with the development of cloud computing, the security and trust management in distributedsystems is changeable. This paper proposes an architecture and solution of security and trust management for distributed system...
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ISBN:
(纸本)9781467345286
with the development of cloud computing, the security and trust management in distributedsystems is changeable. This paper proposes an architecture and solution of security and trust management for distributedsystems which use cloud computing. Since the solution requires future technologies, an optimization to the security and trust management, including multi-paths transmission, virtual personal networks and encryption, is proposed. This optimization will enhance the security and trust in distributedsystems.
distributed publish/subscribe systems are an enabling technology for Industrial Internet of Things applications. While the number of sensors increases, network bandwidth becomes a bottleneck. Existing solutions typica...
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ISBN:
(纸本)9781728123653
distributed publish/subscribe systems are an enabling technology for Industrial Internet of Things applications. While the number of sensors increases, network bandwidth becomes a bottleneck. Existing solutions typically aim to reduce network load either by pre-processing events directly on the edge or by aggregating events into larger batches. However, these approaches are rather static and do not adequately account for the application requirements of subscribers or the actual values of sensor measurements. This paper introduces methods for publish/subscribe systems to dynamically adapt payloads of events at runtime based on i) different data reduction and transformation strategies, ii) a wrapper solution around existing message brokers and iii) a semantics-based event schema registry. Consumers are able to subscribe to various quality levels and receive virtual events, that are reconstructed directly at the subscriber based on knowledge from the semantic model and dynamic decision rules. Our evaluation shows that the concept of virtual events can reduce the network load between publishers, the message broker and subscribers compared to multiple investigated compression techniques.
We carry out a careful study of Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) and propose some implementation schemas in the Spark Framework. Focusing on the setting of weight vectors, we prop...
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ISBN:
(纸本)9781538625880
We carry out a careful study of Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) and propose some implementation schemas in the Spark Framework. Focusing on the setting of weight vectors, we propose two partitioning schemas, which define the distribution mode for the algorithm. The first partitioning schema is to define a partition by a group of weight vectors that are close to each other. The other schema is to distribute close weights to different partitions. Experiments in distributed framework indicate that, for most benchmarks, the schemas in distributed framework can obtain better results and better performance in expansibility.
Centralized electrical storage system management in islanded micro-grids is treated both theoretically and experimentally. An overview of the types of distributed islands in Wi-Fi Long Distance networks is the startin...
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ISBN:
(纸本)9781538625880
Centralized electrical storage system management in islanded micro-grids is treated both theoretically and experimentally. An overview of the types of distributed islands in Wi-Fi Long Distance networks is the starting point, followed by examples of WiLDNets and associated reliability problems. Presentation of an archetypical tree structure communication system serves to introduce a centralized management system that may be used to improve reliability of multi-community private networks. An existing Wi-Fi long distance testbed with distributed storage serves as an islanded micro-grid for experimental study. Centralized management algorithms are tested. The results are generalized to the case of large meshed communication system.
In real-time distributed transaction processing, deadlocks must be detected and resolved. Timeouts are not a viable option because they lead to lost work and missed deadlines. We have proposed a suite of deadlock dete...
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ISBN:
(纸本)9781538625880
In real-time distributed transaction processing, deadlocks must be detected and resolved. Timeouts are not a viable option because they lead to lost work and missed deadlines. We have proposed a suite of deadlock detection protocols and a resolution protocol which carry a varying degree of (generally low) overhead. The protocols behave differently under varying load conditions and transaction characteristics. Further, the invocation period of these protocols can be controlled to improve performance when the overhead tends to become large. The performance of these protocols has been demonstrated using a distributed real-time transaction processing simulator which provides an interactive interface to set parameters, and also has provisions to select from a variety of concurrency control, priority assignment, workload distribution and other protocols. The impact of transaction workload, underlying system configuration, resource availability, detection rates, and congestion on each of the proposed protocols is observed and presented. In general, the multi-cycle detection protocol demonstrated the most superior performance over a broad range of parameters. The results presented in this paper were obtained from over 147,000 simulations.
Change detection in images is of great interest due to its relevance in applications such as video surveillance. This paper presents the underlying theoretical problem of image change detection using wireless sensor n...
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ISBN:
(纸本)9783540730897
Change detection in images is of great interest due to its relevance in applications such as video surveillance. This paper presents the underlying theoretical problem of image change detection using wireless sensor network. The proposed system consists of multiple image sensors which make local decisions independently and send them to the base station which finally makes a global decision and declares whether a significant change has occurred or not.
In this paper, we develop algorithms for distributed computation of averages of the node data over networks With arbitrary but fixed connectivity. The algorithms we develop are linear dynamical systems that generate s...
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In this paper, we develop algorithms for distributed computation of averages of the node data over networks With arbitrary but fixed connectivity. The algorithms we develop are linear dynamical systems that generate sequences of improving approximations to the desired computation at each node, via iterative processing and broadcasting. The algorithms are locally constructed at each node by exploiting only locally available and macroscopic information about the network topology. We present methods for optimizing the convergence rates of these algorithms to the desired computation, and evaluate their performance characteristics in the context of a problem of signal estimation from multinode noisy observations. By conducting simulations based on simple powerloss propagation models, we perform a preliminary comparison of the algorithms we develop against other types of distributed algorithms for computing averages, and identify transmit-power optimized algorithmic implementations as. a function of the size and density of the sensor network.
The large-scale surveillance video processing workloads are gradually migrated to cloud computing platforms. Meanwhile, the hybrid storage architecture, integrating both HDD and SSD storage devices, is increasingly us...
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ISBN:
(纸本)9781538625880
The large-scale surveillance video processing workloads are gradually migrated to cloud computing platforms. Meanwhile, the hybrid storage architecture, integrating both HDD and SSD storage devices, is increasingly used in the current cloud platforms. However, the computing and storage capabilities of the nodes are constantly changing, and this requires the delicate design of the data layout strategy for avoiding the serious load skew in the distributedcomputing nodes with the hybrid storage architecture. In this paper, we propose a Load-Aware Data Migration (LADM) scheme for distributed surveillance video processing with hybrid storage architecture. Specifically, according to the proposed the load estimation model and the storage capacity constraint, the Node-Level Data Migration (NLDM) strategy is used to periodically migrate the appropriate video chunks from the local HDD to the local SSD for improving the node processing performance, and the Cluster-Level Data Migration (CLDM) strategy is used to periodically migrate the appropriate video chunks from the high load nodes to the low load nodes for achieving the overall load balance of cluster. We conduct the extensive experiments based on the distributed surveillance video processing platform we developed, and the experimental results show that the proposed LADM scheme outperforms the current methods.
Trust, reliability, and validation of data collected in distributed edge sensorsystems is an increasingly relevant issue. Though the obvious solution of deploying redundant identical systems can provide validation, r...
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ISBN:
(数字)9781728131016
ISBN:
(纸本)9781728131016
Trust, reliability, and validation of data collected in distributed edge sensorsystems is an increasingly relevant issue. Though the obvious solution of deploying redundant identical systems can provide validation, real-world modification constraints can sometimes make this difficult, or even prevent this. However, many distributedsensors exist for other purposes, that may be available to be used. Introducing validation with existing sensors may impose too high a requirement for bandwidth to use cloud-based validation, while edge-based validation may require too much computing power. A fog-based validation layer using sensory substitution is presented. With the rise of cyber-physical attacks on cloud, fog, and edge computingsystems, validation is important, and lack of correct validation has been seen in some high impact cases where incorrect sensor data can be thought of as as true. A playback cyber-attack is discussed, and an algorithm for increasing reliability of IoT systems in the case of typical sensor errors or more serious incidents like cyber-physical attacks is presented. Given the need for dependable autonomy and reliability in IoT systems, this paper presents a method of sensor validation to increase robustness, resilience and dependability of sensed data by detecting false positives and negatives, and corroboration of true positives and negatives, using sensory substitution. Perhaps sometimes sensor data is trusted without ongoing validation. Using the example of cameras and artificial intelligence-based human presence detection, as well as using ambient distributed magnetometers and luminosity sensors, examples of a fog-based corroboration and validation methodology for human detection is presented. Results show the technique is an effective vector for sensor validation using available sensors, and scenarios where sensory substitution corrects false positives and false negatives from an artificial intelligence visual model are shown.
A programming model that is widely approved today for large applications is parallel programming with shared variables. We propose an implementation of shared arrays on distributed memory architectures: it provides th...
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ISBN:
(纸本)0818675578
A programming model that is widely approved today for large applications is parallel programming with shared variables. We propose an implementation of shared arrays on distributed memory architectures: it provides the user with an uniform addressing scheme while being efficient thanks to a logical paging technique and optimized communication mechanisms.
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