Advanced cargo security handheld network access device

Author(s):  
Sergio Enriques ◽  
Yusuf Ozturk
Keyword(s):  
1998 ◽  
Vol 1649 (1) ◽  
pp. 95-104 ◽  
Author(s):  
David T. Hartgen ◽  
Ji Youn Kim

Commercial development at 63 rural and small-town Interstate exits is quantified and related to local market wealth, size, geography, access, traffic, site competition, and other development. Five development types (gas stations, convenience stores, fast food restaurants, sit-down restaurants, and motels) are studied. The geographic information system TransCAD 3.0 is used to determine network access and local trade area characteristics. Models are then estimated for each development type using classification and regression techniques separately and in combination. Model estimates are then compared with actual development. Results show that the relationships are complex, often nonlinear; and show high correlation between development types. The findings should be useful for planning exit land use, coordinating market assessments, determining the value of land, and assessing sites for business placement.


Author(s):  
O. S. Galinina ◽  
S. D. Andreev ◽  
A. M. Tyurlikov

Introduction: Machine-to-machine communication assumes data transmission from various wireless devices and attracts attention of cellular operators. In this regard, it is crucial to recognize and control overload situations when a large number of such devices access the network over a short time interval.Purpose:Analysis of the radio network overload at the initial network entry stage in a machine-to-machine communication system.Results: A system is considered that features multiple smart meters, which may report alarms and autonomously collect energy consumption information. An analytical approach is proposed to study the operation of a large number of devices in such a system as well as model the settings of the random-access protocol in a cellular network and overload control mechanisms with respect to the access success probability, network access latency, and device power consumption. A comparison between the obtained analytical results and simulation data is also offered. 


2010 ◽  
Vol 2 (2) ◽  
pp. 42-48 ◽  
Author(s):  
Hongyan Luo ◽  
Eric Abel ◽  
Alan Slade ◽  
Zhigang Wang ◽  
Robert Steele

2021 ◽  
Vol 1962 (1) ◽  
pp. 012004
Author(s):  
H A Bakarman ◽  
A Alsaqaf ◽  
M Ba’afiah ◽  
F Baqhoom ◽  
M Baraja
Keyword(s):  

Queue ◽  
2021 ◽  
Vol 19 (1) ◽  
pp. 77-93
Author(s):  
Niklas Blum ◽  
Serge Lachapelle ◽  
Harald Alvestrand

In this time of pandemic, the world has turned to Internet-based, RTC (realtime communication) as never before. The number of RTC products has, over the past decade, exploded in large part because of cheaper high-speed network access and more powerful devices, but also because of an open, royalty-free platform called WebRTC. WebRTC is growing from enabling useful experiences to being essential in allowing billions to continue their work and education, and keep vital human contact during a pandemic. The opportunities and impact that lie ahead for WebRTC are intriguing indeed.


Author(s):  
Lujie Tang ◽  
Bing Tang ◽  
Li Zhang ◽  
Feiyan Guo ◽  
Haiwu He

AbstractTaking the mobile edge computing paradigm as an effective supplement to the vehicular networks can enable vehicles to obtain network resources and computing capability nearby, and meet the current large-scale increase in vehicular service requirements. However, the congestion of wireless networks and insufficient computing resources of edge servers caused by the strong mobility of vehicles and the offloading of a large number of tasks make it difficult to provide users with good quality of service. In existing work, the influence of network access point selection on task execution latency was often not considered. In this paper, a pre-allocation algorithm for vehicle tasks is proposed to solve the problem of service interruption caused by vehicle movement and the limited edge coverage. Then, a system model is utilized to comprehensively consider the vehicle movement characteristics, access point resource utilization, and edge server workloads, so as to characterize the overall latency of vehicle task offloading execution. Furthermore, an adaptive task offloading strategy for automatic and efficient network selection, task offloading decisions in vehicular edge computing is implemented. Experimental results show that the proposed method significantly improves the overall task execution performance and reduces the time overhead of task offloading.


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