scholarly journals Dynamic load balancing technology for cloud-oriented CDN

2015 ◽  
Vol 12 (2) ◽  
pp. 765-786 ◽  
Author(s):  
Hui He ◽  
Yana Feng ◽  
Zhigang Li ◽  
Zhenguang Zhu ◽  
Weizhe Zhang ◽  
...  

With soaring demands of Internet content services, content delivery network (CDN), one of the most effective content acceleration techniques, is applied into Internet services. Content routing functions in CDN are generally realized by load balancing system. Effectiveness of load balancing strategy determines response speed to users and user experience (UE) directly. This paper extracted the most important influencing factor of CDN loading from common network services and proposed the Variable Factor Weighted Least Connection. The proposed algorithm made real-time computing and dynamic regulation in considering of effect of network applications on server load index, performance changes of the server and workload changes. It has been applied in LVS kernel system successfully. The experiment confirmed that the CDN load schedule system with Variable-Factor-Weighted-Least-Connection could balance loads among cluster servers dynamically according to processing capacity changes of servers, thus enabling to provide users desired services and contents during high large-scale concurrence accesses of users.

2013 ◽  
Vol 397-400 ◽  
pp. 1643-1647
Author(s):  
Hui Bo Wang ◽  
Zhi Quan Li

A dual demodulation technique based on tilted grating and InGaAs photodiode array is proposed; using the coupling modes of the cladding, a wavelength demodulation method with the tilted grating as the spectroscopic device is realized. This method can achieve that the demodulation of the channel in which the sensing information changed and the optimization of collection rules of the system. Two tunable F-P filters scan and demodulate the sensing path simultaneously to further improve the system response speed. Simulation analysis and experiments results indicate that the average demodulation time is 40ms and the average signal frequency can reach 15Hz. In addition, the demodulation bandwidth is 40nm, and its wavelength demodulation precision can reach 20pm. The system has advantages of the shorter delay time, and the demodulation time is immune to the number of channels, etc.. Therefore, this system is able to meet the smart requirement of some complex systems and large scale distributed intelligent system.


Author(s):  
Hitomi Tamura ◽  
Masato Uchida ◽  
Masato Tsuru ◽  
Jun'ichi Shimada ◽  
Takeshi Ikenaga ◽  
...  

Author(s):  
Luca Accorsi ◽  
Daniele Vigo

In this paper, we propose a fast and scalable, yet effective, metaheuristic called FILO to solve large-scale instances of the Capacitated Vehicle Routing Problem. Our approach consists of a main iterative part, based on the Iterated Local Search paradigm, which employs a carefully designed combination of existing acceleration techniques, as well as novel strategies to keep the optimization localized, controlled, and tailored to the current instance and solution. A Simulated Annealing-based neighbor acceptance criterion is used to obtain a continuous diversification, to ensure the exploration of different regions of the search space. Results on extensively studied benchmark instances from the literature, supported by a thorough analysis of the algorithm’s main components, show the effectiveness of the proposed design choices, making FILO highly competitive with existing state-of-the-art algorithms, both in terms of computing time and solution quality. Finally, guidelines for possible efficient implementations, algorithm source code, and a library of reusable components are open-sourced to allow reproduction of our results and promote further investigations.


Author(s):  
Mustafa C. Camur ◽  
Thomas Sharkey ◽  
Chrysafis Vogiatzis

We consider the problem of identifying the induced star with the largest cardinality open neighborhood in a graph. This problem, also known as the star degree centrality (SDC) problem, is shown to be [Formula: see text]-complete. In this work, we first propose a new integer programming (IP) formulation, which has a smaller number of constraints and nonzero coefficients in them than the existing formulation in the literature. We present classes of networks in which the problem is solvable in polynomial time and offer a new proof of [Formula: see text]-completeness that shows the problem remains [Formula: see text]-complete for both bipartite and split graphs. In addition, we propose a decomposition framework that is suitable for both the existing and our formulations. We implement several acceleration techniques in this framework, motivated by techniques used in Benders decomposition. We test our approaches on networks generated based on the Barabási–Albert, Erdös–Rényi, and Watts–Strogatz models. Our decomposition approach outperforms solving the IP formulations in most of the instances in terms of both solution time and quality; this is especially true for larger and denser graphs. We then test the decomposition algorithm on large-scale protein–protein interaction networks, for which SDC is shown to be an important centrality metric. Summary of Contribution: In this study, we first introduce a new integer programming (NIP) formulation for the star degree centrality (SDC) problem in which the goal is to identify the induced star with the largest open neighborhood. We then show that, although the SDC can be efficiently solved in tree graphs, it remains [Formula: see text]-complete in both split and bipartite graphs via a reduction performed from the set cover problem. In addition, we implement a decomposition algorithm motivated by Benders decomposition together with several acceleration techniques to both the NIP formulation and the existing formulation in the literature. Our experimental results indicate that the decomposition implementation on the NIP is the best solution method in terms of both solution time and quality.


2017 ◽  
Vol 2017 (2) ◽  
pp. 74-94 ◽  
Author(s):  
Aaron Johnson ◽  
Rob Jansen ◽  
Nicholas Hopper ◽  
Aaron Segal ◽  
Paul Syverson

Abstract We present PeerFlow, a system to securely load balance client traffic in Tor. Security in Tor requires that no adversary handle too much traffic. However, Tor relays are run by volunteers who cannot be trusted to report the relay bandwidths, which Tor clients use for load balancing. We show that existing methods to determine the bandwidths of Tor relays allow an adversary with little bandwidth to attack large amounts of client traffic. These methods include Tor’s current bandwidth-scanning system, TorFlow, and the peer-measurement system EigenSpeed. We present an improved design called PeerFlow that uses a peer-measurement process both to limit an adversary’s ability to increase his measured bandwidth and to improve accuracy. We show our system to be secure, fast, and efficient. We implement PeerFlow in Tor and demonstrate its speed and accuracy in large-scale network simulations.


2018 ◽  
Vol 4 (11) ◽  
pp. eaau1447 ◽  
Author(s):  
Ryan Hard ◽  
Nan Li ◽  
Wei He ◽  
Brian Ross ◽  
Gary C. H. Mo ◽  
...  

Posttranslational modifications (PTMs) play critical roles in regulating protein functions and mediating protein-protein interactions. An important PTM is lysine methylation that orchestrates chromatin modifications and regulates functions of non-histone proteins. Methyllysine peptides are bound by modular domains, of which chromodomains are representative. Here, we conducted the first large-scale study of chromodomains in the human proteome interacting with both histone and non-histone methyllysine peptides. We observed significant degenerate binding between chromodomains and histone peptides, i.e., different histone sites can be recognized by the same set of chromodomains, and different chromodomains can share similar binding profiles to individual histone sites. Such degenerate binding is not dictated by amino acid sequence or PTM motif but rather rooted in the physiochemical properties defined by the PTMs on the histone peptides. This molecular mechanism is confirmed by the accurate prediction of the binding specificity using a computational model that captures the structural and energetic patterns of the domain-peptide interaction. To further illustrate the power and accuracy of our model, we used it to effectively engineer an exceptionally strong H3K9me3-binding chromodomain and to label H3K9me3 in live cells. This study presents a systematic approach to deciphering domain-peptide recognition and reveals a general principle by which histone modifications are interpreted by reader proteins, leading to dynamic regulation of gene expression and other biological processes.


2019 ◽  
Author(s):  
K. Vyse ◽  
L. Faivre ◽  
M. Romich ◽  
M. Pagter ◽  
D. Schubert ◽  
...  

AbstractChromatin regulation ensures stable repression of stress-inducible genes under non-stress conditions and transcriptional activation and memory of such an activation of those genes when plants are exposed to stress. However, there is only limited knowledge on how chromatin genes are regulated at the transcriptional and post-transcriptional level upon stress exposure and relief from stress. We have therefore set-up a RT-qPCR-based platform for high-throughput transcriptional profiling of a large set of chromatin genes. We find that the expression of a large fraction of these genes is regulated by cold. In addition, we reveal an induction of several DNA and histone demethylase genes and certain histone variants after plants have been shifted back to ambient temperature (deacclimation), suggesting a role in the memory of cold acclimation. We also re-analyse large scale transcriptomic datasets for transcriptional regulation and alternative splicing (AS) of chromatin genes, uncovering an unexpected level of regulation of these genes, particularly at the splicing level. This includes several vernalization regulating genes whose AS results in cold-regulated protein diversity. Overall, we provide a profiling platform for the analysis of chromatin regulatory genes and integrative analyses of their regulation, suggesting a dynamic regulation of key chromatin genes in response to low temperature stress.


Author(s):  
Gengbin Zheng ◽  
Abhinav Bhatelé ◽  
Esteban Meneses ◽  
Laxmikant V. Kalé

Large parallel machines with hundreds of thousands of processors are becoming more prevalent. Ensuring good load balance is critical for scaling certain classes of parallel applications on even thousands of processors. Centralized load balancing algorithms suffer from scalability problems, especially on machines with a relatively small amount of memory. Fully distributed load balancing algorithms, on the other hand, tend to take longer to arrive at good solutions. In this paper, we present an automatic dynamic hierarchical load balancing method that overcomes the scalability challenges of centralized schemes and longer running times of traditional distributed schemes. Our solution overcomes these issues by creating multiple levels of load balancing domains which form a tree. This hierarchical method is demonstrated within a measurement-based load balancing framework in Charm++. We discuss techniques to deal with scalability challenges of load balancing at very large scale. We present performance data of the hierarchical load balancing method on up to 16,384 cores of Ranger (at the Texas Advanced Computing Center) and 65,536 cores of Intrepid (the Blue Gene/P at Argonne National Laboratory) for a synthetic benchmark. We also demonstrate the successful deployment of the method in a scientific application, NAMD, with results on Intrepid.


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