25,779 research outputs found

    Using Sphinx to Improve Onion Routing Circuit Construction

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    This paper presents compact message formats for onion routing circuit construction using the Sphinx methodology developed for mixes. We significantly compress the circuit construction messages for three onion routing protocols that have emerged as enhancements to the Tor anonymizing network; namely, Tor with predistributed Diffie-Hellman values, pairing-based onion routing, and certificateless onion routing. Our new circuit constructions are also secure in the universal composability framework, a property that was missing from the original constructions. Further, we compare the performance of our schemes with their older counterparts as well as with each other

    On Compact Routing for the Internet

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    While there exist compact routing schemes designed for grids, trees, and Internet-like topologies that offer routing tables of sizes that scale logarithmically with the network size, we demonstrate in this paper that in view of recent results in compact routing research, such logarithmic scaling on Internet-like topologies is fundamentally impossible in the presence of topology dynamics or topology-independent (flat) addressing. We use analytic arguments to show that the number of routing control messages per topology change cannot scale better than linearly on Internet-like topologies. We also employ simulations to confirm that logarithmic routing table size scaling gets broken by topology-independent addressing, a cornerstone of popular locator-identifier split proposals aiming at improving routing scaling in the presence of network topology dynamics or host mobility. These pessimistic findings lead us to the conclusion that a fundamental re-examination of assumptions behind routing models and abstractions is needed in order to find a routing architecture that would be able to scale ``indefinitely.''Comment: This is a significantly revised, journal version of cs/050802

    Destination Tag Routing Techniques Based on a State Model for the IADM Network

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    A state model is proposed for solving the problem of routing and rerouting messages in the Inverse Augmented Data Manipulator (IADM) network. Using this model, necessary and sufficient conditions for the reroutability of messages are established, and then destination tag schemes are derived. These schemes are simpler, more efficient and require less complex hardware than previously proposed routing schemes. Two destination tag schemes are proposed. For one of the schemes, rerouting is totally transparent to the sender of the message and any blocked link of a given type can be avoided. Compared with previous works that deal with the same type of blockage, the timeXspace complexity is reduced from O(logN) to O(1). For the other scheme, rerouting is possible for any type of link blockage. A universal rerouting algorithm is constructed based on the second scheme, which finds a blockage-free path for any combination of multiple blockages if there exists such a path, and indicates absence of such a path if there exists none. In addition, the state model is used to derive constructively a lower bound on the number of subgraphs which are isomorphic to the Indirect Binary N-Cube network in the IADM network. This knowledge can be used to characterize properties of the IADM networks and for permutation routing in the IADM networks

    Cellular automaton supercolliders

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    Gliders in one-dimensional cellular automata are compact groups of non-quiescent and non-ether patterns (ether represents a periodic background) translating along automaton lattice. They are cellular-automaton analogous of localizations or quasi-local collective excitations travelling in a spatially extended non-linear medium. They can be considered as binary strings or symbols travelling along a one-dimensional ring, interacting with each other and changing their states, or symbolic values, as a result of interactions. We analyse what types of interaction occur between gliders travelling on a cellular automaton `cyclotron' and build a catalog of the most common reactions. We demonstrate that collisions between gliders emulate the basic types of interaction that occur between localizations in non-linear media: fusion, elastic collision, and soliton-like collision. Computational outcomes of a swarm of gliders circling on a one-dimensional torus are analysed via implementation of cyclic tag systems

    Dynamic and Multi-functional Labeling Schemes

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    We investigate labeling schemes supporting adjacency, ancestry, sibling, and connectivity queries in forests. In the course of more than 20 years, the existence of log⁥n+O(log⁥log⁥)\log n + O(\log \log) labeling schemes supporting each of these functions was proven, with the most recent being ancestry [Fraigniaud and Korman, STOC '10]. Several multi-functional labeling schemes also enjoy lower or upper bounds of log⁥n+Ω(log⁥log⁥n)\log n + \Omega(\log \log n) or log⁥n+O(log⁥log⁥n)\log n + O(\log \log n) respectively. Notably an upper bound of log⁥n+5log⁥log⁥n\log n + 5\log \log n for adjacency+siblings and a lower bound of log⁥n+log⁥log⁥n\log n + \log \log n for each of the functions siblings, ancestry, and connectivity [Alstrup et al., SODA '03]. We improve the constants hidden in the OO-notation. In particular we show a log⁥n+2log⁥log⁥n\log n + 2\log \log n lower bound for connectivity+ancestry and connectivity+siblings, as well as an upper bound of log⁥n+3log⁥log⁥n+O(log⁥log⁥log⁥n)\log n + 3\log \log n + O(\log \log \log n) for connectivity+adjacency+siblings by altering existing methods. In the context of dynamic labeling schemes it is known that ancestry requires Ω(n)\Omega(n) bits [Cohen, et al. PODS '02]. In contrast, we show upper and lower bounds on the label size for adjacency, siblings, and connectivity of 2log⁥n2\log n bits, and 3log⁥n3 \log n to support all three functions. There exist efficient adjacency labeling schemes for planar, bounded treewidth, bounded arboricity and interval graphs. In a dynamic setting, we show a lower bound of Ω(n)\Omega(n) for each of those families.Comment: 17 pages, 5 figure

    Space-Efficient Routing Tables for Almost All Networks and the Incompressibility Method

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    We use the incompressibility method based on Kolmogorov complexity to determine the total number of bits of routing information for almost all network topologies. In most models for routing, for almost all labeled graphs Θ(n2)\Theta (n^2) bits are necessary and sufficient for shortest path routing. By `almost all graphs' we mean the Kolmogorov random graphs which constitute a fraction of 1−1/nc1-1/n^c of all graphs on nn nodes, where c>0c > 0 is an arbitrary fixed constant. There is a model for which the average case lower bound rises to Ω(n2log⁥n)\Omega(n^2 \log n) and another model where the average case upper bound drops to O(nlog⁥2n)O(n \log^2 n). This clearly exposes the sensitivity of such bounds to the model under consideration. If paths have to be short, but need not be shortest (if the stretch factor may be larger than 1), then much less space is needed on average, even in the more demanding models. Full-information routing requires Θ(n3)\Theta (n^3) bits on average. For worst-case static networks we prove a Ω(n2log⁥n)\Omega(n^2 \log n) lower bound for shortest path routing and all stretch factors <2<2 in some networks where free relabeling is not allowed.Comment: 19 pages, Latex, 1 table, 1 figure; SIAM J. Comput., To appea

    Near-optimal adjacency labeling scheme for power-law graphs

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    An adjacency labeling scheme is a method that assigns labels to the vertices of a graph such that adjacency between vertices can be inferred directly from the assigned label, without using a centralized data structure. We devise adjacency labeling schemes for the family of power-law graphs. This family that has been used to model many types of networks, e.g. the Internet AS-level graph. Furthermore, we prove an almost matching lower bound for this family. We also provide an asymptotically near- optimal labeling scheme for sparse graphs. Finally, we validate the efficiency of our labeling scheme by an experimental evaluation using both synthetic data and real-world networks of up to hundreds of thousands of vertices
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