An n-dimensional hypercube Q n is well known as bipartite and one of the most efficient networks for parallel computation. Fault tolerance is an important issue for a network since the vertex (or edge) in the network...
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An n-dimensional hypercube Q n is well known as bipartite and one of the most efficient networks for parallel computation. Fault tolerance is an important issue for a network since the vertex (or edge) in the network may fail sometimes. Assume that n ges 4 and P is a faulty path (or cycle) of order les 2n - 4 in Q n . We prove that Q n - P is Hamiltonian laceable. Furthermore, the bound is tight.
The following topics are dealt with: intelligent Web services; P2P networks; video-on-demand and video streaming; ad hoc networks routing algorithms; fault tolerance; multimedia applications; secure mechanisms and DoS...
The following topics are dealt with: intelligent Web services; P2P networks; video-on-demand and video streaming; ad hoc networks routing algorithms; fault tolerance; multimedia applications; secure mechanisms and DoS; distributed systems and models; context-aware systems; intrusion detection; network architecture; cluster and grid computing; sensor network applications; wireless networks; Internet; ubiquitous systems; QoS; access control and congestion control; middleware systems; SNDS; interoperability issues; HWISE; heterogenous networks; virtual reality and tele-existence; machine vision and recognition; database and data storage.
Software systems are often built by composing services distributed over the network. Choreographies are a form of decentralized composition that models the external interaction of the services by specifying peer-to-pe...
A transactional agent is a mobile agent which manipulates objects distributed in computers. A transactional agent is composed of routing, manipulation, and commitment agents. A way to move to computers is decided in t...
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A transactional agent is a mobile agent which manipulates objects distributed in computers. A transactional agent is composed of routing, manipulation, and commitment agents. A way to move to computers is decided in the routing agent. Objects in each computer are manipulated in a manipulation agent. After visiting computers, a transactional agent makes a destination on commitment by using the commitment agent. In addition, objects obtained from a computer in the manipulation agent have to be delivered to other computers where the transactional agent is performed. We discuss a model of transactional agent and implementation of a transactional agent on database servers and evaluate the transactional agents.
SDN is new networking concept which has revolutionized the network architecture in recent years. It decouples control plane from data plane. Architectural change provides re-programmability and centralized control man...
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SDN is new networking concept which has revolutionized the network architecture in recent years. It decouples control plane from data plane. Architectural change provides re-programmability and centralized control management of the network. At the same time it also increases the complexity of underlying physical infrastructure of the network. Unfortunately, the centralized control of the network introduces new vulnerabilities and attacks. Attackers can exploit the limitation of centralized control by DDoS attack on control plane. The entire network can be compromised by DDoS attack. Based on packet entropy, a solution for mitigation of DDoS attack provided in the proposed scheme.
We investigate the impact of an unevenly distributed load among nodes of a distributed key-value store on response times. We find that response times of “get” operations quickly degrade in the presence of power law ...
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We investigate the impact of an unevenly distributed load among nodes of a distributed key-value store on response times. We find that response times of “get” operations quickly degrade in the presence of power law distributions of load and identify the point, at which the system needs to apply a mitigation approach. The migration technique, which we propose, overcomes the long response times of consistent hashing placement techniques. Our technique is a hybrid approach that combines consistent hashing and a directory for exceptions. Our experimental results show an improvement in the average response times and an equal load among the nodes.
Agent platforms provide a framework for development and execution of parallel applications such as multi-agent based simulation (MABS). However, these platforms have limitations to support large-scale MABS application...
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Agent platforms provide a framework for development and execution of parallel applications such as multi-agent based simulation (MABS). However, these platforms have limitations to support large-scale MABS applications in practice. This paper aims at investigating and improving the performance of an agent platform with a MABS workload in distributed environments. We carried out an experimental study with the JADE framework as our agent platform. The experiments show the performance characteristics of the workload and that JADE does not scale well due to message transport and agent directory service limitations. We propose solutions to overcome these performance bottlenecks and facilitate the efficient execution of MABS in a distributed environment. Initial experimental results demonstrate the feasibility of the proposed approaches.
Federated unlearning has emerged as a promising paradigm to erase the client-level data effect without affecting the performance of collaborative learning models. However, the federated unlearning process often introd...
ISBN:
(纸本)9781956792041
Federated unlearning has emerged as a promising paradigm to erase the client-level data effect without affecting the performance of collaborative learning models. However, the federated unlearning process often introduces extensive storage overhead and consumes substantial computational resources, thus hindering its implementation in practice. To address this issue, this paper proposes a scalable federated unlearning framework based on isolated sharding and coded computing. We first divide distributed clients into multiple isolated shards across stages to reduce the number of clients being affected. Then, to reduce the storage overhead of the central server, we develop a coded computing mechanism by compressing the model parameters across different shards. In addition, we provide the theoretical analysis of time efficiency and storage effectiveness for the isolated and coded sharding. Finally, extensive experiments on two typical learning tasks, i.e., classification and generation, demonstrate that our proposed framework can achieve better performance than three state-of-the-art frameworks in terms of accuracy, retraining time, storage overhead, and F1 scores for resisting membership inference attacks.
Many distributed clustering algorithms have been proposed to speed up data clustering on huge database. However, the existing distributed clustering algorithms still suffer from many issues on distributed system such ...
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Many distributed clustering algorithms have been proposed to speed up data clustering on huge database. However, the existing distributed clustering algorithms still suffer from many issues on distributed system such as data synchronization, insufficient scalability, and maintenance difficulties. In this paper, we propose two distributed clustering algorithms named DDC and DGC, which are based on the cloud computing technique. The main ideas of proposed algorithms are to achieve load balance according to an efficient data partition, to cluster more data on many machines in parallel without data dependency, and to merge the result on a machine efficiently with minimal information overlap. The experimental results show that DDC and DGC are able to reduce the execution time and achieve great scalability on the cloud.
The DART (distributed Adaptive Run-Time) project is developing an adaptive software environment for general-purpose distributed applications. The goal of the project is to provide a software run-time system that allow...
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The DART (distributed Adaptive Run-Time) project is developing an adaptive software environment for general-purpose distributed applications. The goal of the project is to provide a software run-time system that allows application authors to quickly develop distributed software, such as network or World Wide Web software, without having to deal with the details of the distribution technology. DART compile-time and run-time components configure the application execution environments depending on hints provided with the application. An essential feature of the run-time component is its ability to reconfigure, or adapt itself, both to the application requirements and to the system and networking environment. To achieve both distribution and adaptation, we use meta-level object programming techniques and run-time monitoring.
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