Construction of multi-level data aggregation trees for energy efficiency and delivery delay in machine-to-machine communications

2020 ◽  
Author(s):  
Prasad Challa ◽  
B. Eswara Reddy
Keyword(s):  
Energy Efficiency ◽  
Data Aggregation ◽  
Machine To Machine ◽  
Delivery Delay ◽  
Level Data ◽  
Multi Level

Detecting Wormhole Attack on Data Aggregation in Hierarchical WSN

2017 ◽  
Vol 11 (1) ◽  
pp. 35-51 ◽  
Author(s):  
Mukesh Kumar ◽  
Kamlesh Dutta
Keyword(s):  
Energy Efficiency ◽  
Data Aggregation ◽  
Low Cost ◽  
Attack Detection ◽  
Sensor Nodes ◽  
Network Data ◽  
Light Weight ◽  
Malicious Node ◽  
Combine Data ◽  
Wormhole Attack

Wireless networks are used by everyone for their convenience for transferring packets from one node to another without having a static infrastructure. In WSN, there are some nodes which are light weight, small in size, having low computation overhead, and low cost known as sensor nodes. In literature, there exists many secure data aggregation protocols available but they are not sufficient to detect the malicious node. The authors require a better security mechanism or a technique to secure the network. Data aggregation is an essential paradigm in WSN. The idea is to combine data coming from different source nodes in order to achieve energy efficiency. In this paper, the authors proposed a protocol for worm hole attack detection during data aggregation in WSN. Main focus is on wormhole attack detection and its countermeasures.

scholarly journals Determinants of Consistent Condom Use Vary by Partner Type among Young Men in Kisumu, Kenya: A Multi-level Data Analysis

2008 ◽  
Vol 14 (4) ◽  
pp. 949-959 ◽  
Author(s):  
Nelli Westercamp ◽  
Christine L. Mattson ◽  
Michelle Madonia ◽  
Stephen Moses ◽  
Kawango Agot ◽  
...  
Keyword(s):  
Data Analysis ◽  
Condom Use ◽  
Young Men ◽  
Consistent Condom ◽  
Consistent Condom Use ◽  
Partner Type ◽  
Level Data ◽  
Multi Level

Improved multi-level data storage properties of germanium-antimony-tellurium films by nitrogen doping

2017 ◽  
Vol 141 ◽  
pp. 120-124 ◽  
Author(s):  
Xiao Yu ◽  
Yue Zhao ◽  
Chao Li ◽  
Chaoquan Hu ◽  
Liang Ma ◽  
...  
Keyword(s):  
Data Storage ◽  
Nitrogen Doping ◽  
Level Data ◽  
Multi Level ◽  
Storage Properties

The influence of immigrant status and concentration on psychiatric disorder in Canada: a multi-level analysis

2011 ◽  
Vol 41 (10) ◽  
pp. 2221-2231 ◽  
Author(s):  
N. M. Menezes ◽  
K. Georgiades ◽  
M. H. Boyle
Keyword(s):  
Psychiatric Disorder ◽  
First Generation ◽  
Psychotic Disorders ◽  
Individual Risk ◽  
Immigrant Status ◽  
Individual Level ◽  
Level Data ◽  
Immigrant Concentration ◽  
Multi Level ◽  
Neighborhood Level

BackgroundMany studies have reported an increased incidence of psychiatric disorder (particularly psychotic disorders) among first generation adult immigrants, along with an increasing risk for ethnic minorities living in low-minority concentration neighborhoods. These studies have depended mostly on European case-based databases. In contrast, North American studies have suggested a lower risk for psychiatric disorder in immigrants, although the effect of neighborhood immigrant concentration has not been studied extensively.MethodUsing multi-level modeling to disaggregate individual from area-level influences, this study examines the influence of first generation immigrant status at the individual level, immigrant concentration at the neighborhood-level and their combined effect on 12-month prevalence of mood, anxiety and substance-dependence disorders and lifetime prevalence of psychotic disorder, among Canadians.ResultsIndividual-level data came from the Canadian Community Health Survey (CCHS) 1.2, a cross-sectional study of psychiatric disorder among Canadians over the age of 15 years; the sample for analysis wasn=35 708. The CCHS data were linked with neighborhood-level data from the Canadian Census 2001 for multi-level logistic regression. Immigrant status was associated with a lower prevalence of psychiatric disorder, with an added protective effect for immigrants living in neighborhoods with higher immigrant concentrations. Immigrant concentration was not associated with elevated prevalence of psychiatric disorder among non-immigrants.ConclusionsThe finding of lower 12-month prevalence of psychiatric disorder in Canadian immigrants, with further lessening as the neighborhood immigrant concentration increases, reflects a model of person–environment fit, highlighting the importance of studying individual risk factors within environmental contexts.

Large Scale Cognitive Wireless Networks

2013 ◽  
pp. 26-52
Author(s):  
Liang Song ◽  
Petros Spachos ◽  
Dimitrios Hatzinakos
Keyword(s):  
Energy Efficiency ◽  
Wireless Networks ◽  
Cognitive Radio ◽  
Data Aggregation ◽  
Network Architecture ◽  
Large Scale ◽  
Vehicular Networks ◽  
Network Resource ◽  
Cognitive Wireless Networks ◽  
Definition Of

Cognitive radio has been proposed to have spectrum agility (or opportunistic spectrum access). In this chapter, the authors introduce the extended network architecture of cognitive radio network, which accesses not only spectrum resource but also wireless stations (networking nodes) and high-level application data opportunistically: the large-scale cognitive wireless networks. The developed network architecture is based upon a re-definition of wireless linkage: as functional abstraction of proximity communications among wireless stations. The operation spectrum and participating stations of such abstract wireless links are opportunistically decided based on their instantaneous availability. It is able to maximize wireless network resource utilization and achieve much higher performance in large-scale wireless networks, where the networking environment can change fast (usually in millisecond level) in terms of spectrum and wireless station availability. The authors further introduce opportunistic routing and opportunistic data aggregation under the developed network architecture, which results in an implementation of cognitive unicast and cognitive data-aggregation wireless-link modules. In both works, it is shown that network performance and energy efficiency can improve with network scale (such as including station density). The applications of large-scale cognitive wireless networks are further discussed in new (and smart) beyond-3G wireless infrastructures, including for example real-time wireless sensor networks, indoor/underground wireless tracking networks, broadband wireless networks, smart grid and utility networks, smart vehicular networks, and emergency networks. In all such applications, the cognitive wireless networks can provide the most cost-effective wireless bandwidth and the best energy efficiency.

IPv6 Routing in a Special Context

2011 ◽  
pp. 415-439
Author(s):  
Zoltán Kanizsai ◽  
Gábor Jeney
Keyword(s):  
Data Aggregation ◽  
System Level ◽  
Routing Schemes ◽  
Ipv6 Network ◽  
Level Data ◽  
Routing Method ◽  
Feedback Data ◽  
Ip Packet ◽  
Information Collecting ◽  
Simple Feedback

This chapter gives an overview of the IPv6 routing techniques focusing on some special IPv6 routing mechanisms, which can ease and optimize IP level data aggregation. Data aggregation should become an important step in information collecting from sensors or other data sources in present-day, IP based networks. In general, a simple feedback message only costs a few bit, or bytes; therefore, using a whole IP packet for every one of them is rather wasteful according to the present resources. Our objective is to introduce a special IPv6 routing method called IPv6 anycasting, which makes possible to identify various services with an IPv6 network address. Basically, by the standard, anycasting is not able to maintain stateful communication sessions, but feedback data aggregation does not require stateful operation, therefore anycasting is an ideal solution to provide feedback routing. The chapter will concentrate on IPv6 advanced routing schemes, and introduce a new IPv6 anycast based system-level data aggregation mechanism.

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