Reduce Packet Loss Rate Research Articles

Data Interactive Control System Based on Heterogeneous Database of Information Fusion and Internet of Things

Abstract To improve the data interaction control effect of a heterogeneous database and reduce packet loss rate and response time, a new heterogeneous database data interaction control system based on information fusion is designed. The system consists of hardware and software parts. The hardware part of the heterogeneous database data interaction control system is composed of a data extraction module, data sending and receiving module, encryption module, and data interaction control module. On the basis of completing hardware design, the system software is designed, a fuzzy similarity matrix is constructed by calculating the similarity among the evidence, the weight coefficient of each piece of evidence is calculated by calculating the support function of each piece of evidence, the evidence source model is modified by using discount rules, and Dempster–Shafer combination rules are transformed into matrix analysis. Combined with the modified evidence source model, information fusion of the heterogeneous database is carried out to complete the software design of the data interactive control system. The experimental results show that the data interaction control effect of the heterogeneous database in this system is good, and the packet loss rate and response time are low, improving the data interaction control effect.

Wireless network handheld terminal-based green ecological sustainable design evaluation system: Improved data communication and reduced packet loss rate

Abstract In response to the challenge of high packet loss rates due to poor mobility of PCs, we introduce a sustainable design evaluation system centered around wireless network handheld terminals. This system combines hardware components, including microprocessor and wireless communication modules, to achieve wireless data transmission and program debugging. In the software domain, a configurable communication protocol is employed to establish an ecological data communication module supporting wireless network handheld terminals. Leveraging real-time monitoring data from multiple points, we introduce an information fusion algorithm and construct a green ecological sustainability design evaluation model. Notably, experimental results reveal that our system outperforms alternatives based on sensor and RFID technologies. It exhibits a lower packet loss rate and extends the distance of zero packet loss, highlighting its advantages in data communication.

Application of University English Teaching Model Based on Artificial Intelligence Technology

Abstract This paper is based on cloud computing technology in artificial intelligence and a clustering algorithm controlled to divide teaching resource attributes and reduce packet loss rates in the system. Data mining is used to reduce the number of iterations and improve processing efficiency, a learner model is designed, and the teaching process and assessment tasks are constructed to realize the teaching model. Two natural classes of students at the University of S. underwent an instructional experiment. The results showed that the experimental class reached about 70% of the overall students in the achievement range of 85-95 and 95-100. The college English teaching model based on artificial intelligence technology’s feasibility and effectiveness are proven by the significant improvement in performance compared to the control class.

A Trust-Based Model for Secure Routing against RPL Attacks in Internet of Things.

In IoT networks, the de facto Routing Protocol for Low Power and Lossy Networks (RPL) is vulnerable to various attacks. Routing attacks in RPL-based IoT are becoming critical with the increase in the number of IoT applications and devices globally. To address routing attacks in RPL-based IoT, several security solutions have been proposed in literature, such as machine learning techniques, intrusion detection systems, and trust-based approaches. Studies show that trust-based security for IoT is feasible due to its simple integration and resource-constrained nature of smart devices. Existing trust-based solutions have insufficient consideration of nodes’ mobility and are not evaluated for dynamic scenarios to satisfy the requirements of smart applications. This research work addresses the Rank and Blackhole attacks in RPL considering the static as well as mobile nodes in IoT. The proposed Security, Mobility, and Trust-based model (SMTrust) relies on carefully chosen trust factors and metrics, including mobility-based metrics. The evaluation of the proposed model through simulation experiments shows that SMTrust performs better than the existing trust-based methods for securing RPL. The improvisation in terms of topology stability is 46%, reduction in packet loss rate is 45%, and 35% increase in throughput, with only 2.3% increase in average power consumption.

An energy-balanced head nodes selection scheme for underwater mobile sensor networks

Underwater sensor networks system is a promising technology for smart ocean monitoring applications. To address the imbalance problem of network overhead and limited energy of underwater sensor nodes, this paper presents a CH–SH Selection and Sink Path-planning (CSSP) scheme to collect vast amount of data from heterogeneous sensor nodes. The scheme firstly establishes a three-layer network structure model for underwater mobile sensor networks (UMSN) based on multi-mode communication mechanism and provides energy-balanced head nodes (cluster head and sub-cluster head nodes) selection algorithm based on particle swarm iterative optimization. Then, the optimal global-path-plan of mobile sink is proposed to visit all the head nodes to collect data, reduce the multi-hop underwater acoustic transmission distance of relay nodes, and avoid the energy hole problem. Lastly, the upper-layer multi-hop network of UMSN is designed to remotely control local-path-plan over mobile sink, in order to implement joint planning of global and local paths of mobile sink. Simulation results verified that the proposed CSSP scheme outperformed 11%, 16% and 22% over three typical protocols in terms of nodes energy consumption, CSSP was 9%, 12% and 19% lower than three typical protocols in terms of SD of energy consumption, packet delivery ratio of CSSP was 8%, 10% and 12% higher than three typical protocols. The scheme could significantly balance energy and reduce packet loss rate.

STEREOS: Smart Table EntRy Eviction for OpenFlow Switches

Software-defined networking (SDN) is fundamentally changing the way networks operate, enabling programmable and flexible network management and configuration. As the de facto standard southbound interface of SDN, OpenFlow defines how the control plane interacts with the data forwarding plane. In OpenFlow, flow tables play a significant role in packet forwarding. However, the size of the flow table is limited due to power, cost, and silicon area constraints and capacity-limited tables cannot hold all of the active flows in medium-to-large-scale SDN networks. Thus, when a flow table reaches capacity, an intelligent eviction strategy, which efficiently manages the limited flow table resource, is critical. In this paper, we propose Smart Table EntRy Eviction for OpenFlow Switches (STEREOS), which uses machine learning to classify flow entries as active or inactive and forms the basis for intelligent eviction. Trace-driven simulations demonstrate that STEREOS increases flow table usage by more than 50% and reduces incorrect flow entry evictions by up to 78%, compared with the dominant Least Recently Used eviction policy. Moreover, packet-level simulations of a datacenter network demonstrate that STEREOS can greatly reduce the control overhead, increase overall network throughput by 19%, and reduce packet loss rate by 70%.

The Impacts of Node Orientation on Radio Propagation Models for Airborne-Deployed Sensor Networks in Large-Scale Tree Vegetation Terrains

In deterministic deployment of wireless sensor networks (WSNs), nodes are carefully placed at desired locations, with careful planning for separation distances, heights, and node orientations. This deployment strategy ensures good radio communication and sensing coverage. However, deterministic deployments are impractical for harsh large tree vegetation environments that span hundreds of kilometers. In these cases, stochastic deployments may enable effective deployment strategies. When relying on stochastic deployments, nodes are likely to be positioned at un-desired locations with unknown node orientations, which can lead to suboptimal radio connectivity and network performance. This paper examines the effects of factors affecting path loss under conditions resembling stochastic aerial deployments of WSN. Unlike previous work in the existing literature, this paper takes into account important deployment factors that affect network performance, such as node orientation and positioning, energy-to-bit-rate ratio, packet loss rate, and the composition of environment. Based on experimentation, a set of path loss models are proposed to model radio signal propagation in jungle-like environments under side-effects encountered in aerial deployments. The proposed models are compared with theoretical models and with other proposed models in the literature. Results show a significant difference with improved network performance that exhibits enhanced energy-to-bit-rate ratio, reduced packet loss rate, and increased node lifetime.

Optimization of Wireless Video Surveillance System for Smart Campus Based on Internet of Things

In order to strengthen school security and build a wireless smart campus, this article optimizes the existing wireless video surveillance system based on the Internet of Things. This paper first optimizes the surveillance quality in the video surveillance system, and proposes a zero-copy buffer strategy, a network congestion suppression strategy, and a codec rate coordination strategy. Secondly, for the distributed wide area video surveillance system, a tracking optimization method based on multi-camera fusion is proposed. Finally, this paper constructs a Bayesian monitoring event modeling method based on genetic algorithm. Experimental results show that the optimized video surveillance system has basically stable delay, significantly reduced packet loss rate, and smooth video playback. This method can effectively realize the coordinated tracking of multiple cameras in a wide-area monitoring scenario, achieve high tracking and monitoring performance, and meet the requirements of smart campus construction.

A novel evolutionary algorithm (MFO) with rate monotonic scheduling for load balancing in LTE advanced networks

In recent days, long term evolution (LTE)-advanced is the newest 4G technology. In this cellular network, the femto cells offered a viable and cost-effective method of enhancing the cellular reporting and capability for each WLAN and WiMAX. However, network allocates resource dissimilar to each and every users. To overcome this difficulty, moth flame optimisation (MFO) technique is used to provide equal resource allocation to user. Using this MFO method to balance the load for routing process. Rate-monotonic scheduling (RMS) algorithm is applied to share the load equally to available user, which increases the throughput and control the overload during communication time instance. The simulation results show that the proposed MFO technique has achieved improved network performance than existing hybrid multilevel feedback queue with round robin (HMFQ-RR) and hybrid weighted round robin with shortest job first (HWRR-SJF) in terms to reduce packet loss rate, packet delay and end to end delay.

A New Affinity Propagation Clustering Algorithm for V2V-Supported VANETs

Clustering is an efficient method for improving the communication performance of Vehicular Ad hoc NETworks (VANETs) that adopt Vehicle to Vehicle (V2V) communications. However, how to maximize the cluster stability while accounting for the high mobility of vehicles remains a challenging problem. In this paper, we first reconstruct the similarity function of the Affinity Propagation (AP) clustering algorithm by introducing communication-related parameters, so the vehicles with low relative mobility and good communication performance can easily be selected as cluster heads. Then, by formally defining three scaling functions, a weighted mechanism is designed to quantitatively assess the effect on the cluster stability when a vehicle joins it. Base on them, from the perspective of global balance, a new AP clustering algorithm for the whole clustering process is proposed. To ensure the validity of simulations, we use the vehicular mobility data generated on the realistic map of Cologne, Germany, and perform a series of simulations for eleven metrics commonly adopted in similar works. The results show that our proposed algorithm performs better than other algorithms in terms of the cluster stability, and it also effectively improves throughput and reduces packet loss rate of VANETs over the classical APROVE algorithm and the NMDP-APC algorithm.

A novel evolutionary algorithm (MFO) with rate monotonic scheduling for load balancing in LTE advanced networks

In recent days, long term evolution (LTE)-advanced is the newest 4G technology. In this cellular network, the femto cells offered a viable and cost-effective method of enhancing the cellular reporting and capability for each WLAN and WiMAX. However, network allocates resource dissimilar to each and every users. To overcome this difficulty, moth flame optimisation (MFO) technique is used to provide equal resource allocation to user. Using this MFO method to balance the load for routing process. Rate-monotonic scheduling (RMS) algorithm is applied to share the load equally to available user, which increases the throughput and control the overload during communication time instance. The simulation results show that the proposed MFO technique has achieved improved network performance than existing hybrid multilevel feedback queue with round robin (HMFQ-RR) and hybrid weighted round robin with shortest job first (HWRR-SJF) in terms to reduce packet loss rate, packet delay and end to end delay.

DABFS: A robust routing protocol for warning messages dissemination in VANETs

Vehicular ad hoc networks play a pivotal role in the enrichment of transportation systems by making them intelligent and capable of avoiding road accidents. For transmission of warning messages, direction-based Greedy protocols select the next hop based on the current location of relay nodes toward the destination node, which is an efficient approach for uni-directional traffic. However, such protocols experience performance degradation by neglecting the movement directions of nodes in bi-directional traffic where topological changes occur dynamically. This paper pioneers the use of movement direction and relative positions of source and destination nodes to cater to the dynamic nature of bi-directional highway environments for efficient and robust routing of warning messages. A novel routing protocol, namely, Direction Aware Best Forwarder Selection (DABFS), is presented in this paper. DABFS takes into account directions and relative positions of nodes, besides the distance parameter, to determine a node’s movement direction using Hamming distance and forwards warning messages through neighbor and best route discovery. Analytical and simulation results demonstrate that DABFS offers improved throughput and reduced packet loss rate and end-to-end delay, as compared with eminent routing protocols.

Parallel Transmission of Distributed Sensor Based on SCTP and TCP for Heterogeneous Wireless Networks in IoT.

Sensors in the Internet of Things (IoT) generate large amounts of data, which requires high-speed data transmission. In order to achieve the parallel transmissions of the wireless sensor network on the transmission layer, the performance of stream control transmission protocol (SCTP) and transmission control protocol (TCP) in the wireless sensor network under different packet error rates was simulated and compared. A dynamic multipath handover method for SCTP (MS-SCTP) was proposed to improve the transmission performance, which selects the transmission path according to the packet error rate and the retransmission ratio in the sender’s buffer. The TCP and SCTP protocol switching method (TCP-SCTP) was proposed to detect the current network traffic and adjust the MS-SCTP or TCP method. Analysis and simulation results show that MS-SCTP and TCP-SCTP could improve network throughput and reduce packet loss rate. MS-SCTP and TCP-SCTP can be combined with other technologies and channel allocation algorithms to improve network traffic.

QoE-aware user association and resource allocation for mixed services in heterogeneous networks

In heterogeneous networks (HetNets), user association and resource allocation (UARA) is a great challenge for radio resource management (RRM). In this paper, a novel QoE-aware UARA scheme is proposed. The delay factor is introduced to QoE metric to weight delays’ effect on service transmitting. Then the UARA scheme based on QoE is formulated as an optimization problem which is a mixed integer nonlinear programming (MINLP) problem. To solve the problem, we adopt the genetic algorithm (GA) and associate the user association and the resource with population and fitness respectively. Through the evolutions of genetic algorithm, the optimal UARA scheme can be worked out. The simulation results indicate that the proposed scheme can reduce packet loss rate, and improve the system load balancing performance.

Using Machine Learning to Provide Reliable Differentiated Services for IoT in SDN-Like Publish/Subscribe Middleware.

At present, most publish/subscribe middlewares suppose that there are equal Quality of Service (QoS) requirements for all users. However, in many real-world Internet of Things (IoT) service scenarios, different users may have different delay requirements. How to provide reliable differentiated services has become an urgent problem. The rise of Software-Defined Networking (SDN) provides endless possibilities to improve the QoS of publish/subscribe middlewares due to its greater programmability. We can encode event topics and priorities into flow entries of SDN switches directly to meet customized requirements. In this paper, we first propose an SDN-like publish/subscribe middleware architecture and describe how to use this architecture and priority queues supported by OpenFlow switches to realize differentiated services. Then we present a machine learning method using the eXtreme Gradient Boosting (XGBoost) model to solve the difficult issue of getting the queuing delay of switches accurately. Finally, we propose a reliable differentiated services guarantee mechanism according to the queuing delay and the programmability of SDN to improve QoS, namely, a two-layer queue management mechanism. Experimental evaluations show that the delay predicted by the XGBoost method is closer to the real value; our mechanism can save end-to-end delay, reduce packet loss rate, and allocate bandwidth more reasonably.

Simulation Modeling and Performance Comparison of RED and ERED Algorithms using Congestion Indicators

Random early detection (RED) is an effective congestion control mechanism acting on the intermediate gateways. The gateway detects and controlling packet dropping function with average queue size. The gateway could notify contacts of congestion either by simply dropping packets arriving in the gateway or simply by setting a bit within packet headers. When the average queue size surpasses a preset threshold, the gateway drops or represents each arriving packet along with a certain probability, where exact probability is a function of the average queue size. In this study describe a new active queue management scheme, Effective RED (ERED) that aims to reduce packet loss rates in a simple and scalable manner. I made a few changes to the packet drop function of the existing RED scheme. The rest of the original RED remains unchanged. In this study, the Simulations demonstrate that ERED achieves a highest throughput and lowest packet drops than RED. ERED is fully compatible with RED, can easily upgrade/replace the existing RED implementations by ERED.

Neural embedded smart link generation scheme for heterogeneous network

The Long Term Evolution (LTE) network is a very much popular network in heterogeneous network. Heterogeneous networks provide maximum data rate by integrating various technologies and channels, based on appropriate network selection. For the sensible data transmission in the LTE network, noise plays an vital role as channel is a free space. The minimum noise channel selection is a decision of present and previous status of network channel. Proposed scheme develop neural network model, which will act as a smart link generation scheme for computing minimum noise channel path for sensible data transmission. Hence, proposed scheme will improve performance of the network. Result indicates that, proposed scheme improves throughput and system reliability. Proposed scheme is also reduces packet loss rate and energy consumption in contrast with conventional techniques.

Design and analysis of a parallel hybrid memory architecture for per-flow buffering in high-speed switches and routers

The network switches and routers require both high-speed and large-capacity packet buffers. However, existing packet buffer architectures have the problems of speed scaling and flow number scaling limitations. To address the two problems simultaneously, this paper proposes a parallel hybrid SRAM/DRAM architecture for per-flow buffering in high-speed switches and routers. Tail SRAM and head SRAM are used to apply per-flow buffering for packet aggregation, so that the middle DRAM is accessed in a larger granularity and the DRAM's bandwidth utilization is improved. To mitigate the flow number scaling limitation, a dynamic memory allocation with hard timeout (DMA-HT) memory management algorithm is designed. The key idea of DMA-HT is that the memory space is dynamically allocated for the newly arrived flows, and a hard timeout is assigned for each queue. After a specific period of time, the memory space is freed, so that the SRAM space is efficiently utilized by the most recently active flows. A queuing system is used to model the proposed method, and theoretical analysis is performed to optimize the timeout value. With the derived formulas, multiple performance parameters are quantitatively analyzed, and the optimal timeout can be obtained. Both numerical results and simulations show that the proposed architecture can and reduce packet loss rate and average delay significantly compared with previous solutions with the same SRAM capacity.

Highly Efficient Multi Channel Packet Forwarding with Round Robin Intermittent Periodic Transmit for Multihop Wireless Backhaul Networks.

Round Robin based Intermittent Periodic Transmit (RR-IPT) has been proposed which achieves highly efficient multi-hop relays in multi-hop wireless backhaul networks (MWBN) where relay nodes are 2-dimensionally deployed. This paper newly investigates multi-channel packet scheduling and forwarding scheme for RR-IPT. Downlink traffic is forwarded by RR-IPT via one of the channels, while uplink traffic and part of downlink are accommodated in the other channel. By comparing IPT and carrier sense multiple access with collision avoidance (CSMA/CA) for uplink/downlink packet forwarding channel, IPT is more effective in reducing packet loss rate whereas CSMA/CA is better in terms of system throughput and packet delay improvement.

Modulation Design for MIMO-CoMP HARQ

Modulation diversity (MoDiv) is a simple and practical transmission enhancement technique that utilizes different modulation mappings to reduce packet loss rate and achieve higher link throughput. MoDiv is particularly meaningful and effective in Hybrid-Automatic Repeat reQuest (HARQ) systems. We study the deployment and optimization of MoDiv for HARQ in a MIMO-coordinated multi-point scenario under Rician fading channel to mitigate packet loss. We formulate the design optimization of MoDiv into a quadratic 3-D assignment problem, then solve it using a modified iterated local search method. Numerical results demonstrate clear performance gain over simple retransmissions and over a heuristic design under fading channels.