|Title: Using an ICN Approach to Support Multiple Controllers in OpenFlow|
|Author(s): Ameen Banjar, Pakawat Pupatwibul, Abdallah AL Sabbagh, Robin Braun|
|Pages: 1-6||Paper ID:141902-6868-IJECS-IJENS||Published: April, 2014|
Abstract: Information Centric Networking (ICN) is an innovative direction for next generation networks. It is a concept of networking paradigm which is considered as a new technique for future search activities. ICN is based on caching contents in several nodes and replicating these contents. It provides contents requested by users from the nearest node instead of creating a communication channel between sender and receiver just for calling information. This paper aims to scale OpenFlow network in traffic engineering by reducing number of transactions, predicting and pre-populating flow entries using the ICN approach. In addition, the paper shows the advantages of implementing ICN designs within OpenFlow. The proposed approach aims to implement ICN concepts to enhance OpenFlow network. This will enable the deployment of networking solutions in the existing network infrastructure and will lead to more flexibility in OpenFlow network. In addition, OpenFlow will have a global management view for all connected networks managed by different controllers. The proposed solution can fulfill current management and utilization of network demands. The paper then debates the implementation of ICN’s design and features based on Software Defined Networking (SDN).
|Keywords: Named Data Object; Information Centric Networks; Software-Defined Networks; Next Generation Network.|
|Full Text (.pdf) | 387 KB|
|Title: ANFIS Based Classification Model for Heart Disease Prediction|
|Author(s): Negar Ziasabounchi, Iman Askerzade|
|Pages: 7-12||Paper ID:146402-7373-IJECS-IJENS||Published: April, 2014|
Abstract: Heart disease diagnosis procedure is very vital and critical issue for the patient's health. Furthermore, it will help to decrease disease to a more specific level. The role of using machine learning techniques and data mining algorithms in diagnosis of heart disease is very considerable. The aim of this study was to develop a method of classifying for heart disease degree of patient based characteristic data using adaptive neuro fuzzy inference system. The data were obtained from the University of California at Irvine (UCI) machine learning repository. Seven variables are used as input of prediction model. To test the ability of the trained anfis models to recognize heart disease diagnosis, we used k-fold cross validation method. The experimental results demonstrate that the model successfully forecasts the patient's heart disease degree with an accuracy rate of 92.30%.
|Keywords: ANFIS; Adaptive Neuro; Fuzzy Interface System; Classification; Heart Disease|
|Full Text (.pdf) | 514 KB|
|Title: Efficient Control of Hybrid Generation System for Domestic and Lower Applications|
|Author(s): Muhammad Aslam, Muhammad Zahir Khan, Qazi Waqar Ali, Naveed Khan|
|Pages: 13-17||Paper ID:149602-5757-IJECS-IJENS||Published: April, 2014|
Abstract: This work presents the plan and model of the control strategy for the interconnection of the hybrid energy system able to regulating this load’s voltage and controlling the energy generation with the energy options. The control strategy contains controlling the energy generated through each energy source, in a hierarchical mode using sliding/dropping mode control, while consuming consideration elements that have an impact on each electrical power source and transform the energy generated in order to suitable circumstances for lower power and domestic programs. The cross alternative energy system consists of photovoltaic cellular material, fuel cellular material and battery packs. A numerical equation in order to estimate the perfect voltage involving photovoltaic systems for virtually every solar irradiance and temperature circumstances is suggested. Simulations of a single or a lot more systems interconnected towards the load with all the proposed control scheme, under different ecological and weight conditions, usually are introduced to indicate this efficiency with the procedure.
|Full Text (.pdf) | 369 KB|
|Title: Hybrid Renewable Energy Source Implementation in Pakistan|
|Author(s): Hamid Ali Kamal, Naeem Arbab, Qazi Waqar Ali|
|Pages: 18-22||Paper ID:149702-8080-IJECS-IJENS||Published: April, 2014|
Abstract: A solar-wind hybrid power generation system has been presented here. The application based system illustrated in this paper is designed on the basis of the solar and wind data for Pakistan. The power generated by the system is intended for domestic use. The most common source of unconventional power in homes is battery based UPS (Uninterrupted power supply) inverter. The UPS inverter charges the battery with conventional grid power. This system will charge the battery of UPS inverter by using only wind and solar power, which will make the system cost effective and more reliable. The reason for using both solar and wind is that recent studies have proven that combined system can be more productive and consistent and other thing is that neither of them can be used for continuous power generation. In the system illustrated in this paper the solar-wind system provides power periodically which is controlled by electronic methods and a microcontroller is used to monitor the power from both the inputs. The switching action is provided from the microcontroller to the battery charging based on the power received from solar photovoltaic panel and wind generators. In this paper, an efficient system has been presented comprising of solar panel, wind generator, charge controller and charge storage unit (battery). Solar panel is selected as the main input and the wind resource will be used only in the absence of the solar photovoltaic (PV) output.
|Keywords: Photovoltaic, hybrid, UPS, grid.|
|Full Text (.pdf) | 320 KB|