the proceedings contain 26 papers. the special focus in this conference is on Cloud computing and Internet of things. the topics include: Towards modelling-based self-adaptive resource allocation in multi-tiers cloud ...
ISBN:
(纸本)9783319232362
the proceedings contain 26 papers. the special focus in this conference is on Cloud computing and Internet of things. the topics include: Towards modelling-based self-adaptive resource allocation in multi-tiers cloud systems;fuzzy logic based energy aware VM consolidation;autonomic and cognitive architectures for the internet of things;sensor web enablement applied to an earthquake early warning system;towards motion characterization and assessment within a wireless body area network;data driven transmission power control for wireless sensor networks;mining regularities in body sensor network data;task execution in distributed smart systems;inferring appliance load profiles from measurements;intra smart grid management frameworks for control and energy saving in buildings;urban crowd steering;towards a self-adaptive middleware for building reliable publish/subscribe systems;review of replication techniques for distributed systems;connectivity recovery in epidemic membership protocols;epidemic fault tolerance for extreme-scale parallel computing;a GPU-based statistical framework for moving object segmentation;containment of fast scanning computer network worms;fragmented-iterated bloom filters for routing in distributed event-based sensor networks;fast adaptive real-time classification for data streams with concept drift;omentum - a peer-to-peer approach for internet-scale virtual microscopy;using social networks data for behavior and sentiment analysis and sentimental preference extraction from online reviews for recommendation.
the following topics are dealt with: mobility, data collection, and network lifetime maximization; camera and multimedia networks; mobile applications and security; routing, MAC, and wireless interference; network dep...
the following topics are dealt with: mobility, data collection, and network lifetime maximization; camera and multimedia networks; mobile applications and security; routing, MAC, and wireless interference; network deployment and topology optimization; estimation and detection; and load balancing.
the method of finding the optimal processing method to answer a query is called Query optimization, whereas a collection of various sites, distributed over a computer network is called distributed database. In Distrib...
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ISBN:
(纸本)9781509030385
the method of finding the optimal processing method to answer a query is called Query optimization, whereas a collection of various sites, distributed over a computer network is called distributed database. In distributed Database, the site communicates with each other through networks. the processing cost and the transmission cost are the important issues arise during evaluation of query cost. Several algorithms have been developed to find the best optimal solution for a particular query;however they all have their certain limitations. Hence, to find the optimal cost for a particular query is emerging as an open challenge for many researchers. therefore the cost-based query optimization technique has emerged as an important concept for dealing withthe query optimization. Withthe help of fragmentations one can replicate each fragment to various distributed sites, since
this paper describes the invited talk given at the 8th international conference on distributed computing and networking (ICDCN 2006), at the Indian Institute of Technology Guwahati, India. this talk was intended to gi...
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ISBN:
(纸本)9783540681397
this paper describes the invited talk given at the 8th international conference on distributed computing and networking (ICDCN 2006), at the Indian Institute of Technology Guwahati, India. this talk was intended to give a partial survey and to motivate further studies of distributed verification. To serve the purpose of motivating, we allow ourselves to speculate freely on the potential impact of such research. In the context of sequential computing, it is common to assume that the task of verifying a property of an object may be much easier than computing it (consider, for example, solving an NP-Complete problem versus verifying a witness). Extrapolating from the impact the separation of these two notions (computing and verifying) had in the context of sequential computing, the separation may prove to have a profound impact on the field of distributedcomputing as well. In addition, in the context of distributedcomputing, the motivation for the separation seems even stronger than in the centralized sequential case. In this paper we explain some motivations for specific definitions, survey some very related notions and their motivations in the literature, survey some examples for problems and solutions, and mention some additional general results such as general algorithmic methods and general lower bounds. Since this paper is mostly intended to "give a taste" rather than be a comprehensive survey, we apologize to authors of additional related papers that we did not mention or detailed.
Network distributed radar track fusion with hierarchical structure is enhanced for distributed data fusion, it has its own characteristic and difficult. In this paper, a two hierarchical structure based fusion frame i...
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ISBN:
(纸本)9781612846835
Network distributed radar track fusion with hierarchical structure is enhanced for distributed data fusion, it has its own characteristic and difficult. In this paper, a two hierarchical structure based fusion frame is describe, simulation plat base on HLA is proposed, the component and framework is described, the process and realization during the whole fusion course for low-lever and high lever fusion center is analyzed, finally the demonstrated simulation is shown.
Fog computing emerged as a new paradigm that pushes cloud applications to the network edge. the fog infrastructure contains mainly distributed and heterogeneous fog nodes that are characterized by their complex distri...
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ISBN:
(纸本)9781728148328
Fog computing emerged as a new paradigm that pushes cloud applications to the network edge. the fog infrastructure contains mainly distributed and heterogeneous fog nodes that are characterized by their complex distribution, high mobility and sporadic resources availability. this dynamic fog nodes behavior triggers new challenges in the resource management process, such as resources coordination for continuous quality-of-service satisfaction. In this paper, we propose a smart online resource allocation approach adapted for dynamic fog computing environments, aiming at maximizing the number of satisfied user requests within a predefined delay threshold. We model the fog computing environment as a Markov discrete process, where dynamic fog node behavior / mobility and resources availability are considered. then, we present our smart deep-reinforcement-learning resource allocation algorithm. Considering real-world mobility data sets, the near-optimal performance of the proposed solution is illustrated through simulations, and its superiority over heuristic state-of-the-art approaches is exposed.
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