Overall Performance Of Network Research Articles

Multitier scalable clustering wireless network design approach using honey bee ratel optimization

Wireless sensor networks (WSNs) have emerged as a one of the most fascinating areas of lookup in the past few years principally due to its massive quantity of workable applications. However limited energy, node deployment strategy, routing techniques has considerable impact on the overall performance of network. This paper proposes sustainable honey bee ratel based hybrid wireless sensor network (SHHWSN) layering framework for improving load balancing and scalability issues in network. In SHHWSN tessellated hexagonal shape clusters are formed to cover entire geographical region without any gaps. Hybrid routing schema constrained with redundant data identification policy used in this, seeks to optimize energy utilization. The proposed SHHWSN was evaluated and validated by simulation, and the results were compared with earlier schematics where mostly one sided stochastic node deployments were followed. The experimental results show that SHHWSN has superior performance in terms of network alive nodes, delay, energy and throughput. The proposed SHHWSN obtained values of 50 nodes is 3, 0.061, 0.14, 0.89, 100 nodes is 3,0.037, 0.19, 0.551, 150 nodes is 13, 0.081, 0.23, 0.415, and 200 nodes is 23, 1.01, 0.25, 0.356, which is significantly more effective than current techniques.

Loop Closure Detection Based on Residual Network and Capsule Network for Mobile Robot.

Loop closure detection based on a residual network (ResNet) and a capsule network (CapsNet) is proposed to address the problems of low accuracy and poor robustness for mobile robot simultaneous localization and mapping (SLAM) in complex scenes. First, the residual network of a feature coding strategy is introduced to extract the shallow geometric features and deep semantic features of images, reduce the amount of image noise information, accelerate the convergence speed of the model, and solve the problems of gradient disappearance and network degradation of deep neural networks. Then, the dynamic routing mechanism of the capsule network is optimized through the entropy peak density, and a vector is used to represent the spatial position relationship between features, which can improve the ability of image feature extraction and expression to optimize the overall performance of networks. Finally, the optimized residual network and capsule network are fused to retain the differences and correlations between features, and the global feature descriptors and feature vectors are combined to calculate the similarity of image features for loop closure detection. The experimental results show that the proposed method can achieve loop closure detection for mobile robots in complex scenes, such as view changes, illumination changes, and dynamic objects, and improve the accuracy and robustness of mobile robot SLAM.

Active Queue Management in RED Considering Critical Point on Target Queue

The basic philosophy behind RED is to prevent congestion. When the average queue length exceeds the minimum threshold, packets are randomly dropped, or the explicit congestion notification bit is marked. Since network requirements differ significantly, it is not an optimal approach to establish RED parameters with constant value. There is a new algorithm we are proposing called Critical Point on Target Queue (AQM-RED-CPTQ), provide greater congestion management over the network while also preserving the value of RED. To overcome the problem in RED without changing queue weight parameter, we have proposed few models to control the congestion by introducing range parameter with probability and control mechanism which will belong between minimum and maximum threshold. The current queue size is controlled together with average queue size. A new range variable has been introduced to improve the performance of priority queue of existing RED based algorithm which improves the overall performance of networks. For each packet, minimum and maximum threshold has been updated and dropped with probability (Pa) for a special condition. Instead of multiplicative increase and decrease the maximum probability, the scheme uses additive-increase and multiplicative-decrease. Once the AVG queue length is close to the minimum threshold value, our approach automatically sets queue parameter according to queue conditions and handles queuing delay and improve throughput. The simulated results proof that our approaches are better than RED in terms of throughput, end to end delay, packet delivery ratio and goodput.

Spatial correlation modeling and ergodic capacity analysis of networks with overlapping conflict

AbstractThe fifth generation (5G) network development trends (e.g., more cells, larger and distributed antenna arrays, higher frequency spectrum) and new technologies are driving beyond 5G (B5G) and even sixth generation (6G) research together. In existing works, performance analysis is based on typical users, but no user is typical, because of spatial correlation in the scheduling of transmission points (TPs) caused by overlapping conflict between the different transmission point groups (TPGs). Using stochastic geometry, this article analyzes ergodic capacity of entire network by deriving the semiclosed form expression of area spectral efficiency (ASE), where Matérn‐like model is proposed to capture the spatial correlation of overlapping conflict. Specifically, the serving probability of TP is lower to avoid intense overlapping conflict in heavily overlapping region, thanks to Matérn‐like model requires that only one TP with best channel condition be in serving within the same TPG. In addition, considering different serving probabilities of TPs, user performance is nonindependent, thus ASE could more accurately characterize the overall level of user performance by traversing nonindependent user performance. Simulation and analytical results show that ASE considering spatial correlation can more accurately fit the overall performance of networks with overlapping conflict.

A novel simulation-annealing enabled ranking and scaling statistical simulation constrained optimization algorithm for Internet-of-things (IoTs)

PurposeSimulation-based optimization is a decision-making tool for identifying an optimal design of a system. Here, optimal design means a smart system with sensing, computing and control capabilities with improved efficiency. As compared to testing the physical prototype, computer-based simulation provides much cheaper, faster and lesser time-and resource-consuming solutions. In this work, a comparative analysis of heuristic simulation optimization methods (genetic algorithms, evolutionary strategies, simulated annealing, tabu search and simplex search) is performed.Design/methodology/approachIn this work, a comparative analysis of heuristic simulation optimization methods (genertic algorithms, evolutionary strategies, simulated annealing, tabu search and simplex search) is performed. Further, a novel simulation annealing-based heuristic approach is proposed for critical infrastructure.FindingsA small scale network of 50–100 nodes shows that genetic simulation optimization with multi-criteria and multi-dimensional features performs better as compared to other simulation optimization approaches. Further, a minimum of 3.4 percent and maximum of 16.2 percent improvement is observed in faster route identification for small scale Internet-of-things (IoT) networks with simulation optimization constraints integrated model as compared to the traditional method.Originality/valueIn this work, simulation optimization techniques are applied for identifying optimized Quality of service (QoS) parameters for critical infrastructure which in turn helps in improving the network performance. In order to identify optimized parameters, Tabu search and ant-inspired heuristic optimization techniques are applied over QoS parameters. These optimized values are compared with every monitoring sensor point in the network. This comparative analysis helps in identifying underperforming and outperforming monitoring points. Further, QoS of these points can be improved by identifying their local optimum values which in turn increases the performance of overall network. In continuation, a simulation model of bus transport is taken for analysis. Bus transport system is a critical infrastructure for Dehradun. In this work, feasibility of electric recharging units alongside roads under different traffic conditions is checked using simulation. The simulation study is performed over five bus routes in a small scale IoT network.

Cost and Sub-Epoch Based Stable Energy-Efficient Clustering Algorithm for Heterogeneous Wireless Sensor Networks

This paper proposes a cost and sub-epoch based stable energy-efficient clustering (CSSEEC) algorithm for heterogeneous wireless sensor networks. In this paper, we provide a cost function for cluster heads selection and a sub-epoch to re-stands the previously selected cluster heads as normal nodes in cluster head selection process for future rounds. Cost function alleviates the energy consumption of sensor nodes by optimum selection of cluster heads and modified sub-epoch makes the energy balance among the normal nodes. Thereby, the performance parameters like stability period, usable period, throughput and network lifetime are improved remarkably. It is also discerned that the stability period is the paramount parameter than others. By improving this parameter, overall performance of network is improved. Simulation results verified that proposed CSSEEC protocol is more efficient than existing protocols.

Measurements and applications of QoE for multimedia communications

With the rapid development of smart devices and mobile networks, multimedia services will dominate most of data traffic in 4G/5G networks. Applications such as conversational videos, online multimedia sharing, remote education, etc. have gained their popularity and will become more ubiquitous among customers. Traditional criteria for evaluating the overall performance of networks are usually summarized in several objective aspects such as error rates, bandwidth, throughput, transmission delay, availability, etc., which are commonly called quality of service (QoS). However, to evaluate the subjective quality of multimedia services, only part of QoS can be involved (e.g., transmission delay), which is not a suitable measure. Quality of experience (QoE), on the other hand, is a subjective measure on the overall performance of network services from user's perspective, which is also called the perceptual QoS from user's perspective.

Energy-efficiency opportunistic spectrum allocation in cognitive wireless sensor network

The developments in wireless sensor network (WSN) that enriches with the unique capabilities of cognitive radio technique are giving impetus to the evolution of Cognitive Wireless Sensor Network (CWSN). In a CWSN, wireless sensor nodes can opportunistically transmit on vacant licensed frequencies and operate under a strict interference avoidance policy with the other licensed users. However, typical constraints of energy conservation from battery-driven design, local spectrum availability, reachability with other sensor nodes, and large-scale network architecture with complex topology are factors that maintain an acceptable network performance in the design of CWSN. In addition, the distributed nature of sensor networks also forces each sensor node to act cooperatively for a goal of maximizing the performance of overall network. The desirable features of CWSN make Multi-agent Reinforcement Learning (RL) technique an attractive choice. In this paper, we propose a reinforcement learning-based transmission power and spectrum selection scheme that allows individual sensors to adapt and learn from their past choices and those of their neighbors. Our proposed scheme is multi-agent distributed and is adaptive to both the end-to-end source to sink data requirements and the level of residual energy contained within the sensors in the network. Results show significant improvement in network lifetime when compared with greedy-based resource allocation schemes.

An Intra and Inter Service Dependent Security Aware Packet Scheduling in Mobile Ad-Hoc Networks

An improved security-aware packet scheduling algorithm (ISAPS) was proposed for efficient packet scheduling and obtaining high level security irrespective of the system workload. In ISAPS, packets from multiple wireless modes are assumed as independent. Many service oriented packets in Mobile Ad-hoc Networks (MANET) are dependent one another, scheduling packets based on service dependency improves overall performance of networks In this paper, Intra service dependent security aware packet scheduling algorithm (ISDSPS) is proposed to enhance scheduling performance by clustering the packets. However, some impurity clusters occurred during clustering. To overcome this issue an intra and inter service dependent security aware packet scheduling algorithm (IISDSPS) is proposed for identifying similar type of packets among clusters. IISDSPS maximizes the security levels as well as schedulability performance by providing priority to packets based on intra and inter service dependency. Simulation results proved that IISDSPS algorithm outperforms than existing algorithms in terms of guarantee ratio, average security level, packet delivery ratio and End to End delay.

Prioritized Mobile Node Deployment to Enhance the Lifetime of Wireless Sensor Network

In Wireless Sensor Networks, the available energy of the prevailing sensor nodes is limited and is difficult to replenish. It is very critical to supervise the available energy. In Mission Critical Surveillance application, due to node’s battery depletion, coverage hole may be created. Hole at Critical Point (CP) leads to the degradation of performance of overall network. It is merely impossible, to redeploy sensor nodes or to recharge the battery while monitoring. The proposed Energy Balanced-Dynamic Deployment Optimization approach, positions the self deployable mobile sensors towards CP according to its available Energy Density. This balances the Energy Density of the network thereby increasing the Reliable Lifetime. The simulation results show the effectiveness of the approach in terms of the balanced Energy Density around CPs with less mobility.

Energy efficient cluster head selection for cross layer design over wireless sensor network

Wireless sensor network energy efficiency acquired attraction of the research community. In WSN, nodes deploy in sensor environment and communicate with other nodes with the help of cluster node. Here cluster node directly connected through base station. Due to very small equipments, sensor devices have very less power capacity and it affects the overall performance of networks. Energy is one of the most important issues that have been accepted by the research community to obtain the network scalability, stability and increase performance of the sensor network. While data transmission nodes deduct their energy, and this is most difficult to select effective cluster head when node have less energy. In this paper we proposed an algorithm for selection cluster head in minimum energy over cross layer. We simulate our algorithm over LEACH routing protocol, which has been acquired for their energy efficiency and easiness. The objective of this paper is to provide optimised selection procedure for cluster head node bashed on node energy to increase the life time of a sensor network, which increase the total performance of the network.

Performance Evaluation of AODV Using Fuzzy Logic to Reduce Congestion in MANET

Mobile ad-hoc network is an infrastructure less network as it doesn’t follow any particular network topology. In MANET congestion is a major problem in small size networks congestion’s effect is low as compared to the large size networks. Congestion degrades the performance of overall network drastically. Many algorithms have been proposed to handle the congestion famous one are the active que management algorithms (AQMs). But still there is no universally accepted solution for it. In this paper a congestion control solution is devised using fuzzy logic controller. In this node density and load are taken as input and packet drop probability as output, which is effective to control congestion in large networks.

Research on Communication Protocol Agreement Based on Ad Hoc Network

Routing technology is the key technology of Ad Hoc network and is one of the most important factors influencing overall performance of network. Routing protocol has not adapted to topological structure of dynamic change for Ad Hoc network, so the new Ad Hoc routing protocol must be designed. The paper starts from the basic concept of Ad Hoc network and proposes an effective key protocol agreement in Ad Hoc network based on bilinear pairing and hierarchical routing protocol which not only makes logical key agreement model correspond to topological structure of actual network , but also supports the establishment and dynamic update of initial group of key and has less communication traffic. The performance analysis indicates that the protocol proposed in the paper is very effective on the network with larger range, stronger ability of equipment process and worse communication environment.

A Channel Allocation Algorithm Based on Minimum Interference in Wireless Mesh Network

Channel allocation based on multi-interface is a very important and difficult problem. Network throughput needs to be maximized while full consideration should be given to interference reduction and network connectivity. To solve this problem, the extended conflict graph was utilized to establish the link interference matrix; the frequency assignment technique in spectrum management based on greedy algorithm was introduced for channel allocation, and a channel assignment algorithm based on minimum interference was proposed. The algorithm fully considered link interference situation, and selected the link which currently suffers the minimum interference. For the selected link, select the idle channels when there are sufficient channels; select the channels with least potential interference when there are no idle channels. Based on this strategy, the link interference is effectively reduced, the number of links that can work simultaneously is increased, which fully maintained the connectivity of the network and effectively improved network throughput. Simulation results show that this scheme can effectively improve the performance of overall network.

차량 통신 네트워크에서 효율적인 긴급 메시지 전파를 위한 클러스터링 기반의 라우팅 알고리즘

차량 통신 네트워크는 이동하는 차량과 차량 간의 통신 및 차량과 인프라 간의 통신을 이용하여 운전자의 안전 및 교통 흐름 개선 등 다양한 서비스를 제공하는 차세대 네트워크 기술이다. 이러한 차량 통신 네트워크에서는 운전자의 안전을 위하여 최근 다양한 연구가 활발히 이루어지고 있으며, 특히 긴급 메시지를 전송하여 이동하는 차량에게 경고 메시지를 전달함으로써 교통안전의 효율성을 높이기 위한 연구가 활발히 진행되고 있다. 이동하는 차량에게 긴급 메시지를 효율적으로 전파하기 위해서는 차량 노드의 전송 범위 안에 속해 있는 노드들에게 브로드캐스팅을 통하여 최대한 많은 노드들에게 빠르게 메시지를 전송하는 것이 매우 중요하다. 하지만 기존 제안되었던 연구들은 메시지 전송 시 통신에 참여하는 노드들의 무분별한 브로드캐스팅으로 인한 브로드캐스팅 폭풍 문제가 발생하였으며, 이로 인하여 전체적인 성능이 감소하는 문제를 야기하였다. 또한 이러한 문제는 도심 지역과 같이 차량 노드의 밀도가 높고 다양한 도로의 형태에서 많은 문제점을 야기한다. 따라서 본 논문에서는 도심지역과 같이 차량의 밀도가 높은 지역에서 효율적으로 메시지를 전달할 수 있는 클러스터링 기반의 라우팅 알고리즘 (CBRA, Clustering based Routing Algorithm)을 제안한다. 제안하는 라우팅 알고리즘은 메시지 전송 시 클러스터링 방법을 통해 차량을 관리함으로써 도로 형태에 따른 링크 단절 문제를 해결하고 각 클러스터에서 선택적 플러딩 방법을 적용하여 브로드캐스팅 폭풍문제와 메시지 전송 시 효율성을 향상시킨다. ns-2를 이용한 시뮬레이션 결과 본 논문에서 제안하는 CBRA 방법이 기존 제안되었던 방법보다 더 우수한 성능을 보이는 것을 입증하였다. Vehicle Ad hoc Network (VANET) is next-generation network technology to provide various services using V2V (Vehicle-to-Vehicle) and V2I (Vehicle-to-Infrastructure). In VANET, many researchers proposed various studies for the safety of drivers. In particular, using the emergency message to increase the efficiency of traffic safety have been actively studied. In order to efficiently transmit to moving vehicle, to send a quick message to as many nodes is very important via broadcasting belong to communication range of vehicle nodes. However, existing studies have suggested a message for transmission to the communication node through indiscriminate broadcasting and broadcast storm problems, thereby decreasing the overall performance has caused the problem. In addition, theses problems has decreasing performance of overall network in various form of road and high density of vehicle node as urban area. Therefore, this paper proposed Clustering based Routing Algorithm (CBRA) to efficiently transmit emergency message in high density of vehicle as urban area. The CBRA managed moving vehicle via clustering when vehicle transmit emergency messages. In addition, we resolve linkage problem between vehicles according to various form of road. The CBRA resolve link brokage problem according to various form of road as urban using clustering. In addition, we resolve broadcasting storm problem and improving efficacy using selection flooding method. simulation results using ns-2 revealed that the proposed CBRA performs much better than the existing routing protocols.

UNISM: Unified Scheduling and Mapping for General Networks on Chip

Task scheduling and core mapping have a significant impact on the overall performance of network on chip (NOC). In this paper, a unified task scheduling and core mapping algorithm called UNISM is proposed for different NOC architectures including regular mesh, irregular mesh and custom networks. First, a unified model combining scheduling and mapping is introduced using mixed integer linear programming (MILP). Then, a novel graph model is proposed to consider the network irregularity and estimate communication energy and latency, since the number of network hops is not accurate enough for irregular mesh and custom networks. To make the MILP-based UNISM scalable, a heuristic is employed to speed up our method. Compared with two previous state-of-the-art works, experimental results show that more than 15% and 11.5% improvement on the execution time is achieved with similar energy consumption on average for regular mesh NOC. For irregular and custom NOC, the improvement is 27.3% and 14.5% on the execution time with 24.3% and 18.5% lower energy. Moreover, our method is scalable for large benchmarks in terms of runtime.

Improve Packet Delivery Ratio Using Extended Deflection Routing Algorithm in Optical Burst Switching Network

In order to ensure the quality of service in the optical burst switching network and solve the control problem of the deflection algorithm, this paper proposes extended deflection routing algorithm that based on priority and adjustable parameters. The algorithm detects the function of packet loss rate by increasing the deflection conditions to control the deflection of conflict burst packet, and find the best deflection routing from the sense of adjustable packet loss rate and deflection’s path length. When a conflict occurs, if satisfying the conditions, we deflect it, otherwise put it away, thus ensuring the network load balancing. Finally, the results of the simulation show that the algorithm can effectively reduce the packet loss rate of the entire network, choose the best deflection path, and to a certain extent reduce the end to end transmission delay effectively, reduce pressure of the offset time to guarantee quality of service for deflection burst, thus improve the performance of overall network. The proposed algorithm is effective.

An agent-assisted QoS-based routing algorithm for wireless sensor networks

Existing routing algorithms are not effective in supporting the dynamic characteristics of wireless sensor networks (WSNs) and cannot ensure sufficient quality of service in WSN applications. This paper proposes a novel agent-assisted QoS-based routing algorithm for wireless sensor networks. In the proposed algorithm, the synthetic QoS of WSNs is chosen as the adaptive value of a Particle Swarm Optimization algorithm to improve the overall performance of network. Intelligent software agents are used to monitor changes in network topology, network communication flow, and each node's routing state. These agents can then participate in network routing and network maintenance. Experiment results show that the proposed algorithm can ensure better quality of service in wireless sensor networks compared with traditional algorithms.

Performance Analysis of Multilayered Multipriority Asymmetric-Sized Delta Networks

The performance of multilayered asymmetric-sized finite-buffered delta networks supporting multiclass routing traffic is presented and analyzed in the uniform traffic conditions under various loads using simulations. The rationale behind introducing asymmetric-sized buffered systems is to have a better exploitation of available buffer spaces, while the implementation of multilayered architecture is applied in order to further improve the overall performance of network. The findings of this performance evaluation can be used by network designers for drawing optimal configurations while setting up the network, so as to best meet the performance and cost requirements under the anticipated traffic load and quality of service specifications.