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      • Open Access Article

        1 - EBG Structures Properties and their Application to Improve Radiation of a Low Profile Antenna
        Masoumeh Rezaei Abkenar Pejman Rezaei
        In this paper we have studied the characteristics of mushroom-like Electromagnetic Band Gap (EBG) structure and performance of a low profile antenna over it. Afterward, a novel EBG surface is presented by some modifications in mushroom-like EBG structure. This structure More
        In this paper we have studied the characteristics of mushroom-like Electromagnetic Band Gap (EBG) structure and performance of a low profile antenna over it. Afterward, a novel EBG surface is presented by some modifications in mushroom-like EBG structure. This structure, which has more compact electrical dimensions, is analyzed and its electromagnetic properties are derived. Results show that resonant frequency of this novel structure is about 15.3% lower than the basic structure with the same size. Moreover, the novel EBG structure has been used as the ground plane of antenna. Its application has improved radiation of a low profile dipole antenna. The antenna performance over the new EBG ground plane is compared with the conventional mushroom-like EBG structure. Simulation results show that using this slot loaded EBG surface, results in 13.68dB improvement in antenna return loss, in comparison with conventional mushroom-like EBG, and 33.87dB improvement in comparison with metal ground plane. Besides, results show that, EBG ground planes have increased the input match frequency bandwidth of antenna. Manuscript profile
      • Open Access Article

        2 - A Novel Approach for Cluster Self-Optimization Using Big Data Analytics
        Abbas Mirzaei Amir Rahimi
        One of the current challenges in providing high bitrate services in next generation mobile networks is limitation of available resources. The goal of proposing a self-optimization model is to maximize the network efficiency and increase the quality of services provided More
        One of the current challenges in providing high bitrate services in next generation mobile networks is limitation of available resources. The goal of proposing a self-optimization model is to maximize the network efficiency and increase the quality of services provided to femto-cell users, considering the limited resources in radio access networks. The basis for our proposed scheme is to introduce a self-optimization model based on neighbouring relations. Using this model, we can create the possibility of controlling resources and neighbouring parameters without the need of human manipulation and only based on the network’s intelligence. To increase the model efficiency, we applied the big data technique for analyzing data and increasing the accuracy of the decision-making process in a way that on the uplink, the sent data by users is to be analyzed in self-optimization engine. The experimental results show that despite the tremendous volume of the analyzed data – which is hundreds of times bigger than usual methods – it is possible to improve the KPIs, such as throughput, up to 30 percent by optimal resource allocation and reducing the signaling load. Also, the presence of feature extraction and parameter selection modules will reduce the response time of the self-optimization model up to 25 percent when the number of parameters is too high Moreover, numerical results indicate the superiority of using support vector machine (SVM) learning algorithm. It improves the accuracy level of decision making based on the rule-based expert system. Finally, uplink quality improvement and 15-percent increment of the coverage area under satisfied SINR conditions can be considered as outcome of the proposed scheme. Manuscript profile
      • Open Access Article

        3 - BSFS: A Bidirectional Search Algorithm for Flow Scheduling in Cloud Data Centers
        Hasibeh Naseri Sadoon Azizi Alireza Abdollahpouri
        To support high bisection bandwidth for communication intensive applications in the cloud computing environment, data center networks usually offer a wide variety of paths. However, optimal utilization of this facility has always been a critical challenge in a data cent More
        To support high bisection bandwidth for communication intensive applications in the cloud computing environment, data center networks usually offer a wide variety of paths. However, optimal utilization of this facility has always been a critical challenge in a data center design. Flow-based mechanisms usually suffer from collision between elephant flows; while, packet-based mechanisms encounter packet re-ordering phenomenon. Both of these challenges lead to severe performance degradation in a data center network. To address these problems, in this paper, we propose an efficient mechanism for the flow scheduling problem in cloud data center networks. The proposed mechanism, on one hand, makes decisions per flow, thus preventing the necessity for rearrangement of packets. On the other hand, thanks do SDN technology and utilizing bidirectional search algorithm, our proposed method is able to distribute elephant flows across the entire network smoothly and with a high speed. Simulation results confirm the outperformance of our proposed method with the comparison of state-of-the-art algorithms under different traffic patterns. In particular, compared to the second-best result, the proposed mechanism provides about 20% higher throughput for random traffic pattern. In addition, with regard to flow completion time, the percentage of improvement is 12% for random traffic pattern Manuscript profile
      • Open Access Article

        4 - Energy Efficient Cross Layer MAC Protocol for Wireless Sensor Networks in Remote Area Monitoring Applications
        R Rathna L Mary Gladence J Sybi Cynthia V Maria Anu
        Sensor nodes are typically less mobile, much limited in capabilities, and more densely deployed than the traditional wired networks as well as mobile ad-hoc networks. General Wireless Sensor Networks (WSNs) are designed with electro-mechanical sensors through wireless d More
        Sensor nodes are typically less mobile, much limited in capabilities, and more densely deployed than the traditional wired networks as well as mobile ad-hoc networks. General Wireless Sensor Networks (WSNs) are designed with electro-mechanical sensors through wireless data communication. Nowadays the WSN has become ubiquitous. WSN is used in combination with Internet of Things and in many Big Data applications, it is used in the lower layer for data collection. It is deployed in combination with several high end networks. All the higher layer networks and application layer services depend on the low level WSN in the deployment site. So to achieve energy efficiency in the overall network some simplification strategies have to be carried out not only in the Medium Access Control (MAC) layer but also in the network and transport layers. An energy efficient algorithm for scheduling and clustering is proposed and described in detail. The proposed methodology clusters the nodes using a traditional yet simplified approach of hierarchically sorting the sensor nodes. Few important works on cross layer protocols for WSNs are reviewed and an attempt to modify their pattern has also been presented in this paper with results. Comparison with few prominent protocols in this domain has also been made. As a result of the comparison one would get a basic idea of using which type of scheduling algorithm for which type of monitoring applications. Manuscript profile