Software Defined Networking (SDN) has emerged as a new paradigm that highly increase the network management flexibility through simple but powerful abstractions. The key idea is decoupling the control plane, which mak...
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Software Defined Networking (SDN) has emerged as a new paradigm that highly increase the network management flexibility through simple but powerful abstractions. The key idea is decoupling the control plane, which makes the forward decisions, from the data plane, which effectively makes the forward. However, the OpenFlow, the main SDN enabler, is designed mainly by wired networks characteristics. As consequence, Wireless Mesh Networks (WMNs) is not suitable for operating as control plane and many wireless networks features are neglected in the OpenFlow, e.g.: power control and network ID. In addition, there are few effort research to extend SDN to wireless networks and these existing works focus on very specific issues of this integration. In this paper, we propose an architecture to extent the OpenFlow functionalities in order to proper deal with wireless networks, including an approach for transporting the control plane over wireless multihop networks. The extensions include new rules, actions, and commands, which bring the network management flexibility to the wireless context. We validated our proposal by implementing and testing some extensions in a small real world testbed. As a proof of concept, we illustrate the OpenFlow capability of isolation between research and production traffics in a wireless backhaul.
Conventional super-junction lateral double diffused MOSFET (SJ-LDMOS) fabricated on Silicon on Insulator (SOI) substrate suffers from low breakdown voltage under the same on-resistance due to substrate-assisted deplet...
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Centrality metrics have shown to be highly correlated with the importance and loads of the nodes within the network traffic. In this work, we provide fast incremental algorithms for closeness centrality computation. O...
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Centrality metrics have shown to be highly correlated with the importance and loads of the nodes within the network traffic. In this work, we provide fast incremental algorithms for closeness centrality computation. Our algorithms efficiently compute the closeness centrality values upon changes in network topology, i.e., edge insertions and deletions. We show that the proposed techniques are efficient on many real-life networks, especially on small-world networks, which have a small diameter and spike-shaped shortest distance distribution. We experimentally validate the efficiency of our algorithms on large-scale networks and show that they can update the closeness centrality values of 1.2 million authors in the temporal DBLP-coauthorship network 460 times faster than it would take to recompute them from scratch.
Ever since mobile applications were developed and became popular, they have started to take part in almost every field of our lives. Healthcare is one of the most popular fields that mobile applications have become a ...
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In this work we propose a new unified PON-RAN architecture for LTE mobile backhaul networks, employing ring-based WDM PONs. The proposed architecture supports dynamic setup of virtual circuits for inter-base station c...
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In this work we propose a new unified PON-RAN architecture for LTE mobile backhaul networks, employing ring-based WDM PONs. The proposed architecture supports dynamic setup of virtual circuits for inter-base station communication, over a dedicated λ LAN channel. The reservation mechanism is arbitrated by the OLT, which also monitors the traffic imbalances of downstream channels. The proposed architecture also supports load balancing, by dynamically reallocating and sharing the capacity of the downstream wavelengths.
Tele-immersive applications, which are regarded as the next generation distributed multimedia applications, are highly interactive and aims to offer an immersive experience to its users. A challenge with such applicat...
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ISBN:
(纸本)9781467322331
Tele-immersive applications, which are regarded as the next generation distributed multimedia applications, are highly interactive and aims to offer an immersive experience to its users. A challenge with such applications is to provide the best possible quality of experience (QoE) under changing conditions. In particular, it would be highly desirable to be able to predict the QoE perceived by users in response to adaptation, prior to actual deployment. However, there are no QoE prediction models for tele-immersive applications. Instead QoE is evaluated after deployment using either objective or subjective assessment techniques. Unfortunately, objective assessment lacks the accuracy of human perception. At the same time, subjective assessment requires human-provided ratings of the applications, which is time consuming and thus not cost-effective. In this paper, we propose QoE prediction models that will accurately predict the user-perceived QoE of a tele-immersive conferencing application. The proposed models are cost-effective and lend themselves to fast evaluation cycles, because the models does not involve human-provided ratings. We validate our models using results from subjective assessment experiments. The models can be used for real-time monitoring of user-perceived QoE, in addition to designing QoE-driven adaptation for tele-immersive applications.
During the last decades, research efforts have been focused on the derivation of effective preconditioned iterative methods. The preconditioned iterative methods are mainly categorized into implicit preconditioned met...
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ISBN:
(纸本)9781450318518
During the last decades, research efforts have been focused on the derivation of effective preconditioned iterative methods. The preconditioned iterative methods are mainly categorized into implicit preconditioned methods and explicit preconditioned methods. In this manuscript we review implicit preconditioned methods, based on incomplete and approximate factorization, and explicit preconditioned methods, based on sparse approximate inverses and explicit approximate inverses. Modified Moore-Penrose conditions are presented and theoretical estimates for the sensitivity of the explicit approximate inverse matrix of the explicit preconditioned method are derived. Finally, the performance of the preconditioned iterative methods is illustrated by solving characteristic 2D elliptic problem and numerical results are given indicating a qualitative agreement with the theoretical estimates. Copyright 2013 ACM.
This paper propose parallel implementation of Ant Colony System (ACS) algorithm for automated combinational circuit design. Ant Colony System is one of the most popular and widely used Ant Colony Optimization (ACO) al...
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This paper propose parallel implementation of Ant Colony System (ACS) algorithm for automated combinational circuit design. Ant Colony System is one of the most popular and widely used Ant Colony Optimization (ACO) algorithm and heuristic algorithm in general. As digital logic circuits become more complex, efficient circuit design is priority and use of heuristic methods are unavoidable. Unfortunately, the optimization problems became so complex in sense of their size, even the most powerful heuristic algorithms can't solve them on single CPU. In order to be able to tackle the problem, parallel version of ACS is needed and this paper presents CUDA (Compute Unified Device Architecture) C language implementation.
The monitoring and the analysis of public clouds gains momentum, due to their widespread exploitation by individual users, researchers and companies for their daily tasks. We propose an algorithm for optimizing the co...
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The monitoring and the analysis of public clouds gains momentum, due to their widespread exploitation by individual users, researchers and companies for their daily tasks. We propose an algorithm for optimizing the cost and the utilization of a set of running Amazon EC2 instances by resizing them appropriately. The algorithm, namely Cost and Utilization Optimization (CUO) algorithm, receives information regarding the current set of instances used (their number, type, utilization) and proposes a new set of instances for serving the same load, so as to minimize cost and maximize utilization, or increase performance efficiency. CUO is integrated in Smart cloud Monitoring (SuMo), an open-source tool we develop for collecting monitoring data from Amazon Web Services (AWS) and analyzing them. A number of experiments are performed, using input data that correspond to realist AWS configuration scenarios, which exhibit the benefits of the CUO algorithm.
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