با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
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Big Data Analytics for User-Activity Analysis and User-Anomaly Detection in Mobile Wireless Network
تجزیه و تحلیل داده بزرگ برای تجزیه و تحلیل کاربری فعالیت و تشخیص ناهنجاری کاربر در شبکه های بی سیم سیار-2017 The next generation wireless networks are expected to
operate in fully automated fashion to meet the burgeoning
capacity demand and to serve users with superior quality of
experience. Mobile wireless networks can leverage spatiotemporal information about user and network condition to
embed the system with end-to-end visibility and intelligence. Big
data analytics has emerged as a promising approach to unearth
meaningful insights and to build artificially intelligent models
with assistance of machine learning tools. Utilizing
aforementioned tools and techniques, this paper contributes in
two ways. First, we utilize mobile network data (big data) – call
detail record (CDR) – to analyze anomalous behavior of mobile
wireless network. For anomaly detection purposes, we use
unsupervised clustering techniques namely k-means clustering
and hierarchical clustering. We compare the detected anomalies
with ground truth information to verify their correctness. From
the comparative analysis, we observe that when the network
experiences abruptly high (unusual) traffic demand at any
location and time, it identifies that as anomaly. This helps in
identifying regions of interest (RoI) in the network for special
action such as resource allocation, fault avoidance solution etc.
Second, we train a neural-network based prediction model with
anomalous and anomaly-free data to highlight the effect of
anomalies in data while training/building intelligent models. In
this phase, we transform our anomalous data to anomaly-free
and we observe that the error in prediction while training the
model with anomaly-free data has largely decreased as compared
to the case when the model was trained with anomalous data.
Index Terms: Next generation wireless networks | 5G | Anomaly detection | call detail record | machine learning | network analytics | network behavior analysis | wireless cellular network |
مقاله انگلیسی |
2 |
A Survey on Green Communication and Security Challenges in 5G Wireless Communication Networks
بررسی چالش های ارتباطات و امنیت سبز در شبکه های ارتباطی بی سیم 5G-2017 PII: S1084-8045(17)30226-6 DOI: http://dx.doi.org/10.1016/j.jnca.2017.07.002 Reference: YJNCA1933 To appear in: Journal of Network and Computer Applications Received date: 16 February 2017 Revised date: 6 June 2017 Accepted date: 4 July 2017 Abstract The 5G wireless cellular networks are evolving, to meet the drastic subscriber demands in near future. This is accompanied with a rise in the energy consumption in cellular networks. Higher energy consumption result in a rise in the carbon dioxide emissions into the environment, and exposure to greater amount of harmful radiations. To indemnify the ecological and health concerns associated with the rise in CO2 levels, an important technology is GREEN communication. This paper presents a survey on various energyefficient scenarios for green communication, involving device-to-device (D2D) communication, spectrum sharing, ultra-dense networks (UDNs), massive MIMO, millimeter wave networks and the Internet of Things (IoT). For improving the battery lifetime of user terminals in a network, a three-layer architecture is proposed, which emphasizes on transmitting information through relays, between a given pair of users. The susceptibility of security attack on relays is also enumerated. As security in the networks cannot be overlooked, secure power optimization is studied, and the possible security attack on users within the small cell access point (SCA) of the 5G networks is proposed. Some of the key research challenges in association to green communication and security have been discussed, and the ongoing projects and standardization activities also stated in the paper. Keyword: Carbon dioxide emissions | D2D communication | Ultra dense Networks (UDNs) | massive MIMO | spectrum sharing | Internet of Things (IoT) | mmWave | small cell access point (SCA) | relay |
مقاله انگلیسی |