Presentation is loading. Please wait.

Presentation is loading. Please wait.

Simulating the Cognitive Networks Using Cloud to Solve Hidden Terminal Problem Presented By: Stephen Ellis Advisor Dr. Yenumula B. Reddy Department of.

Similar presentations


Presentation on theme: "Simulating the Cognitive Networks Using Cloud to Solve Hidden Terminal Problem Presented By: Stephen Ellis Advisor Dr. Yenumula B. Reddy Department of."— Presentation transcript:

1 Simulating the Cognitive Networks Using Cloud to Solve Hidden Terminal Problem Presented By: Stephen Ellis Advisor Dr. Yenumula B. Reddy Department of Computer Science, Grambling State University

2 Overview Objectives and Requirements Introduction Statement of Problem (Eliminating Hidden Terminal Problem by introducing Cloud Application) Applications Simulation Results Future Work Department of Computer Science, Grambling State University

3 Objectives and System Requirements Objective Understand and model a Cognitive Radio Network in Cloud Application Requirements: Linux Ubuntu Operating System (12.04 – Precision) XAMP 1.8.1 (including PHPAdmin) Eclipse (PyDev) Python 2.7.3 Department of Computer science, Grambling State University

4 Introduction What is a Cognitive Radio? Cognitive Radio (CR) is an intelligent transceiver to detect the available channels in wireless spectrum. Cognitive Radio helps to improve the spectrum utilization to meet the needs of users. The detection of spectrum, adjusting its parameters, and efficient utilization, is also called dynamic spectrum management. This operation or process includes:  spectrum sensing  spectrum management  spectrum sharing  spectrum mobility Cognitive radio can sense and understand its environment and use that knowledge to serve users better. Department of Computer Science, Grambling State University

5 Introduction Cognitive Radio Network A Cognitive Radio Network (CRN) is a group of cognitive radios connected to verify the concepts, algorithms, and protocols. The CRN improves the performance ofspectrum utilization and helps smooth transmissiontransfer of packets. The tools for total functionality require a significant amount of computing resources in a real time environment. CRN uses knowledge representation, machine learning, genetic algorithms, and game theory techniques for efficient resource (spectrum) utilization. This is referred to as an existing network, where the primary users (PUs) have a license to operate in a certain spectrum band. This does not have a license to operate in a desired band. Hence, additional functionality is required for CR users to share the licensed spectrum band. Also, CR users are mobile, and can communicate with each other in a multi-hop manner on both licensed and unlicensed spectrum bands. Department of Computer Science, Grambling State University

6 Introduction Cognitive Radio Network with Cloud (CRNC) CRNC Model CR has limited storage capacity and computing capabilities. Connectivity The detection, of unused spectrum (spectrum holes) and efficient allocation, needs the support of machine learning algorithms, protocols, and security policies. Cloud application stores, processes, and makes decisions. These capabilities help the CR at node (mobile or fixed) level to overcome the basic needs (challenges) such as battery power. Department of Computer Science, Grambling State University

7 RTS/CTS IEEE 802.11 RTS/CTS - Request to Send/Clear to Send is also known as “virtual carrier sensing” and is one of the two mechanisms used by the 802.11 wireless networking protocol to reduce frame collisions or inference introduced by the hidden node problem. Drawbacks: The effectiveness of RTS/CTS handshake is based on the assumption that hidden nodes are within transmission range of receivers. The “virtual carrier sensing” implemented by RTS/CTS handshake cannot prevent all interferences. Department of Computer Science, Grambling State University

8 Hidden Terminal Problem The hidden terminal problem occurs when a node is visible from the access point but cannot communicate to the nodes within communication distance. For example, a user tries to transmit the information from node A to node C. The node A cannot hear the transmission from node C by sensing the medium. Similarly, node C cannot sense the transmission from node A; therefore, they try to communicate and collide at node B. Department of Computer Science, Grambling State University

9 Hidden Terminal Problem In the beginning, the node A assumes that channel 2 is free. Once the packet reaches node Bit understands that node C is in communication with node D for channel 2. That is node C sends the request for communication (RTS: request to send) to node B for channel 2. The node, B - waits to get the signal clear to send (CTS) from node C for channel 2. Both nodes are waiting for channel 2 at node B and cannot move further. The RTS/CTS mechanisms implemented in the MAC (medium access control) protocol helps to eliminate the hidden terminal problem with time overhead. If nodes C and B are synchronized with the same packet size and data rate, RTS/CTS can work. If the nodes are not synchronized, the neighboring node may not hear the CTS during transmission and exposed terminal problem may occur. Department of Computer Science, Grambling State University

10 Applications Application areas Multimedia, Military, Consumer cellular, Emergency and public safety networks Capabilities CR can sense its environment, and without the intervention of the user, can adapt to the user's communications needs while conforming to Federal Communications Commission (FCC) rules in the United States. CR has the ability to adapt to real-time spectrum conditions, offering regulators, licenses and the general public flexible, efficient and comprehensive use of the spectrum A CR can intelligently detect whether any portion of the spectrum is in use, and can temporarily use it without interfering with the transmissions of other users. Department of Computer Science, Grambling State University

11 Simulation Packet Transfer in Cloud Application Packet travelling to the cloud from node Packet travelling to the node from cloud Packet travelling from a node to another node Primary user packet Node Cloud Describes the system activity Graphical simulation of system activity Key Department of Computer Science, Grambling State University

12 Using IEEE 802.11 RTS/CTS, if the channels are not available at the middle of the transfer or sudden entrance of the primary user, the packet loss may happen. The CRNC Interface tries to reassign the transmission of the packet to another channel if available. The CRNC Interface allows the packet to be buffered in the cloud until it is able to forward the packet to destination. Sudden Entry of Primary User No packet loss Problem of Sudden Entry of Primary User Department of Computer Science, Grambling State University

13 Packet travelling to the cloud from node Packet travelling to the node from cloud Packet travelling from a node to another node Primary user packet Node Cloud Key Primary User entered system Assumption: When Primary User enters, it occupies two channels to prevent inference or any disturbance to ensure successful communication and transmission The cloud allows for the packet that was originally scheduled for channel 2 on node 7 to be reassigned to channel 3 The Primary User, takes the channels it needs unconditionally because of its high priority Department of Computer Science, Grambling State University Simulation Sudden Entry of Primary user – Reassign Channel

14 Simulation Sudden Entry of Primary user - Cloud Buffering Packet travelling to the cloud from node Packet travelling to the node from cloud Packet travelling from a node to another node Primary user packet Node Cloud Key Packet being sent to cloud since there is no free channels for transmission Assumption: When Primary User enters, it occupies two channels to prevent inference or any disturbance to ensure successful communication and transmission Instances where there is no free channel, packets are sent to the cloud and forwarded to the destination when able The Primary User frees the channels it occupied after it is finished transmitting Packet being sent to node after being buffered till open channel is available Department of Computer Science, Grambling State University

15 Results & Future Work In the proposed CRNC structure, the interface is connected to CRN nodes and CRNC. This framework solves the issues affecting the original IEEE 802.11 RTS/CTS as proven by the simulations conducted. The future research includes : Security issues of Cloud application Node failures that affect network reliability and robustness Steps to address cloud failure (level of backup requirements) Eliminate overheads of RTS/CTS in IEEE 802.11 protocol using cloud application Real-time response for channel analysis using Graphics processing Unit (GPU) – a problem of High Performance Computing Department of Computer Science, Grambling State University

16 References and Acknowledgement Yenumula B. Reddy, “Solving Hidden Terminal Problem in Cognitive Networks Using Cloud Application,” SENSORCOMM 2012, August 19 - 24, 2012 - Rome, Italy. Kaixin Xu, Mario Gerla, and Sang Bae., “How Effective is the IEEE 802.11 RTS/CTS Handshake in Ad Hoc Networks?,” Global Telecommunications Conference (GLOBECOM '02), November 2002, Los Angels, CA, USA. Acknowledgement Dr. Connie Walton, Provost & Vice President for Academic Affairs, Grambling State University for her continuous support. Questions?? Department of Computer Science, Grambling State University


Download ppt "Simulating the Cognitive Networks Using Cloud to Solve Hidden Terminal Problem Presented By: Stephen Ellis Advisor Dr. Yenumula B. Reddy Department of."

Similar presentations


Ads by Google