scholarly journals A Periodic Caching Strategy Solution for the Smart City in Information-Centric Internet of Things

2018 ◽  
Vol 10 (7) ◽  
pp. 2576 ◽  
Author(s):  
Muhammad Naeem ◽  
Rashid Ali ◽  
Byung-Seo Kim ◽  
Shahrudin Nor ◽  
Suhaidi Hassan
Keyword(s):  
Internet Of Things ◽  
Response Latency ◽  
Smart City ◽  
Rapid Expansion ◽  
Caching Strategy ◽  
Simulation Results ◽  
Cost Efficient ◽  
Multicast Communications ◽  
The Impact ◽  
Caching Strategies

Named Data Networking is an evolving network model of the Information-centric networking (ICN) paradigm which provides Named-based data contents. In-network caching is the responsible for dissemination of these contents in a scalable and cost-efficient way. Due to the rapid expansion of Internet of Things (IoT) traffic, ICN is envisioned to be an appropriate architecture to maintain the IoT networks. In fact, ICN offers unique naming, multicast communications and, most beneficially, in-network caching that minimizes the response latency and server load. IoT environment involves a study of ICN caching policies in terms of content placement strategies. This paper addressed the caching strategies with the aim to recognize which caching strategy is the most suitable for IoT networks. Simulation results show the impact of different IoT ICN-based caching strategies, out of these; periodic caching is the most appropriate strategy for IoT environments in terms of stretch that results in decreasing the retrieval latency and improves the cache-hit ratio.

scholarly journals Neighbor Aware Protocols for IoT Devices in Smart Cities—Overview, Challenges and Solutions

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 902
Author(s):  
Sungwon Lee ◽  
Muhammad Azfar Azfar Yaqub ◽  
Dongkyun Kim
Keyword(s):  
Internet Of Things ◽  
Duty Cycle ◽  
Smart City ◽  
Mac Protocol ◽  
Smart Cities ◽  
Iot Applications ◽  
Simulation Results ◽  
Iot Devices ◽  
The Impact

The principle of Smart Cities is the interconnection of services, based on a network of Internet of Things (IoT) devices. As the number of IoT devices continue to grow, the demand to organize and maintain the IoT applications is increased. Therefore, the solutions for smart city should have the ability to efficiently utilize the resources and their associated challenges. Neighbor aware solutions can enhance the capabilities of the smart city. In this article, we briefly overview the neighbor aware solutions and challenges in smart cities. We then categorize the neighbor aware solutions and discuss the possibilities using the collaboration among neighbors to extend the lifetime of IoT devices. We also propose a new duty cycle MAC protocol with assistance from the neighbors to extend the lifetime of the nodes. Simulation results further coagulate the impact of neighbor assistance on the performance of IoT devices in smart cities.

scholarly journals Impact of IoT Technologies on Smart City Infrastructure: Current Applications and Future Potential

2019 ◽  
Vol 8 (2S11) ◽  
pp. 2387-2391
Keyword(s):  
Internet Of Things ◽  
Smart City ◽  
It Infrastructure ◽  
Government Officials ◽  
It Industry ◽  
Study Approach ◽  
Potential Applications ◽  
Future Potential ◽  
Industrial Level ◽  
The Impact

With the advent of digitization, upcoming technologies like Internet of Things (IOT) are being used by organizations to manage their business, infrastructure as well as assets. In order to make the IT Infrastructure more efficient, upcoming technologies like Internet of things play a very important role as IoT has increased the scale of the storage and the server spaces, improved the internet connectivity thereby leading to a smarter IT infrastructure. Although IoT adoption is taking place rapidly at the enterprise and industrial level; there is a dearth of academic literature in this area. Hence the objective of the paper is to study the adoption of various IoT technologies for smart city infrastructure, understand the impact/benefits of these technologies and propose future potential applications which can be used for smart infrastructure. A case study approach has been adopted for this research wherein various use cases in the IT industry have been analysed with respect to the adoption of IoT technologies 0066or smart city infrastructure and the benefits of the same to the various sectors. The study will be useful for academicians, and practitioners, and Government officials to design and develop solutions for smart city infrastructure that will add to wellbeing of society at large.

scholarly journals PB-NCC: A Popularity-Based Caching Strategy with Number-of-Copies Control in Information-Centric Networks

2022 ◽  
Vol 12 (2) ◽  
pp. 653
Author(s):  
Yuanhang Li ◽  
Jinlin Wang ◽  
Rui Han
Keyword(s):  
Content Distribution ◽  
Future Internet ◽  
Cache Replacement ◽  
Promising Candidate ◽  
Caching Strategy ◽  
Resolution System ◽  
Content Acquisition ◽  
The Future ◽  
Simulation Results ◽  
Caching Strategies

The Information-Centric Network (ICN), designed for efficient content acquisition and distribution, is a promising candidate architecture for the future Internet. In-network caching in ICN makes it possible to reuse contents and the Name Resolution System (NRS) makes cached contents better serve users. In this paper, we focused on the ICN caching scenario equipped with an NRS, which records the positions of contents cached in ICN. We propose a Popularity-based caching strategy with Number-of-Copies Control (PB-NCC) in this paper. PB-NCC is proposed to solve the problems of unreasonable content distribution and frequent cache replacement in traditional caching strategies in ICN. We examine PB-NCC with a large number of experiments in different topologies and workloads. The simulation results reveal that PB-NCC can improve the cache hit ratio by at least 8.85% and reduce the server load by at least 11.34% compared with other on-path caching strategies, meanwhile maintaining a low network latency.

scholarly journals Measuring Hydrometeors Using a Precipitation Microphysical Characteristics Sensor: Sampling Effect of Different Bin Sizes on Drop Size Distribution Parameters

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Xichuan Liu ◽  
Taichang Gao ◽  
Yuntao Hu ◽  
Xiaojian Shu
Keyword(s):  
Drop Size ◽  
Rain Rate ◽  
Monte Carlo Model ◽  
Rain Gauge ◽  
Sampling Schemes ◽  
Distribution Parameters ◽  
Optimum Sampling ◽  
Simulation Results ◽  
The Impact ◽  
Good Agreement

In order to improve the measurement of precipitation microphysical characteristics sensor (PMCS), the sampling process of raindrops by PMCS based on a particle-by-particle Monte-Carlo model was simulated to discuss the effect of different bin sizes on DSD measurement, and the optimum sampling bin sizes for PMCS were proposed based on the simulation results. The simulation results of five sampling schemes of bin sizes in four rain-rate categories show that the raw capture DSD has a significant fluctuation variation influenced by the capture probability, whereas the appropriate sampling bin size and width can reduce the impact of variation of raindrop number on DSD shape. A field measurement of a PMCS, an OTT PARSIVEL disdrometer, and a tipping bucket rain Gauge shows that the rain-rate and rainfall accumulations have good consistencies between PMCS, OTT, and Gauge; the DSD obtained by PMCS and OTT has a good agreement; the probability of N0, μ, and Λ shows that there is a good agreement between the Gamma parameters of PMCS and OTT; the fitted μ-Λ and Z-R relationship measured by PMCS is close to that measured by OTT, which validates the performance of PMCS on rain-rate, rainfall accumulation, and DSD related parameters.

scholarly journals A New Method to Determine the Impact of Individual Field Quantities on Cycle-to-Cycle Variations in a Spark-Ignited Gas Engine

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4136
Author(s):  
Clemens Gößnitzer ◽  
Shawn Givler
Keyword(s):  
Kinetic Energy ◽  
Flow Field ◽  
Turbulent Kinetic Energy ◽  
Negative Impact ◽  
Operating Conditions ◽  
Engine Operation ◽  
Gas Engine ◽  
Cycle Simulation ◽  
Simulation Results ◽  
The Impact

Cycle-to-cycle variations (CCV) in spark-ignited (SI) engines impose performance limitations and in the extreme limit can lead to very strong, potentially damaging cycles. Thus, CCV force sub-optimal engine operating conditions. A deeper understanding of CCV is key to enabling control strategies, improving engine design and reducing the negative impact of CCV on engine operation. This paper presents a new simulation strategy which allows investigation of the impact of individual physical quantities (e.g., flow field or turbulence quantities) on CCV separately. As a first step, multi-cycle unsteady Reynolds-averaged Navier–Stokes (uRANS) computational fluid dynamics (CFD) simulations of a spark-ignited natural gas engine are performed. For each cycle, simulation results just prior to each spark timing are taken. Next, simulation results from different cycles are combined: one quantity, e.g., the flow field, is extracted from a snapshot of one given cycle, and all other quantities are taken from a snapshot from a different cycle. Such a combination yields a new snapshot. With the combined snapshot, the simulation is continued until the end of combustion. The results obtained with combined snapshots show that the velocity field seems to have the highest impact on CCV. Turbulence intensity, quantified by the turbulent kinetic energy and turbulent kinetic energy dissipation rate, has a similar value for all snapshots. Thus, their impact on CCV is small compared to the flow field. This novel methodology is very flexible and allows investigation of the sources of CCV which have been difficult to investigate in the past.

scholarly journals Improving Sustainability of Smart Cities through Visualization Techniques for Big Data from IoT Devices

2020 ◽  
Vol 12 (14) ◽  
pp. 5595 ◽  
Author(s):  
Ana Lavalle ◽  
Miguel A. Teruel ◽  
Alejandro Maté ◽  
Juan Trujillo
Keyword(s):  
Big Data ◽  
Smart City ◽  
Smart Cities ◽  
Fire Department ◽  
Heterogeneous Data ◽  
Fire Extinguishing ◽  
Heterogeneous Data Sources ◽  
Iot Devices ◽  
Visualization Techniques ◽  
The Impact

Fostering sustainability is paramount for Smart Cities development. Lately, Smart Cities are benefiting from the rising of Big Data coming from IoT devices, leading to improvements on monitoring and prevention. However, monitoring and prevention processes require visualization techniques as a key component. Indeed, in order to prevent possible hazards (such as fires, leaks, etc.) and optimize their resources, Smart Cities require adequate visualizations that provide insights to decision makers. Nevertheless, visualization of Big Data has always been a challenging issue, especially when such data are originated in real-time. This problem becomes even bigger in Smart City environments since we have to deal with many different groups of users and multiple heterogeneous data sources. Without a proper visualization methodology, complex dashboards including data from different nature are difficult to understand. In order to tackle this issue, we propose a methodology based on visualization techniques for Big Data, aimed at improving the evidence-gathering process by assisting users in the decision making in the context of Smart Cities. Moreover, in order to assess the impact of our proposal, a case study based on service calls for a fire department is presented. In this sense, our findings will be applied to data coming from citizen calls. Thus, the results of this work will contribute to the optimization of resources, namely fire extinguishing battalions, helping to improve their effectiveness and, as a result, the sustainability of a Smart City, operating better with less resources. Finally, in order to evaluate the impact of our proposal, we have performed an experiment, with non-expert users in data visualization.

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