including human beings, physical, digital, and AI agents. One preliminary study for EFL writing was conducted to investigate not only whether all things can speed up their knowledge but also whether EFL learners as humans can also obtain the benefits of using X-Education. Further, the forwarding mechanisms of questioning and answering (Q&A) were designed to speed up interactions among all things. In total, 22 learners were divided into two groups, the experimental group (EG) and the control group (CG), with/without the Q&A forwarding mechanisms, respectively. A mixed-method approach with the two experimental phases was used in this study. The results showed that the knowledge of all things in the EG increased significantly more than the CG. Moreover, the EG received better EFL answers from the on-device AI with the forwarding mechanisms. They also felt that X-Education could help them to learn EFL writing better through Q&A. Furthermore, it was demonstrated that X-Education can accommodate not only humans but also all things to improve their knowledge.

Study on public willingness and incentive mechanism of ecological compensation for inter-basin water transfer in China in the carbon neutral perspective

Constructing payments for ecosystem services (PES) for inter-basin water transfer is one of the effective means to adjust the interest relationship and promote low-carbon development in the region. The inter-basin water transfer ecological compensation policy (IWTECP) in China is a PES project facing a series of problems. To this end, we applied contingent valuation method (CVM) to examine the willingness to pay (WTP) in water-receiving area and willingness to accept (WTA) in water-source area of the eastern route of South-to-North Water Transfer Project, China. The WTP and WTA values were 206.29 RMB/(person·year) (USD 32.37/(person·year)) and 443.29 RMB/(person·year) (USD 69.55/(person·year)) respectively. Bayesian network model was employed to explore the influencing factors, it was found that educational background, per capita monthly household income and the recognition of the importance of the project to the city or the country had the greater influence on WTP, while age, per capita monthly household income and the influence of project on personal life were the most influential factors on WTA. By comparing the influencing factors of WTP and WTA, the intention preference of the respondents was discussed. Then, SWOT matrix analysis method was adopted to put forward incentive mechanism from the perspectives of internal public background and external environmental policies. Our results could provide incentive policies for target groups of consumers, improve the efficiency of ecological protection, and promote the reform of the IWTECP.

DrTM+B: Replication-Driven Live Reconfiguration for Fast and General Distributed Transaction Processing

Recent in-memory database systems leverage advanced hardware features like RDMA to provide transaction processing at millions of transactions per second. Distributed transaction processing systems can scale to even higher rates, especially for partitionable workloads. Unfortunately, it is challenging to sustain such high rates during live reconfiguration of partitions. In this article, we observe that state-of-the-art approaches would cause notable performance disruption under fast transaction processing. To this end, this article presents DrTM+B, a live reconfiguration approach that seamlessly repartitions data with little performance disruption to running transactions. DrTM+B uses a pre-copy-based mechanism to avoid excessive data transfer by leveraging common properties in recent transactional systems. DrTM+B's reconfiguration plans reduce data movement by preferring existing data replicas, while copying data from multiple replicas asynchronously and in parallel. It further reuses the log forwarding mechanism in primary-backup replication to seamlessly track and forward dirty database tuples and avoids iterative copying costs. To commit a reconfiguration plan in a transactional-safe way, DrTM+B designs a cooperative commit protocol for synchronization of data and state among replicas. To boost the performance during data migration, DrTM+B combines the pre-copy and post-copy schemes to propose a hybrid copy scheme. The live reconfiguration approach can also coexist with fault-tolerance mechanisms of primary-backup replication to provide high availability. Evaluation on a working system based on DrTM+R with 3-way replication using typical OLTP workloads like TPC-C and SmallBank shows that DrTM+B incurs only very small performance degradation during live reconfiguration and provides high availability. Both the reconfiguration time and the downtime are also minimal.

Comprehensive characterization of vertical GaN-on-GaN Schottky barrier diodes

This paper reports comprehensive characterization of vertical GaN-on-GaN Schottky barrier diodes (SBDs) fabricated on free-standing GaN substrates. The GaN active layer properties are evaluated by atomic force microscopy (AFM), secondary-ion mass spectrometry (SIMS), micro-Raman spectroscopy, cathodoluminescence (CL), and deep-level transient Fourier spectroscopy (DLTFS). The GaN SBDs exhibit near-unity ideality factor (n = 1.1), promising Schottky barrier height (SBH) of ΦB = 0.82 eV, low turn-on voltage ∼0.56 V, leakage current density of JR < 5.5 × 10−6 Acm−2 at −100 V, breakdown voltage VBR < −200 V, and less interface state density (NSS < 5 × 1012 eV−1 cm−2) at the Ni/GaN Schottky contact. The forward and reverse current transport mechanisms of the SBD are identified by fitting analysis of measured J-V. Weak temperature dependence of ΦB and n is detected from I–V-T measurements. Similar traps at EC - 0.18 eV and EC - 0.56 are identified in the various SBDs from DLTFS, signifying that these traps are omnipresent defects in the epilayer.

Using dual evolutionary search to construct decision tree based ensemble classifier

A typical ensemble learning process typically uses a forward integration mechanism to construct the ensemble classifier with a large number of base classifiers. Based on this mechanism, it is difficult to adjust the diversity among base classifiers and optimize the structure inside ensemble since the generation process has a certain amount of randomness, which makes the performance of ensemble classifiers heavily dependent on the human design decisions. To address this issue, we proposed an automatic ensemble classifier construction method based on a dual-layer evolutionary search mechanism, which includes a tree coding-based base classifier population and a binary coding-based ensemble classifier population. Through a collaborative searching process between the two populations, the proposed method can be driven by training data to update the base classifier population and optimize the ensemble classifiers globally. To verify the effectiveness of the dual evolutionary ensemble learning method (DEEL), we tested it on 22 classification tasks from 4 data repositories. The results show that the proposed method can generate a diverse decision tree population on the training data while searching and constructing ensemble classifiers from them. Compared with 9 competitor algorithms, the proposed method achieved the best performance on 17 of 22 test tasks and improved the average accuracies by 0.97–7.65% over the second place. In particular, the generated ensemble classifiers show excellent structure, which involve small number and diverse decision trees. That increases the transparency of ensembles and helps to perform interpretability analysis on them.

M-PolKA: Multipath Polynomial Key-Based Source Routing for Reliable Communications

Innovative traffic engineering functions and services require disrupting routing and forwarding mechanisms to be performed with low overhead over complex network topologies. Source routing (SR) is a prominent alternative to table-based routing for providing the needed expressiveness and agility by reducing the number of network states. This work proposes the M-PolKA, a topology-agnostic multipath source routing scheme and orchestration architecture for reliable communications, which explores special properties from the Residue Number System (RNS) polynomial arithmetic. A P4-based proof-of-concept is experimentally demonstrated using emulated and hardware prototypes. Also, use cases for revealing M-PolKA’s functionalities are tested in different scenarios in order to address problems, such as communication reliability improvement, agile path migration and fast failure reaction. Finally, low overhead for extra functionalities is observed when RNS-based SR is compared to traditional routing approaches.

A Sparse Feature Matching Model Using a Transformer towards Large-View Indoor Visual Localization

Accurate indoor visual localization has been a challenging task under large-view scenes with wide baselines and weak texture images, where it is difficult to accomplish accurate image matching. To address the problem of sparse image features mismatching, we develop a coarse-to-fine feature matching model using a transformer, termed MSFA-T, which assigns the corresponding semantic labels to image features for an incipient coarse matching. To avoid the anomalous scoring of sparse feature interrelationship in the attention assigning phase, we propose a multiscale forward attention mechanism that decomposes the similarity-based features to learn the specificity of sparse features, the influence of position-independence on sparse features is reduced and the performance of the fine image matching in visual localization is effectively improved. We conduct extensive experiments on the challenging datasets; the results show that our model achieves image matching with an average 79.8% probability of the area under the cumulative curve of the corner point error, which outperforms the related state-of-the-art algorithms by an improvement of 13% probability at 1 m accuracy for the image-based visual localization in large view scenes.

Performance assessment of OppNet routing protocols with real world mobility traces

A new paradigm has been introduced by researchers in the field of data accessing at several mobile positions through implementation of WAN instead of cellular telephony. Based on range/coverage and network topology WAN taxonomy has been categorized as fixed network, mobile access network and ad – hoc network/wireless mesh networks respectively. Several interesting challenges has been posed by researchers in wireless networks such as routing, bandwidth, congestion, security, quality of service (QoS) and data rate enhancement. Of late, researchers around the world have started working in the domain of SHiP (Sparse, Hybrid, Intermittent and Partitioned) Network, which are plagued by several characteristics features such as: sporadic connections, intermittent routing, store – carry – forward type of message forwarding mechanism, dynamic network topology, transitive closure of message transmission, fluctuating network link, bottleneck probability, trust, and security in social networks. In this paper an outline of Oppnet (Opportunistic Network), part of SHiP Network has been presented with as in-depth coverage of routing problems and research challenges in it. Additionally, taxonomy of Oppnet routing protocols is illustrated with the features on basis of which categorization has been done. An exhaustive investigation through implementation of well-known routing schemes like: Epidemic, Spray and Wait, PROPHET and Direct delivery against mobility models such as: Random Walk, Random Waypoint, Shortest path-based movement and Cluster Movement has been accomplished in open-source software: ONE simulator with real world mobility dataset and traces of city of New Delhi, capital of India. Results achieved have been good and exceed our expectations.

Linear network coding with forward error correction in wireless packet relaying system

Research subject. The paper presents the results of comparing three byte error-correcting codes according to their probabilistic characteristics in a system with network coding. Method. Simulation modeling has been carried out to determine the probabilistic characteristics of byte error-correcting codes for a transmission system with network coding. The principles of coding and decoding of the studied codes are considered. Core results. The probabilistic characteristics of byte error-correcting codes are determined and presented, and recommendations are developed for their use in a transmission system with network coding, depending on its purpose. Practical relevance. The application of the considered error-correcting codes for the construction of transmission systems with network coding is proposed. The applicability of these codes in the development of applied byte protocols that require the use of forward error correction mechanisms in communication channels is noted.

EESR: Energy efficient sector-based routing protocol for reliable data communication in UWSNs

There is a remarkable need of advancement in data communication for application of sensor and ad-hoc networks for reliable and secure delivery of data. Due to the dynamic behavior of the network, it is an emerging demand to achieve reliability in data communication. The existence of different network environment features and diverse dynamic topology leads to the need of protocol design for efficient and reliable delivery of data in underwater acoustic sensor networks. The paper proposes energy efficient and reliable protocol design for routing data packets in Underwater Wireless Sensor Networks environment using sector based forwarding mechanism. The sector based forwarding mechanism helps in routing the reliable data in an efficient and secure manner The proposal suggests to model the network in such a way that the entire network is divided into sectors to optimize the hop count that further leads towards the energy efficient delivery of data. The mechanism of data forwarding is done vertically by maintaining sector wise sequence through pivot node which is considered as sector head. The proposed sector-based network topology mechanism is useful in identifying the number of hops used in communication along with enhancement in energy for effective data communication. The experiment performed and its consecutive results suggests that the proposed protocol enriches the energy utilization of the network. The enhancement of data communication reliability in Underwater Wireless Sensor Networks environment is managed by the mechanism of reduced hop count.

Probabilistic cooperative coded forwarding for broadcast transmissions in industrial mobile edge communications

Mobile edge computing (MEC) is considered as a key enabler for the industrial internet of things (IIoT) to cope with the ever-increasing communication and computing demands of nodes. In consideration of the limited resource of the IIoT nodes, it is necessary to design cost-effective multi-hop data transmission schemes for mobile edge IIoTs. However, most of the traditional schemes have to spend enormous cost to meet the reliability requirement, which cannot support timely information processing of MEC-based IIoT. In this article, the probabilistic cooperative coded forwarding (PCCF) scheme for multi-hop data transmission in mobile edge IIoTs is proposed to address the above problem. First, the data packets are encoded at a source IIoT node using the systematic sparse network coding (SSNC) mechanism, then the source broadcasts the coded packets to its one-hop neighbors. To minimize the required number of redundant coded packets, the sparsity of coded packets is optimized. Second, the nodes which received the packets will become volunteer relay nodes and forward the coded packets using the cooperative coded forwarding (CCF) mechanism. The volunteer relays first forward the received coded packets with a forwarding probability, and then re-encode a pair of received coded packets and broadcast the re-encoded packet with a re-encoding probability. To guarantee the broadcast performance while minimizing the transmission number at relay nodes, the feasible forwarding and re-encoding probability are provided. Third, the receiver nodes will try to decode the received coded and re-encoded packets and recover data packets without sending acknowledgments. Finally, through a series of experiments, we verify the accuracy of analytical approximations and also find out the optimal sparsity of coded packets and the existence of minimum transmission numbers. These provide insights for further optimization of multi-hop data transmission in mobile edge IIoTs.

Scheduling flexible manufacturing cell with no-idle flow-lines and job-shop via Q-learning-based genetic algorithm

Owing to enormous varieties in product quantities and types in customer orders, two production methods, flow production and job production, should be simultaneously carried out in the flexible manufacturing cell so that standardized products in high volume and individualized products in low volume can be compatibly manufactured.Thus, this work schedules such a realistic manufacturingcell with these two production methods. A mixed-integer linear programming model is developed to determine cell formation and machine assignment, and particularly to locally sequence standardized products within each product family and globally schedule all individualized products and product families. Meanwhile, a Q-learning-based genetic algorithm (Q-GA) is proposed to solve large-scaled cases effectively and efficiently. In Q-GA, a rule-based initialization improves the quality of initial solutions; a forward and no-idle backward decoding mechanism satisfies the job availability, machine availability and no-idle time constraints; a Q-learning-based approach adaptively controls the crossover/mutation rates to lower relative percentage deviation. Experimental results demonstrate that for the flexible manufacturing cell scheduling problem with two production methods, the proposed Q-GA obtains the lower bounds of small-scaled cases and outperforms the comparison algorithms for large-scaled cases in the solution effectiveness and robustness.

Cycle-Based Time-Sensitive and Deterministic Networks: Architecture, Challenges, and Open Issues

The emerging time-critical applications, such as industrial automation, smart grids, and telesurgery, pose strong demands for enabling end-to-end time-sensitive and deterministic networks. However, most of the existing research only considers the time-sensitive network in the layer 2 local area, or separately designs the deterministic network in the layer 3 wide area. The feasibility of end-to-end scheduling has been largely ignored. Moreover, the problem of multi-layer deterministic architecture design and cross-domain resource co-scheduling have not been fully considered. Therefore, this article proposes a novel architecture named C-TSDN, in which the cyclic queuing and forwarding mechanism and the cycle-specified queuing and forwarding mechanism are jointly designed to solve the bandwidth, cycle, and queue mismatch problems in end-to-end scheduling. The key functional modules of the proposed C-TSDN are detailed, including SRv6, network slicing, cycle alignment, and global computing. We elaborately exhibit the promising technical challenges, such as traffic analysis with AI. Finally, some potential open issues as future research directions are pointed out.

Enhancing OLSR Protocol by an Advanced Greedy Forwarding Mechanism for VANET in Smart Cities

The future Intelligent Transport System "ITS" is one of the major challenges of the smart city. It requires fast and efficient communication between vehicles (vehicle-to-vehicle “V2V”), to ensure information exchange in order to improve safety, which reduces accidents and consequently save lives, hence the need of the Vehicular Ad Hoc Network “VANET”, which makes possible the inter-vehicle communication. This network is characterized by a variable topology. Therefore, MANET (Mobile Adhoc NETwork) routing protocols need a few tweaks to be available for the vehicle environment. In this paper, we start by exposing some works related to the evaluation of the most well-known protocols. After a comparative study, we deduce that the OLSR (Optimized Link State Routing) protocol outperforms other routing protocols in terms of End-to-End Delay (EED) and Packet Delivery Ratio (PDR). In addition, we note that the Greedy forwarding “GF” mechanism is suited for the VANET environment, which has been improved and called Greedy forwarding Advanced “GFA”, to overcome the stationary node problem. Our approach improves the OLSR protocol to be more suitable and efficient for VANET by introducing the GFA mechanism. Moreover, we compare our approach to the OLSR classic version. In this work, we use a realistic scenario from Open Street Map (OSM), and simulations are performed using SUMO (Simulation of Urban MObility). The trace files generated from SUMO are used for further simulation in NS-3 (Network Simulator) to validate our proposition. The simulation results are analyzed and discussed. Our approach performs best compared to OLSR in terms of EED and PDR, especially for dense traffic.

Step-by-Step Regulation of Productive and Abortive Transcription Initiation by Pyrophosphorolysis

An understanding of the kinetics and mechanism of bacterial transcription initiation is needed to understand regulation of gene expression and advance fields from antibiotic discovery to promoter design. The step-by-step forward kinetics and mechanism of initiation and RNA-DNA hybrid growth, made irreversible by omitting pyrophosphate (PPi) byproduct, were determined recently for E. coli RNA polymerase (RNAP)-λPR promoter complexes. Strong position-dependences of overall rate constants (kcat/Km analogs) for each nucleotide-addition step were observed because of coupling of hybrid growth to disruption of promoter contacts, bubble closing, and RNAP escape. Here we investigate reversal of these steps (pyrophosphorolysis) at PPi concentrations ([PPi]) found in exponentially-growing cells. We quantify [PPi] effects on the amount and rate of synthesis of long (>10-mer, post-escape) and short (stalled, abortive) RNA to determine how PPi regulates initiation. Physiological [PPi] makes uridine incorporation and some other initiation steps significantly reversible. Physiological [PPi] reduces the fraction of RNAP-promoter complexes that productively initiate and the rate of RNA synthesis per productive complex, while increasing the fraction of complexes that abortively initiate, affecting abortive rates, and shifting the abortive-product distribution to shorter RNAs. Pyrophosphorolysis rates for some initiation complexes are orders of magnitude larger than for removal of the same nucleotide from elongation complexes because of the strong bias toward the pre-translocated state in initiation, and exhibit even stronger dependences on nucleotide identity (pyrimidine ≫ purine). Because cytoplasmic [PPi] is much higher in exponential-phase than stationary-phase cells, these [PPi] effects on initiation rates and amounts of RNA synthesis must be physiologically-relevant.

An Efficient Routing Scheme Based on Node Attributes for Opportunistic Networks in Oceans.

Along with the fast development of the marine economy and ever-increasing human activities, handy and reliable marine networking services are increasingly required in recent years. The ocean faces challenges to support cost-effective communication due to its special environments. Opportunistic networks with easy deployment and self-curing capability are expected to play an important role to adapt to such dynamic networking environments. In the literature, routing schemes for opportunistic networks mainly exploit node mobility and local relaying technologies. They did not take into account the impact of node behaviors on encountering opportunities and in case of no further relaying, network performance would be greatly degraded. To solve the problem, we propose an efficient routing scheme based on node attributes for opportunistic networks. We first construct delivery competency to predict the further relay nodes. Then a forwarding willingness mechanism is introduced to evaluate the relaying probability combining device capacity and movement behaviors of nodes. Finally, the utility metric is used to make decisions on message forwarding. The results show that the proposed scheme improves network performance in terms of delivery ratio, average latency, and overhead ratio as compared to other schemes.

Cross Layered Network Condition Aware Mobile-Wireless Multimedia Sensor Network Routing Protocol for Mission Critical Communication

The high pace emergence in wireless technologies have given rise to an immense demand towards Quality of Service (QoS) aware multimedia data transmission over mobile wireless multimedia sensor network (WMSN). Ensuring reliable communication over WMSN while fulfilling timely and optimal packet delivery over WMSN can be of great significance for emerging IoT ecosystem. With these motivations, in this paper a highly robust and efficient cross layered routing protocol named network condition aware mobile-WMSN routing protocol (NCAM-RP) has been developed. NCAM-RP introduces a proactive neighbour table management, congestion awareness, packet velocity estimation, dynamic link quality estimation (DLQE), and deadline sensitive service differentiation based multimedia traffic prioritization, and multi-constraints based best forwarding node selection mechanisms. These optimization measures have been applied on network layer, MAC layer and the physical layer of the protocol stack that eventually strengthen NCAM-RP to enable QoS-aware multimedia data transmission over WMSNs. The proposed NCAM-RP protocol intends to optimize real time mission critical (even driven) multimedia data (RTMD) transmission while ensuring best feasible resource allocation to the non-real time (NRT) data traffic over WMSNs. NCAM-RP has outperform RPAR based routing scheme in terms of higher data delivery, lower packet drops and deadline miss ratio. It signifies that NCAM-RP can ensure minimal retransmission that eventually can reduce energy consumption, delay and computational overheads. Being the mobility based WMSN protocol, NCAM-RP can play significant role in IoT ecosystem.

Ferry–Based Directional Forwarding Mechanism for Improved Network Life-Time in Cluster-Based Wireless Sensor Network

Considerable energy saving can be achieved with mobility-based wireless sensor networks (WSN's), where a mobile node (ferry) visits sensing nodes in a network to collect sensed data. However, the critical issues of such WSN's are limited networks lifetime and high data latency, these critical issues are due to the slow mobility and relatively long route distance for ferries to collect and forward data to the sink. Incorporating ferries in WSNs eliminates the need for multi-hop forwarding of data, and as a result, reduce energy consumption at sensing nodes. In this paper, we introduce the One Hop Cluster-Head Algorithm (OHCH), where a subset of ferries serve as cluster heads (CH), travel between nodes with short distance mobility, collect data originated from sources, and transfer it to the sink with minimum hop count possible, this approach can achieve more balance between network energy saving and data collection delay, also, it is an efficient design to combine between ferries and noise.

A Content Dissemination Technique Based on Priority to Improve Quality of Service of Vehicular Ad Hoc Networks

Due to the ability of Vehicular Ad Hoc Networks (VANETs) to improve mobility and create innovative services, they have received increasing attention from both industry and academia fields. Named Data Networking (NDN) is a network service that has been developed for Internet’s host-based packet delivery model. In VANETs, NDN is used as an emerging architecture for improving the quality of service (QoS) of the networks connected cloud and mobile Internet of Things (IoT). We can achieve this improvement using an efficient content dissemination and forwarding technique that depends on name-based routing, in-network content caching, and interest-based content retrieval. The large amount of data processed by several IoT sensors or nodes of VANETs makes content prioritizing and forwarding mechanism is crucial, especially when many end-users need common content simultaneously. Therefore, in this paper, we propose a content dissemination technique based on priority for boosting the service requirements of NDN-based cloud and mobile IoT nodes in the VANETs. The approach prioritizes the data flow of traffic into four classes: urgent, emergency, least, and average using a novel constrained location and deadline method, called New method employing Deadline Distance and Size of Data (NDDS). The highest priority is assigned to the data traffic with the emergency class, then urgent, average, and least class. To evaluate this proposed technique, a numerical simulation experiment is conducted by using the CloudSim toolkit. The simulation results demonstrate that the emergency data flow has minimum processing time, compared to the average, urgent, and least data flow, which can significantly enhance the QoS of NDN protocol-based Ad Hoc networks.

Low density of interface trap states and temperature dependence study of Ga2O3 Schottky barrier diode with p-NiOx termination

This work acquires a vertical β-Ga2O3 Schottky barrier diode (SBD) with the advanced termination structure of p-type NiOx and n-type β-Ga2O3 heterojunctions and coupled field plate structures to alleviate the crowding electric field. A Ga2O3 SBD delivers an average breakdown voltage of 1860 V and a specific on-resistance of 3.12 mΩ cm2, yielding a state-of-the-art direct-current Baliga's power figure of merit of 1.11 GW/cm2 at an anode area of 2.83 × 10−5 cm2. In addition, the Ga2O3 SBD with the same fabrication process at a large area of 1.21 × 10−2 cm2 also presents a high forward current of 7.13 A, a breakdown voltage of 1260 V, and a power figure-of-merit of 235 MW/cm2. According to dynamic pulse switching and capacitance-frequency characteristics, an optimized p-NiOx/Ga2O3 interface with a maximum trap density of 4.13 × 1010 eV−1 cm−2 is delivered. Moreover, based on the forward current-voltage measurement at various temperatures, the physics behind a forward conduction mechanism is illustrated. Ga2O3 SBDs with p-NiOx/n-Ga2O3 heterojunction termination, field plate, high power figure of merit, and high quality interface as well as suppressed resistance increase after dynamic pulse switching, verifying their great promise for future high power applications.