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distributed Optimal Energy Management for Energy Internet

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2017年第6期13卷 3081-3097页

作者： Zhang, Huaguang Li, Yushuai Gao, David Wenzhong Zhou, Jianguo Northeastern Univ Sch Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China Univ Denver Dept Elect & Comp Engn Denver CO 80208 USA

In this paper, a novel energy management framework for energy Internet with many energy bodies is presented, which features multicoupling of different energy forms, diversified energy roles, and peer-to-peer energy supply/demand, etc. The energy body as an integrated energy unit, which may have various functionalities and play multiple roles at the same time, is formulated for the system model development. Forecasting errors, confidence intervals, and penalty factor are also taken into account to model renewable energy resources to provide tradeoff between optimality and possibility. Furthermore, a novel distributed-consensus alternating direction method of multipliers (ADMM) algorithm, which contains a dynamic average consensus algorithm and distributed ADMM algorithm, is presented to solve the optimal energy management problem of energy Internet. The proposed algorithm can effectively handle the problems of power-heat-gas-coupling, global constraint limits, and nonlinear objective function. With this effort, not only the optimal energy market clearing price but also the optimal energy outputs/demands can be obtained through only local communication and computation. Simulation results are presented to illustrate the effectiveness of the proposed distributed algorithm.

关键词： distributed algorithm energy Internet energy management multiagent

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A distributed and parallel control mechanism for self-reconfiguration of modular robots using L-systems and cellular automata

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JOURNAL OF PARALLEL AND distributed COMPUTING 2017年 102卷 80-90页

作者： Zhu, Yanhe Bie, Dongyang Wang, Xiaolu Zhang, Yu Jin, Hongzhe Zhao, Jie Harbin Inst Technol State Key Lab Robot & Syst Harbin Heilongjiang Peoples R China

For distributed self-reconfiguration of Modular Self-Reconfigurable (MSR) robots, one of the main difficulties is the contradiction between limited information of decentralized modules and well-organized global structure. This paper presents a distributed and parallel mechanism for decentralized self-reconfiguration of MSR robots. This mechanism is hybrid by combining Lindenmayer systems (L-systems) describing the topological structure as configuration target and Cellular Automata (CA) for local motion planning of individual modules. Turtle interpretations are extended to modular robotics for generating module-level predictions from global description. According to local information, independent modules make motion planning by Cellular Automata in parallel. This distributed mechanism is robust to failure of modules, scalable to varying module numbers, and convergent to predefined reconfiguration targets. Simulations and statistical results are provided for validating the proposed algorithm. (C) 2016 Elsevier Inc. All rights reserved.

关键词： Modular robots distributed algorithm Parallel algorithm Self-reconfiguration Self-repair L-systems Cellular automata

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distributed Recursive Gaussian Processes for RSS Map Applied to Target Tracking

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IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 2017年第3期11卷 492-503页

作者： Yin, Feng Gunnarsson, Fredrik Chinese Univ Hong Kong Shenzhen & Shenzhen Res Inst Big Data Shenzhen 518172 Peoples R China Ericsson Res SE-58330 Linkoping Sweden

We propose a distributed recursive Gaussian process (drGP) regression framework for building received-signal-strength (RSS) map. The proposed framework adopts independent mobile devices in prescribed local areas to construct local RSS maps through recursive computation of the posterior distribution of the RSS on a fixed set of grids as training data gradually become available. The training input positions can be either precise or subject to errors of known distribution. All the local RSS maps are then fused to give a global map in the second step. The proposed framework is of significantly reduced computational complexity and scalable to big data generated from large-scale sensor networks. We further demonstrate its use in both static fingerprinting and mobile target tracking. The experimental results show that with our distributed framework satisfactory positioning accuracy can be achieved with much less complexity and storage than the standard framework.

关键词： distributed algorithm Gaussian processes particle filtering recursive algorithm RSS fingerprinting

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distributed in-network processing and resource optimization over mobile-health systems

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JOURNAL OF NETWORK AND COMPUTER APPLICATIONS 2017年 82卷 65-76页

作者： Awad, Alaa Mohamed, Amr Chiasserini, Carla-Fabiana Elfouly, Tarek Qatar Univ Dept Comp Sci & Engn Doha Qatar Politecnico Torino Dept Elect & Telecommun Turin Italy

Advances in wireless and mobile communication technologies has promoted the development of Mobile-health (m-health) systems to find new ways to acquire, process, transport, and secure the medical data. M-health systems provide the scalability needed to cope with the increasing number of elderly and chronic disease patients requiring constant monitoring. However, the design and operation of such systems with Body Area Sensor Networks (BASNs) is challenging in twofold. First, limited energy, computational and storage resources of the sensor nodes. Second, the need to guarantee application level Quality of Service (QoS). In this paper, we integrate wireless network components, and application-layer characteristics to provide sustainable, energy efficient and high-quality services for m-health systems. In particular, we propose an Energy-Cost-Distortion solution, which exploits the benefits of in-network processing and medical data adaptation to optimize the transmission energy consumption and the cost of using network services. Moreover, we present a distributed cross-layer solution, which is suitable for heterogeneous wireless m-health systems with variable network size. Our scheme leverages Lagrangian duality theory to find efficient trade-off among energy consumption, network cost, and vital signs distortion, for delay sensitive transmission of medical data. Simulation results show that the proposed scheme achieves the optimal trade-off between energy efficiency and QoS requirements, while providing 15% savings in the objective function (i.e., energy-cost-distortion utility function), compared to solutions based on equal bandwidth allocation.

关键词： Convex optimization Decomposition distributed algorithm EEG signals Cross-layer design M-health system

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An Asymmetric distributed Method for Sorting a Robot Swarm

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IEEE ROBOTICS AND AUTOMATION LETTERS 2017年第1期2卷 261-268页

作者： Zhou, Yu Goldman, Ron McLurkin, James Rice Univ Dept Comp Sci Houston TX 77005 USA

We consider the problem of sorting a swarm of labeled robots in Euclidean space. Our goal is to organize the robots into a sorted and equally-spaced straight line between the robots with lowest and highest labels, while maintaining a connected communication network. We break the symmetry between the minimum and maximum, in order to keep time, travel distance, and communication costs low, without using central control. We run in parallel a set of functions, including leader election, tree formation, path formation, path modification, and geometric straightening. We show that our algorithm is safe, correct, efficient, and robust to changes in population and connectivity. We validate our theoretical results with simulations. Our implementation uses messages of fixed size and robots of constant memory, and is a practical solution for large populations of low-cost robots.

关键词： distributed robot systems distributed algorithm path planning for multiple mobile robots or agents physical sorting swarms

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distributed Medium Access Control Protocol for Successive Interference Cancellation-Based Wireless Ad Hoc Networks

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IEEE COMMUNICATIONS LETTERS 2017年第2期21卷 354-357页

作者： Kontik, Mehmet Ergen, Sinem Coleri Koc Univ Dept Elect & Elect Engn TR-34450 Istanbul Turkey

Successive interference cancellation (SIC) enables the successful reception of multiple concurrent transmissions and elimination of interference through successive decoding. However, previously proposed distributed medium access control protocols have not exploited SIC. They mostly focused on either interference avoidance, based on the assumption that a receiver can only decode one transmission at a time, or self-interference cancellation, where a node can be a receiver and a transmitter at the same time. In this letter, we propose the first distributed communication protocol for SIC-based wireless networks, based on a novel message exchange and decision mechanism, to enable the simultaneous transmission of multiple neighboring nodes around the transmitter and receiver. The message exchange allows a random subset of neighboring nodes to test the feasibility of their simultaneous transmission. The decision mechanism evaluates the successive decoding capability of SIC receivers with the additional activation of neighboring nodes. We demonstrate the throughput improvement of the proposed algorithm via extensive simulations.

关键词： Wireless ad hoc networks successive interference cancellation distributed algorithm medium access control protocol

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Robust Real-Time distributed Optimal Control Based Energy Management in a Smart Grid

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IEEE TRANSACTIONS ON SMART GRID 2017年第4期8卷 1568-1579页

作者： Xu, Yinliang Yang, Zaiyue Gu, Wei Li, Ming Deng, Zicong Sun Yat Sen Univ Sun Yat Sen Univ Carnegie Mellon Univ SYSU CMU Jo Guangzhou 510275 Guangdong Peoples R China SYSU CMU Shunde Int Joint Res Inst Shunde 528300 Peoples R China Zhejiang Univ Dept Control Sci & Engn State Key Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China Southeast Univ Sch Elect Engn Nanjing 210096 Jiangsu Peoples R China

With the integration of distributed generations and controllable loads, the power grid becomes geographically distributed with a time-varying topology. The operation conditions may change rapidly and frequently;thus, management and control of the smart grid pose great challenges on traditional centralized control strategies. This paper proposes a distributed algorithm for energy management in a power grid, while dynamically minimizing the adjustment costs. The objective function is designed to optimize the overall social welfare considering generation suppliers and load users simultaneously. The proposed algorithm integrates consensus algorithm and optimal control algorithm, which requires only information exchanging among neighboring units and enables the sharing of computational and communication burden among distributed local controllers. It is robust to communication failures and adaptive to topology changes. Simulation results of the IEEE 9-bus, 39-bus systems, and a 200-unit system demonstrate the effectiveness of the proposed algorithm and indicate the promising applications to practical power systems.

关键词： distributed algorithm optimal control energy management consensus algorithm smart grid

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distributed User Association with Resource Partitioning in Heterogeneous Cellular Networks

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WIRELESS PERSONAL COMMUNICATIONS 2017年第4期95卷 4131-4148页

作者： Zhou, Tian-Qing Huang, Yong-Ming Sun, Yuan Yang, Lu-Xi East China Jiaotong Univ Sch Informat Engn Nanchang 330013 Jiangxi Peoples R China Southeast Univ Sch Informat Sci & Engn Nanjing 210009 Jiangsu Peoples R China

To fully utilize the resources of heterogeneous cellular networks (HCNs), an effective approach that offloads users to the underloaded small cells from overloaded macrocells is widely advocated. However, this operation often leads to a bad result that the offloaded users achieve lower signal-to-interference-plus-noise-ratio (SINR) than these users in macrocells. Thus, some appropriate interference avoidance techniques should be adopted to partially alleviate the SINR degradation. For this, we consider the resource (frequency) partitioning that turns off some fraction of such resources in a macrocell. Naturally, an optimal offloading strategy should be closely coupled with resource partitioning, and in turn the optimal partition decides the offloading performance. In this paper, we propose a distributed association strategy with joint offloading and resource partitioning for HCNs. We reveal that load balancing, by itself, is insufficient, and additional resource partitioning is required to improve system performance. Meanwhile, we also show that, compared with the best power association and range extension association, the proposed scheme provides better association performance.

关键词： Heterogeneous cellular networks Load balancing User association distributed algorithm

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Parallel and distributed Resource Allocation With Minimum Traffic Disruption for Network Virtualization

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IEEE TRANSACTIONS ON COMMUNICATIONS 2017年第3期65卷 1162-1175页

作者： Hung Khanh Nguyen Zhang, Yanru Chang, Zheng Han, Zhu Univ Houston Dept Elect & Comp Engn Houston TX 77004 USA Univ Jyvaskyla Dept Math Informat Technol FIN-40014 Jyvaskyla Finland

Wireless network virtualization has been advocated as one of the most promising technologies to provide multifarious services and applications for the future Internet by enabling multiple isolated virtual wireless networks to coexist and share the same physical wireless resources. Based on the multiple concurrent virtual wireless networks running on the shared physical substrate, service providers can independently manage and deploy different end-users services. This paper proposes a new formulation for bandwidth allocation and routing problem for multiple virtual wireless networks that operate on top of a single substrate network to minimize the operation cost of the substrate network. We also propose a preventive traffic disruption model for virtual wireless networks to minimize the amount of traffic that service providers have to reduce when substrate links fail by incorporating l(1)-norm into the objective function. Due to the large number of constraints in both normal state and link failure states, the formulated problem becomes a large-scale optimization problem and is very challenging to solve using the centralized computational method. Therefore, we propose the decomposition algorithms using the alternating direction method of multipliers that can be implemented in a parallel and distributed fashion. The simulation results demonstrate the computational efficiency of our proposed algorithms as well as the advantage of the formulated model in ensuring the minimal amount of traffic disruption when substrate links fail.

关键词： Wireless network virtualization resource allocation routing ADMM distributed algorithm preventive traffic disruption

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distributed Estimation of All the Eigenvalues and Eigenvectors of Matrices Associated With Strongly Connected Digraphs

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IEEE CONTROL SYSTEMS LETTERS 2017年第2期1卷 328-333页

作者： Gusrialdi, Azwirman Qu, Zhihua Univ Cent Florida Dept Elect & Comp Engn Orlando FL 32816 USA

This letter considers the problem of estimating all the eigenvalues and eigenvectors of an irreducible matrix, corresponding to a strongly connected digraph, in the absence of knowledge on the global network topology. To this end, we propose a unified distributed strategy performed by each node in the network and relies only on the local information. The key idea is to transform the nonlinear problem of computing both the eigenvalues and eigenvectors of an irreducible matrix into a linear one. Specifically, we first transform distributively the irreducible matrix into a nonsingular irreducible matrix. Each node in the network then estimates in a distributed fashion the inverse of the nonsingular matrix by solving a set of linear equations based on a consensus-type algorithm. The eigenvalues and the corresponding eigenvectors are finally computed by exploiting the relations between the eigenvalues and eigenvectors of both the inverse and the original irreducible matrices. A numerical example is provided to demonstrate the effectiveness of the proposed distributed strategy.

关键词： Estimation distributed algorithm irreducible matrix network analysis and control

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