CHESS: An application-aware space for enhanced scalable services in overlay networks
Computer Communications
Phoenix: Towards an Accurate, Practical and Decentralized Network Coordinate System
NETWORKING '09 Proceedings of the 8th International IFIP-TC 6 Networking Conference
HNDP: a novel network distance prediction mechanism
NPC'07 Proceedings of the 2007 IFIP international conference on Network and parallel computing
Orion: shortest path estimation for large social graphs
WOSN'10 Proceedings of the 3rd conference on Online social networks
Reducing TIV interference in network coordinate systems
Proceedings of the ACM CoNEXT Student Workshop
Using the last-mile model as a distributed scheme for available bandwidth prediction
Euro-Par'11 Proceedings of the 17th international conference on Parallel processing - Volume Part I
Decentralized prediction of end-to-end network performance classes
Proceedings of the Seventh COnference on emerging Networking EXperiments and Technologies
Network distance prediction based on decentralized matrix factorization
NETWORKING'10 Proceedings of the 9th IFIP TC 6 international conference on Networking
CloudGPS: a scalable and ISP-friendly server selection scheme in cloud computing environments
Proceedings of the 2012 IEEE 20th International Workshop on Quality of Service
NCShield: securing decentralized, matrix factorization-based network coordinate systems
Proceedings of the 2012 IEEE 20th International Workshop on Quality of Service
Towards a robust framework of network coordinate systems
IFIP'12 Proceedings of the 11th international IFIP TC 6 conference on Networking - Volume Part I
Multi-manifold model of the Internet delay space
Journal of Network and Computer Applications
Network latency prediction using high accuracy prediction tree
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
DMFSGD: a decentralized matrix factorization algorithm for network distance prediction
IEEE/ACM Transactions on Networking (TON)
| Hi-index | 0.07 |
The responsiveness of networked applications is limited by communications delays, making network distance an important parameter in optimizing the choice of communications peers. Since accurate global snapshots are difficult and expensive to gather and maintain, it is desirable to use sampling techniques in the Internet to predict unknown network distances from a set of partially observed measurements. This paper makes three contributions. First, we present a model for representing and predicting distances in large-scale networks by matrix factorization which can model suboptimal and asymmetric routing policies, an improvement on previous approaches. Second, we describe two algorithms-singular value decomposition and non-negative matrix factorization-for representing a matrix of network distances as the product of two smaller matrices. Third, based on our model and algorithms, we have designed and implemented a scalable system-Internet Distance Estimation Service (IDES)-that predicts large numbers of network distances from limited samples of Internet measurements. Extensive simulations on real-world data sets show that IDES leads to more accurate, efficient and robust predictions of latencies in large-scale networks than existing approaches