The Experts below are selected from a list of 2036931 Experts worldwide ranked by ideXlab platform
Milind M Buddhikot - One of the best experts on this subject based on the ideXlab platform.
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sas assisted coexistence aware dynamic channel assignment in cbrs band
IEEE Transactions on Wireless Communications, 2018Co-Authors: Xuhang Ying, Milind M BuddhikotAbstract:The paradigm of shared spectrum allows secondary devices to opportunistically access spectrum bands underutilized by primary owners. Recently, the FCC has targeted the sharing of the 3.5 GHz (3550–3700 MHz) federal spectrum with commercial systems such as small cells. The rules require a spectrum access system (SAS) to accommodate three service tiers: 1) incumbent access; 2) priority access (PA); and 3) generalized authorized access (GAA). In this paper, we study the SAS-assisted dynamic channel assignment (CA) for PA and GAA tiers. We introduce the node-channel-pair conflict graph to capture pairwise interference, channel and geographic contiguity constraints, spatially varying channel availability, and coexistence awareness. The proposed graph representation allows us to formulate PA CA and GAA CA with binary conflicts as max-cardinality and max-reward CA, respectively. Approximate solutions can be found by a Heuristic-Based Algorithm that searches for the maximum weighted independent set. We further formulate GAA CA with non-binary conflicts as max-utility CA. We show that the utility function is submodular, and the problem is an instance of matroid-constrained submodular maximization. A local-search-based polynomial-time Algorithm is proposed which provides a provable performance guarantee. Extensive simulations using a real-world Wi-Fi hotspot location data set are performed to evaluate the proposed Algorithms. Our results have demonstrated the advantages of the proposed graph representation and improved performance of the proposed Algorithms over the baseline Algorithms.
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sas assisted coexistence aware dynamic channel assignment in cbrs band
arXiv: Networking and Internet Architecture, 2018Co-Authors: Xuhang Ying, Milind M BuddhikotAbstract:The paradigm of shared spectrum allows secondary devices to opportunistically access spectrum bands underutilized by primary owners. Recently, the FCC has targeted the sharing of the 3.5 GHz (3550-3700 MHz) federal spectrum with commercial systems such as small cells. The rules require a Spectrum Access System (SAS) to accommodate three service tiers: 1) Incumbent Access, 2) Priority Access (PA), and 3) Generalized Authorized Access (GAA). In this work, we study the SAS-assisted dynamic channel assignment (CA) for PA and GAA tiers.We introduce the node-channel-pair conflict graph to capture pairwise interference, channel and geographic contiguity constraints, spatially varying channel availability, and coexistence awareness. The proposed conflict graph allows us to formulate PA CA and GAA CA with binary conflicts as max-cardinality and max-reward CA, respectively. Approximate solutions can be found by a Heuristic-Based Algorithm that search for the maximum weighted independent set. We further formulate GAA CA with non-binary conflicts as max-utility CA. We show that the utility function is submodular, and the problem is an instance of matroid-constrained submodular maximization. A polynomial-time Algorithm based on local search is proposed that provides a provable performance guarantee. Extensive simulations using a real-world Wi-Fi hotspot location dataset are conducted to evaluate the proposed Algorithms. Our results have demonstrated the advantages of the proposed graph representation and improved performance of the proposed Algorithms over the baseline Algorithms.
Xuhang Ying - One of the best experts on this subject based on the ideXlab platform.
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sas assisted coexistence aware dynamic channel assignment in cbrs band
IEEE Transactions on Wireless Communications, 2018Co-Authors: Xuhang Ying, Milind M BuddhikotAbstract:The paradigm of shared spectrum allows secondary devices to opportunistically access spectrum bands underutilized by primary owners. Recently, the FCC has targeted the sharing of the 3.5 GHz (3550–3700 MHz) federal spectrum with commercial systems such as small cells. The rules require a spectrum access system (SAS) to accommodate three service tiers: 1) incumbent access; 2) priority access (PA); and 3) generalized authorized access (GAA). In this paper, we study the SAS-assisted dynamic channel assignment (CA) for PA and GAA tiers. We introduce the node-channel-pair conflict graph to capture pairwise interference, channel and geographic contiguity constraints, spatially varying channel availability, and coexistence awareness. The proposed graph representation allows us to formulate PA CA and GAA CA with binary conflicts as max-cardinality and max-reward CA, respectively. Approximate solutions can be found by a Heuristic-Based Algorithm that searches for the maximum weighted independent set. We further formulate GAA CA with non-binary conflicts as max-utility CA. We show that the utility function is submodular, and the problem is an instance of matroid-constrained submodular maximization. A local-search-based polynomial-time Algorithm is proposed which provides a provable performance guarantee. Extensive simulations using a real-world Wi-Fi hotspot location data set are performed to evaluate the proposed Algorithms. Our results have demonstrated the advantages of the proposed graph representation and improved performance of the proposed Algorithms over the baseline Algorithms.
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sas assisted coexistence aware dynamic channel assignment in cbrs band
arXiv: Networking and Internet Architecture, 2018Co-Authors: Xuhang Ying, Milind M BuddhikotAbstract:The paradigm of shared spectrum allows secondary devices to opportunistically access spectrum bands underutilized by primary owners. Recently, the FCC has targeted the sharing of the 3.5 GHz (3550-3700 MHz) federal spectrum with commercial systems such as small cells. The rules require a Spectrum Access System (SAS) to accommodate three service tiers: 1) Incumbent Access, 2) Priority Access (PA), and 3) Generalized Authorized Access (GAA). In this work, we study the SAS-assisted dynamic channel assignment (CA) for PA and GAA tiers.We introduce the node-channel-pair conflict graph to capture pairwise interference, channel and geographic contiguity constraints, spatially varying channel availability, and coexistence awareness. The proposed conflict graph allows us to formulate PA CA and GAA CA with binary conflicts as max-cardinality and max-reward CA, respectively. Approximate solutions can be found by a Heuristic-Based Algorithm that search for the maximum weighted independent set. We further formulate GAA CA with non-binary conflicts as max-utility CA. We show that the utility function is submodular, and the problem is an instance of matroid-constrained submodular maximization. A polynomial-time Algorithm based on local search is proposed that provides a provable performance guarantee. Extensive simulations using a real-world Wi-Fi hotspot location dataset are conducted to evaluate the proposed Algorithms. Our results have demonstrated the advantages of the proposed graph representation and improved performance of the proposed Algorithms over the baseline Algorithms.
Shengchun Deng - One of the best experts on this subject based on the ideXlab platform.
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a fast greedy Algorithm for outlier mining
Lecture Notes in Computer Science, 2006Co-Authors: Shengchun Deng, Joshua Zhexue HuangAbstract:The task of outlier detection is to find small groups of data objects that are exceptional when compared with rest large amount of data. Recently, the problem of outlier detection in categorical data is defined as an optimization problem and a local-search heuristic based Algorithm (LSA) is presented. However, as is the case with most iterative type Algorithms, the LSA Algorithm is still very time-consuming on very large datasets. In this paper, we present a very fast greedy Algorithm for mining outliers under the same optimization model. Experimental results on real datasets and large synthetic datasets show that: (1) Our new Algorithm has comparable performance with respect to those state-of-the-art outlier detection Algorithms on identifying true outliers and (2) Our Algorithm can be an order of magnitude faster than LSA Algorithm.
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an optimization model for outlier detection in categorical data
International Conference on Intelligent Computing, 2005Co-Authors: Shengchun DengAbstract:In this paper, we formally define the problem of outlier detection in categorical data as an optimization problem from a global viewpoint. Moreover, we present a local-search heuristic based Algorithm for efficiently finding feasible solutions. Experimental results on real datasets and large synthetic datasets demonstrate the superiority of our model and Algorithm.
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an optimization model for outlier detection in categorical data
arXiv: Databases, 2005Co-Authors: Shengchun DengAbstract:The task of outlier detection is to find small groups of data objects that are exceptional when compared with rest large amount of data. Detection of such outliers is important for many applications such as fraud detection and customer migration. Most existing methods are designed for numeric data. They will encounter problems with real-life applications that contain categorical data. In this paper, we formally define the problem of outlier detection in categorical data as an optimization problem from a global viewpoint. Moreover, we present a local-search heuristic based Algorithm for efficiently finding feasible solutions. Experimental results on real datasets and large synthetic datasets demonstrate the superiority of our model and Algorithm.
Katia Sycara - One of the best experts on this subject based on the ideXlab platform.
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heuristic based multiple mobile depots route planning for recharging persistent surveillance robots
Intelligent Robots and Systems, 2019Co-Authors: Yifan Ding, Wenhao Luo, Katia SycaraAbstract:Persistent surveillance of a target space using multiple unmanned aerial vehicles (UAVs) has multiple applications such as geographical surveys, air quality monitoring, and security monitoring. The limited onboard battery capacity challenges the continuous operation in these applications of persistent robots. We consider the problem for recharging persistent robots using mobile depots. The mobile depots collectively compute a set of tours to recharge all persistent robots with the minimum total cost. Compared to other works, the persistent UAVs are not required to detour to a static depot for energy replenishment such as recharging or battery swapping. We formulate this problem as a Generalized Multiple Depots Travelling Salesman Problem (GMDTSP) on a complete graph. A Heuristic-Based Algorithm Multiple Depots Random Select (RSMD) is proposed to solve the recharging problem efficiently. The RSMD has proved to have an analytical constant upper bound in the worst-case scenario. We also propose a post-processing heuristic (RSMD-IM) to improve the solution quality further. We demonstrate the efficiency and effectiveness of our Algorithm via benchmark on multiple instances from TSPLIB and GTSPLIB. The simulation results show that RSMD and RSMD-IM will perform significantly faster than the state of the art heuristic solver LKH with a loss of about 10% of solution quality.
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decentralized multiple mobile depots route planning for replenishing persistent surveillance robots
2019 International Symposium on Multi-Robot and Multi-Agent Systems (MRS), 2019Co-Authors: Yifan Ding, Wenhao Luo, Katia SycaraAbstract:Ahstract- Persistent surveillance of a target space using multiple robots has numerous applications. The continuous operation in these applications is challenged by limited onboard battery capacity of the persistent robots. We consider the problem for replenishing persistent robots using mobile depots, where mobile depots collectively compute a set of tours to drop off batteries for replenishing all persistent robots with the minimum total cost. Compared to other works, persistent robots are not required to detour for recharging or battery swapping. We formulate this problem as generalized multiple depots traveling salesman problem (GMDTSP) on a complete graph. An efficient centralized Heuristic-Based Algorithm Multiple Depots Random Select (MDRS) is proposed, which has been proved to have an analytical constant upper bound in the worst case scenario. To provide scalability and robustness, a fully decentralized asynchronous MDRS (dec-MDRS) is proposed, with the analysis of its correctness and efficiency. We also propose a post-processing heuristic (MDRS-IM) to improve the solution quality. We demonstrate the efficiency and effectiveness of our Algorithm via benchmark on multiple instances from TSPLIB and GTSPLIB. The simulation results show that the complexity of dec-MDRS grows linearly as the number of robots increases. The simulation also shows that MDRS and MDRS-IM perform significantly faster than the state of the art heuristic solver LKH with only a loss of about 10% of solution quality.
Luciano Paschoal Gaspary - One of the best experts on this subject based on the ideXlab platform.
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a heuristic based Algorithm for privacy oriented virtual network embedding
Network Operations and Management Symposium, 2014Co-Authors: Leonardo Richter Bays, Rodrigo Ruas Oliveira, Luciana S Buriol, Marinho P Barcellos, Luciano Paschoal GasparyAbstract:Network virtualization has become increasingly popular in recent years. It has the potential to allow timely handling of network infrastructure requests and, after instantiated, their lifecycle. In addition, it enables improved physical resource utilization. However, the use of network virtualization in large-scale, real environments depends on the ability to adequately map virtual routers and links to physical resources, as well as to protect virtual networks against security threats. With respect to security, confidentiality and privacy mechanisms have become essential in light of recent discoveries related to pervasive electronic surveillance. In this paper we propose a heuristic method for virtual network embedding with security support. The method features precise modeling of overhead costs of security mechanisms and handles incoming requests in an online manner. Additionally, we present a detailed performance comparison between the proposed heuristic and an optimization model based on the same problem. The obtained results demonstrate that the heuristic method is able to find feasible mappings in the order of seconds even when dealing with large network infrastructures, while the optimization model is limited to smaller networks.