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1. TransKV: A Networking Support for Transaction Processing in Distributed Key-value Stores

   https://doi.org/10.1109/BigDataService52369.2021.00011  

   Eldakiky, Hebatalla; Du, David Hung-Chang (August 2021, IEEE International Conference on Big Data Computing Service and Applications (BigDataService))

   IEEE (Ed.)

   Through the massive use of mobile devices, data clouds, and the rise of Internet of Things, enormous amount of data has been generated and analyzed for the benefit of society. NoSQL Databases and specially key-value stores be­ come the backbone in managing these large amounts of data. Most of key-value stores ignore transactions due to their ef­fect on degrading key-value store's performance. Meanwhile, programmable switches with the software-defined networks and the Programming Protocol-Independent Packet Processor (P4) lead to a programmable network where in-network computa­ tion can help accelerating the performance of applications. In this paper, we proposed a networking support for transaction processing in distributed key-value stores. Our system leverages the programmable switch to act as a transaction coordinator. Using a variation of the time stamp ordering concurrency control approach, the programmable switch can decide to proceed in transaction processing or abort the transaction directly from the network. Our experimental results on an initial prototype show that our proposed approach, while supporting transactions, improves the throughput by up to 4X and reduces the latency by 35% when compared to the existing architectures. 

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2. The glassy solid as a statistical ensemble of crystalline microstates

   https://doi.org/10.1038/s41524-020-0329-2  

   Jones, Eric B.; Stevanović, Vladan (May 2020, npj Computational Materials)

   Abstract We present an alternative and, for the purpose of non-crystalline materials design, a more suitable description of covalent and ionic glassy solids as statistical ensembles of crystalline local minima on the potential energy surface. Motivated by the concept of partially broken ergodicity, we analytically formulate the set of approximations under which the structural features of ergodic systems such as the radial distribution function (RDF) and powder X-ray diffraction (XRD) intensity can be rigorously expressed as statistical ensemble averages over different local minima. Validation is carried out by evaluating these ensemble averages for elemental Si and SiO₂over the local minima obtained through the first-principles random structure sampling that we performed using relatively small simulation cells, thereby restricting the sampling to a set of predominantly crystalline structures. The comparison with XRD and RDF from experiments (amorphous silicon) and molecular dynamics simulations (glassy SiO₂) shows excellent agreement, thus supporting the ensemble picture of glasses and opening the door to fully predictive description without the need for experimental inputs. 

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3. Edge computing framework for distributed smart applications

   https://doi.org/10.1109/UIC-ATC.2017.8397448  

   Liu, Kaikai; Gurudutt, Abhishek; Kamaal, Tejeshwar; Divakara, Chinmayi; Prabhakaran, Praveen (August 2017, The IEEE Smart World Congress 2017 (IEEE SWC 2017))

   The rapid growth in technology and wide use of internet has increased smart applications such as intelligent transportation control system, and Internet of Things, which heavily rely on an efficient and reliable connectivity network. To overcome high bandwidth work load on the network, as well as minimize latency for real-time applications, the computation can be moved from the central cloud to a distributed edge cloud. The edge computing benefits various smart applications that uses distributed network for data analytics and services. Different from the existing cloud management solutions, edge computing needs to move cloud management services towards distributed heterogeneous edge nodes for multi-tenant user applications. However, existing cloud management services do not offer remote deployment of multi-tenant user applications on the cloud of edge nodes. In this paper, we propose a practical edge cloud software framework for deploying multi-tenant distributed smart applications. Having multiple distributed end nodes, auto discovery of all active end nodes is required for deploying multi-tenant user applications. However, existing cloud solutions require either private network or fixed IP address, which is not achievable for the distributed edge nodes. Most of the edge nodes connected through the public internet without fixed IP, and some of them even connect through IEEE 802.15 based sensor networks. We propose to build a software platform to manage the distributed edge nodes as well as support services to deploy and launch isolated, multi-tenant user applications through a lightweight container. We propose an architectural solution to remotely access edge cloud management services through intermittent internet connections. We open sourced our whole set of software solutions, and analyzed the major performance metrics of the edge cloud platform. 

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4. Majorization Minimization Methods for Distributed Pose Graph Optimization with Convergence Guarantees

   https://doi.org/10.1109/IROS45743.2020.9341063  

   Fan, Taosha; Murphey, Todd (October 2020, International Conference on Intelligent Robots and Systems)

   null (Ed.)

   In this paper, we consider the problem of distributed pose graph optimization (PGO) that has extensive applications in multi-robot simultaneous localization and mapping (SLAM). We propose majorization minimization methods for distributed PGO and show that our proposed methods are guaranteed to converge to first-order critical points under mild conditions. Furthermore, since our proposed methods rely a proximal operator of distributed PGO, the convergence rate can be significantly accelerated with Nesterov’s method, and more importantly, the acceleration induces no compromise of theoretical guarantees. In addition, we also present accelerated majorization minimization methods for the distributed chordal initialization that have a quadratic convergence, which can be used to compute an initial guess for distributed PGO. The efficacy of this work is validated through applications on a number of 2D and 3D SLAM datasets and comparisons with existing state-of-the-art methods, which indicates that our proposed methods have faster convergence and result in better solutions to distributed PGO. 

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5. CyPhyHouse: A programming, simulation, and deployment toolchain for heterogeneous distributed coordination

   https://doi.org/10.1109/ICRA40945.2020.9196513  

   Ghosh, Ritwika; Jansch-Porto, Joao P.; Hsieh, Chiao; Gosse, Amelia; Jiang, Minghao; Taylor, Hebron; Du, Peter; Mitra, Sayan; Dullerud, Geir (May 2020, ICRA, 2020)

   Programming languages, libraries, and development tools have transformed the application development processes for mobile computing and machine learning. This paper introduces CyPhyHouse-a toolchain that aims to provide similar programming, debugging, and deployment benefits for distributed mobile robotic applications. Users can develop hardware-agnostic, distributed applications using the high-level, event driven Koord programming language, without requiring expertise in controller design or distributed network protocols. The modular, platform-independent middleware of CyPhyHouse implements these functionalities using standard algorithms for path planning (RRT), control (MPC), mutual exclusion, etc. A high-fidelity, scalable, multi-threaded simulator for Koord applications is developed to simulate the same application code for dozens of heterogeneous agents. The same compiled code can also be deployed on heterogeneous mobile platforms. The effectiveness of CyPhyHouse in improving the design cycles is explicitly illustrated in a robotic testbed through development, simulation, and deployment of a distributed task allocation application on in-house ground and aerial vehicles. 

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