Graph-based approximate nearest neighbor algorithms have shown high performance and quality. However, such approaches require a large amount of memory and still take a long time to construct high-quality nearest neigh...
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Recent years have seen a notable rise in the variety of network attacks due to the widespread usage and expansion of the cyber world. One of the most significant threats to the Internet nowadays is a distributed denia...
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ISBN:
(纸本)9798350391558;9798350379990
Recent years have seen a notable rise in the variety of network attacks due to the widespread usage and expansion of the cyber world. One of the most significant threats to the Internet nowadays is a distributed denial-of-service (DDoS) attack, in which the attacker bombards the target system with a high number of packets in an attempt to prohibit regular users from accessing it. To protect against these threats, accurate attack detection measurement is essential. To identify abnormalities, an optimized long-short-term memory (LSTM) algorithm is proposed in this research. In optimized LSTM, the hyperparameters are optimized by using improved bacterial colony optimization (IBFO). IBFO uses the centroid opposition-based learning (COBL) method for initializing the population and position updating. The experimental result demonstrated that the modified LSTM method achieved excellent detection accuracy and quick convergence when compared to a few popular detection techniques.
Nowadays, load balancing is more and more important for huge data centers. Most data centers usually adopt a software-based load balancer (LB), which consumes too many server resources and does not scale with the incr...
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ISBN:
(纸本)9798350386066;9798350386059
Nowadays, load balancing is more and more important for huge data centers. Most data centers usually adopt a software-based load balancer (LB), which consumes too many server resources and does not scale with the increasing traffic volume. However, there is an increased demand for layer-4 load balancers, which need to check more bits in packet headers. Although hardware-based load balancers can meet the requirements, they are much more expensive. During the past years, data centers frequently update their devices, including kinds of switches. Thus, there exists a huge number of obsolete switches, some of which are in good condition and equipped with high-performance storage like SRAM (Static Random Access memory). In this paper, we proposed BCLB (Bit-based Collaborative Load Balancer), a new cooperative LB, which builds more powerful load balancing based on existing switches. Different with previous cooperative mechanisms that distribute rules to different LBs, BCLB lets switches cooperate based on bits. Many switches along the data path check different bits, and cooperatively check all bits in 5-tuple (which would be 296 bits in IPv6) for layer-4 packet header. In this way, rule updating will not influence the load balancing in BCLB. To optimize the performance of BCLB, we formulate the problem as an optimization problem, then we propose a dynamic programming algorithm to solve it. Finally, we conduct comprehensive simulations using both real-world traffic datasets and a P4-based prototype, the results show that BCLB performs much better than previous rule-based cooperative schemes.
distributed systems based on the Internet allow resources widely dispersed throughout the network to be utilized cooperatively and shared. This allows the end-user to obtain massive computational power to perform a co...
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The SWMR atomic register is a fundamental building block in shared memorydistributed systems and implementing it from SWSR atomic registers is an important problem. While this problem has been solved in crash-prone s...
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In this paper, we propose a novel GPU cache system for COMPSs, a task-based distributedcomputing framework that enables the execution of parallel applications on heterogeneous clusters. GPU COMPSs tasks can exploit t...
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ISBN:
(纸本)9783031695827;9783031695834
In this paper, we propose a novel GPU cache system for COMPSs, a task-based distributedcomputing framework that enables the execution of parallel applications on heterogeneous clusters. GPU COMPSs tasks can exploit the computational power of NVIDIA GPUs to process large data blocks. However, the current implementation of COMPSs requires each task to write its output data to disk and the subsequent tasks to read them from disk, which introduces significant overhead. To overcome this limitation, we design and implement a GPU cache system that allows tasks to store and retrieve data from the GPU memory, avoiding unnecessary disk operations and reducing data transfer time. We conducted extensive experiments on several benchmarks and demonstrated that our GPU cache system can achieve significant speedups compared to the baseline COMPSs implementation.
The amazing success of deep neural network benefits from the rise of big data. As deep learning models are becoming more scale than ever before, their requirements for memory bandwidth are growing at a tremendous pace...
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In this paper, a distributed Arithmetic (DA) method for reconfigurable digital filters with finite impulse response (FIR) on FPGA is presented. The inherent parallelism of the DA architecture is used to optimize resou...
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distributedcomputing capabilities at the network's edge enable new use cases, e.g., smart factories, industrial internet of things, or autonomous mobility systems. While new applications evolve, managing the reso...
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ISBN:
(纸本)9798350361360;9798350361353
distributedcomputing capabilities at the network's edge enable new use cases, e.g., smart factories, industrial internet of things, or autonomous mobility systems. While new applications evolve, managing the resources and being capable of integrating and adjusting the execution of tasks in a distributed edge infrastructure is of great importance. For this, applications need to be migrated between different nodes. These migrations must happen without interruption, allowing the system to meet service requirements while fully utilizing all available hardware resources. Therefore, applications should also be executable on all different compute nodes in a heterogeneous edge system without interfering with each other. To this end, applications should be granted only necessary permission, especially when un-trusted applications are integrated into the system. We, therefore, propose a migration method for isolated applications across heterogeneous compute nodes in service-oriented edge architectures. A service-oriented architecture is used to decouple applications, allowing for flexible scheduling. The migration method enables the fast migration of sandboxed applications based on WebAssembly by utilizing a two-stage migration approach. The concept can utilize multiple communication protocols for management and service communication. We have implemented a proof of concept based on the Zenoh(1) communication protocol. While the time required depends on the communication protocol and the memory size, we achieved migration delays of under 51 milliseconds for smaller applications. By providing a method for fast migration for applications across heterogeneous compute nodes, it is possible for distributed edge infrastructures to run applications independently from each other and adjust the execution node based on changes in the system's environment. By integrating applications into our framework, they are executed isolated and with strict access control, allowing for easier reuse
Various Internet of Things (IoT) devices bring great convenience to users. However, the privacy protection and overall performance still need improvements due to their limited storage and computation abilities. Cloud ...
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