ABSTRACT
To construct an efficient overlay network, the information of underlay is important. We consider using end-to-end measurement tools such as traceroute to infer the underlay topology among a group of hosts. Previously, Max-Delta has been proposed to infer a highly accurate topology with a low number of traceroutes. However, Max-Delta relies on a central server to collect traceroute results and to select paths for hosts to traceroute. It is not scalable to large groups. In this paper, we investigate a distributed inference scheme to support scalable inference. In our scheme, each host joins an overlay tree before conducting traceroute. A host then independently selects paths for tracerouting and exchanges traceroute results with others through the overlay tree. As a result, each host can maintain a partially discovered topology. We have studied the key issue in the scheme, that is, how a low-diameter overlay tree can be constructed. Furthermore, we propose several techniques to reduce the measurement cost for topology inference. They include 1) integrating the Doubletree algorithm into our scheme to reduce measurement redundancy, 2) setting up a lookup table for routers to reduce traceroute size, and 3) conducting topology abstraction and reducing the computational frequency to reduce the computational overhead. As compared to the naive Max-Delta, our scheme is fully distributed and scalable. The computational loads for target selection are distributed to all the hosts instead of a single server. In addition, each host only communicates with a few other hosts. The consumption of edge bandwidth at a host is hence limited. We have done simulations on Internet-like topologies and conducted measurements on PlanetLab. The results show that the constructed tree has a low diameter and can support quick data exchange between hosts. Furthermore, the proposed improvements can efficiently reduce measurement redundancy, bandwidth consumption, and computational overhead.
TABLE OF CONTENT
TITLE PAGE
CERTIFICATION
APPROVAL
DEDICATION
ACKNOWLEDGEMENT
ABSTRACT
TABLE OF CONTENT
CHAPTER ONE
1.0 INTRODUCTION
1.1 STATEMENT OF PROBLEM
1.2 PURPOSE OF STUDY
1.3 AIMS AND OBJECTIVES
1.4 SCOPE/DELIMITATIONS
1.5 LIMITATIONS/CONSTRAINTS
1.6 DEFINITION OF TERMS
CHAPTER TWO
2.0 LITERATURE REVIEW
CHAPTER THREE
3.0 METHODS FOR FACT FINDING AND DETAILED DISCUSSIONS OF THE SYSTEM
3.1 METHODOLOGIES FOR FACT-FINDING
3.2 DISCUSSIONS
CHAPTER FOUR
4.0 FUTURES, IMPLICATIONS AND CHALLENGES OF THE SYSTEM
4.1 FUTURES
4.2 IMPLICATIONS
4.3 CHALLENGES
CHAPTER FIVE
5.0 RECOMMENDATIONS, SUMMARY AND CONCLUSION
5.1 RECOMMENDATION
5.2 SUMMARY
5.3 CONCLUSION
5.4 REFERENCES
Disclaimer: Note this academic material is intended as a guide for your academic research work. Do not copy word for word. Note: For Computer or Programming related works, some works might not contain source codes
CITE THIS WORK
(2014, 08). Scalable And Efficient End To End Network Topology Inference.. ProjectStoc.com. Retrieved 08, 2014, from https://projectstoc.com/read/2768/scalable-and-efficient-end-to-end-network-topology-inference-5063
"Scalable And Efficient End To End Network Topology Inference." ProjectStoc.com. 08 2014. 2014. 08 2014 <https://projectstoc.com/read/2768/scalable-and-efficient-end-to-end-network-topology-inference-5063>.
"Scalable And Efficient End To End Network Topology Inference.." ProjectStoc.com. ProjectStoc.com, 08 2014. Web. 08 2014. <https://projectstoc.com/read/2768/scalable-and-efficient-end-to-end-network-topology-inference-5063>.
"Scalable And Efficient End To End Network Topology Inference.." ProjectStoc.com. 08, 2014. Accessed 08, 2014. https://projectstoc.com/read/2768/scalable-and-efficient-end-to-end-network-topology-inference-5063.
- Related Works
- Design And Implementation Of Computer Based Marketing Information System (a Case Study Of Guniess Nig. Plc)
- Xtc: An Active Virtual Queue (avq) Algorithm For Active Queue Management
- Design And Implementation Of Duplex Messaging For Enterprise System (a Case Study Of Nokia)
- Peer To Peer Messaging
- Design Of A Computerized System For Departmental Student Result Processing (a Case Study Of Department Of Computer Science Imt Enugu)
- Online Student Admission System (case Study Of Enugu State College Of Education Technical- Escet)
- Steganography – An Art Of Hiding Digital Information
- The Effects Of Different Processign Techniquies On The Organoleptic Quality Of Soymilk Processing And Storage
- Design And Implementation Of Computerized Tourism Information System A Case Study Of Enugu State Tourism Board
- Design And Implementation Of A Software Based Quality Control System (a Case Study Of Anammco Nig. Ltd Emene Enugu)