Today the Internet offers a single path between end-systems even though it intrinsically has a large multiplicity of paths. This paper proposes an evolutionary architectural framework “BANANAS ” aimed at simplifying the introduction of multipath routing in the Internet. The framework starts with the observation that a path can be encoded as a short hash (“PathID”) of a sequence of globally known identifiers. The PathID therefore has global significance (unlike MPLS or ATM labels). This property allows multipath capable nodes to autonomously compute PathIDs in a partially upgraded network without requiring an explicit signaling protocol for path setup. We show that this framework allows the introduction of sophisticated explicit routing and multipath capabilities within the context of widely deployed connectionless routing protocols (e.g. OSPF, IS-IS, BGP) or overlay networks. We establish these characteristics through the development of PathID encoding and routecomputation schemes. The BANANAS framework also allows considerable flexibility in terms of architectural function placement and complexity management. To illustrate this feature, we develop an efficient variable-length hashing scheme that moves control-plane complexity and state overheads to network edges, allowing a very simple interior node design. All the schemes have been evaluated using both sizable SSFNet simulations and Linux/Zebra implementation evaluated on Utah’s Emulab testbed facility. 1.

Current distributed routing paradigms (such as link-state, distancevector, and path-vector) involve a convergence process consisting of an iterative exploration of intermediate routes triggered by certain events such as link failures. The convergence process increases router load, introduces outages and transient loops, and slows reaction to failures. We propose a new routing paradigm where the goal is not to reduce the convergence times but rather to eliminate the convergence process completely. To this end, we propose a technique called Failure-Carrying Packets (FCP) that allows data packets to autonomously discover a working path without requiring completely up-to-date state in routers. Our simulations, performed using real-world failure traces and Rocketfuel topologies, show that: (a) the overhead of FCP is very low, (b) unlike traditional link-state routing (such as OSPF), FCP can provide both low lossrate as well as low control overhead, (c) compared to prior work in backup path precomputations, FCP provides better routing guarantees under failures despite maintaining lesser state at the routers.

We present the results of an extensive computational study on dynamic algorithms for all pairs shortest path problems. We describe our implementations of the recent dynamic algorithms of King and of Demetrescu and Italiano, and compare them to the dynamic algorithm of Ramalingam and Reps and to static algorithms on random, real-world and hard instances. Our experimental data suggest that some of the dynamic algorithms and their algorithmic techniques can be really of practical value in many situations. 1

Heuristic search methods promise to find shortest paths for path-planning problems faster than uninformed search methods. Incremental search methods, on the other hand, promise to find shortest paths for series of similar path-planning problems faster than is possible by solving each path-planning problem from scratch. In this article, we develop Lifelong Planning A * (LPA*), an incremental version of A * that combines ideas from the artificial intelligence and the algorithms literature. It repeatedly finds shortest paths from a given start vertex to a given goal vertex while the edge costs of a graph change or vertices are added or deleted. Its first search is the same as that of a version of A * that breaks ties in favor of vertices with smaller g-values but many of the subsequent searches are potentially faster because it reuses those parts of the previous search tree that are identical to the new one. We present analytical results that demonstrate its similarity to A * and experimental results that demonstrate its potential advantage in two different domains if the path-planning problems change only slightly and the changes are close to the goal.

A key functionality in today's widely used interior gateway routing protocols such as OSPF and IS-IS involves the computation of a shortest path tree (SPT). In many existing commercial routers, the computation of an SPT is done from scratch following changes in the link states of the network. As there may coexist multiple SPTs in a network with a set of given link states, such recomputation of an entire SPT not only is inefficient but also causes frequent unnecessary changes in the topology of an existing SPT and creates routing instability. This paper presents a new dynamic SPT algorithm that makes use of the structure of the previously computed SPT. Our algorithm is derived by recasting the SPT problem into an optimization problem in a dual linear programming framework, which can also be interpreted using a ball-andstring model. In this model, the increase (or decrease) of an edge weight in the tree corresponds to the lengthening (or shortening) of a string. By stretching the strings...

Abstract. Many speed-up techniques for route planning in static graphs exist, only few of them are proven to work in a dynamic scenario. Most of them use preprocessed information, which has to be updated whenever the graph is changed. However, goal directed search based on landmarks (ALT) still performs correct queries as long as an edge weight does not drop below its initial value. In this work, we evaluate the robustness of ALT with respect to traffic jams. It turns out that—by increasing the efficiency of ALT—we are able to perform fast (down to 20 ms on the Western European network) random queries in a dynamic scenario without updating the preprocessing as long as the changes in the network are moderate. Furthermore, we present how to update the preprocessed data without any additional space consumption and how to adapt the ALT algorithm to a time-dependent scenario. A time-dependent scenario models predictable changes in the network, e.g. traffic jams due to rush hour. 1

This paper represents a first step in exploring the formation of connected topologies in ad-hoc networks built on the Bluetooth technology. Connectivity is the most basic requirement for any system aimed at allowing devices to communicate with each other and in this paper we illustrate that this seemingly innocuous goal gives rise to many significant challenges in the context of the Bluetooth technology. We start with a brief overview of Bluetooth and its operation and then identify some of the major problems the technology faces when used to build ad-hoc networks. The paper's contributions are in introducing basic algorithmic problems associated with building connected Bluetooth networks and in developing several possible solutions capable of generating "good" connected topologies

In this paper, we analyze the blocking probability of distributed lightpath establishment in wavelength-routed WDM networks by studying the two basic methods: destination-initiated reservation (DIR) and source-initiated reservation (SIR). We discuss three basic types of connection blocking: (1) blocking due to insufficient network capacity; (2) blocking due to outdated information; and (3) blocking due to over-reservation. It is shown that the proposed models are highly accurate for both the DIR and the SIR methods, in both the regular and irregular network topologies, under the whole range of traffic loads.

This paper presents a receding horizon controller (RHC) that can be used to design trajectories for an aerial vehicle flying through a three dimensional terrain with obstacles and no-fly zones. To avoid exposure to threats, the paths are chosen to stay as close to the terrain as possible, but the vehicle can choose to pop-up over the obstacles if necessary. The approach is similar to our previous two-dimensional algorithms that construct a coarse cost map to provide approximate paths from a sparse set of nodes to the goal and then use Mixed-integer Linear Programming (MILP) optimization to design a detailed trajectory. The main contribution of this paper is to extend this approach to 3D, in particular providing a new algorithm for connecting the cost map and the detailed path in the MILP. This connection is done by introducing a new cost-to-go function that includes an altitude penalty and accounts for the vehicle dynamics. Initial guess for MILP RHC is constructed from the previous solution and is shown to reduce the solution time. Several simulation results are presented to show that the path planning algorithm yields good overall performance and is computationally tractable in a complex environment.

Abstract We consider the problem of computing the optimal swap edges of a shortest-path tree. This theoretical problem arises in practice in systems that offer point-offailure shortest-path rerouting service in presence of a single link failure: if the shortest path is not affected by the failed link, then the message will be delivered through that path; otherwise, the system will guarantee that, when the message reaches the node where the failure has occurred, the message will then be rerouted through the shortest-path to its destination. There exist highly efficient serial solutions for the problem, but unfortunately because of the structures they use, there is no known (nor foreseeable) efficient distributed implementation for them. A distributed protocol exists only for finding swap edges, not necessarily optimal ones. We present two simple and efficient distributed algorithms for computing the optimal swap edges of a shortest-path tree. One algorithm uses messages containing a constant amount of information, while the other is tailored for systems that allow long messages. The amount of data transferred by the protocols is the same and depends on on the structure of the shortest-path spanning-tree; it is no more, and sometimes significantly less, than the cost of constructing the shortest-path tree.