Heon Young Yeom

MRBench: A Benchmark for MapReduce Framework

MapReduce is Googles programming model for easy development of scalable parallel applications which process huge quantity of data on many clusters. Due to its conveniency and efficiency, MapReduce is used in various applications (e.g., Web search services and online analytical processing). However, there are only few good benchmarks to evaluate MapReduce implementations by realistic testsets. In this paper, we present MRBench that is a benchmark for evaluating MapReduce systems. MRBench focuses on processing business oriented queries and concurrent data modifications. To this end, we build MRBench to deal with large volumes of relational data and execute highly complex queries. By MRBench, users can evaluate the performance of MapReduce systems while varying environmental parameters such as data size and the number of (map/reduce) tasks. Our extensive experimental results show that MRBench is a useful tool to benchmark the capability of answering critical business questions.

An efficient recovery scheme for mobile computing environments

This paper presents an efficient recovery scheme based on checkpointing and message logging for mobile computing systems. For the efficient management of checkpoints and message logs, a movement-based scheme is proposed. Mobile hosts carrying their recovery information to the nearby mobile support station can recover instantly in case of a failure, however, the cost to transfer the recovery information must be high. On the other hand, the recovery information remaining dispersed over a number of support stations visited by mobile hosts must incur very high recovery cost. To balance the failure-free operation cost and the recovery cost, in the proposed scheme, the recovery information of a mobile host remains at the visited support stations while the host moves within a certain range. Only when the host moves out of the range, the recovery information is transferred to a nearby mobile support station. As a result, the proposed scheme can control the information transfer cost as well as the recovery cost.

The performance of checkpointing and replication schemes for fault tolerant mobile agent systems

We evaluate the performance of checkpointing and replication schemes for the fault tolerant mobile agent system. For the quantitative comparison, we have implemented an experimental system on top of the Mole mobile agent system and also built a simulation system to include various failure cases. Our experiment aims to have the insight into the behavior of agents under two schemes and provide a guideline for the fault tolerant system design. The experimental results show that the checkpointing scheme shows a very stable performance; and for the replication scheme, some controllable system parameter values should be chosen carefully to achieve the desirable performance.

Providing VCR functionality in staggered video broadcasting

A true video-on-demand (TVoD) system allows users to view any video program, at any time, and perform any VCR function, but its per-user video delivery cost is very expensive. A near video-on-demand (NVoD) system uses a more scalable approach by batching multiple clients to a shared stream of broadcasting videos. Staggered video broadcasting, one of the NVoD techniques, broadcasts multiple streams of the same video at staggered times, with one stream serving multiple clients. In order to provide subscribers with a high-quality VoD service, it is desirable to add VCR functionality, such as fast forward and fast rewind, but it is not easy to provide VCR functionality in NVoD, especially a video broadcasting system where no dedicated or interactive channel is available. We analyze the conditions necessary to provide VCR functions and then propose a reception schedule that satisfies these conditions, with minimal resource requirements. Since our proposed scheme receives video frames as units, it can rapidly sustain a changing VCR action pattern. It is demonstrated, by simulation, that the scheme provides VCR functionality consistently with minimal buffer space.

A RESTful Approach to the Management of Cloud Infrastructure

Recently, REpresentational State Transfer (REST) has been proposed as an alternative architecture for Web services.In the era of Cloud and Web 2.0, many complex Web service-based systems such as e-Business an de-Government applications have adopted REST. Unfortunately, the REST approach has been applied to few cases in management systems, especially for a management system for cloud computing infrastructures.In this paper, we design and implement a RESTful Cloud Management System (CMS).Managed elements can be modeled as resources in REST and operations in existing systems can be evaluated using four methods of REST or a combination of them.We also show how components of existing management systems can be realized as REST-style Web services.

An efficient optimistic message logging scheme for recoverable mobile computing systems

A number of checkpointing and message logging algorithms have been proposed to support fault tolerance of mobile computing systems. However, little attention has been paid to the optimistic message logging scheme. Optimistic logging has a lower failure-free operation cost compared to other logging schemes. It also has a lower failure recovery cost compared to the checkpointing schemes. This paper presents an efficient scheme to implement optimistic logging for the mobile computing environment. In the proposed scheme, the task of logging is assigned to the mobile support station so that volatile logging can be utilized. In addition, to reduce the message overhead, the mobile support station takes care of dependency tracking and the potential dependency between mobile hosts is inferred from the dependency between mobile support stations. The performance of the proposed scheme is evaluated by an extensive simulation study. The results show that the proposed scheme requires a small failure-free overhead and the cost of unnecessary rollback caused by the imprecise dependency is adjustable by properly selecting the logging frequency.

An asynchronous recovery scheme based on optimistic message logging for mobile computing systems

This paper presents an asynchronous recovery scheme to provide fault-tolerance for mobile computing systems. The proposed scheme is based on optimistic message logging, since the checkpointing-only schemes are not suitable for the mobile environment in which unreliable mobile hosts and fragile network connection may hinder any kind of coordination for checkpointing and recovery. Also, in order to reduce the overhead imposed on mobile hosts, mobile support stations take charge of logging and dependency tracking, and mobile hosts maintain only a small amount of information for mobility tracking. As a result, truly asynchronous recovery for mobile systems can be achieved with little overhead.

A single phase distributed commit protocol for main memory database systems

Distributed databases systems need commit processing so that transactions executing on them still preserve the ACID property. With the advance of main memory database systems which become possible due to dropping price and increasing capacity of the RAM and CPU, the database processing speed has been increased in one order of magnitude. However, when it comes to distributed commit processing, it is still very slow since disk logging has to precede the transaction commit where the database access does not incur any disk access at all in the case of main memory databases. In this paper, we re-evaluate the various distributed commit protocols and come up with a single phase distributed commit protocol suitable for the distributed main memory database systems. Our simulation study confirms that the new protocol greatly reduces the time it takes to commit distributed transactions without any consistency problem.

A scalable lock manager for multicores

Modern implementations of DBMS software are intended to take advantage of high core counts that are becoming common in high-end servers. However, we have observed that several database platforms, including MySQL, Shore-MT, and a commercial system, exhibit throughput collapse as load increases, even for a workload with little or no logical contention for locks. Our analysis of MySQL identifies latch contention within the lock manager as the bottleneck responsible for this collapse. We design a lock manager with reduced latching, implement it in MySQL, and show that it avoids the collapse and generally improves performance. Our efficient implementation of a lock manager is enabled by a staged allocation and de-allocation of locks. Locks are pre-allocated in bulk, so that the lock manager only has to perform simple list-manipulation operations during the acquire and release phases of a transaction. De-allocation of the lock data-structures is also performed in bulk, which enables the use of fast implementations of lock acquisition and release, as well as concurrent deadlock checking.

Cashing in on the Cache in the Cloud

Over the past decades, caching has become the key technology used for bridging the performance gap across memory hierarchies via temporal or spatial localities; in particular, the effect is prominent in disk storage systems. Applications that involve heavy I/O activities, which are common in the cloud, probably benefit the most from caching. The use of local volatile memory as cache might be a natural alternative, but many well-known restrictions, such as capacity and the utilization of host machines, hinder its effective use. In addition to technical challenges, providing cache services in clouds encounters a major practical issue (quality of service or service level agreement issue) of pricing. Currently, (public) cloud users are limited to a small set of uniform and coarse-grained service offerings, such as High-Memory and High-CPU in Amazon EC2. In this paper, we present the cache as a service (CaaS) model as an optional service to typical infrastructure service offerings. Specifically, the cloud provider sets aside a large pool of memory that can be dynamically partitioned and allocated to standard infrastructure services as disk cache. We first investigate the feasibility of providing CaaS with the proof-of-concept elastic cache system (using dedicated remote memory servers) built and validated on the actual system, and practical benefits of CaaS for both users and providers (i.e., performance and profit, respectively) are thoroughly studied with a novel pricing scheme. Our CaaS model helps to leverage the cloud economy greatly in that 1) the extra user cost for I/O performance gain is minimal if ever exists, and 2) the providers profit increases due to improvements in server consolidation resulting from that performance gain. Through extensive experiments with eight resource allocation strategies, we demonstrate that our CaaS model can be a promising cost-efficient solution for both users and providers.