Providing Predictable Performance during Network Contingencies

In IP backbone networks, packets may get dropped due to: i) lack of viable next hops when a link/router fails, ii) forwarding loops during network convergence, and iii) buffer overflows in case of congestion. Similarly, packets may be lost in wireless networks due to variations in signal strength between a pair of mobile nodes. This dissertation explores the possibility of providing a predictable performance during such network contingencies in wired backbone networks and robotic wireless networks. First, we study the feasibility of developing a combination of local reroute and global update mechanisms that can achieve loop-free convergence, while performing disruption-free forwarding around a failed link/router, without carrying any additional information in the IP datagrams and with out needing any coordination between routers. We show that order of updates rarely matters for loop-free convergence when failure inference based fast reroute (FIFR) scheme with interface-specific forwarding is employed for dealing with link or router failures. In the rare cases where order matters, it can be coupled with progressive link metric increments to ensure loop-freedom with unordered updates of forwarding tables. We also demonstrate that, apart from providing protection against failures, FIFR can also be utilized to mitigate packet drops due to network congestion caused by micro traffic bursts. Second, we address the problem of constructing a communication map, which encodes information on whether two robots at given locations can communicate using a wireless network. Unlike previous offline approaches that do not utilize data measured by robots, we propose an online method, utilizing Gaussian Processes, to efficiently build a communication map with multiple robots, by exploiting prior communication models that can be derived from the physical map of the environment. Our evaluation, using a team of TurtleBot 2 platforms, confirms that the proposed method requires robots to take fewer signal strength measurements and travel less distance, and yet obtain similar accuracy as methods that consider all the locations in the environment

Loop-Free Convergence With Unordered Updates

This paper studies the feasibility of minimizing convergence delay and forwarding disruption without carrying any additional bits in the IP header, to provide high availability despite link failures in traditional IP networks. Previously proposed mechanisms achieve two of these three objectives by trading off the other objective. For instance, the ordered forwarding information base updates approach may prolong the convergence delay, whereas the SafeGuard scheme requires carrying the path cost in the IP header. As a better alternative, we propose a scheme called fast convergence with fast reroute (FCFR), which combines the features of IP fast rerouting and interface-specific forwarding. We show that FCFR can achieve minimal convergence delay, while ensuring loop-free delivery during convergence, after a single non-partitioning failure in an IP network, without altering the IP header format, making it amenable for immediate deployment