In the wireless network of finite spectrum resource, some communication users probably do not allocate the spectrum so that their communication should be delayed. Thus it is necessary to arrange the communication time...
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ISBN:
(纸本)9781424408146;1424408156
In the wireless network of finite spectrum resource, some communication users probably do not allocate the spectrum so that their communication should be delayed. Thus it is necessary to arrange the communication time of the systems when we allocate the communication frequency. We construct a frequency-time spectrum model and propose a joint pre-allocation in a two-dimension space. Through the distributed games learning algorithm, each system could obtain its communication schedule, which makes the bandwidth utilization achieve a quite high level and arranges the global communication time as short as possible. The experiments show that our results have obvious superiorities in both bandwidth utilization and temporal performance relative to other allocation algorithms.
Polymorphic circuits are a special kind of digital logic components, which possess multiple build-in functions. In different environments, a polymorphic circuit would perform different functions. Evolutionary Algorith...
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The ultimate purpose of a pedestrian-detection system (PDS) is to reduce pedestrian-vehicle-related injury. Most such systems tend to adopt expensive sensors, such as infrared devices, in expectation of better perform...
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Modern Very Long Instruction (VLIW) DSP can improve performance by using instruction-level parallelism (ILP) and obtain better parallelism through instruction clustering. The essence of clustering is resource allocati...
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Neighbor discovery is an essential step for the self-organization of wireless sensor networks. Many algorithms have been proposed for efficient neighbor discovery. However, most of those algorithms need nodes to keep ...
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Neighbor discovery is an essential step for the self-organization of wireless sensor networks. Many algorithms have been proposed for efficient neighbor discovery. However, most of those algorithms need nodes to keep active during the process of neighbor discovery, which might be difficult for low-duty-cycle wireless sensor networks in many real deployments. In this paper, we investigate the problem of neighbor discovery in low-duty-cycle wireless sensor networks. We give an ALOHA-like algorithm and analyze the expected time to discover all n - 1 neighbors for each node. By reducing the analysis to the classical K Coupon Collector's Problem, we show that the upper bound is ne(log 2 n + (3 log 2 n - 1) log 2 log 2 n + c) with high probability, for some constant c, where e is the base of natural logarithm. Furthermore, not knowing number of neighbors leads to no more than a factor of two slowdown in the algorithm performance. Then, we validate our theoretical results by extensive simulations, and explore the performance of different algorithms in duty-cycle and non-duty-cycle networks. Finally, we apply our approach to analyze the scenario of unreliable links in low-duty-cycle wireless sensor networks.
Basic Linear Algebra Subroutines (BLAS) is a widely used basic mathematical library for high-performance computing. It has a great impact on the performance of supercomputers. This paper focuses on memory accessing op...
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With the popularity of cloud native and DevOps, container technology is widely used and combined with microservices. The deployment of container-based microservices in distributed cloud-edge infrastructure requires su...
With the popularity of cloud native and DevOps, container technology is widely used and combined with microservices. The deployment of container-based microservices in distributed cloud-edge infrastructure requires suitable strategies to ensure the quality of service for users. However, the existing container orchestration tools cannot flexibly select the best deployment location according to the user’s cost budget, and are insufficient in personalized deployment solutions. From the perspective of application providers, this paper considers the location distribution of users, application dependencies, and server price differences, and proposes a genetic algorithm-based Internet-of-Things (IoT) application deployment strategy for personalized cost budgets. The application deployment problem is defined as an optimization problem that minimizes user service latency under cost constraints. This problem is an NP-hard problem, and genetic algorithm is introduced to solve the optimization problem effectively and improve the deployment efficiency. The proposed algorithm is compared with four baseline algorithms, Time-Greedy, Cost-Greedy, Random and PSO, using real datasets and some synthetic datasets. The results show that the proposed algorithm outperforms other competing baseline algorithms.
This paper proposes an energy-efficient and collision-free medium access control protocol TDMA-WSN for wireless sensor networks. The protocol is based on time division multiple access (TDMA) principle and reduces ener...
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This paper proposes an energy-efficient and collision-free medium access control protocol TDMA-WSN for wireless sensor networks. The protocol is based on time division multiple access (TDMA) principle and reduces energy consumption by avoiding overhearing, collision and idle listening. Nodes in TDMA-WSN build schedules based on information about their neighborhood to determine when they can transmit to their neighbors and when they should listen to the channel or sleep. TDMA-WSN proposes a novel resolution with three-d-hop neighborhood information to avoid collision caused by the two-hop collision-free principle used in some protocols. TDMA-WSN can accelerate passing message by arranging schedule based on routing information from the upper-layer. The simulation results indicate that TDMA-WSN outperforms contention-based protocols (e.g., S-MAC) and scheduling-based protocols (e.g., NAMA) with significant energy savings.
The task of talking head generation for the media interaction system is to take images and audio clips of the target face as input, and generate a realistic video of the target synchronized with the audio. Most of the...
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The task of talking head generation for the media interaction system is to take images and audio clips of the target face as input, and generate a realistic video of the target synchronized with the audio. Most of the existing works directly take all the information in the image as input, which causes the problem of feature information redundancy. At the same time, in the stage of feature fusion, the image and audio information is directly spliced, and the relationship between the two modal information is ignored. To solve the problems, we initially implement the disentanglement of image by introducing a loss function to separate the image into identity features and content-related features. Besides, we introduce a multi-head selfattention mechanism to learn the relationship between the two modal information of image and audio, and implement the full fusion of multi-modal information. In addition, we validate the effectiveness of our model through extensive quantitative and qualitative analysis of two datasets. Extensive experiments show the superiority of the proposed model in all aspects.
In this work, we study a link-weighted and distance-constrained channel assignment problem in multi-channel mesh networks with stationary router nodes, such as community wireless networks. A good channel assignment is...
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In this work, we study a link-weighted and distance-constrained channel assignment problem in multi-channel mesh networks with stationary router nodes, such as community wireless networks. A good channel assignment is given as the one which can minimize interference of each link from its neighboring links and subsequently improve the network throughput. In response to it, we introduce an interference metric, namely, min-max i-value of an edge (MMIE), to explicitly accounts for interference among links that are at distance one. In addition, we further show that the link-weighted and distance-constrained channel assignment problem with respect to the interference metric is NP-hard in computation. This guides us to propose a new heuristic channel assignment algorithm called LD-CA algorithm. We study the performance of our algorithm by implementing it in a wireless simulation environment consisting of 25 nodes, each equipped with one 802.11 wireless card. The ns-2 simulation results show that in a multi-channel environment, the LD-CA algorithm significantly outperforms previously proposed channel assignment schemes by minimizing MMIE of all links.
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