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Area Convergence of Monoculus Robots With Additional Capabilities

COMPUTER JOURNAL 2022年第5期65卷 1306-1319页

作者： Pattanayak, Debasish Mondal, Kaushik Mandal, Partha Sarathi Schmid, Stefan Indian Inst Technol Dept Math Gauhati 781039 India Indian Inst Technol Dept Math Ropar 140001 India Univ Vienna Fac Comp Sci A-1090 Vienna Austria

This paper considers the area convergence problem, which requires a group of robots to gather in a small area not defined a priori. While it is known that robots can gather at a point if they can precisely measure distances, we, in this paper, show that without any agreement on the coordinate system, it is impossible for robots to converge to an area if they cannot measure distances or angles. We denote these robots without the ability to measure distances or angles as monoculus robots. We present a counterexample showing that monoculus robots fail in area convergence even with the capability of measuring angles. However, monoculus robots with a weak notion of distance or minimal agreement on the coordinate system are sufficient to achieve area convergence. In particular, we present area convergence algorithms in asynchronous model for such monoculus robots with one of the two following simple additional capabilities: (1) locality detection (LD), a notion of distance or (2) orthogonal line agreement (OLA), a notion of direction. We discuss extensions corresponding to multiple dimensions and the termination. Additionally, we validate our findings using simulation and show the robustness of our algorithms in the presence of errors in observation or movement.

关键词： area convergence monoculus robots oblivious mobile robots asynchronous distributed algorithm

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distributed Broadcasting in Dynamic Networks

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IEEE-ACM TRANSACTIONS ON NETWORKING 2021年第5期29卷 2142-2155页

作者： Yu, Dongxiao Zou, Yifei Yu, Jiguo Wu, Yu Lv, Weifeng Cheng, Xiuzhen Dressler, Falko Lau, Francis C. M. Shandong Univ Sch Comp Sci & Technol Inst Intelligent Comp Qingdao 266510 Peoples R China Qilu Univ Technol Sch Comp Sci & Technol Shandong Acad Sci Jinan 250014 Peoples R China Natl Supercomp Ctr Jinan Shandong Comp Sci Ctr Jinan 250014 Peoples R China Natl Super Comp Ctr Jinan Shandong Comp Sci Ctr Dongguan 523808 Peoples R China Beihang Univ Sch Comp Sci & Engn Beijing 100191 Peoples R China TU Berlin Sch Elect Engn & Comp Sci D-10587 Berlin Germany Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China

In this paper, we investigate distributed broadcasting in dynamic networks, where the topology changes continually over time. We propose a network model that captures the dynamicity caused by both churn and mobility of nodes. In contrast to existing work on dynamic networks, our model defines the dynamicity in terms of localized topological changes in the vicinity of each node, rather than a global view of the whole network. Obviously, a local dynamic model suits distributed algorithms better than a global one. The proposed dynamic model uses the more realistic SINR model to depict wireless interference, instead of oversimplified graph-based models adopted in most existing work. We consider the fundamental communication primitive of global broadcast, which is to disseminate a message from a source node to the whole network. Specifically, we present a randomized distributed algorithm that can accomplish dynamic broadcasting in an asymptotically optimal running time of O(D-T) with a high probability guarantee, under the assumption of reasonably constant dynamicity rate, where D-T is the dynamic diameter, a parameter proposed to depict the complexity of dynamic broadcasting. We believe our local dynamic model can greatly facilitate distributed algorithm studies in mobile and dynamic wireless networks.

关键词： Heuristic algorithms Interference Signal to noise ratio distributed algorithms Broadcasting Network topology Computational modeling Dynamic network SINR model distributed algorithm global broadcast

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A Queueing Network-Based distributed Laplacian Solver

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algorithmICA 2021年第9期83卷 2859-2894页

作者： Gillani, Iqra Altaf Bagchi, Amitabha IIT Delhi Dept Comp Sci & Engn New Delhi 110016 India

We use queueing networks to present a new approach to solving Laplacian systems. This marks a significant departure from the existing techniques, mostly based on graph-theoretic constructions and sampling. Our distributed solver works for a large and important class of Laplacian systems that we call "one-sink" Laplacian systems. Specifically, our solver can produce solutions for systems of the form Lx = b where exactly one of the coordinates of b is negative. Our solver is a distributed algorithm that takes (O) over tilde (t(hit) (d) over cap (max)) time (where (O) over tilde hides poly log n factors) to produce an approximate solution where t(hit) is the worst-case hitting time of the random walk on the graph, which is Theta(n) for a large set of important graphs, and (d) over cap (max) is the maximum degree of the graph. The class of one-sink Laplacians includes the important voltage computation problem and allows us to compute the effective resistance between nodes in a distributed setting. As a result, our Laplacian solver can be used to adapt the approach by Kelner and Madry (2009) to give the first distributed algorithm to compute approximate random spanning trees efficiently.

关键词： Laplacian solver distributed algorithm Queueing networks Random walks Random spanning trees

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Population-distributed stochastic optimization for distillation processes: Implementation and distribution strategy

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CHEMICAL ENGINEERING RESEARCH & DESIGN 2021年 168卷 357-368页

作者： Lyu, Hao Cui, Chengtian Zhang, Xiaodong Sun, Jinsheng Tianjin Univ Sch Chem Engn & Technol Tianjin 300072 Peoples R China Nanjing Tech Univ Inst Intelligent Mfg Nanjing 211816 Peoples R China

Stochastic optimization is inefficient, although it shows robustness against local optimum and can guarantee high-quality solutions. Parallel computation can be a promising way to improve the efficiency of stochastic optimization. However, the common environments do not support calling multiple simulators through the win32com interface, which hinders parallel computation. As a countermeasure, this study proposes a population-distributed differential evolution (DDE) framework, which combines multiple optimizers through the shared message passing medium. The framework distributes the population into groups (subpopulations) on different threads by a pool model, which can make full use of a multi core CPU and significantly accelerate the computation. Moreover, we considered both the synchronously and asynchronously distributed differential evolution. Three case studies (benzene/toluene/xylene conventional distillation, acetone/methanol/water extractive distillation, and heat pump assisted dividing-wall column separating benzene/toluene/xylene) are optimized to show the superior performance of the DDEs. The parallel framework can reduce the computing time by similar to 70% on a 4-core CPU, which is a significant improvement. DDEs cause some parallel efficiency loss, which is 5-10% and 10-20% for ADDE and SDDE, respectively. Further, based on time consumption analysis, we explain the reasons for the efficiency loss.\

关键词： Population-distributed stochastic& nbsp optimization Parallel distributed algorithm optimization Distillation process optimization Pool model

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On Heterogeneous Sensing Capability or distributed Rendezvous in Cognitive Radio Networks

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2021年第11期20卷 3211-3226页

作者： Gu, Zhaoquan Wang, Yuexuan Shen, Tong Lau, Francis C. M. Guangzhou Univ Cyberspace Inst Adv Technol CIAT Guangzhou 510405 Peoples R China Zhejiang Univ Coll Comp Sci Hangzhou 310027 Zhejiang Peoples R China Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China

Cognitive radio networks (CRNs) have been proposed to solve the spectrum scarcity problem. One of their fundamental procedures is to construct a communication link on a common channel for the users, which is referred to as rendezvous. In reality, the capability to sense the spectrum may vary from user to user. We study distributed rendezvous for heterogeneous sensing capabilities in this paper. The licensed spectrum is divided into ,t channels, U = {1, 2, ..., n}. We denote the sensing capability of user i as C-i subset of U and the set of available channels (i.e., the channels not occupied by paying users) as V-i subset of C-i. Due to hardware differences, the users may have different sensing capabilities: C-i not equal Cj, and this is called heterogeneous sensing capability. In this paper, we propose efficient algorithms for two scenarios: the fully available scenario where V-i = C-i and the partially available scenario where V-i subset of C-i. Our idea is to utilize two 'pointers' to traverse the sensing capability set, which sets our algorithms apart from the extant rendezvous algorithms. Considering any two neighboring users a, b, we propose the Traversing Pointer (TP) algorithm that guarantees rendezvous in O(max{vertical bar C-a vertical bar, vertical bar C-b vertical bar}log log n) time slots for the fully available scenario. This result is only O(log log n) larger than the theoretical lower bound. Moreover, it removes an O(min{vertical bar C-a vertical bar, vertical bar C-b vertical bar}) factor when compared to the state-of-the-art result (O(vertical bar C-a vertical bar vertical bar C-b vertical bar) in S.-H. Wu et a/. For the partially available scenario, we propose the Moving Traversing Pointers (MTP) and Prime based Moving Traversing Pointers {P-MTP) algorithms that can guarantee rendezvous within O((max{ vertical bar V-a vertical bar, vertical bar V-b vertical bar}(2)log log n) and O(O(vertical bar V-a vertical bar vertical bar V-b vertical bar log lo

关键词： Cognitive radio network rendezvous heterogeneous sensing capability distributed algorithm

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Sparse Backbone and Optimal distributed SINR algorithms

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ACM TRANSACTIONS ON algorithmS 2021年第2期17卷 1–34页

作者： Halldorsson, Magnus M. Tonoyan, Tigran Reykjavik Univ Dept Comp Sci ICE TCS Menntavegur 1 IS-102 Reykjavik Iceland Technion Dept Comp Sci IL-320000 Haifa Israel

We develop randomized distributed algorithms for many of the most fundamental communication problems in wireless networks under the Signal to Interference and Noise Ratio (SINR) model of communication, including (multi-message) broadcast, local broadcast, coloring, Maximal Independent Set, and aggregation. The complexity of our algorithms is optimal up to polylogarithmic preprocessing time. It shows-contrary to expectation-that the plain vanilla SINR model is just as powerful and fast (modulo the preprocessing) as various extensions studied, including power control, carrier sense, collision detection, free acknowledgements, and geolocation knowledge. Central to these results is an efficient construction of a constant-density backbone structure over the network, which is of independent interest. This is achieved using an indirect sensing technique, where message non-reception is used to deduce information about relative node-distances.

关键词： Wireless network distributed algorithm plain SINR

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Multi-Criterion Partial Clustering algorithm for Wireless Sensor Networks

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IEEE ACCESS 2022年 10卷 108366-108373页

作者： Neamatollahi, Peyman Hakim Sabzevari Univ Fac Comp & Elect Engn Comp Engn Dept Sabzevar *** Iran

Cluster architectures are an effective approach for organizing sensor networks to balance the load and prolong network life. To cluster wireless sensor networks, this paper proposes an energy-efficient distributed algorithm. This algorithm uses two techniques (partial clustering and multi-criterion cluster formation) for efficient use of the sensor nodes' energy. When a header expends a certain amount of power, it only notifies the nodes in its cluster that new clustering is required in the next round. Therefore, in contrast to previous studies that performed complete clustering, clustering in the present work is performed partially, which considerably reduces the clustering overhead. In addition, a multi-criterion score is calculated for each node. In this algorithm, a node with the highest remaining energy and score is a more suitable candidate to be selected as the head of the cluster. In addition, a regular node becomes the member of the cluster with the highest score in its vicinity. The experiments reveal the superiority of the proposed algorithm over other simulated algorithms in terms of energy savings and network lifetime.

关键词： Clustering algorithms Wireless sensor networks Heuristic algorithms Time division multiple access Steady-state Energy efficiency Spread spectrum communication distributed processing Wireless sensor networks Load management Sensor networks clustering network lifetime energy efficiency distributed algorithm

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Invex Relaxation Based Cooperative Localization Using RSS Measurements

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IEEE TRANSACTIONS ON COMMUNICATIONS 2022年第8期70卷 5482-5497页

作者： Mukhopadhyay, Bodhibrata Srirangarajan, Seshan Kar, Subrat Indian Inst Technol Delhi IIT Delhi Dept Elect Engn New Delhi 110016 India King Abdullah Univ Sci & Technol KAUST Comp Elect & Math Sci & Engn Ctr CEMSE Thuwal 239556900 Saudi Arabia Indian Inst Technol Delhi IIT Delhi Bharti Sch Telecommun Technol & Management New Delhi 110016 India

Received signal strength (RSS)-based localization techniques have attracted a lot of interest as they are easy to implement and do not require any localization-specific hardware. However, maximum likelihood (ML) formulation of RSS-based localization problem is non-convex, non-linear, and discontinuous, and cannot be solved using standard optimization techniques. We propose techniques that converts the ML objective function into an invex (invariant convex) function and solve them using gradient descent. We also employ coordinate descent to solve the invex problem in a completely distributed manner without any synchronization requirements. The coordinate descent-based technique can be implemented on the sensor nodes as it has low computational complexity and scales very well to large networks. We prove the convergence theoretically, derive the convergence rate, and provide a detailed computational complexity and communication overhead analysis of the techniques. We perform extensive performance analysis and compare our techniques with centralized and distributed localization methods, and demonstrate the superior performance of the proposed techniques in terms of convergence rate, localization accuracy, and execution time.

关键词： Location awareness Maximum likelihood estimation Convergence Wireless sensor networks Standards Transforms Optimization Cooperative localization maximum likelihood non-linear programming invex relaxation distributed algorithm

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Reward fairness-based optimal distributed real-time pricing to enable supply-demand matching

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NEUROCOMPUTING 2021年 427卷 1-12页

作者： Wang, L. L. Chen, J. J. Peng, K. Zhao, Y. L. Zhang, X. H. Shandong Univ Technol Sch Elect & Elect Engn Zibo 255049 Peoples R China

Real-time pricing (RTP) is the pivotal component of demand response (DR) that promotes the power utilization of users in a cost-efficient way. This paper presents a reward fairness-based distributed RTP (RFbDRTP) framework for electric users to reduce the electricity consumption cost as well as experience the fairness from participating in DR. In RFbDRTP, a behavior welfare model (BWM) is developed to exploit the reward fairness strategy that returns the cost savings as a reward to the users in proportion to their load increase or decrease in DR. The model can motivate users to react to the price signal through adjusting their electricity consumption patterns, to in turn enable optimal distributed RTP for matching supply-demand. In this paper, users are assumed to interact with each other because of pricing based on the imbalance between load demand and electricity supply. We formulate the interactions among the users into a noncooperative game and give a sufficient condition to ensure the unique equilibrium in the game. After that, we develop a distributed algorithm and give a sufficient convergence condition of the algorithm. The simulation results show that the proposed RFbDRTP is effective in motivating users to participate in DR and matching demand with supply, and the distributed algorithm can converge to the equilibrium with a significant convergence rate. (c) 2020 Elsevier B.V. All rights reserved.

关键词： Demand response distributed algorithm Noncooperative game distributed real-time pricing Reward fairness

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A Fast distributed Solver for Linear Systems Under Generalized Diagonal Dominance

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2021年第5期66卷 2423-2429页

作者： Zhang, Zhaorong Cai, Qianqian Fu, Minyue Univ Newcastle Sch Elect Engn & Comp Univ Dr Callaghan NSW 2308 Australia Guangdong Univ Technol Sch Automat Guangdong Key Lab ioT Informat Technol Guangzhou 510006 Peoples R China

This article proposes a new distributed algorithm for solving linear systems associated with a sparse graph under a generalized diagonal dominance assumption. The algorithm runs iteratively on each node of the graph, with low complexities on local information exchange between neighboring nodes, local computation, and local storage. For an acyclic graph under the condition of diagonal dominance, the algorithm is shown to converge to the correct solution in a finite number of iterations, equaling the graph diameter. For a loopy graph, the algorithm is shown to converge to the correct solution asymptotically. Simulations verify that the proposed algorithm significantly outperforms the classical Jacobi method and an orthogonal projection-based method.

关键词： Linear systems distributed algorithms Jacobian matrices Information exchange Nickel Complexity theory Iterative methods distributed algorithm distributed estimation distributed optimization linear systems

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