In this paper we study the unsplittable flow problem (UFP) on tree networks in a distributed setting. We have a set of processors (or agents) and a set of tree networks defined over some vertex set. Each processor can...
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ISBN:
(纸本)9781467360661
In this paper we study the unsplittable flow problem (UFP) on tree networks in a distributed setting. We have a set of processors (or agents) and a set of tree networks defined over some vertex set. Each processor can access a subset of the tree networks. Each edge in each of the tree networks is associated with a capacity. Each processor has a demand specified as a pair of vertices u and v, along with a profit and a height; the processor wishes to send data between u and v and requires bandwidth equal to its height. Towards that goal, the processor needs to select a tree network accessible to it. A feasible solution selects a subset of demands and schedules each selected demand on a tree network accessible to the processor owning the demand. The requirement is that for any tree network and any edge in the network, the sum of heights of demands scheduled on the network and passing through the edge must not exceed the capacity offered by the edge. The goal is to output a solution having the maximum aggregate profit. Prior work has addressed the above problem in a distributed setting for the special case where all the edge capacities are uniform, say one unit. The main contributions of this paper is to address the general case where the edge capacities can be non-uniform and arbitrary. For this case, we present distributed algorithms with poly-logarithmic approximation ratio.
Previously, we developed the broadcast incremental power (BIP) algorithm (Wieselthier, J.E. et al., Proc. IEEE INFOCOM 2000, p.585-94, 2000; Mobile Networks and Applications (MONET), vol.7, no.6, 2002), which is a cen...
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Previously, we developed the broadcast incremental power (BIP) algorithm (Wieselthier, J.E. et al., Proc. IEEE INFOCOM 2000, p.585-94, 2000; Mobile Networks and Applications (MONET), vol.7, no.6, 2002), which is a centralized heuristic for energy-efficient broadcasting of source-initiated session-based traffic in wireless networks. This algorithm, which exploits the characteristics of the wireless channel, was shown to perform better than adaptations of conventional algorithms that were originally developed for wired networks. However, as a consequence of its centralized nature, it is "expensive" in terms of both communication and computation requirements. We now develop two distributed versions of BIP, and compare their performance to that of centralized BIP and to an algorithm based on the minimum-cost spanning tree formulation.
This paper presents a family of discrete-time distributed algorithms that enable nodes in an undirected, connected network to solve, in a fully decentralized fashion, a system of modular congruences whose residues and...
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ISBN:
(数字)9781538682661
ISBN:
(纸本)9781538682678
This paper presents a family of discrete-time distributed algorithms that enable nodes in an undirected, connected network to solve, in a fully decentralized fashion, a system of modular congruences whose residues and pairwise coprime moduli are locally known to the nodes. We show that each algorithm in the family is able to determine, in finite time, the congruence class of solutions whose existence and uniqueness is guaranteed by the Chinese remainder theorem. We also describe and analyze three specific algorithms from the family called Synchronous Updating (SU), Pairwise Equalizing (PE), and Groupwise Equalizing (GE), relating the convergence rate of SU to the network diameter and those of PE and GE to their asynchronous update patterns. Finally, we provide simulation results that illustrate their effectiveness.
A wireless network using a mesh topology is offered as an alternative to a star topology in a dynamic mobile network. A great challenge for a mobile mesh network is the ability to share resources between nodes to allo...
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ISBN:
(纸本)9783800742530
A wireless network using a mesh topology is offered as an alternative to a star topology in a dynamic mobile network. A great challenge for a mobile mesh network is the ability to share resources between nodes to allow connectivity throughout the network. As the network is dynamic, it is proposed that the algorithm for resource sharing be distributed and be easily adaptable to changes. This research suggests two distributive algorithms for resource allocation and compares the results to the minimal distribution in one predetermined scenario, and to a in random scenarios. The research assumes the ability to perform frequency and time division, and also suggests a method for resource allocation when using orthogonal subbands.
A distributed sampling strategy for multiple (N) agents is considered that minimizes the sample complexity and regret of acquiring the best subset of size N among total K ≥ N channels in a cognitive radio access setu...
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ISBN:
(数字)9783903176201
ISBN:
(纸本)9781728130859
A distributed sampling strategy for multiple (N) agents is considered that minimizes the sample complexity and regret of acquiring the best subset of size N among total K ≥ N channels in a cognitive radio access setup. Agents cannot directly communicate with each other, and no central coordination is possible. Each agent can transmit on one channel at a time, and if multiple agents transmit on the same channel at the same time, a collision occurs, and no agent gets any information about the channel gain or how many other agents transmitted on the same channel. If no collision occurs, the agent observes a reward (or gain) sample drawn from an underlying distribution associated with the channel. An algorithm to minimize the sample complexity and regret is proposed. One important property of our algorithm that distinguishes it from the prior work (that do not assume knowledge of N) is that it requires no information about the difference of the means of the channel gains of the K channels. Our approach results in fewer collisions with improved regret performance compared to the state-of-the-art algorithms. We validate our theoretical guarantees with experiments.
For a connected graph , a set of edges(vertices) is a cyclic edge(vertex) cutset if-is not connected and at least two components contain a cycle respectively. The cyclic edge(vertex) connectivity (8((8) is the cardina...
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For a connected graph , a set of edges(vertices) is a cyclic edge(vertex) cutset if-is not connected and at least two components contain a cycle respectively. The cyclic edge(vertex) connectivity (8((8) is the cardinality of a minimum cyclic edge(vertex) cutset. In this paper, we gave distributed algorithms determining cyclic edge connectivity and cyclic vertex connectivity of cubic graphs. The experiment results showed that the distributed algorithms were significantly improved in time compared to the original algorithms when the graph was large. Time costs of the distributed algorithms separately for cyclic edge connectivity and cyclic vertex connectivity are correspondingly less than 33% and less than 40% that of the single machine algorithms when the graph was large enough.
This paper discusses efficient distributed detection of global conjunctive predicates in a distributed program. Our methods correctly detect the first consistent cut in which the predicate is true, even if the predica...
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This paper discusses efficient distributed detection of global conjunctive predicates in a distributed program. Our methods correctly detect the first consistent cut in which the predicate is true, even if the predicate is unstable. Previous work in detection of such predicates is based on a centralized checker process. In this paper we introduce algorithms which distribute the computation and space requirements of the detection procedure. Two algorithms are presented. The first algorithm requires O (n/sup 2/ m) time and space where m is the number of messages sent by any process and n is the number of processes over which the predicate is defined. This algorithm has identical time complexity to the original centralized algorithm. However computation, space and message requirements are distributed evenly over the n processes. The second algorithm requires O(Nm) total work, where N is the total number of processes in the system. The relative values of n and N determine which algorithm is more efficient for a specific application. Parallelism can be introduced into either distributed algorithm, reducing the average case time complexity. We show that the worst-case time complexity can not be improved beyond O(mn) with any on-line detection algorithm.
The paper is devoted to Time Division Multiple Access Link Scheduling Protocols in wireless sensor networks for full duplex (two-way) communication, where each sensor is scheduled on an incident link as a transmitter ...
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The paper is devoted to Time Division Multiple Access Link Scheduling Protocols in wireless sensor networks for full duplex (two-way) communication, where each sensor is scheduled on an incident link as a transmitter and as a receiver in two different time slots. We formulate the full duplex link scheduling problem (FDLSP) as distance-2 edge coloring in bidirected graphs. We proves that there exists a Δ-approximation algorithm for FDLSP (Δ being the maximum node degree in the network). Then, we present two distributed algorithms. The first is a synchronous algorithm based on finding maximal independent sets. The second is an asynchronous depth first search (DFS) algorithm. The maximal independent set based algorithm requires only O(Δlog*n) communication rounds (where n is the number of processors in the network) for growth bounded graphs, which is a realistic geometric model of sensor networks. For general graphs, the maximal independent set based algorithm requires O(Δ 4 + Δ 3 log*n) communication rounds, improving upon the previous best algorithm with O(nΔ 2 +n 2 m) communication rounds (where m is the number of links in the network). The asynchronous DFS based algorithm requires only O(n) communication rounds for both general and growth bounded graphs. The simulations show that the proposed algorithms assign on average equal or fewer number of time slots compared to the best known distributed algorithm while being significantly faster.
The advances in radio design and wireless networking, along with the growth of multimedia home entertainment technologies, is creating the concept of a cognitive digital home requiring spectrum coexistence of various ...
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The advances in radio design and wireless networking, along with the growth of multimedia home entertainment technologies, is creating the concept of a cognitive digital home requiring spectrum coexistence of various devices and networks of networks. Recent work in has considered a framework for resource allocation in a cognitive digital home (CDH) with a multiplicity of radio access technologies (RAT) such as cognitive radios and legacy radio devices supporting heterogeneous applications. A spectrum manager, named the home genie node (HG), is used to coordinate spectrum coexistence across different services, with degrees of freedom ranging from transmission parameters such as frequency, bandwidth, and power, to the choice of radio access technology itself. distributed algorithms for the resource allocation problems in a CDH, namely maximizing sum rate and maximizing service capacity, which have been previously solved using centralized approaches in, are designed and studied using partial Lagrangian decomposition techniques in this paper.
The Nash arbitration scheme from cooperative game theory provides a natural framework to address the allocation of available bandwidth in network links which is network (Pareto) optimal and satisfies precise notions o...
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The Nash arbitration scheme from cooperative game theory provides a natural framework to address the allocation of available bandwidth in network links which is network (Pareto) optimal and satisfies precise notions of fairness. In this paper we propose two distributed bandwidth allocation schemes that allocate available bandwidths to elastic sources according to the Nash arbitration scheme. We prove convergence to the desired allocations for both algorithms. Finally we show how such a scheme can be implemented in a real network.
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