584549
A measurement study on the impact of routing events on end-to-end internet path performance
Extensive measurement studies have shown that end-to-end Internet path performance degradation is correlated with routing dynamics. However, the root cause of the correlation between routing dynamics and such performance degradation is poorly understood. In particular, how do routing changes result in degraded end-to-end path performance in the first place? How do factors such as topological properties, routing policies, and iBGP configurations affect the extent to which such routing events can cause performance degradation? Answers to these questions are critical for improving network performance.In this paper, we conduct extensive measurement that involves both controlled routing updates through two tier-1 ISPs and active probes of a diverse set of end-to-end paths on the Internet. We find that routing changes contribute to end-to-end packet loss significantly. Specifically, we study failover events in which a link failure leads to a routing change and recovery events in which a link repair causes a routing change. In both cases, it is possible to experience data plane performance degradation in terms of increased long loss burst as well as forwarding loops. Furthermore, we find that common routing policies and iBGP configurations of ISPs can directly affect the end-to-end path performance during routing changes. Our work provides new insights into potential measures that network operators can undertake to enhance network performance.
7334644
Analyzing peer-to-peer traffic across large networks
The use of peer-to-peer (P2P) applications is growing dramatically, particularly for sharing large video/audio files and software. In this paper, we analyze P2P traffic by measuring flow-level information collected at multiple border routers across a large ISP network, and report our investigation of three popular P2P systems-FastTrack, Gnutella, and Direct-Connect. We characterize the P2P traffic observed at a single ISP and its impact on the underlying network. We observe very skewed distribution in the traffic across the network at different levels of spatial aggregation (IP, prefix, AS). All three P2P systems exhibit significant dynamics at short time scale and particularly at the IP address level. Still, the fraction of P2P traffic contributed by each prefix is more stable than the corresponding distribution of either Web traffic or overall traffic. The high volume and good stability properties of P2P traffic suggests that the P2P workload is a good candidate for being managed via application-specific layer-3 traffic engineering in an ISP's network.
9192804
Efficient and robust streaming provisioning in VPNs
Today, most large companies maintain virtual private networks (VPNs) to connect their remote locations into a single secure network. VPNs can be quite large covering more than 1000 locations and in most cases use standard Internet protocols and services. Such VPNs are implemented using a diverse set of technologies such as Frame Relay, MPLS, or IPSEC to achieve the goal of privacy and performance isolation from the public Internet.Using VPNs to distribute live content has recently received tremendous interest. For example, a VPN could be used to broadcast a CEO-employee town hall meeting. To distribute this type of content economically without overloading the network, the deployment of streaming caches or splitters is most likely required.In this paper, we address the problem of optimally placing such streaming splitters or caches to broadcast to a given set of VPN endpoints under the constraints typically found within a VPN. In particular, we introduce an efficient algorithm with complexity O(V), V being the number of routers in the VPN. This guarantees the optimal cache placement if interception is used for redirection. We prove that the general problem is NP-hard and introduce multiple heuristics for efficient and robust cache placement suitable under different constraints. At the expense of increased implementation complexity, each heuristic solution provides additional saving in the number of caches required. We evaluate proposed solutions using extensive simulations. In particular, we show our flow-based solution is very close to the optimal.
15532439
Scalable and accurate identification of AS-level forwarding paths
Traceroute is used heavily by network operators and researchers to identify the IP forwarding path from a source to a destination. In practice, knowing the autonomous system (AS) associated with each hop in the path is also quite valuable. In previous work we showed that the IP-to-AS mapping extracted from BGP routing tables is not sufficient for determining the AS-level forwarding paths. By comparing BGP and traceroute AS paths from multiple vantage points, Z. Morley Mao et al. (2003) proposed heuristics that identify the root causes of the mismatches and fix the inaccurate IP-to-AS mappings. These heuristics, though effective, are labor-intensive and mostly ad hoc. This paper proposes a systematic way to construct accurate IP-to-AS mappings using dynamic programming and iterative improvement. Our algorithm reduces the initial mismatch ratio of 15% between BGP and traceroute AS paths to 5% while changing only 2.9% of the assignments in the initial IP-to-AS mappings. This is in contrast to the results of Z. Morley Mao et al. (2003), where 10% of the assignments were modified and the mismatch ratio was only reduced to 9%. We show that our algorithm is robust and can yield near-optimal results even when the initial mapping is corrupted or when the number of probing sources or destinations is reduced. Our work is a key step towards building a scalable and accurate AS-level traceroute tool
985166
On AS-level path inference
The ability to discover the AS-level path between two end-points is valuable for network diagnosis, performance optimization, and reliability enhancement. Virtually all existing techniques and tools for path discovery require direct access to the source. However, the uncooperative nature of the Internet makes it difficult to get direct access to any remote end-point. Path inference becomes challenging when we have no access to the source or the destination. Moveover even when we have access to the source and know the forward path, it is nontrivial to infer the reverse path, since the Internet routing is often asymmetric.In this paper, we explore the feasibility of AS-level path inference without direct access to either end-points. We describe RouteScope-a tool for inferring AS-level paths by finding the shortest policy paths in an AS graph obtained from BGP tables collected from multiple vantage points. We identify two main factors that affect the path inference accuracy: the accuracy of AS relationship inference and the ability to determine the first AS hop. To address the issues, we propose two novel techniques: a new AS relation-ship inference algorithm, and a novel scheme to infer the first AS hop by exploiting the TTL information in IP packets. We evaluate the effectiveness of RouteScope using both BGP tables and the AS paths collected from public BGP gateways. Our results show that it achieves 70% - 88% accuracy in path inference.
2808817
BGP routing stability of popular destinations
The Border Gateway Protocol (BGP) plays a crucial role in the delivery of traffic in the Internet. Fluctuations in BGP routes cause degradation in user performance, increased processing load on routers, and changes in the distribution of traffic load over the network. Although earlier studies have raised concern that BGP routes change quite often, previous work has not considered whether these routing fluctuations affect a significant portion of the traffic. This paper shows that the small number of popular destinations responsible for the bulk of Internet traffic have remarkably stable BGP routes. The vast majority of BGP instability stems from a small number of unpopular destinations. We draw these conclusions from a joint analysis of BGP update messages and flow-level traffic measurements from AT&T's IP backbone. In addition, we analyze the routing stability of destination prefixes corresponding to the NetRating's list of popular Web sites using the update messages collected by the RouteViews and RIPE-NCC servers. Our results suggest that operators can engineer their networks under the assumption that the BGP advertisements associated with most of the traffic are reasonably stable.
3185763
Address generation for nanowire decoders
Nanoscale crossbars built from nanowires can form high density memories and programmable logic devices. To integrate such nanoscale devices with CMOS circuits, nanowire decoders were invented. Due to the stochastic nature of the nanoscale fabrication, the decoder addresses that address the nanowires selectively must be generated after fabrication. In this paper, we develop a mathematical model of the nanowire decoders for the generation of the proper addresses. Assuming a simple testing approach calledon-off measurement, we prove that the maximum number of the proper addresses can be generated in finite time. We design the algorithms to generate the required number of the proper addresses. Experimental results confirm the efficiency of our algorithms.
18621072
Primal and dual neural networks for shortest-path routing
Presents two recurrent neural networks for solving the shortest path problem. Simplifying the architecture of a recurrent neural network based on the primal problem formulation, the first recurrent neural network called the primal routing network has less complex connectivity than its predecessor. Based on the dual problem formulation, the second recurrent neural network called the dual routing network has even simpler architecture. While being simple in architecture, the primal and dual routing networks are capable of shortest-path routing like their predecessor.
2685835
Energy Consumption of Swarm Intelligence inspired Routing Algorithms in MANETs
Swarm Intelligence (SI) inspired routing algorithms have become a research focus in recent years due to their self-organizing nature, which is very suitable to the routing problems in Mobile Ad hoc Networks (MANETs). The network information can be collected and updated in a decentralized and dynamic way through the localized cooperation among these swarm agents. In this paper, we, for the first time, provide a comprehensive comparison about current SI inspired routing algorithms in MANETs in the aspects of network metrics and simulation environment. Then, we make a detailed study about the energy consumption of the SI inspired routing problem in MANETs. Based on this study, we present the selection criterion of the intermediate nodes so as to be energy efficient. Experimental results are provided with reasonable verification.
34091874
Incremental architectural modeling and verification of real-time concurrent systems
An incremental approach for architectural modeling and analysis of real-time concurrent systems is presented. The approach integrates existing formal methods, more specifically time Petri nets and real-time computational tree logic, and leverages their complementary strengths in a way that allows us to systematically enforce that architectural design meets the system's timing requirements, and to incrementally verify the conformance. Consequently, our approach is able to provide better assurance to system design and yet reduce the complexity of analysis. The approach is based on a Real-time Architectural Specification (RAS) model, which provides a formal basis to systematically maintain a correlation between the (timing) requirements of a system and its architectural design. Based on RAS, we further present a method to verify timing properties of a system design. This method helps conquer the complexity of analysis in two dimensions. Horizontally at each design level, incremental verification is achieved by introducing TPN reduction rules that allow us to compose analysis results on individual system components. Vertically across design levels, incremental verification is achieved by propagating higher-level constraints to lower-level designs so that we can safely plug a component design into a high-level architecture without having to re-verify the entire model. A naval command and control (C2) system is used throughout the paper to demonstrate the concept and usability of our approach.
207558887
Self-adaptive neuro-fuzzy systems for autonomous underwater vehicle control
This paper presents a systematic approach for developing a concise self-adaptive neurofuzzy inference system (SANFIS) with a fast hybrid parameter learning algorithm for on-line learning of the control knowledge for autonomous underwater vehicle (AUV) control. The multi-layered network structure of SANFIS incorporates fuzzy basis functions for better function approximations. We investigate three SANFIS structures with three different types of fuzzy IF-THEN rule-based models and cast the rule formation problem as a clustering problem. A recursive least-squares algorithm and a modified Levenberg-Marquardt algorithm with limited memory are exploited to accelerate the parameter learning process. This hybrid parameter learning algorithm together with an on-line clustering technique and rule examination provide SANFIS with the capability of selforganizing and self-adapting its internal structure (i.e. the fuzzy rules and term sets) for learning the required control knowledge for an AUV to follow desired trajectories. Computer simulations for modeling a control system for an AUV have been conducted to validate the effectiveness of the proposed SANFIS.