Offloading Content with Self-organizing Mobile Fogs

Mobile users in an urban environment access content on the internet from different locations. It is challenging for the current service providers to cope with the increasing content demand from a large number of collocated mobile users. In-network caching to offload content at nodes closer to users alleviate the issue, though efficient cache management is required to find out who should cache what, when and where in an urban environment, given nodes limited computing, communication and caching resources. To address this, we first define a novel relation between content popularity and availability in the network and investigate a node's eligibility to cache content based on its urban reachability. We then allow nodes to self-organize into mobile fogs to increase the distributed cache and maximize content availability in a cost-effective manner. However, to cater rational nodes, we propose a coalition game for the nodes to offer a maximum "virtual cache" assuming a monetary reward is paid to them by the service/content provider. Nodes are allowed to merge into different spatio-temporal coalitions in order to increase the distributed cache size at the network edge. Results obtained through simulations using realistic urban mobility trace validate the performance of our caching system showing a ratio of 60-85% of cache hits compared to the 30-40% obtained by the existing schemes and 10% in case of no coalition

Scalable cooperative caching algorithm based on bloom filters

This thesis presents the design, implementation and evaluation of a novel cooperative caching algorithm based on the bloom filter data structure. The new algorithm uses a decentralized approach to resolve the problems that prevent the existing solutions from being scalable. The problems consist of an overloaded manager, a communication overhead among clients, and a memory overhead on the global cache. The new solution reduces the manager load and the communication overhead by distributing the global cache information among cooperating clients. Thus, the manager no longer maintains the global cache. Furthermore, the memory overhead is decreased due to a bloom filter data structure. The bloom filter saves memory space in the global cache and makes the new algorithm scalable. The correctness of the research hypothesis is verified by running experiments on the caching algorithms. The experiment results demonstrate that the new caching algorithm maintains a low block access time as existing algorithms. In addition, the new algorithm decreases the manager load by the factor of nine. Moreover, the communication overhead is reduced by nearly a factor of six as a result of distributing the global cache to clients. Finally, the results show a significant reduction in the memory overhead which also contributes to the scalability of the new algorithm

Content storage and retrieval mechanisms for vehicular delay-tolerant networks

Vehicular delay-tolerant networks (VDTNs) were proposed as a novel disruptive network concept based on the delay tolerant networking (DTN) paradigm. VDTN architecture uses vehicles to relay messages, enabling network connectivity in challenging scenarios. Due to intermittent connectivity, network nodes carry messages in their buffers, relaying them only when a proper contact opportunity occurs. Thus, the storage capacity and message retrieving of intermediate nodes directly affects the network performance. Therefore, efficient and robust caching and forwarding mechanisms are needed. This dissertation proposes a content storage and retrieval (CSR) solution for VDTN networks. This solution consists on storage and retrieval control labels, attached to every data bundle of aggregated network traffic. These labels define cacheable contents, and apply cachecontrol and forwarding restrictions on data bundles. The presented mechanisms gathered several contributions from cache based technologies such as Web cache schemes, ad-hoc and DTN networks. This solution is fully automated, providing a fast, safe, and reliable data transfer and storage management, while improves the applicability and performance of VDTN networks significantly. This work presents the performance evaluation and validation of CSR mechanisms through a VDTN testbed. Furthermore it presents several network performance evaluations and results using the well-known DTN routing protocols, Epidemic and Spray and Wait (including its binary variant). The comparison of the network behavior and performance on both protocols, with and without CSR mechanisms, proves that CSR mechanisms improve significantly the overall network performance

데이터 집약적 응용의 효율적인 시스템 자원 활용을 위한 메모리 서브시스템 최적화

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 전기·컴퓨터공학부, 2020. 8. 염헌영.With explosive data growth, data-intensive applications, such as relational database and key-value storage, have been increasingly popular in a variety of domains in recent years. To meet the growing performance demands of data-intensive applications, it is crucial to efficiently and fully utilize memory resources for the best possible performance. However, general-purpose operating systems (OSs) are designed to provide system resources to applications running on a system in a fair manner at system-level. A single application may find it difficult to fully exploit the systems best performance due to this system-level fairness. For performance reasons, many data-intensive applications implement their own mechanisms that OSs already provide, under the assumption that they know better about the data than OSs. They can be greedily optimized for performance but this may result in inefficient use of system resources. In this dissertation, we claim that simple OS support with minor application modifications can yield even higher application performance without sacrificing system-level resource utilization. We optimize and extend OS memory subsystem for better supporting applications while addressing three memory-related issues in data-intensive applications. First, we introduce a memory-efficient cooperative caching approach between application and kernel buffer to address double caching problem where the same data resides in multiple layers. Second, we present a memory-efficient, transparent zero-copy read I/O scheme to avoid the performance interference problem caused by memory copy behavior during I/O. Third, we propose a memory-efficient fork-based checkpointing mechanism for in-memory database systems to mitigate the memory footprint problem of the existing fork-based checkpointing scheme; memory usage increases incrementally (up to 2x) during checkpointing for update-intensive workloads. To show the effectiveness of our approach, we implement and evaluate our schemes on real multi-core systems. The experimental results demonstrate that our cooperative approach can more effectively address the above issues related to data-intensive applications than existing non-cooperative approaches while delivering better performance (in terms of transaction processing speed, I/O throughput, or memory footprint).최근 폭발적인 데이터 성장과 더불어 데이터베이스, 키-밸류 스토리지 등의 데이터 집약적인 응용들이 다양한 도메인에서 인기를 얻고 있다. 데이터 집약적인 응용의 높은 성능 요구를 충족하기 위해서는 주어진 메모리 자원을 효율적이고 완벽하게 활용하는 것이 중요하다. 그러나, 범용 운영체제(OS)는 시스템에서 수행 중인 모든 응용들에 대해 시스템 차원에서 공평하게 자원을 제공하는 것을 우선하도록 설계되어있다. 즉, 시스템 차원의 공평성 유지를 위한 운영체제 지원의 한계로 인해 단일 응용은 시스템의 최고 성능을 완전히 활용하기 어렵다. 이러한 이유로, 많은 데이터 집약적 응용은 운영체제에서 제공하는 기능에 의지하지 않고 비슷한 기능을 응용 레벨에 구현하곤 한다. 이러한 접근 방법은 탐욕적인 최적화가 가능하다는 점에서 성능 상 이득이 있을 수 있지만, 시스템 자원의 비효율적인 사용을 초래할 수 있다. 본 논문에서는 운영체제의 지원과 약간의 응용 수정만으로도 비효율적인 시스템 자원 사용 없이 보다 높은 응용 성능을 보일 수 있음을 증명하고자 한다. 그러기 위해 운영체제의 메모리 서브시스템을 최적화 및 확장하여 데이터 집약적인 응용에서 발생하는 세 가지 메모리 관련 문제를 해결하였다. 첫째, 동일한 데이터가 여러 계층에 존재하는 중복 캐싱 문제를 해결하기 위해 응용과 커널 버퍼 간에 메모리 효율적인 협력 캐싱 방식을 제시하였다. 둘째, 입출력시 발생하는 메모리 복사로 인한 성능 간섭 문제를 피하기 위해 메모리 효율적인 무복사 읽기 입출력 방식을 제시하였다. 셋째, 인-메모리 데이터베이스 시스템을 위한 메모리 효율적인 fork 기반 체크포인트 기법을 제안하여 기존 포크 기반 체크포인트 기법에서 발생하는 메모리 사용량 증가 문제를 완화하였다; 기존 방식은 업데이트 집약적 워크로드에 대해 체크포인팅을 수행하는 동안 메모리 사용량이 최대 2배까지 점진적으로 증가할 수 있었다. 본 논문에서는 제안한 방법들의 효과를 증명하기 위해 실제 멀티 코어 시스템에 구현하고 그 성능을 평가하였다. 실험결과를 통해 제안한 협력적 접근방식이 기존의 비협력적 접근방식보다 데이터 집약적 응용에게 효율적인 메모리 자원 활용을 가능하게 함으로써 더 높은 성능을 제공할 수 있음을 확인할 수 있었다.Chapter 1 Introduction 1 1.1 Motivation 1 1.1.1 Importance of Memory Resources 1 1.1.2 Problems 2 1.2 Contributions 5 1.3 Outline 6 Chapter 2 Background 7 2.1 Linux Kernel Memory Management 7 2.1.1 Page Cache 7 2.1.2 Page Reclamation 8 2.1.3 Page Table and TLB Shootdown 9 2.1.4 Copy-on-Write 10 2.2 Linux Support for Applications 11 2.2.1 fork 11 2.2.2 madvise 11 2.2.3 Direct I/O 12 2.2.4 mmap 13 Chapter 3 Memory Efficient Cooperative Caching 14 3.1 Motivation 14 3.1.1 Problems of Existing Datastore Architecture 14 3.1.2 Proposed Architecture 17 3.2 Related Work 17 3.3 Design and Implementation 19 3.3.1 Overview 19 3.3.2 Kernel Support 24 3.3.3 Migration to DBIO 25 3.4 Evaluation 27 3.4.1 System Configuration 27 3.4.2 Methodology 28 3.4.3 TPC-C Benchmarks 30 3.4.4 YCSB Benchmarks 32 3.5 Summary 37 Chapter 4 Memory Efficient Zero-copy I/O 38 4.1 Motivation 38 4.1.1 The Problems of Copy-Based I/O 38 4.2 Related Work 40 4.2.1 Zero Copy I/O 40 4.2.2 TLB Shootdown 42 4.2.3 Copy-on-Write 43 4.3 Design and Implementation 44 4.3.1 Prerequisites for z-READ 44 4.3.2 Overview of z-READ 45 4.3.3 TLB Shootdown Optimization 48 4.3.4 Copy-on-Write Optimization 52 4.3.5 Implementation 55 4.4 Evaluation 55 4.4.1 System Configurations 56 4.4.2 Effectiveness of the TLB Shootdown Optimization 57 4.4.3 Effectiveness of CoW Optimization 59 4.4.4 Analysis of the Performance Improvement 62 4.4.5 Performance Interference Intensity 63 4.4.6 Effectiveness of z-READ in Macrobenchmarks 65 4.5 Summary 67 Chapter 5 Memory Efficient Fork-based Checkpointing 69 5.1 Motivation 69 5.1.1 Fork-based Checkpointing 69 5.1.2 Approach 71 5.2 Related Work 73 5.3 Design and Implementation 74 5.3.1 Overview 74 5.3.2 OS Support 78 5.3.3 Implementation 79 5.4 Evaluation 80 5.4.1 Experimental Setup 80 5.4.2 Performance 81 5.5 Summary 86 Chapter 6 Conclusion 87 요약 100Docto

Building Internet caching systems for streaming media delivery

The proxy has been widely and successfully used to cache the static Web objects fetched by a client so that the subsequent clients requesting the same Web objects can be served directly from the proxy instead of other sources faraway, thus reducing the server\u27s load, the network traffic and the client response time. However, with the dramatic increase of streaming media objects emerging on the Internet, the existing proxy cannot efficiently deliver them due to their large sizes and client real time requirements.;In this dissertation, we design, implement, and evaluate cost-effective and high performance proxy-based Internet caching systems for streaming media delivery. Addressing the conflicting performance objectives for streaming media delivery, we first propose an efficient segment-based streaming media proxy system model. This model has guided us to design a practical streaming proxy, called Hyper-Proxy, aiming at delivering the streaming media data to clients with minimum playback jitter and a small startup latency, while achieving high caching performance. Second, we have implemented Hyper-Proxy by leveraging the existing Internet infrastructure. Hyper-Proxy enables the streaming service on the common Web servers. The evaluation of Hyper-Proxy on the global Internet environment and the local network environment shows it can provide satisfying streaming performance to clients while maintaining a good cache performance. Finally, to further improve the streaming delivery efficiency, we propose a group of the Shared Running Buffers (SRB) based proxy caching techniques to effectively utilize proxy\u27s memory. SRB algorithms can significantly reduce the media server/proxy\u27s load and network traffic and relieve the bottlenecks of the disk bandwidth and the network bandwidth.;The contributions of this dissertation are threefold: (1) we have studied several critical performance trade-offs and provided insights into Internet media content caching and delivery. Our understanding further leads us to establish an effective streaming system optimization model; (2) we have designed and evaluated several efficient algorithms to support Internet streaming content delivery, including segment caching, segment prefetching, and memory locality exploitation for streaming; (3) having addressed several system challenges, we have successfully implemented a real streaming proxy system and deployed it in a large industrial enterprise

Dynamic organization schemes for cooperative proxy caching

In a generic cooperative caching architecture, web proxies form a mesh network. When a proxy cannot satisfy a request, it forwards the request to the other nodes of the mesh. Since a local cache cannot fulfill the majority of the arriving requests (typical values of the local hit ratio are about 30-50%), the volume of queries diverted to neighboring nodes can substantially grow and may consume considerable amount of system resources. A proxy does not need to cooperate with every node of the mesh due to the following reasons: (i) the traffic characteristics may be highly diverse; (ii) the contents of some nodes may extensively overlap; (iii) the inter-node distance might be too large. Furthermore, organizing N proxies in a mesh topology introduces scalability problems, since the number of queries is of the order of N/sup 2/. Therefore, restricting the number of neighbors for each proxy to k < N - 1 will likely lead to a balanced trade-off between query overhead and hit ratio, provided cooperation is done among useful neighbors. For a number of reasons the selection of useful neighbors is not efficient. An obvious reason is that web access patterns change dynamically. Furthermore, availability of proxies is not always globally known. This paper proposes a set of algorithms that enable proxies to independently explore the network and choose the k most beneficial (according to local criteria) neighbors in a dynamic fashion. The simulation experiments illustrate that the proposed dynamic neighbor reconfiguration schemes significantly reduce the overhead incurred by the mesh topology while yielding higher hit ratios compared to the static approach.published_or_final_versio

Improving the Performance of the Distributed File System through Anticipated Parallel Processing

In the emerging Big Data scenario, distributed File systems (DFSs) are used for storing and accessing information in a scalable manner. Many cloud computing systems use DFS as the main storage component. The Big Data applications de-ployed in cloud computing systems more frequently perform read operations and less frequently the write operations. So, improving the performance of read access has become an im-portant research issue in DFS. In the literature, many client side caching with appropriate pre fetching techniques are proposed for improving the performance read access in the DFS. A speculation-based approach which uses client side caching is also proposed in the literature for improving the performance of read access in the DFS. In this paper, we have proposed a new read algorithm for the DFS based on anticipated parallel processing. We have evaluated the per- formance of the proposed algorithm using mathematical and simulation methods and the results indicate that the pro-posed algorithm performs better than the speculation-based algorithm proposed in the literature