B.3. Communication/Networking and Information Technology
A. Azimi Kashani; M. Ghanbari; A. M. Rahmani
Abstract
Vehicular ad hoc networks are an emerging technology with an extensive capability in various applications including vehicles safety, traffic management and intelligent transportation systems. Considering the high mobility of vehicles and their inhomogeneous distributions, designing an efficient routing ...
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Vehicular ad hoc networks are an emerging technology with an extensive capability in various applications including vehicles safety, traffic management and intelligent transportation systems. Considering the high mobility of vehicles and their inhomogeneous distributions, designing an efficient routing protocol seems necessary. Given the fact that a road is crowded at some sections and is not crowded at the others, the routing protocol should be able to dynamically make decisions. On the other hand, VANET networks environment is vulnerable at the time of data transmission. Broadcast routing, similar to opportunistic routing, could offer better efficiency compared to other protocols. In this paper, a fuzzy logic opportunistic routing (FLOR) protocol is presented in which the packet rebroadcasting decision-making process is carried out through the fuzzy logic system along with three input parameters of packet advancement, local density, and the number of duplicated delivered packets. The rebroadcasting procedures use the value of these parameters as inputs to the fuzzy logic system to resolve the issue of multicasting, considering the crowded and sparse zones. NS-2 simulator is used for evaluating the performance of the proposed FLOR protocol in terms of packet delivery ratio, the end-to-end delay, and the network throughput compared with the existing protocols such as: FLOODING, P-PERSISTENCE and FUZZBR. The performance comparison also emphasizes on effective utilization of the resources. Simulations on highway environment show that the proposed protocol has a better QoS efficiency compared to the above published methods in the literature
B.3. Communication/Networking and Information Technology
Z. Shaeiri; J. Kazemitabar; Sh. Bijani; M. Talebi
Abstract
As fraudsters understand the time window and act fast, real-time fraud management systems becomes necessary in Telecommunication Industry. In this work, by analyzing traces collected from a nationwide cellular network over a period of a month, an online behavior-based anomaly detection system is provided. ...
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As fraudsters understand the time window and act fast, real-time fraud management systems becomes necessary in Telecommunication Industry. In this work, by analyzing traces collected from a nationwide cellular network over a period of a month, an online behavior-based anomaly detection system is provided. Over time, users' interactions with the network provides a vast amount of usage data. These usage data are modeled to profiles by which users can be identified. A statistical model is proposed that allocate a risk number to each upcoming record which reveals deviation from the normal behavior stored in profiles. Based on the amount of this deviation a decision is made to flag the record as normal or anomaly. If the activity is normal the associated profile is updated; otherwise the record is flagged as anomaly and it will be considered for further investigation. For handling the big data set and implementing the methodology we have used the Apache Spark engine which is an open source, fast and general-purpose cluster computing system for big data handling and analyzes. Experimental results show that the proposed approach can perfectly detect deviations from the normal behavior and can be exploited for detecting anomaly patterns.
B.3. Communication/Networking and Information Technology
V. Babaiyan; Seyyede A. Sarfarazi
Abstract
Telecommunication Companies use data mining techniques to maintain good relationships with their existing customers and attract new customers and identifying profitable/unprofitable customers. Clustering leads to better understanding of customer and its results can be used to definition and decision-making ...
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Telecommunication Companies use data mining techniques to maintain good relationships with their existing customers and attract new customers and identifying profitable/unprofitable customers. Clustering leads to better understanding of customer and its results can be used to definition and decision-making for promotional schemes. In this study, we used the 999-customer purchase records in South Khorasan Telecommunication Company which has been collected during a year. The purpose of this study is to classify customers into several clusters. Since the clusters and the number of their members are determined, high-consumption users will be logged out of the system and high-value customers who are missed will be identified. In this research we divided our customers into five categories: loyal, potential, new, missed and high-consumption by using the Clementine software, developing the RFM model to the LRFM model and TwoStep and k_Means algorithms. Thus, this category will be a good benchmark for company's future decisions and we can make better decisions for each group of customers in the future.
B.3. Communication/Networking and Information Technology
Seyed M. Hosseinirad
Abstract
Due to the resource constraint and dynamic parameters, reducing energy consumption became the most important issues of wireless sensor networks topology design. All proposed hierarchy methods cluster a WSN in different cluster layers in one step of evolutionary algorithm usage with complicated parameters ...
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Due to the resource constraint and dynamic parameters, reducing energy consumption became the most important issues of wireless sensor networks topology design. All proposed hierarchy methods cluster a WSN in different cluster layers in one step of evolutionary algorithm usage with complicated parameters which may lead to reducing efficiency and performance. In fact, in WSNs topology, increasing a layer of cluster is a tradeoff between time complexity and energy efficiency. In this study, regarding the most important WSN’s design parameters, a novel dynamic multilayer hierarchy clustering approach using evolutionary algorithms for densely deployed WSN is proposed. Different evolutionary algorithms such as Genetic Algorithm (GA), Imperialist Competitive Algorithm (ICA) and Particle Swarm Optimization (PSO) are used to find an efficient evolutionary algorithm for implementation of the clustering proposed method. The obtained results demonstrate the PSO performance is more efficient compared with other algorithms to provide max network coverage, efficient cluster formation and network traffic reduction. The simulation results of multilayer WSN clustering design through PSO algorithm show that this novel approach reduces the energy communication significantly and increases lifetime of network up to 2.29 times with providing full network coverage (100%) till 350 rounds (56% of network lifetime) compared with WEEC and LEACH-ICA clsutering.
B.3. Communication/Networking and Information Technology
M. Zahedi; A. Arjomandzadeh
Abstract
Multi-part words in English language are hyphenated and hyphen is used to separate different parts. Persian language consists of multi-part words as well. Based on Persian morphology, half-space character is needed to separate parts of multi-part words where in many cases people incorrectly use space ...
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Multi-part words in English language are hyphenated and hyphen is used to separate different parts. Persian language consists of multi-part words as well. Based on Persian morphology, half-space character is needed to separate parts of multi-part words where in many cases people incorrectly use space character instead of half-space character. This common incorrectly use of space leads to some serious issues in Persian text processing and text readability. In order to cope with the issues, this work proposes a new model to correct spacing in multi-part words. The proposed method is based on statistical machine translation paradigm. In machine translation paradigm, text in source language is translated into a text in destination language on the basis of statistical models whose parameters are derived from the analysis of bilingual text corpora. The proposed method uses statistical machine translation techniques considering unedited multi-part words as a source language and the space-edited multi-part words as a destination language. The results show that the proposed method can edit and improve spacing correction process of Persian multi-part words with a statistically significant accuracy rate.
B.3. Communication/Networking and Information Technology
A. Ghaffari; S. Nobahary
Abstract
Wireless sensor networks (WSNs) consist of a large number of sensor nodes which are capable of sensing different environmental phenomena and sending the collected data to the base station or Sink. Since sensor nodes are made of cheap components and are deployed in remote and uncontrolled environments, ...
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Wireless sensor networks (WSNs) consist of a large number of sensor nodes which are capable of sensing different environmental phenomena and sending the collected data to the base station or Sink. Since sensor nodes are made of cheap components and are deployed in remote and uncontrolled environments, they are prone to failure; thus, maintaining a network with its proper functions even when undesired events occur is necessary which is called fault tolerance. Hence, fault management is essential in these networks. In this paper, a new method has been proposed with particular attention to fault tolerance and fault detection in WSN. The performance of the proposed method was simulated in MATLAB. The proposed method was based on majority vote which can detect permanently faulty sensor nodes with high detection. Accuracy and low false alarm rate were excluded them from the network. To investigate the efficiency of the new method, the researchers compared it with Chen, Lee, and hybrid algorithms. Simulation results indicated that the novel proposed method has better performance in parameters such as detection accuracy (DA) and a false alarm rate (FAR) even with a large set of faulty sensor nodes.
