scholarly journals A comprehensive evaluation of cache utilization characteristics in large scale WSN considering network driven cache replacement techniques

2018 ◽  
Vol 188 ◽  
pp. 05004
Author(s):  
Christos Panagiotou ◽  
Christos Antonopoulos ◽  
Stavros Koubias
Keyword(s):  
Smart City ◽  
Large Scale ◽  
Network Performance ◽  
Comprehensive Evaluation ◽  
Resource Conservation ◽  
Data Sources ◽  
Data Cache ◽  
Cache Replacement ◽  
Large Scale Networks ◽  
Result Analysis

WSNs as adopted in current smart city deployments, must address demanding traffic factors and resilience in failures. Furthermore, caching of data in WSN can significantly benefit resource conservation and network performance. However, data sources generate data volumes that could not fit in the restricted data cache resources of the caching nodes. This unavoidably leads to data items been evicted and replaced. This paper aims to experimentally evaluate the prominent caching techniques in large scale networks that resemble the Smart city paradigm regarding network performance with respect to critical application and network parameters. Through respective result analysis valuable insights are provided concerning the behaviour of caching in typical large scale WSN scenarios.

scholarly journals Software Defined Networking Flow Table Management of OpenFlow Switches Performance and Security Challenges: A Survey

2020 ◽  
Vol 12 (9) ◽  
pp. 147 ◽  
Author(s):  
Babangida Isyaku ◽  
Mohd Soperi Mohd Zahid ◽  
Maznah Bte Kamat ◽  
Kamalrulnizam Abu Bakar ◽  
Fuad A. Ghaleb
Keyword(s):  
Large Scale ◽  
Network Performance ◽  
Software Defined Networking ◽  
Cloud Services ◽  
Future Research ◽  
Control Plane ◽  
Processing Load ◽  
Flow Table ◽  
Data Plane ◽  
Large Scale Networks

Software defined networking (SDN) is an emerging network paradigm that decouples the control plane from the data plane. The data plane is composed of forwarding elements called switches and the control plane is composed of controllers. SDN is gaining popularity from industry and academics due to its advantages such as centralized, flexible, and programmable network management. The increasing number of traffics due to the proliferation of the Internet of Thing (IoT) devices may result in two problems: (1) increased processing load of the controller, and (2) insufficient space in the switches’ flow table to accommodate the flow entries. These problems may cause undesired network behavior and unstable network performance, especially in large-scale networks. Many solutions have been proposed to improve the management of the flow table, reducing controller processing load, and mitigating security threats and vulnerabilities on the controllers and switches. This paper provides comprehensive surveys of existing schemes to ensure SDN meets the quality of service (QoS) demands of various applications and cloud services. Finally, potential future research directions are identified and discussed such as management of flow table using machine learning.

scholarly journals PERBANDINGAN FASTETHERNET , GIGABITETHERNET DAN SERIAL DALAM JARINGAN BERBASIS ROUTING PROTOKOL EIGRP

2017 ◽  
Author(s):  
Oris Krianto Sulaiman ◽  
Adi Widarma
Keyword(s):  
Routing Protocol ◽  
Large Scale ◽  
Network Performance ◽  
Computer Network ◽  
Network Access ◽  
Improve Performance ◽  
Technological Developments ◽  
Increasing Demand ◽  
Large Scale Networks ◽  
Selection Of

Technological developments in the computer network gradually grew rapidly along with the increasing demand for network access that is efficient, stable and fast . One of the factors that affect the speed of the network is to use ethernet and a serial technology in which each of these technologies has its own characteristics to improve performance in the network. This technology is supported by a good network design . In large-scale networks is needed a high ability to improve network performance , EIGRP routing protocol enables improved network performance effectively where one of them for ethernet and serial technologies . Selection of Ethernet and serial technologies within EIGRP routing protocol would greatly assist in improving the performance of the network , with the calculation of EIGRP metric to compare which technology is better in the EIGRP routing protocol.

Intelligent Lighting Control System in Large-Scale Sports Competition Venues

2018 ◽  
pp. 172-182 ◽  
Author(s):  
Shengmin CAO
Keyword(s):  
Control System ◽  
Large Scale ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Fuzzy Comprehensive Evaluation ◽  
Practical Significance ◽  
Lighting Control ◽  
Sports Events ◽  
Planning And Design ◽  
Comprehensive Evaluation Model

This paper mainly studies the application of intelligent lighting control system in different sports events in large sports competition venues. We take the Xiantao Stadium, a large­scale sports competition venue in Zaozhuang City, Shandong Province as an example, to study its intelligent lighting control system. In this paper, the PID (proportion – integral – derivative) incremental control model and the Karatsuba multiplication model are used, and the intelligent lighting control system is designed and implemented by multi­level fuzzy comprehensive evaluation model. Finally, the paper evaluates the actual effect of the intelligent lighting control system. The research shows that the intelligent lighting control system designed in this paper can accurately control the lighting of different sports in large stadiums. The research in this paper has important practical significance for the planning and design of large­scale sports competition venues.

scholarly journals HTPC: heterogeneous traffic-aware partition coding for random packet spraying in data center networks

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Jiawei Huang ◽  
Shiqi Wang ◽  
Shuping Li ◽  
Shaojun Zou ◽  
Jinbin Hu ◽  
...  
Keyword(s):  
Data Center ◽  
Large Scale ◽  
Network Performance ◽  
Rooted Tree ◽  
Heterogeneous Traffic ◽  
Data Center Networks ◽  
Packet Reordering ◽  
Traffic Characteristics ◽  
Network Utilization ◽  
The Impact

AbstractModern data center networks typically adopt multi-rooted tree topologies such leaf-spine and fat-tree to provide high bisection bandwidth. Load balancing is critical to achieve low latency and high throughput. Although the per-packet schemes such as Random Packet Spraying (RPS) can achieve high network utilization and near-optimal tail latency in symmetric topologies, they are prone to cause significant packet reordering and degrade the network performance. Moreover, some coding-based schemes are proposed to alleviate the problem of packet reordering and loss. Unfortunately, these schemes ignore the traffic characteristics of data center network and cannot achieve good network performance. In this paper, we propose a Heterogeneous Traffic-aware Partition Coding named HTPC to eliminate the impact of packet reordering and improve the performance of short and long flows. HTPC smoothly adjusts the number of redundant packets based on the multi-path congestion information and the traffic characteristics so that the tailing probability of short flows and the timeout probability of long flows can be reduced. Through a series of large-scale NS2 simulations, we demonstrate that HTPC reduces average flow completion time by up to 60% compared with the state-of-the-art mechanisms.

scholarly journals Contribution of Ionotropic Glutamatergic Receptors to Excitability and Attentional Signals in Macaque Frontal Eye Field

2021 ◽  
Author(s):  
Miguel Dasilva ◽  
Christian Brandt ◽  
Marc Alwin Gieselmann ◽  
Claudia Distler ◽  
Alexander Thiele
Keyword(s):  
Attentional Control ◽  
Large Scale ◽  
Neuronal Excitability ◽  
Cell Types ◽  
Receptor Activation ◽  
Frontal Eye Field ◽  
Control Signals ◽  
Cognitive Operations ◽  
Eye Field ◽  
Large Scale Networks

Abstract Top-down attention, controlled by frontal cortical areas, is a key component of cognitive operations. How different neurotransmitters and neuromodulators flexibly change the cellular and network interactions with attention demands remains poorly understood. While acetylcholine and dopamine are critically involved, glutamatergic receptors have been proposed to play important roles. To understand their contribution to attentional signals, we investigated how ionotropic glutamatergic receptors in the frontal eye field (FEF) of male macaques contribute to neuronal excitability and attentional control signals in different cell types. Broad-spiking and narrow-spiking cells both required N-methyl-D-aspartic acid and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor activation for normal excitability, thereby affecting ongoing or stimulus-driven activity. However, attentional control signals were not dependent on either glutamatergic receptor type in broad- or narrow-spiking cells. A further subdivision of cell types into different functional types using cluster-analysis based on spike waveforms and spiking characteristics did not change the conclusions. This can be explained by a model where local blockade of specific ionotropic receptors is compensated by cell embedding in large-scale networks. It sets the glutamatergic system apart from the cholinergic system in FEF and demonstrates that a reduction in excitability is not sufficient to induce a reduction in attentional control signals.

scholarly journals Leveraging Edge Intelligence for Video Analytics in Smart City Applications

Information ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 14
Author(s):  
Aluizio Rocha Neto ◽  
Thiago P. Silva ◽  
Thais Batista ◽  
Flávia C. Delicato ◽  
Paulo F. Pires ◽  
...  
Keyword(s):  
Distributed System ◽  
Smart City ◽  
Large Scale ◽  
Facial Recognition ◽  
Public Spaces ◽  
Hardware Accelerators ◽  
Video Streams ◽  
Video Analytics ◽  
Learning Tasks ◽  
Naive Approach

In smart city scenarios, the huge proliferation of monitoring cameras scattered in public spaces has posed many challenges to network and processing infrastructure. A few dozen cameras are enough to saturate the city’s backbone. In addition, most smart city applications require a real-time response from the system in charge of processing such large-scale video streams. Finding a missing person using facial recognition technology is one of these applications that require immediate action on the place where that person is. In this paper, we tackle these challenges presenting a distributed system for video analytics designed to leverage edge computing capabilities. Our approach encompasses architecture, methods, and algorithms for: (i) dividing the burdensome processing of large-scale video streams into various machine learning tasks; and (ii) deploying these tasks as a workflow of data processing in edge devices equipped with hardware accelerators for neural networks. We also propose the reuse of nodes running tasks shared by multiple applications, e.g., facial recognition, thus improving the system’s processing throughput. Simulations showed that, with our algorithm to distribute the workload, the time to process a workflow is about 33% faster than a naive approach.

scholarly journals How does the position of firms in the supply chain affect their performance? An empirical study

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Siddharth Arora ◽  
Alexandra Brintrup
Keyword(s):  
Supply Chain ◽  
Empirical Data ◽  
Large Scale ◽  
Individual Performance ◽  
Supply Network ◽  
Supply Chain Networks ◽  
Focal Firm ◽  
Cooperative Competition ◽  
Large Scale Networks ◽  
The Relationship

AbstractThe relationship between a firm and its supply chain has been well studied, however, the association between the position of firms in complex supply chain networks and their performance has not been adequately investigated. This is primarily due to insufficient availability of empirical data on large-scale networks. To addresses this gap in the literature, we investigate the relationship between embeddedness patterns of individual firms in a supply network and their performance using empirical data from the automotive industry. In this study, we devise three measures that characterize the embeddedness of individual firms in a supply network. These are namely: centrality, tier position, and triads. Our findings caution us that centrality impacts individual performance through a diminishing returns relationship. The second measure, tier position, allows us to investigate the concept of tiers in supply networks because we find that as networks emerge, the boundaries between tiers become unclear. Performance of suppliers degrade as they move away from the focal firm (i.e., Toyota). The final measure, triads, investigates the effect of buying and selling to firms that supply the same customer, portraying the level of competition and cooperation in a supplier’s network. We find that increased coopetition (i.e., cooperative competition) is a performance enhancer, however, excessive complexity resulting from being involved in both upstream and downstream coopetition results in diminishing performance. These original insights help understand the drivers of firm performance from a network perspective and provide a basis for further research.

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