In this paper we introduce two discrete-time, distributed optimization algorithms executed by a set of agents whose interactions are subject to a communication graph. The algorithms can be applied to optimization prob...
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ISBN:
(纸本)9781467357159
In this paper we introduce two discrete-time, distributed optimization algorithms executed by a set of agents whose interactions are subject to a communication graph. The algorithms can be applied to optimization problems where the cost function is expressed as a sum of functions, and where each function is associated to an agent. In addition, the agents can have equality constraints as well. The algorithms are not consensus-based and can be applied to non-convex optimization problems with equality constraints. We demonstrate that the first distributed algorithm results naturally from applying a first order method to solve the first order necessary conditions for a lifted optimization problem with equality constraints;the solution of our original problem is embedded in the solution of this lifted optimization problem. Using an augmented Lagrangian idea, we derive a second distributed algorithm that requires weaker conditions for local convergence compared to the first algorithm. For both algorithms we address the local convergence properties.
This paper is about the design and quantitative analysis of distributed approaches for optical flow switching (using dynamic lightpath setup) in a wide area WDM backbone network. The major contribution of this work is...
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This paper is about the design and quantitative analysis of distributed approaches for optical flow switching (using dynamic lightpath setup) in a wide area WDM backbone network. The major contribution of this work is to design realistic integrated approaches for flow routing, wavelength assignment, and connection setup in a truly distributed setting, and assess the relative performance of these on a nationwide wide area network (WAN) backbone. A simulation model is used which models timing, wavelength, and fiber constraints. Results are presented in terms of backbone utilization for a given blocking probability of optical flows.
This paper addresses the problem of robotic task allocation for incident response. In particular, we propose a solution for the distributed dynamic assignment of ground robots for the extraction of victims within an i...
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ISBN:
(纸本)9781509025923
This paper addresses the problem of robotic task allocation for incident response. In particular, we propose a solution for the distributed dynamic assignment of ground robots for the extraction of victims within an incident scene. Aerial robots communicate among them in order to assign tasks to the ground robots for victim extraction in the shortest possible time. Aerial robots perform two consecutive distributed algorithms: the first one aims at correctly detecting in a completely cooperative manner the exact positions and criti-cality of the victims of the incident;the second one consists of distributed multi-agent optimizations in order to reach a common assignment of the victims needing to be extracted. Finally, the efficiency of the method is shown by an illustrative example.
We briefly recall the paradigm for distributed stochastic approximation with consensus introduced by Tsitsiklis et al and describe some recent `nonlinear' versions of it. Some possible future directions will also ...
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We briefly recall the paradigm for distributed stochastic approximation with consensus introduced by Tsitsiklis et al and describe some recent `nonlinear' versions of it. Some possible future directions will also be indicated.
Internet service providers increasingly deploy internal CDNs with the objective of reducing the traffic on their transit links and to improve their customers' quality of experience. Once ISP managed CDNs (nCDNs) b...
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Internet service providers increasingly deploy internal CDNs with the objective of reducing the traffic on their transit links and to improve their customers' quality of experience. Once ISP managed CDNs (nCDNs) become commonplace, ISPs would likely provide common interfaces to interconnect their nCDNs for mutual benefit, as they do with peering today. In this paper we consider the problem of using distributed algorithms for computing a content allocation for nCDNs. We show that if every ISP aims to minimize its cost and bilateral payments are not allowed then it may be impossible to compute a content allocation. For the case of bilateral payments we propose two distributed algorithms, the aggregate value compensation (AC) and the object value compensation (OC) algorithms, which differ in terms of the level of parallelism they allow and in terms of the amount of information exchanged between nCDNs. We prove that the algorithms converge, and we propose a scheme to ensure ex-post individual rationality. Simulations performed on a real AS-level network topology and synthetic topologies show that the algorithms have geometric rate of convergence, and scale well with the graphs' density and the nCDN capacity.
This paper introduces two distributed algorithms for resource allocation in cellular networks with coexisting femtocells and macrocells. Network interference in these complex networks is modeled by a random graph to m...
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This paper introduces two distributed algorithms for resource allocation in cellular networks with coexisting femtocells and macrocells. Network interference in these complex networks is modeled by a random graph to maintain the complexity of the examined networks' interference scenarios while abstracting away details such as node density and propagation characteristics. We propose two distributed algorithms for interference-free resource assignment: An uncoordinated algorithm designed for a case with no communications between base stations, and a coordinated algorithm designed to exploit information sharing between base stations. We assess the two algorithms by comparing their performance against a centralized heuristic algorithm and a centralized genetic algorithm, which together approximate the (computationally intractable) optimal allocation.
The growing popularity of mobile multimedia content and the increase of wireless access bitrates are straining backhaul capacity in mobile networks. A cost-effective solution to reduce the strain, enabled by emerging ...
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The growing popularity of mobile multimedia content and the increase of wireless access bitrates are straining backhaul capacity in mobile networks. A cost-effective solution to reduce the strain, enabled by emerging all-IP 4G and 5G mobile backhaul architectures, could be in-network caching of popular content during times of peak demand. In this paper we formulate the problem of content caching in a mobile backhaul as a binary integer programming problem, and we propose a 2- approximation algorithm for the problem. The 2-approximation requires full information about the network topology and the link costs, as well as about the content demands at the different caches, we thus propose two distributed algorithms that are based on limited information on the content demands. We show that the distributed algorithms terminate in a finite number of steps, and we provide analytical results on their approximation ratios. We use simulations to evaluate the proposed algorithms in terms of the achieved approximation ratio and computational complexity on realistic mobile backhaul topologies.
Aiming at the problem that communication constraint and the states of agents restricted, distributed convex optimization algorithm for multi-agent network with state quantization is proposed. Firstly, considering comm...
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Aiming at the problem that communication constraint and the states of agents restricted, distributed convex optimization algorithm for multi-agent network with state quantization is proposed. Firstly, considering communication constraint, the sampled-data model of closed-loop system is formulated. Then, considering convex inequalities with some set constraints, a corresponding control protocol is designed for all agents to drive to the intersection of all convex sets of the agents to reach a consensus through local interactions. By using the analysis method of Lyapunov theory and graph theory, conditions associated with connectivity are derived for all agents to come to an agreement when the network is strongly connected. Finally, a simulation example shows the availability of the proposed method.
We derive a sequential algorithm Find-Ham-Cycle with the following property. On input: k and n (specifying the k-ary n-cube Q n k ); F, a set of at most 2n - 2 faulty links; and v, a node of Q n k , the algorithm outp...
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We derive a sequential algorithm Find-Ham-Cycle with the following property. On input: k and n (specifying the k-ary n-cube Q n k ); F, a set of at most 2n - 2 faulty links; and v, a node of Q n k , the algorithm outputs nodes v + and v - such that if Find-Ham-Cycle is executed once for every node v of Q n k then the node v + (resp. v - ) denotes the successor (resp. predecessor) node of v on a fixed Hamiltonian cycle in Q n k in which no link is in F. Moreover, the algorithm Find-Ham-Cycle runs in time polynomial in n and log k. We also obtain a similar algorithm for an n-dimensional hypercube with at most n - 2 faulty links. We use our algorithms to obtain distributed algorithms to embed Hamiltonian cycles in k-ary n-cubes and hypercubes with faulty links
distributed algorithms have been proposed as options to scale control propositions to the massive number of intelligent energy devices, sub-systems, and distributed energy resources being integrated into the electrici...
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ISBN:
(纸本)9781665405072
distributed algorithms have been proposed as options to scale control propositions to the massive number of intelligent energy devices, sub-systems, and distributed energy resources being integrated into the electricity grid. distributed algorithms rely on the communication network for exchanging information. Failures in the communication network can jeopardize distributed decision-making and in the worst-case scenario can lead to system-level stability problems. This paper proposes a communication-failure-resilient architecture for distributed operation and control in smart grids with hybrid producer/consumer (prosumer) agents. We describe the relations between system-wide performance and communication failures and identify topological conditions on the cyber-physical network, under which prosumers can perform key operating tasks such as distributed frequency regulation through an imperfect communication network.
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