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IEEE Global Telecommunications Conference (GLOBECOM 04)

作者： Madan, R Lall, S Stanford Univ Dept Elect Engn Stanford CA 94305 USA

ISBN: (纸本)0780387945

A sensor network of nodes with wireless transceiver capabilities and limited energy is considered. We propose distributed algorithms to compute an optimal routing scheme that maximizes the time at which the first node in the network drains out of energy. The problem is formulated as a linear programming problem and subgradient algorithms are used to solve it in a distributed manner. The resulting algorithms have low computational complexity and are guaranteed to converge to an optimal routing scheme that maximizes the network lifetime. The algorithms are illustrated by an example in which an optimal flow is computed for a network of randomly distributed nodes.

关键词： linear programming dual decomposition subgradient algorithm sensor networks network lifetime

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Radio Resource Allocation for Multicast Transmissions over High Altitude Platforms

Radio Resource Allocation for Multicast Transmissions over H...

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IEEE Globecom Workshops (GC Wkshps)

作者： Ibrahim, Ahmed Alfa, Attahiru S. Univ Manitoba Dept Elect & Comp Engn Winnipeg MB R3T 2N2 Canada

ISBN: (纸本)9781479928514

In this paper, we study radio resource allocation (RRA) for multicasting in OFDMA based High Altitude Platforms (HAPs). We formulate an optimization problem for a scenario in which different sessions are multicasted to user terminals (UTs) across HAP service area. We then solve it to find the best allocation of HAP resources such as radio power, sub-channels, and time slots. The objective is to maximize the number of UTs that receive the requested multicast streams in the HAP service area in a given OFDMA frame. The optimization problem comes out to be a Mixed Integer Non-Linear Program (MINLP). Due to the high complexity of the problem and lack of special structures, we believe that breaking it into two easier subproblems and iterating between them to achieve convergence can lead to an acceptable solution. Subproblem 1 turns out to be a Binary Integer Linear Program (BILP) of no explicitly noticeable structure and therefore Lagrangian relaxation is used to dualize some constraints to get a BILP with some special structure that is easy to solve. The subgradient method is used to solve for the dual variables in the dual problem for three proposed methods to get the tightest bound in each. The obtained bounds can be used in a branch and bound (BnB) algorithm as its bounding subroutine at each node. Subproblem 2 turns out to be a simple linear program (LP) for which the simplex algorithm can be used to solve the subproblem to optimality. This paper focuses on subproblem 1 and its proposed solution techniques. In the results section of this paper, we compare the solution goodness for each method versus the well known bounding technique used in BnB which is linear program (LP) relaxation.

关键词： High Altitude Platforms Multicasting Radio Resource Allocation OFDMA Optimization Binary Integer Linear Program Lagrangian Relaxation subgradient algorithm

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Lagrangian Heuristics for Capacitated Shortest Path Tour Problem Based Online Service Chaining

Lagrangian Heuristics for Capacitated Shortest Path Tour Pro...

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IEEE/IFIP Network Operations and Management Symposium

作者： Hara, Takanori Sasabe, Masahiro Nara Inst Sci & Technol Grad Sch Sci & Technol 8916-5 Takayama Cho Nara 6300192 Japan

ISBN: (纸本)9781665406017

Network functions virtualization (NFV) can flexibly deploy diverse network services by liberating network functions from traditional network appliances and executing them as virtual network functions (VNFs) on generic hardware. A certain network service can be represented by a service chain, which consists of VNFs in required order. The service chaining problem is finding a suitable service path from the origin to the destination such that the VNFs are executed at the intermediate nodes in the required order under the resource constraints, which belongs to the complexity class NP-hard. In our previous work, considering the similarity between the service chaining problem and the shortest path tour problem (SPTP), we formulated the service chaining as the capacitated SPTP (CSPTP) based ILP, where CSPTP is an extended version of the SPTP with the node and link capacity constraints. In this paper, to address both computational complexity and optimality of resource allocation, we propose Lagrangian heuristics to solve the CSPTP-based ILP especially for the online service chaining. Through simulation results, we show that the proposed algorithm almost achieves the optimal resource allocation with much smaller execution time compared with the existing solver, CPLEX.

关键词： Network functions virtualization (NFV) service chaining capacitated shortest path tour problem (CSPTP) integer linear programming (ILP) Lagrangian relaxation subgradient algorithm

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Transmission Delay Minimization via Joint Power Control and Caching in Wireless HetNets 19

Transmission Delay Minimization via Joint Power Control and ...

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19th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt)

作者： Malak, Derya Mutlu, Faruk, V Zhang, Jinkun Yeh, Edmund M. EURECOM Commun Syst Dept F-06904 Biot Sophia Antipolis France Northeastern Univ Boston MA 02115 USA

ISBN: (纸本)9783903176379

A fundamental challenge in wireless heterogeneous networks (HetNets) is to effectively use the limited transmission and storage resources in the presence of increasing deployment density and backhaul capacity constraints. To alleviate bottlenecks and reduce resource consumption, we design optimal caching and power control algorithms for multi-hop wireless HetNets. We devise a joint optimization framework to minimize the average transmission delay as a function of the caching variables and the signal-to-interference-plus-noise ratios (SINR) as determined by the transmission powers, while explicitly accounting for backhaul connection costs and the power constraints. Using convex relaxation and rounding, we obtain a reduced-complexity formulation (RCF) of the joint optimization problem, which can provide a constant factor approximation to the globally optimal solution. We characterize the necessary (KKT) conditions for an optimal solution to RCF, and use strict quasi-convexity to show that the KKT points are Pareto optimal for RCF. We then devise a subgradient projection algorithm to jointly update the caching and power variables, and show that under appropriate conditions, the algorithm converges at a linear rate to the local minima of RCF, under general SINR. We support our analytical findings with results from numerical experiments.

关键词： Joint power-caching optimization biconvexity quasi-convexity Pareto optimality subgradient algorithm

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Distributed Optimization for Resource Allocation with Event-Triggered Communication under Directed Topology 3

Distributed Optimization for Resource Allocation with Event-...

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2017 3rd IEEE International Conference on Control Science and Systems Engineering (ICCSSE)

作者： Xiasheng Shi Sumian Song Yun Xu Gangfeng Yan College of Electrical Engineering Zhejiang University

ISBN: (纸本)9781538604854

This paper focuses on the resource allocation problem with equality and inequality constraints in a fixed weight-balanced directed or undirected network. Moreover, we propose a fully decentralized subgradient algorithm with event-triggered for solving above resource allocation problem based on first-order discrete-time multi-agent systems. Where each agent only communicates with its neighbors and the triggering function only requires local information. The above algorithm aims to minimize the total cost by a distributed manner, that is, each agent updates its state by employing the states collected from itself and its neighboring agents at their last triggering time. Finally, an example is given to analyze the feasibility of the event-triggered algorithm.

关键词： subgradient algorithm event-triggered resource allocation

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On the Dual Decomposition of Linear Quadratic Optimal Control Problems for Vehicular Formations 49

On the Dual Decomposition of Linear Quadratic Optimal Contro...

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49th IEEE Conference on Decision and Control (CDC)

作者： Fardad, Makan Lin, Fu Jovanovic, Mihailo R. Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA Univ Minnesota Dept Elect & Comp Engn Minneapolis MN 55455 USA

ISBN: (纸本)9781424477463

We use the dual decomposition method along with the dual subgradient algorithm to decouple the linear quadratic optimal control problem for a system of single-integrator vehicles. This produces the optimal control law in a localized manner, in the sense that vehicles can iteratively compute their primal and dual variables by only communicating with their immediate neighbors. In particular, we demonstrate that each vehicle only needs to receive the primal variable of the vehicle ahead and the dual variable of the vehicle behind. We then assume a structured feedback gain relationship between the state and actuation signals, and reformulate the optimization problem to find the optimal feedback gains. We develop an algorithm whereby vehicles can compute structured feedback gains in a localized manner. Convergence properties of the latter algorithm are improved by employing a relaxed version of the augmented Lagrangian method, and numerical examples are provided to demonstrate the utility of our results.

关键词： Distributed optimization dual decomposition subgradient algorithm localized cooperative control multivehicle systems

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SERVICE TIME OPTIMIZATION OF FLOW SHOP SYSTEMS

SERVICE TIME OPTIMIZATION OF FLOW SHOP SYSTEMS

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作者： Omer Selvi BILKENT UNIVERSITY

学位级别：博士

One of the key questions that engineers face in ‡ow shop systems is the service time control, i. e., how long jobs should be processed at each machine. This is an important question because processing times can have great impacts on the cost e¢ciency of the ‡ow shop systems. In order to meet job completion deadlines and to decrease inventory costs, one may set the service times as small as possible; however, this usually comes at the expense of reduced tool life increasing service costs. In this thesis, we study the ‡ow shop systems under such trade-o¤s. We consider the service time optimization of deterministic ‡ow shop systems process- ing identical jobs that arrive at the system at known times and are processed in the order they arrive within deadlines. The cost function to be minimized con- sists of service costs at machines and regular completion-time costs of jobs. The decision variables are the service times that are controllable within constraints. We... rst consider the... xed service time ‡ow shop systems formed of initially controllable machines, where the service times are set only once at the start up time and cannot be altered between processes, and uncontrollable machines, where the service times are... xed and known in advance. For such systems, we formulate a non-convex and non-di¤erentiable optimization problem with a stan- dard solution procedure based on the linearization of the constraints allowing for a convex optimization problem with high memory requirements. Regardless of the cost function, we present a set of waiting and completion time characteristics in such ‡ow shop systems and employ them to derive a simpler equivalent convex optimization problem which improves solution times and alleviates the memory requirements enabling solutions for larger systems. However, the resulting sim- pli... ed convex optimization problem still needs the use of a convex optimization solver which may not be available at some of the manufacturing companies. To

关键词： Deterministic flow shop systems Optimal control Controllable service times Controllable/Uncontrollable machines Convex programming subgradient algorithm

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Speedy and Efficient Service Chaining and Function Placement Based on Lagrangian Heuristics for Capacitated Shortest Path Tour Problem

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JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT 2023年第1期31卷 24-24页

作者： Hara, Takanori Sasabe, Masahiro Nara Inst Sci & Technol Div Informat Sci 8916-5 Takayama cho Ikoma Nara 6300192 Japan

Network functions virtualization (NFV) can realize flexible and diverse network services by replacing the conventional network equipment with the combination of virtual network functions (VNFs) and commodity servers. A certain network service can be composed of a sequence of VNFs, i.e., service (function) chain. The service chaining (SC) problem aims to establish an appropriate service path from the origin node to the destination node, which holds both the resource constraints and service chain requirements of executing the required VNFs in the designated order. SC belongs to the complexity class NP-hard. In the previous work, inspired by the similarity between the SC problem and the shortest path tour problem (SPTP), we showed the capacitated SPTP (CSPTP) based ILP for the SC problem, where CSPTP is a generalized version of the SPTP with both the node and link capacity constraints. In this paper, we propose Lagrangian heuristics to solve the CSPTP-based ILP for the SC in a speedy and efficient manner. We further present that the proposed heuristics can also solve both the service chaining and function placement by slightly extending the network model called an augmented network. Through numerical results, we show that the proposed heuristics for the SC is competitive with the optimal resource allocation while executing much faster than the combination of the CSPTP-based ILP and the existing solver, i.e., CPLEX. Furthermore, we also show that the proposed heuristics for both the service chaining and function placement can still balance the solution optimality and computational complexity, thanks to the parallel computation architectures.

关键词： Network functions virtualization (NFV) Service chaining Function placement Integer linear programming (ILP) Capacitated shortest path tour problem (CSPTP) Lagrangian relaxation Linear relaxation subgradient algorithm Totally unimodular

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ResEntSG: Restoration entropy estimation for dynamical systems via Riemannian metric optimization

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SOFTWAREX 2021年 15卷

作者： Kawan, Christoph Hafstein, Sigurdur Freyr Giesl, Peter Ludwig Maximilians Univ Munchen Inst Informat Oettingenstr 67 D-80538 Munich Germany Univ Iceland Sci Inst Dunhagi 3 IS-107 Reykjavik Iceland Univ Sussex Dept Math Falmer BN1 9QH England

In the remote state estimation problem, an observer reconstructs the state of a dynamical system at a remote location, where no direct sensor measurements are available. The estimator only has access to information sent through a digital channel. The notion of restoration entropy provides a way to determine the smallest channel capacity above which an observer can be designed that observes the system without a degradation of the initial estimation error. In general, restoration entropy is hard to compute. We present a class library in C++, that estimates the restoration entropy of a given system by computing an adapted metric for the system. The library is simple to use and implements a version of the subgradient algorithm for geodesically convex functions to compute an optimal metric in a class of conformal metrics. Included in the software are three example systems to demonstrate the use and efficacy of the library. (C) 2021 The Author(s). Published by Elsevier B.V.

关键词： Restoration entropy subgradient algorithm Geodesic convexity Riemannian metric Dynamical systems C plus Scientific computing

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A market mechanism for multiple air traffic resources

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2023年 178卷

作者： Brugnara, Irene Castelli, Lorenzo Pesenti, Raffaele Univ Trieste Trieste Italy Univ CaFoscari Venezia Venice Italy

We introduce a model that extends the concept of air traffic flow management slot to the concept of time window, allowing to effectively deal with a network of interacting regulations. The model aims at minimising the total cost of delay of a time window allocation to flights and is based on an integer programming problem. It consists in a market-based mechanism between flights and a central authority to trade time windows, which fulfils the properties of individual rationality (every participating airline has a non-negative profit from the mechanism) and weak budget-balance (the mechanism requires no external subsidisation). Equity is assumed to be respected because the First Planned First Served allocation is an endowment guaranteed to all flights and allocated for free. The proposed market mechanism can be implemented in a distributed manner preventing the disclosure of confidential information by airlines, and is based on the Lagrangian relaxation of the integer optimisation problem, solved through the subgradient algorithm. We present some computational experiments conducted to test the model on some real instances of air traffic data.

关键词： Air Traffic Management (ATM) Air Traffic Flow Management (ATFM) ATFM regulation subgradient algorithm Market mechanism Pricing equilibrium

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