Cache policies for cloud-based systems: To keep or not to keep

In this paper, we study cache policies for cloud-based caching. Cloud-based caching uses cloud storage services such as Amazon S3 as a cache for data items that would have been recomputed otherwise. Cloud-based caching departs from classical caching: cloud resources are potentially infinite and only paid when used, while classical caching relies on a fixed storage capacity and its main monetary cost comes from the initial investment. To deal with this new context, we design and evaluate a new caching policy that minimizes the overall cost of a cloud-based system. The policy takes into account the frequency of consumption of an item and the cloud cost model. We show that this policy is easier to operate, that it scales with the demand and that it outperforms classical policies managing a fixed capacity.Comment: Proceedings of IEEE International Conference on Cloud Computing 2014 (CLOUD 14

Cloud Computing Trace Characterization and Synthetic Workload Generation

This thesis researches cloud computing workload characteristics and synthetic workload generation. A heuristic presented in the work guides the process of workload trace characterization and synthetic workload generation. Analysis of a cloud trace provides insight into client request behaviors and statistical parameters. A versatile workload generation tool creates client connections, controls request rates, defines number of jobs, produces tasks within each job, and manages task durations. The test system consists of multiple clients creating workloads and a server receiving request, all contained within a virtual machine environment. Statistical analysis verifies the synthetic workload experimental results are consistent with real workload behaviors and characteristics

Enhancing the Accuracy of Synthetic File System Benchmarks

File system benchmarking plays an essential part in assessing the file system’s performance. It is especially difficult to measure and study the file system’s performance as it deals with several layers of hardware and software. Furthermore, different systems have different workload characteristics so while a file system may be optimized based on one given workload it might not perform optimally based on other types of workloads. Thus, it is imperative that the file system under study be examined with a workload equivalent to its production workload to ensure that it is optimized according to its usage. The most widely used benchmarking method is synthetic benchmarking due to its ease of use and flexibility. The flexibility of synthetic benchmarks allows system designers to produce a variety of different workloads that will provide insight on how the file system will perform under slightly different conditions. The downside of synthetic workloads is that they produce generic workloads that do not have the same characteristics as production workloads. For instance, synthetic benchmarks do not take into consideration the effects of the cache that can greatly impact the performance of the underlying file system. In addition, they do not model the variation in a given workload. This can lead to file systems not optimally designed for their usage. This work enhanced synthetic workload generation methods by taking into consideration how the file system operations are satisfied by the lower level function calls. In addition, this work modeled the variations of the workload’s footprint when present. The first step in the methodology was to run a given workload and trace it by a tool called tracefs. The collected traces contained data on the file system operations and the lower level function calls that satisfied these operations. Then the trace was divided into chunks sufficiently small enough to consider the workload characteristics of that chunk to be uniform. Then the configuration file that modeled each chunk was generated and supplied to a synthetic workload generator tool that was created by this work called FileRunner. The workload definition for each chunk allowed FileRunner to generate a synthetic workload that produced the same workload footprint as the corresponding segment in the original workload. In other words, the synthetic workload would exercise the lower level function calls in the same way as the original workload. Furthermore, FileRunner generated a synthetic workload for each specified segment in the order that they appeared in the trace that would result in a in a final workload mimicking the variation present in the original workload. The results indicated that the methodology can create a workload with a throughput within 10% difference and with operation latencies, with the exception of the create latencies, to be within the allowable 10% difference and in some cases within the 15% maximum allowable difference. The work was able to accurately model the I/O footprint. In some cases the difference was negligible and in the worst case it was at 2.49% difference

Cross-Layer Peer-to-Peer Track Identification and Optimization Based on Active Networking

P2P applications appear to emerge as ultimate killer applications due to their ability to construct highly dynamic overlay topologies with rapidly-varying and unpredictable traffic dynamics, which can constitute a serious challenge even for significantly over-provisioned IP networks. As a result, ISPs are facing new, severe network management problems that are not guaranteed to be addressed by statically deployed network engineering mechanisms. As a first step to a more complete solution to these problems, this paper proposes a P2P measurement, identification and optimisation architecture, designed to cope with the dynamicity and unpredictability of existing, well-known and future, unknown P2P systems. The purpose of this architecture is to provide to the ISPs an effective and scalable approach to control and optimise the traffic produced by P2P applications in their networks. This can be achieved through a combination of different application and network-level programmable techniques, leading to a crosslayer identification and optimisation process. These techniques can be applied using Active Networking platforms, which are able to quickly and easily deploy architectural components on demand. This flexibility of the optimisation architecture is essential to address the rapid development of new P2P protocols and the variation of known protocols

A methodology for full-system power modeling in heterogeneous data centers

The need for energy-awareness in current data centers has encouraged the use of power modeling to estimate their power consumption. However, existing models present noticeable limitations, which make them application-dependent, platform-dependent, inaccurate, or computationally complex. In this paper, we propose a platform-and application-agnostic methodology for full-system power modeling in heterogeneous data centers that overcomes those limitations. It derives a single model per platform, which works with high accuracy for heterogeneous applications with different patterns of resource usage and energy consumption, by systematically selecting a minimum set of resource usage indicators and extracting complex relations among them that capture the impact on energy consumption of all the resources in the system. We demonstrate our methodology by generating power models for heterogeneous platforms with very different power consumption profiles. Our validation experiments with real Cloud applications show that such models provide high accuracy (around 5% of average estimation error).This work is supported by the Spanish Ministry of Economy and Competitiveness under contract TIN2015-65316-P, by the Gener- alitat de Catalunya under contract 2014-SGR-1051, and by the European Commission under FP7-SMARTCITIES-2013 contract 608679 (RenewIT) and FP7-ICT-2013-10 contracts 610874 (AS- CETiC) and 610456 (EuroServer).Peer ReviewedPostprint (author's final draft

Realistic Traffic Generation for Web Robots

Critical to evaluating the capacity, scalability, and availability of web systems are realistic web traffic generators. Web traffic generation is a classic research problem, no generator accounts for the characteristics of web robots or crawlers that are now the dominant source of traffic to a web server. Administrators are thus unable to test, stress, and evaluate how their systems perform in the face of ever increasing levels of web robot traffic. To resolve this problem, this paper introduces a novel approach to generate synthetic web robot traffic with high fidelity. It generates traffic that accounts for both the temporal and behavioral qualities of robot traffic by statistical and Bayesian models that are fitted to the properties of robot traffic seen in web logs from North America and Europe. We evaluate our traffic generator by comparing the characteristics of generated traffic to those of the original data. We look at session arrival rates, inter-arrival times and session lengths, comparing and contrasting them between generated and real traffic. Finally, we show that our generated traffic affects cache performance similarly to actual traffic, using the common LRU and LFU eviction policies.Comment: 8 page

A Detailed Analysis of Contemporary ARM and x86 Architectures

RISC vs. CISC wars raged in the 1980s when chip area and processor design complexity were the primary constraints and desktops and servers exclusively dominated the computing landscape. Today, energy and power are the primary design constraints and the computing landscape is significantly different: growth in tablets and smartphones running ARM (a RISC ISA) is surpassing that of desktops and laptops running x86 (a CISC ISA). Further, the traditionally low-power ARM ISA is entering the high-performance server market, while the traditionally high-performance x86 ISA is entering the mobile low-power device market. Thus, the question of whether ISA plays an intrinsic role in performance or energy efficiency is becoming important, and we seek to answer this question through a detailed measurement based study on real hardware running real applications. We analyze measurements on the ARM Cortex-A8 and Cortex-A9 and Intel Atom and Sandybridge i7 microprocessors over workloads spanning mobile, desktop, and server computing. Our methodical investigation demonstrates the role of ISA in modern microprocessors? performance and energy efficiency. We find that ARM and x86 processors are simply engineering design points optimized for different levels of performance, and there is nothing fundamentally more energy efficient in one ISA class or the other. The ISA being RISC or CISC seems irrelevant