فهرست مطالب

Information Systems and Telecommunication - Volume:7 Issue: 4, 2020
  • Volume:7 Issue: 4, 2020
  • تاریخ انتشار: 1399/03/18
  • تعداد عناوین: 7
  • Maryam Bavaghar*, Amin Mohajer, Sarah Taghavi Motlagh Pages 238-247

    In Wireless Sensor Networks (WSNs), sensor nodes are usually deployed with limited energy reserves in remote environments for a long period of time with less or no human intervention. It makes energy efficiency as a challenging issue both for the design and deployment of sensor networks. This paper presents a novel approach named Energy Efficient Clustering Algorithm (EECA) for Wireless Sensor Networks which is based on two phases clustering model and provides maximum network coverage in an energy efficient way. In this framework, an effective resource-aware load balancing approach applied for autonomous methods of configuring the parameters in accordance with the signaling patterns in which approximately the same bit rate data is provided for each sensor. This resource-efficient clustering model can also form energy balanced clusters which results in increasing network life time and ensuring better network coverage. Simulation results prove that EECA is better than LEACH, LEA2C and EECS with respect to network lifetime and at the same time achieving more network coverage. In addition to obtained an optimal cluster size with minimum energy loss, the proposed approach also suggests new and better way for selecting cluster heads to reduce energy consumption of the distributed nodes resulting in increased operational reliability of sensor networks.

    Keywords: Wireless Sensor Networks, Energy-Efficient Clustering, Cluster Head Selection, Network Coverage, Network Life Time
  • Kasra Babaei, ZhiYuan Chen*, Tomas Maul Pages 248-261

    Fraudulent activities have been rising globally resulting companies losing billions of dollars that can cause severe financial damages. Various approaches have been proposed by researchers in different applications. Studying these approaches can help us obtain a better understanding of the problem. The aim of this paper is to investigate different aspects of fraud prevention and detection in telecommunication. This study presents a review of different fraud categories in telecommunication, the challenges that hinder the detection process, and some proposed solutions to overcome them. Also, the performance of some of the state-of-the-art approaches is reported followed by our guideline and recommendation in choosing the best metrics.

    Keywords: Fraud Detection, Machine Learning, Telecommunication
  • Wasswa Shafik, S.Mojtaba Matinkhah*, Mohammad Ghasemzadeh Pages 262-277

    Unmanned Aerial vehicles (UAVs) emerged into a promising research trend applied in several disciplines based on the benefits, including efficient communication, on-time search, and rescue operations, appreciate customer deliveries among more. The current technologies are using fixed base stations (BS) to operate onsite and off-site in the fixed position with its associated problems like poor connectivity. These open gates for the UAVs technology to be used as a mobile alternative to increase accessibility in beam selection with a fifth-generation (5G) connectivity that focuses on increased availability and connectivity. This paper presents a first fast semi-online 3-Dimensional machine learning algorithm suitable for proper beam selection as is emitted from UAVs. Secondly, it presents a detailed step by step approach that is involved in the multi-armed bandit approach in solving UAV solving selection exploration to exploitation dilemmas. The obtained results depicted that a multi-armed bandit problem approach can be applied in optimizing the performance of any mobile networked devices issue based on bandit samples like Thompson sampling, Bayesian algorithm, and ε-Greedy Algorithm. The results further illustrated that the 3-Dimensional algorithm optimizes utilization of technological resources compared to the existing single and the 2-Dimensional algorithms thus close optimal performance on the average period through machine learning of realistic UAV communication situations.

    Keywords: Unmanned Ariel Vehicle, Multi-Armed Bandit, Reinforcement Learning Algorithms, Beam selection
  • Fatemeh Fakhar Pages 278-293

    Network simulation is a technique that models network behavior by performing transaction calculations between different network entities and using mathematical formulas and taking observations of network products. A network simulator is a software program have been applied to analyze the performance of a computer network without the presence of a real network. Hardware equipment, equipment configuration, communication, and routing protocols and network traffic modeled in simulation software and the behavior of the network and its components examined from different dimensions. The user can also customize the simulation software according to their needs. Simulation software has different uses, and the user can use these tools to model their network by recognizing this software. In terms of research, it is difficult to create a network, especially large networks, in a real-time scenario, and it is not easily possible to carry out it in the real world, and it is very costly. So, simulators help network developers to control whether the network can work in real-time or not, or whether it is efficient enough. This reduces the time and cost of network application testing.Today, simulation technology is successfully used to model, design and manage a variety of intelligent systems. Numerous tools have been created in this regard. In this article, we review and compare important network simulators such as CloudSim, GloMoSim, GNS3, NS-2, Opnet, OMNet ++, NetSim, NS-3, AVRORA, Packet Tracer, QualNet, J-Sim, REAL and OptSim and their results. These comparisons express from several perspectives in the tables.

    Keywords: Simulation, network simulator, network simulation, Network simulation languages, comparison
  • Nima Seyyed Anzabi Nezhad*, Ghosheh Abed Hodtani Pages 294-304

    Gaussian interference known at the transmitter can be fully canceled in a Gaussian communication channel employing dirty paper coding, as Costa shows, when interference is independent of the channel noise and when the channel input designed independently of the interference. In this paper, a new and general version of the Gaussian channel in presence of two-sided state information correlated to the channel input and noise is considered. Determining a general achievable rate for the channel and obtaining the capacity in a non-limiting case, we try to analyze and solve the Gaussian version of the Cover-Chiang theorem mathematically and information-theoretically. Our capacity theorem, while including all previous theorems as its special cases, explains situations that can not be analyzed by them; for example, the effect of the correlation between the side information and the channel input on the capacity of the channel that can not be analyzed with Costa’s “writing on dirty paper" theorem. Meanwhile, we try to exemplify the concept of “cognition" of the transmitter or the receiver on a variable (here, the channel noise) with the information-theoretic concept of “side information" correlated to that variable and known at the transmitter or at the receiver. According to our theorem, the channel capacity is an increasing function of the mutual information of the side information and the channel noise.

    Keywords: Communication channel capacity, Gaussian channel capacity, correlated side information, two sided state information, interference cancellation, dirty paper coding
  • Ali Ghaffari*, Afshin Mahdavi Pages 305-315

    Cloud computing is becoming an important and adoptable technology for many of the organization which requires a large amount of physical tools. In this technology, services are provided and presented according to users’ requests. Due to the presence of a large number of data centers in cloud computing, power consumption has recently become an important issue. However, data centers hosting Cloud applications consume huge amounts of electrical energy and contributing to high operational costs to the environment. Therefore, we need Green Cloud computing solutions that can not only minimize operational costs but also reduce the environmental impact. Live migration of virtual machines and their scheduling and embedding lead to enhanced efficiency of dynamic resources. The guarantee of service quality and service reliability is an indispensable and irrevocable requirement with respect to service level agreement. Hence, providing a method for reducing costs of power consumption, data transmission, bandwidth and, also, for enhancing quality of service (QoS) in cloud computing is critical. In this paper, a Big Bang–Big Crunch (BB-BC) based algorithm for embedding virtual machines in cloud computing was proposed. We have validated our approach by conducting a performance evaluation study using the CloudSim toolkit. Simulation results indicate that the proposed method not only enhances service quality, thanks to the reduction of agreement violation, but also reduces power consumption.

    Keywords: Cloud computing, Virtual machine, Big Bang–Big Crunch algorithm, Energy, Service level agreement
  • Hojjat Farrahi Farimani, Davoud Bahrepour, Seyed Reza Kamel Tabbakh*, reza Ghaemi Pages 316-325

    Due to the increased use of cloud computing services, cloud data centers are in search of solutions in order to better provide the services demanded by their users. Virtual machine consolidation is an appropriate solution to the trade-off between power consumption and service level agreement violation. The present study aimed to identify low, medium, and high load identification techniques, as well as the energy consumption and SLAv to minimize. In addition to the reduced costs of cloud providers, these techniques enhance the quality of the services demanded by the users. To this end, reallocation of resources to physical hosts was performed at the medium load level using a centralized method to classify the physical hosts. In addition, quartile was applied in each medium to reduce the energy consumption parameters and violation level. The three introduced SMT - NMT and FMT methods for reallocation of resources were tested and the best results were compared with previous methods.The proposed method was evaluated using the Cloudsim software with real Planet Lab data and five times run, the simulation results confirmed the efficiency of the proposed algorithm, which tradeoff between decreased the energy consumption and service level of agreement violation (SLAv) properly.

    Keywords: Cloud Computing, Energy Consumption, Service Level Agreement Violation, Virtual Machine Consolidation