338 research outputs found

    The Complexity of Distributed Edge Coloring with Small Palettes

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    The complexity of distributed edge coloring depends heavily on the palette size as a function of the maximum degree Δ\Delta. In this paper we explore the complexity of edge coloring in the LOCAL model in different palette size regimes. 1. We simplify the \emph{round elimination} technique of Brandt et al. and prove that (2Δ2)(2\Delta-2)-edge coloring requires Ω(logΔlogn)\Omega(\log_\Delta \log n) time w.h.p. and Ω(logΔn)\Omega(\log_\Delta n) time deterministically, even on trees. The simplified technique is based on two ideas: the notion of an irregular running time and some general observations that transform weak lower bounds into stronger ones. 2. We give a randomized edge coloring algorithm that can use palette sizes as small as Δ+O~(Δ)\Delta + \tilde{O}(\sqrt{\Delta}), which is a natural barrier for randomized approaches. The running time of the algorithm is at most O(logΔTLLL)O(\log\Delta \cdot T_{LLL}), where TLLLT_{LLL} is the complexity of a permissive version of the constructive Lovasz local lemma. 3. We develop a new distributed Lovasz local lemma algorithm for tree-structured dependency graphs, which leads to a (1+ϵ)Δ(1+\epsilon)\Delta-edge coloring algorithm for trees running in O(loglogn)O(\log\log n) time. This algorithm arises from two new results: a deterministic O(logn)O(\log n)-time LLL algorithm for tree-structured instances, and a randomized O(loglogn)O(\log\log n)-time graph shattering method for breaking the dependency graph into independent O(logn)O(\log n)-size LLL instances. 4. A natural approach to computing (Δ+1)(\Delta+1)-edge colorings (Vizing's theorem) is to extend partial colorings by iteratively re-coloring parts of the graph. We prove that this approach may be viable, but in the worst case requires recoloring subgraphs of diameter Ω(Δlogn)\Omega(\Delta\log n). This stands in contrast to distributed algorithms for Brooks' theorem, which exploit the existence of O(logΔn)O(\log_\Delta n)-length augmenting paths

    The Energy Complexity of Broadcast

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    Energy is often the most constrained resource in networks of battery-powered devices, and as devices become smaller, they spend a larger fraction of their energy on communication (transceiver usage) not computation. As an imperfect proxy for true energy usage, we define energy complexity to be the number of time slots a device transmits/listens; idle time and computation are free. In this paper we investigate the energy complexity of fundamental communication primitives such as broadcast in multi-hop radio networks. We consider models with collision detection (CD) and without (No-CD), as well as both randomized and deterministic algorithms. Some take-away messages from this work include: 1. The energy complexity of broadcast in a multi-hop network is intimately connected to the time complexity of leader election in a single-hop (clique) network. Many existing lower bounds on time complexity immediately transfer to energy complexity. For example, in the CD and No-CD models, we need Ω(logn)\Omega(\log n) and Ω(log2n)\Omega(\log^2 n) energy, respectively. 2. The energy lower bounds above can almost be achieved, given sufficient (Ω(n)\Omega(n)) time. In the CD and No-CD models we can solve broadcast using O(lognloglognlogloglogn)O(\frac{\log n\log\log n}{\log\log\log n}) energy and O(log3n)O(\log^3 n) energy, respectively. 3. The complexity measures of Energy and Time are in conflict, and it is an open problem whether both can be minimized simultaneously. We give a tradeoff showing it is possible to be nearly optimal in both measures simultaneously. For any constant ϵ>0\epsilon>0, broadcast can be solved in O(D1+ϵlogO(1/ϵ)n)O(D^{1+\epsilon}\log^{O(1/\epsilon)} n) time with O(logO(1/ϵ)n)O(\log^{O(1/\epsilon)} n) energy, where DD is the diameter of the network

    A constant factor approximation for Nash social welfare with subadditive valuations

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    We present a constant-factor approximation algorithm for the Nash social welfare maximization problem with subadditive valuations accessible via demand queries. More generally, we propose a template for NSW optimization by solving a configuration-type LP and using a rounding procedure for (utilitarian) social welfare as a blackbox, which could be applicable to other variants of the problem

    Time-Varying Integral Adaptive Sliding Mode Control for the Large Erecting System

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    Considering the nonlinearities, uncertainties of large erecting system, and the circumstance disturbances in erecting process, a novel sliding mode control strategy is proposed in this research. The proposed control strategy establishes the sliding mode without reaching phase using an integral sliding surface. Thus, robustness against uncertainties increases from the very beginning of the process. Furthermore, adaptive laws are used for the controller to estimate the unknown but bounded system uncertainties. Therefore, the upper bounds of the system uncertainties are not required to be known in advance. Then, the time-varying term is applied to ensure the global robustness. Moreover, the boundary layer method is used to attenuate the high frequency chattering. The experiment results demonstrated that the proposed strategy could effectively restrain parametric uncertainties and external disturbances and improve the tracking accuracy in the erecting process. In addition, the control performance of the proposed control strategy is better than that of the PID control and the conventional sliding mode control
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