1. Ch. 1. Distributed System Models1 Ch. 1. Distributed System Models and Enabling Technologies 병렬처리로 고성능과 고처리 컴퓨팅 시스템을 연구 컴퓨터 클러스터, 서비스 - 지향 구조, 계산 그리드, P2P 망, 인터넷 클라우드, 사물 인터넷 The Internet of Things refers to uniquely identifiable objects (things) and their virtual representations in an Internet-like structure. 사물 인터넷

2. Ch. 1. Distributed System Models2 1.1 Scalable Computing over the Internet A parallel and distributed computing system uses multiple computers to solve large-scale problems over the Internet. 1.1.1 The Age of Internet Computing  The emergence of computing clouds instead demands high-throughput computing (HTC) systems built with parallel and distributed computing technologies.  The Platform Evolution The general computing trend is to leverage shared web resources and massive amounts of data over the Internet. Figure 1.1 illustrates the evolution of HPC and HTC systems. Supercomputers (massively parallel processors or MPPs) are gradually replaced by clusters of cooperative computers. (HPC 측면 ) Peer-to-peer (P2P) networks are formed for distributed file sharing and content delivery application. (HTC 측면 ) HTC paradigm pays more attention to high-flux computing. The main application for high-flux computing is in Internet searches and web services by millions or more users simultaneously.

3. Ch. 1. Distributed System Models3 HTC system HPC system P2P network Clusters or MPPs Computational and data grid Web 2.0 services Internet clouds Internet of Things 이질 노드들 동질 노드들 파일 공유 고속 분산제어집중제어 지리적 분산이질 클러스터들 서비스 지향 구 조 (SOA) RFID 와 센서들 가상화

4. Ch. 1. Distributed System Models4  Computing Paradigm Distinctions Centralized computing Parallel computing Distributed computing Cloud computing 1.1.2 Scalable Computing Trends and New Paradigms  Degree of Parallelism BLP(bit-level parallelism): Advancements in computer architecture were done by increasing bit- level parallelism. Increasing the word size reduces the number of instructions the processor must execute in order to perform an operation on variables whose sizes are greater than the length of the word.  Innovative Applications Table 1.1 Applications of HPS and HTS  The Trend toward Utility Computing Utility computing focuses on a business model in which customers receive computing resources from a paid service provider. All grid/cloud platforms are regarded as utility service providers. Cloud computing offers a broader concept than utility computing.

5. Ch. 1. Distributed System Models5 1.1.3 The Internet of Things and Cyber-Physical Systems  The Internet of Things The IoT refers to the networked interconnection of everyday objects, tools, devices, or computers. One can view the IoT as a wireless network of sensors that connected all things in our daily life. These things can be large or small and they vary with respect to time and place. The idea is to tag every object using RFID or related sensor or electronic technology such as GPS. In the IoT era, all objects and devices are instrumented, interconnected, and interacted with each other intelligently. This communication can be made between people and things or among the things themselves. Three communication patterns co-exist: namely H2H (human-to-human), H2T (human-to-thing), and T2T (thing-to-thing).  Cyber-Physical Systems A cyber-physical system (CPS) is the result of interaction between computational processes and the physical world. A CPS merges the “ 3C ” technologies of computation, communication, and control into an intelligent closed feedback system between the physical world and the information world.

6. Ch. 1. Distributed System Models6 1.2 Technologies for Network-Based Systems 1.2.1 Multicore CPUs and Multithreading Technologies  Advances in CPU Processors The architecture of a typical multicore processor (Fig. 1.5).  Multicore CPU and Many-Core GPU Architecture  Multithreading Technology Typical instruction scheduling patterns (Fig. 1.6) Only instructions from the same thread are executed in a super-scalar processor. Fine-grain multithreading switches the execution of instructions from different threads per cycle. Coarse-grain multi-threading executes many instructions from the same thread for quite a few cycles before switching to another thread,. The multicore CMP executes instructions from different threads completely. The SMT allows simultaneous scheduling of instructions from different threads in the same cycle. 1.2.3 Memory, Storage, and Wide-Area Networking  Storage-Area Interconnects A storage area network (SAN) connects servers to network storage, such as disk array. Network attached storage (NAS) connects client hosts directly to the disk arrays.

7. Ch. 1. Distributed System Models7 1.2.4 Virtual Machines and Virtualization Middleware  Today, to build large clusters, grids, and clouds, we need to access large amount of computing, storage, and networking resources in a virtualized manners.

8. Ch. 1. Distributed System Models8 1.2.5 Data Center Virtualization for Cloud Computing  Cloud computing is enables by the convergence of technologies in four areas. hardware virtualization and multi-core chips utility and grid computing SOA, Web 2.0, and WS mashups SOA(Service-Oriented Architecture) 는 비즈니스를 링크된 서비스 세트 또는 반복 가능한 비 즈니스 작업으로 변환하여 필요할 때 네트워크를 통해 액세스할 수 있도록 지원하는 IT 아 키텍처의 한 가지 스타일이다. autonomic computing and data center automation