scholarly journals Street-Level IP Geolocation Algorithm Based on Landmarks Clustering

2021 ◽  
Vol 66 (3) ◽  
pp. 3345-3361
Author(s):  
Fan Zhang ◽  
Fenlin Liu ◽  
Rui Xu ◽  
Xiangyang Luo ◽  
Shichang Ding ◽  
...  
Keyword(s):  
Ip Geolocation ◽  
Street Level

scholarly journals A Street-Level IP Geolocation Method Based on Delay-Distance Correlation and Multilayered Common Routers

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Shichang Ding ◽  
Fan Zhao ◽  
Xiangyang Luo
Keyword(s):  
Geographical Location ◽  
Capital City ◽  
Smart Devices ◽  
5G Networks ◽  
Distance Correlation ◽  
Ip Geolocation ◽  
Street Level ◽  
Relative Delay ◽  
Geolocation Accuracy ◽  
Geographical Locations

The geographical locations of smart devices can help in providing authentication information between multimedia content providers and users in 5G networks. The IP geolocation methods can help in estimating the geographical location of these smart devices. The two key assumptions of existing IP geolocation methods are as follows: (1) the smallest relative delay comes from the nearest host; (2) the distance between hosts which share the closest common routers is smaller than others. However, the two assumptions are not always true in weakly connected networks, which may affect accuracy. We propose a novel street-level IP geolocation algorithm (Corr-SLG), which is based on the delay-distance correlation and multilayered common routers. The first key idea of Corr-SLG is to divide landmarks into different groups based on relative-delay-distance correlation. Different from previous methods, Corr-SLG geolocates the host based on the largest relative delay for the strongly negatively correlated groups. The second key idea is to introduce the landmarks which share multilayered common routers into the geolocation process, instead of only relying on the closest common routers. Besides, to increase the number of landmarks, a new street-level landmark collection method called WiFi landmark is also presented in this paper. The experiments in one province capital city of China, Zhengzhou, show that Corr-SLG can improve the geolocation accuracy remarkably in a real-world network.

scholarly journals Street-Level Landmark Evaluation Based on Nearest Routers

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Ruixiang Li ◽  
Yuchen Sun ◽  
Jianwei Hu ◽  
Te Ma ◽  
Xiangyang Luo
Keyword(s):  
Binomial Distribution ◽  
Evaluation Method ◽  
Relational Model ◽  
Distance Constraint ◽  
Distance Correlation ◽  
Ip Geolocation ◽  
Mean Error ◽  
Street Level ◽  
Relation Model ◽  
The Mean

High reliable street-level landmarks are the basis of IP geolocation, but landmark evaluation methods having been proposed cannot evaluate the street-level landmarks. Therefore, in this paper, a street-level landmark evaluation method based on nearest router is proposed. The location organization declared is regarded as an area not a point. Firstly, the declared location of preevaluated landmark is verified by IP location databases. Secondly, the preevaluated landmarks are grouped according to their nearest router. Then, the distance constraint is obtained using delay value between landmark and its nearest router by delay-distance correlation. And relation model is established among distance constraint, organization’s region radius, and distance between two landmarks. Finally, the reliability value of landmarks is calculated in each group based on relational model and binomial distribution. Landmarks evaluation experiment is taken based on 7082 preevaluated landmarks, and the results show that geolocation errors decrease obviously using evaluated landmarks. The mean error of 100 targets in Shanghai is reduced from 7.832km to 2.185km.

The Working Sheep Dog as a Model of the Street- Level Public Servant

Public Voices ◽  
2017 ◽  
Vol 6 (1) ◽  
pp. 51
Author(s):  
Anne J. Hacker
Keyword(s):  
Organizational Structures ◽  
Servant Leader ◽  
Street Level ◽  
Public Servant ◽  
The Relationship

There are examples all around us of natural, simple, yet amazingly complex organizational structures that demonstrate models of leadership that are of use today. The working sheep dog is one such example. It is a vision of grace, ability, stamina and integrity. The relationship that exists between theses canine and human partners mirrors that of the street-level public servant and servant leader.

The Art of Improvisation and Street-Level Bureaucracy

Public Voices ◽  
2016 ◽  
Vol 12 (2) ◽  
pp. 68
Author(s):  
Lauren Bock Mullins
Keyword(s):  
Bureaucratic Discretion ◽  
Street Level ◽  
Similarities And Differences ◽  
New Framework ◽  
Street Level Bureaucracy

This article explores the similarities and differences between the art of improvisation and street-level bureaucracy. By offering a new framework that points out the similarities between bureaucratic discretion and improvisation, we see how street-level bureaucracy has artistic elements, which can be helpful in expanding our understanding of this phenomenon.

Policy Refiners and Street-Level Lesson Learners

2018 ◽  
Author(s):  
Alastair Stark
Keyword(s):  
Policy Evaluation ◽  
Central Government ◽  
Street Level ◽  
Street Level Bureaucrats ◽  
Central Level ◽  
Government Level ◽  
Inquiry Lesson

This chapter explores agents who are influential in terms of inquiry lesson-learning but have not been examined before in inquiry literature. The key argument is that two types of agent—policy refiners and street-level bureaucrats—are important when it comes to the effectiveness of post-crisis lesson-learning. As they travel down from the central government level, street-level actors champion, reinterpret, and reject inquiry lessons, often because those lessons do not consider local capacities. Policy refiners, however, operate at the central level in the form of taskforces, implementation reviews, and policy evaluation processes. These refiners examine potentially problematic inquiry lessons in greater detail in order to determine whether and how they should be implemented. In doing so, these ‘mini-inquiries’ can reformulate or even abandon inquiry recommendations.

scholarly journals Mapping Urban Environmental Performance with Emerging Data Sources: A Case of Urban Greenery and Traffic Noise in Sydney, Australia

2021 ◽  
Vol 13 (2) ◽  
pp. 605
Author(s):  
Zahra Nourmohammadi ◽  
Tanapon Lilasathapornkit ◽  
Mudabber Ashfaq ◽  
Ziyuan Gu ◽  
Meead Saberi
Keyword(s):  
Negative Correlation ◽  
Seasonal Variations ◽  
Environmental Performance ◽  
Traffic Noise ◽  
Time Dependent ◽  
Data Sources ◽  
Street Level ◽  
Urban Greenery ◽  
Key Aspects ◽  
Sydney Australia

Measuring urban environmental performance supports understanding and improving the livability and sustainability of a city. Creating a more livable and attractive environment facilitates a greater shift to active and greener transport modes. Two key aspects, among many others, that determine the environmental performance of an urban area are greenery and noise. This study aims to map street-level greenery and traffic noise using emerging data sources including crowd-sourced mobile phone-based data and street-level imagery data in Sydney, Australia. Results demonstrate the applicability of emerging data sources and the presented advanced techniques in capturing the seasonal variations in urban greenery and time-dependent nature of traffic noise. Results also confirm the presence of a negative correlation between urban greenery and traffic noise.

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