In recent years, blockchain technology has received extensive attention and applied in various fields including healthcare, IoT and database systems. Utilizing the decentralization and anti-tampering properties, the b...
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ISBN:
(纸本)9798350381993;9798350382006
In recent years, blockchain technology has received extensive attention and applied in various fields including healthcare, IoT and database systems. Utilizing the decentralization and anti-tampering properties, the blockchain provides potential solutions to achieve verification of data queries, without the assumption of the trusted third parties in traditional data verification studies. However, for kNN queries, a common query type in practical location-based scenarios, few existing solutions can directly support the location-based kNN query processing and result authentication based on blockchain. To address this problem, in this paper, we propose a blockchain-based verifiable kNN query processing method. In this method, we first design a novel authenticated data structure called VMR-Tree, which stores the data objects and their neighboring objects in leaf nodes and stores the hash values used for data verification in non-leaf nodes. To verify the results with the minimum size of verification objects (VOs), we design a query result verification method based on the blockchain, in which the client can verify the query results by processing the VOs generated based on the proposed VMR-Tree index and the blockchain. Besides, we further propose an optimization algorithm to reduce the size of VOs. We theoretically analyze the computational complexity and security guarantees of the proposed approaches. We also conducted extensive experiments on real and synthetic datasets to evaluate the efficiency of the proposed method on the result verification of location-based kNN queries.
This paper analyzes and researches the problems of poor robustness and high arithmetic complexity that exist in the traditional methods of distributed radar target detection and tracking, and proposes a point track fu...
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Due to the increasing privacy demand in data processing, Fully Homomorphic Encryption (FHE) has recently received growing attention for its ability to perform calculations over encrypted data. Since the data can be pr...
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ISBN:
(纸本)9798350333398
Due to the increasing privacy demand in data processing, Fully Homomorphic Encryption (FHE) has recently received growing attention for its ability to perform calculations over encrypted data. Since the data can be processed in encrypted form and the output remains encrypted, only an authorized user or a user who holds the key can decrypt the data and understand its meaning. Hence, it is possible to securely outsource data processing to untrustworthy but powerful public computing resources on the edge. However, due to the high computational complexity, FHE-based data processing experiences scalability related concerns. It is currently unclear whether FHE can be used to solve large-scale problems. In this paper, we propose a novel general distributed FHE-based data processing approach as a concrete step towards solving the scalability challenge. The main idea behind our approach is to use slightly more communication overhead for a shorter computing circuit in FHE, hence, reducing the overall complexity. We verify our new model's efficiency and effectiveness by comparing the distributed approach with the central approach over various FHE schemes (CKKS, BGV, and BFV). This is performed using one of the most popular libraries of FHE "Microsoft SEAL", by performing specific mathematical operations and observing the time consumed. The empirical results demonstrate that the proposed approach results in a significant reduction in time, up to 54% compared to the traditional central approach.
Fuzzy Cognitive Maps (FCMs) are powerful tools for the modeling of complex systems, one of which is time series modeling. Although advocated for their interpretability, existing methods measure concept relevance based...
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Coded distributedcomputing (CDC) has been recently proposed as a promising technique to mitigate the straggler effect in the distributedcomputing cluster which consists of workers with different computing capabiliti...
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ISBN:
(纸本)9798350333398
Coded distributedcomputing (CDC) has been recently proposed as a promising technique to mitigate the straggler effect in the distributedcomputing cluster which consists of workers with different computing capabilities, and to reduce the end-to-end task execution latency. However, the heterogeneity of computing and transmission will critically impact the latency performance, especially in the wireless multiple-access network. In this paper, we use CDC over the heterogeneous wireless multiple-access network (HWMAN) including both computation stragglers and transmission stragglers with various capabilities. In order to reduce the computing task completion latency (computing latency and transmission latency), the optimal stop computing time of workers and the sorting order of result transmission back are obtained via two designed algorithms, namely straggler detection and ordered transmission (SDOT) and worker sorting and ordered transmission (WSOT), respectively, which not only fully utilize the computing results of stragglers, but also improve the total latency performance compared with other existing state-of-the-art algorithms.
We introduce a distributed memory parallel algorithm for force-directed node embedding that places vertices of a graph into a low-dimensional vector space based on the interplay of attraction among neighboring vertice...
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ISBN:
(纸本)9798350364613;9798350364606
We introduce a distributed memory parallel algorithm for force-directed node embedding that places vertices of a graph into a low-dimensional vector space based on the interplay of attraction among neighboring vertices and repulsion among distant vertices. We develop our algorithms using two sparse matrix operations, SDDMM and SpMM. We propose a configurable pull -push -based communication strategy that optimizes memory usage and data transfers based on computing resources and asynchronous MPI communication to overlap communication and computation. Our algorithm scales up to 256 nodes on distributed supercomputers by surpassing the performance of state-of-the-art algorithms
The proceedings contain 20 papers. The topics discussed include: split DNN inference for exploiting near-edge accelerators;DONNA: distributed optimized neural network allocation on CIM-based heterogeneous accelerators...
ISBN:
(纸本)9798350368499
The proceedings contain 20 papers. The topics discussed include: split DNN inference for exploiting near-edge accelerators;DONNA: distributed optimized neural network allocation on CIM-based heterogeneous accelerators;reliable network performance for edge networks with QoS-aware adaptive routing;the impact of GPU on containerized computer vision applications on edge nodes;cross network layer cognitive service orchestration in edge computingsystems;a case for deploying dynamic neural network on edge-cloud continuum environment;data sharing-aware online algorithms for task allocation in edge computingsystems;and SlimNet: a lightweight attentive network for speech-music-noise classification and voice activity detection.
Connection and routing parameters of wireless sensor networks are considered for static topologies and uniform distribution of nodes. Most of the studied models do not take into account the parameters of message conne...
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ISBN:
(纸本)9798350310856
Connection and routing parameters of wireless sensor networks are considered for static topologies and uniform distribution of nodes. Most of the studied models do not take into account the parameters of message connectivity and their delivery time between unevenly distributed nodes. in the proposed study, models of connectivity analysis and message delivery between unevenly distributed nodes are developed. Models of wireless sensor networks with uniform and normal distribution of nodes and research on the network connectivity parameter for these models are proposed. Network models with different types of distributions are built based on the Erdosh-Rani random graph model, which allows describing of the connectivity of wireless sensor networks as the connectivity of a random graph, that is, to determine the connectivity of wireless sensor networks with the probability of finding the distance between two vertices of the graph. Simulation models with a uniform and normal distribution of nodes are implemented to investigate the probability of network connection. The choice of these types of distribution is explained by possible real distributions of nodes in the studied area.
This paper explores an innovative method for distributed state estimation aimed at reducing computational complexity while detecting sensor faults in natural gas pipelines. The proposed framework utilizes a partial-di...
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ISBN:
(纸本)9798350371420;9781737749769
This paper explores an innovative method for distributed state estimation aimed at reducing computational complexity while detecting sensor faults in natural gas pipelines. The proposed framework utilizes a partial-distributed ensemble Kalman filter (EnKF), comprising linear local filters and a non-linear main filter. The main filter handles non-linear computations during the time update, while the simultaneous operation of linear local filters manages linear computations during the measurement update. These local filters generate distinct local state estimates based on their specific sensor measurements, which are then transmitted to an information mixer to compute fault-free state estimates. Moreover, a fault diagnosis strategy is developed using local state variances and residuals. Faulty sensors are identified and isolated by comparing these metrics against a threshold. Additionally, an adaptive thresholding approach is incorporated to enhance effective fault identification. The effectiveness of the proposed technique is demonstrated in systems characterized by high nonlinearity and dimensionality, and featuring simultaneous multiple sensor faults, through extensive simulations and comparative analyses.
With the development of network society, individuals and enterprises generate massive data every day. However, the traditional relational MySQL database has poor performance in storing and processing massive data. In ...
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