Cloud Index Tracking: Enabling Predictable Costs in Cloud Spot Markets

Cloud spot markets rent VMs for a variable price that is typically much lower than the price of on-demand VMs, which makes them attractive for a wide range of large-scale applications. However, applications that run on spot VMs suffer from cost uncertainty, since spot prices fluctuate, in part, based on supply, demand, or both. The difficulty in predicting spot prices affects users and applications: the former cannot effectively plan their IT expenditures, while the latter cannot infer the availability and performance of spot VMs, which are a function of their variable price. To address the problem, we use properties of cloud infrastructure and workloads to show that prices become more stable and predictable as they are aggregated together. We leverage this observation to define an aggregate index price for spot VMs that serves as a reference for what users should expect to pay. We show that, even when the spot prices for individual VMs are volatile, the index price remains stable and predictable. We then introduce cloud index tracking: a migration policy that tracks the index price to ensure applications running on spot VMs incur a predictable cost by migrating to a new spot VM if the current VM's price significantly deviates from the index price.Comment: ACM Symposium on Cloud Computing 201

Flexible Management on BSP Process Rescheduling: Offering Migration at Middleware and Application Levels

This article describes the rationales for developing jMigBSP - a Java programming library that offers object rescheduling. It was designed to work on grid computing environments and offers an interface that follows the BSP (Bulk Synchronous Parallel) style. jMigBSP’s main contribution focuses on the rescheduling facility in two different ways: (i) by using migration directives on the application coded irectly and (ii) through automatic load balancing at middleware level. Especially, this second idea is feasible thanks to the Java’s inheritance feature, in which transforms a simple jMigBSP application in amigratable one only by changing a single line of code. In addition, the presented library makes the object interaction easier by providing one-sided message passing directives and hides network latency through asynchronous communications. Finally, we developed three BSP applications: (i) Prefix Sum; (ii) Fractal Image Compression (FIC) and; (iii) Fast Fourier Transform (FFT).They show our library as viable solution to offer load balancing on BSP applications. Specially, the FIC results present gains up to 37% when applying migration directives inside the code. Finally, the FFT tests emphasize strength of jMigBSP. In this situation, it outperforms a native library denoted BSPlib when migration facilities take place.Keywords: Bulk Synchronous Parallel, rescheduling, Java, adaptation, object migration, grid computing

DNA electrophoresis studied with the cage model

The cage model for polymer reptation, proposed by Evans and Edwards, and its recent extension to model DNA electrophoresis, are studied by numerically exact computation of the drift velocities for polymers with a length L of up to 15 monomers. The computations show the Nernst-Einstein regime (v ~ E) followed by a regime where the velocity decreases exponentially with the applied electric field strength. In agreement with de Gennes' reptation arguments, we find that asymptotically for large polymers the diffusion coefficient D decreases quadratically with polymer length; for the cage model, the proportionality coefficient is DL^2=0.175(2). Additionally we find that the leading correction term for finite polymer lengths scales as N^{-1/2}, where N=L-1 is the number of bonds.Comment: LaTeX (cjour.cls), 15 pages, 6 figures, added correctness proof of kink representation approac

DHLP 1&2: Giraph based distributed label propagation algorithms on heterogeneous drug-related networks

Background and Objective: Heterogeneous complex networks are large graphs consisting of different types of nodes and edges. The knowledge extraction from these networks is complicated. Moreover, the scale of these networks is steadily increasing. Thus, scalable methods are required. Methods: In this paper, two distributed label propagation algorithms for heterogeneous networks, namely DHLP-1 and DHLP-2 have been introduced. Biological networks are one type of the heterogeneous complex networks. As a case study, we have measured the efficiency of our proposed DHLP-1 and DHLP-2 algorithms on a biological network consisting of drugs, diseases, and targets. The subject we have studied in this network is drug repositioning but our algorithms can be used as general methods for heterogeneous networks other than the biological network. Results: We compared the proposed algorithms with similar non-distributed versions of them namely MINProp and Heter-LP. The experiments revealed the good performance of the algorithms in terms of running time and accuracy.Comment: Source code available for Apache Giraph on Hadoo