Routing quantum information in spin chains

Two different models for performing efficiently routing of a quantum state are presented. Both cases involve an XX spin chain working as data bus and additional spins that play the role of sender and receivers, one of which is selected to be the target of the quantum state transmission protocol via a coherent quantum coupling mechanism making use of local/global magnetic fields. Quantum routing is achieved, in the first of the models considered, by weakly coupling the sender and the receiver to the data bus. In the second model, strong magnetic fields acting on additional spins located between the sender/receiver and the data bus allow us to perform high fidelity routing.Comment: added references in v

CAIR: Using Formal Languages to Study Routing, Leaking, and Interception in BGP

The Internet routing protocol BGP expresses topological reachability and policy-based decisions simultaneously in path vectors. A complete view on the Internet backbone routing is given by the collection of all valid routes, which is infeasible to obtain due to information hiding of BGP, the lack of omnipresent collection points, and data complexity. Commonly, graph-based data models are used to represent the Internet topology from a given set of BGP routing tables but fall short of explaining policy contexts. As a consequence, routing anomalies such as route leaks and interception attacks cannot be explained with graphs. In this paper, we use formal languages to represent the global routing system in a rigorous model. Our CAIR framework translates BGP announcements into a finite route language that allows for the incremental construction of minimal route automata. CAIR preserves route diversity, is highly efficient, and well-suited to monitor BGP path changes in real-time. We formally derive implementable search patterns for route leaks and interception attacks. In contrast to the state-of-the-art, we can detect these incidents. In practical experiments, we analyze public BGP data over the last seven years

Global Modeling and Prediction of Computer Network Traffic

We develop a probabilistic framework for global modeling of the traffic over a computer network. This model integrates existing single-link (-flow) traffic models with the routing over the network to capture the global traffic behavior. It arises from a limit approximation of the traffic fluctuations as the time--scale and the number of users sharing the network grow. The resulting probability model is comprised of a Gaussian and/or a stable, infinite variance components. They can be succinctly described and handled by certain 'space-time' random fields. The model is validated against simulated and real data. It is then applied to predict traffic fluctuations over unobserved links from a limited set of observed links. Further, applications to anomaly detection and network management are briefly discussed

An integrated placement and routing approach

As the feature size continues scaling down, interconnects become the major contributor of signal delay. Since interconnects are mainly determined by placement and routing, these two stages play key roles to achieve high performance. Historically, they are divided into two separate stages to make the problem tractable. Therefore, the routing information is not available during the placement process. Net models such as HPWL, are employed to approximate the routing to simplify the placement problem. However, the good placement in terms of these objectives may not be routable at all in the routing stage because different objectives are optimized in placement and routing stages. This inconsistancy makes the results obtained by the two-step optimization method far from optimal;In order to achieve high-quality placement solution and ensure the following routing, we propose an integrated placement and routing approach. In this approach, we integrate placement and routing into the same framework so that the objective optimized in placement is the same as that in routing. Since both placement and routing are very hard problems (NP-hard), we need to have very efficient algorithms so that integrating them together will not lead to intractable complexity;In this dissertation, we first develop a highly efficient placer - FastPlace 3.0 for large-scale mixed-size placement problem. Then, an efficient and effective detailed placer - FastDP is proposed to improve global placement by moving standard cells in designs. For high-degree nets in designs, we propose a novel performance-driven topology design algorithm to generate good topologies to achieve very strict timing requirement. In the routing phase, we develop two global routers, FastRoute and FastRoute 2.0. Compared to traditional global routers, they can generate better solutions and are two orders of magnitude faster. Finally, based on these efficient and high-quality placement and routing algorithms, we propose a new flow which integrates placement and routing together closely. In this flow, global routing is extensively applied to obtain the interconnect information and direct the placement process. In this way, we can get very good placement solutions with guaranteed routability

Vertex routing models

A class of models describing the flow of information within networks via routing processes is proposed and investigated, concentrating on the effects of memory traces on the global properties. The long-term flow of information is governed by cyclic attractors, allowing to define a measure for the information centrality of a vertex given by the number of attractors passing through this vertex. We find the number of vertices having a non-zero information centrality to be extensive/sub-extensive for models with/without a memory trace in the thermodynamic limit. We evaluate the distribution of the number of cycles, of the cycle length and of the maximal basins of attraction, finding a complete scaling collapse in the thermodynamic limit for the latter. Possible implications of our results on the information flow in social networks are discussed.Comment: 12 pages, 6 figure

Continuum Equilibria and Global Optimization for Routing in Dense Static Ad Hoc Networks

We consider massively dense ad hoc networks and study their continuum limits as the node density increases and as the graph providing the available routes becomes a continuous area with location and congestion dependent costs. We study both the global optimal solution as well as the non-cooperative routing problem among a large population of users where each user seeks a path from its origin to its destination so as to minimize its individual cost. Finally, we seek for a (continuum version of the) Wardrop equilibrium. We first show how to derive meaningful cost models as a function of the scaling properties of the capacity of the network and of the density of nodes. We present various solution methodologies for the problem: (1) the viscosity solution of the Hamilton-Jacobi-Bellman equation, for the global optimization problem, (2) a method based on Green's Theorem for the least cost problem of an individual, and (3) a solution of the Wardrop equilibrium problem using a transformation into an equivalent global optimization problem

Cross-layer Congestion Control, Routing and Scheduling Design in Ad Hoc Wireless Networks

This paper considers jointly optimal design of crosslayer congestion control, routing and scheduling for ad hoc wireless networks. We first formulate the rate constraint and scheduling constraint using multicommodity flow variables, and formulate resource allocation in networks with fixed wireless channels (or single-rate wireless devices that can mask channel variations) as a utility maximization problem with these constraints. By dual decomposition, the resource allocation problem naturally decomposes into three subproblems: congestion control, routing and scheduling that interact through congestion price. The global convergence property of this algorithm is proved. We next extend the dual algorithm to handle networks with timevarying channels and adaptive multi-rate devices. The stability of the resulting system is established, and its performance is characterized with respect to an ideal reference system which has the best feasible rate region at link layer. We then generalize the aforementioned results to a general model of queueing network served by a set of interdependent parallel servers with time-varying service capabilities, which models many design problems in communication networks. We show that for a general convex optimization problem where a subset of variables lie in a polytope and the rest in a convex set, the dual-based algorithm remains stable and optimal when the constraint set is modulated by an irreducible finite-state Markov chain. This paper thus presents a step toward a systematic way to carry out cross-layer design in the framework of “layering as optimization decomposition” for time-varying channel models