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Introduction. Chapter 1. The Textbook. Andrew S. Tanenbaum & Maarten van Steen, Distributed Systems: Principles and Paradigms, Prentice Hall, 2002. 全華科技圖書 , (03)401-5467, M: 0952296068. Grade Counting Rule. Midterm Exam 30% Final Exam 30%
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Introduction Chapter 1
The Textbook • Andrew S. Tanenbaum & Maarten van Steen, Distributed Systems: Principles and Paradigms, Prentice Hall, 2002. • 全華科技圖書, (03)401-5467, M: 0952296068
Grade Counting Rule • Midterm Exam 30% • Final Exam 30% • Roll call 10% (base grade 80, 5 times during the term) • Homework or Report 30% • TA: Semmer 孫瑞祥 3282,
Definition of a Distributed System (1) A distributed system is: A collection of independent computers that appears to its users as a single coherent system.
Definition of a Distributed System (2) 1.1 A distributed system organized as middleware.Note that the middleware layer extends over multiple machines.
The Goals of DS • Connecting Users and Resources: To make it easy for users to access, remote resources, and to share them with other users in a controlled way. • Transparency: To hide the act that its processes and resources are physically distributed across multiple computers. • Definition: A distributed system that is able to present itself to users and applications as if it were only a single computer system is said to be transparent. • Openness: A system that offers services according to standard rules that describe the syntax and semantics of those services. • Scalability:
Transparency in a Distributed System Different forms of transparency in a distributed system.
Scalability Problems Examples of scalability limitations.
Decentralized Algorithm’s Characteristics • No machine has complete information about the system state. • Machines make decisions based only on local information. • Failure of one machine does not ruin the algorithm. • There is no implicit assumption that a global clock exists. • No way to get a globally synchronized time. • In LAN, they are based on synchronous communication.
Scaling Techniques • There are three basic techniques for DS scaling: • Hiding communication latencies • Try to avoid waiting for responses to remote service requests as much as possible. • Using asynchronous communication. • Distribution • Splitting a component into smaller parts, and subsequently spreading those parts across the system. • For example, the Internet DNS • Replication • Divide attention • But caching and replication may lead to consistency problem.
Scaling Techniques (1) 1.4 • The difference between letting: • a server or • a client check forms as they are being filled
Scaling Techniques (2) 1.5 An example of dividing the DNS name space into zones.
Hardware Concepts 1.6 Different basic organizations and memories in distributed computer systems
Multiprocessors (1) • A bus-based multiprocessor. 1.7
Multiprocessors (2) • A crossbar switch • An omega switching network 1.8
Homogeneous Multicomputer Systems • System Area Networks (SANs) • The nodes are mounted in a big rack and are connected through a single, often high-performance interconnection network. • Two popular connection types of SAN • Mesh • Hypercube
Homogeneous Multicomputer Systems • Other samples • Massively Parallel Processors (MPPs) • Consisting of thousands of CPUs • High-performance interconnection network • Fault tolerance is required • Clusters of Workstations (COWs) • A collection of standard PCs or workstations connected through off-the-shelf communication components such as Ethernet.
Heterogeneous Multicomputer Systems • Distributed ASIC Supercomputer (DAS) • a wide-area distributed cluster designed by the Advanced School for Computing and Imaging (ASCI). • Consisting of four clusters of multicomputers (64 nodes each), interconnected through a ATM-switched backbone.
Software Concepts • Tightly-coupled • DOS (Distributed Operating Systems) • Used for managing multiprocessors and homogeneous multicomputers. • Loosely-coupled • NOS (Network Operating Systems) • Used for hetergeneous multicomputer systems • Distinction from traditional OS: local services are made available to remote clients. • Middleware
Distributed Operating Systems • Two types of DOSs • Multiprocessor operating system • Multicomputer operating system • Uniprocessor Operating System • Like a virtual machine to applications • Kernel mode • Can access memory and registers, and execute instructions • User mode • Memory and register access is restricted.
Uniprocessor Operating Systems • Separating applications from operating system code through • a microkernel. 1.11
Uniprocessor Operating Systems (cont.) • Benefits to using microkernels • Flexibility • A large part of the OS is executed in user mode, it is relatively easy to replaced a module without having to recompile or re-install the entire system. • Could be placed on different machines • Disadvantages of microkernels • Due to the well-entrenched status quo • Have extra communication overheads (about 20% performance degradation)
Multiprocessor Operating Systems (1) • A monitor to protect an integer against concurrent access. monitor Counter { private: int count = 0; public: int value() { return count;} void incr () { count = count + 1;} void decr() { count = count – 1;} }
Multiprocessor Operating Systems (2) • A monitor to protect an integer against concurrent access, but blocking a process. monitor Counter { private: int count = 0; int blocked_procs = 0; condition unblocked; public: int value () { return count;} void incr () { if (blocked_procs == 0) count = count + 1; else signal (unblocked); } void decr() { if (count ==0) { blocked_procs = blocked_procs + 1; wait (unblocked); blocked_procs = blocked_procs – 1; } else count = count – 1; } }
Multicomputer Operating Systems (1) • General structure of a multicomputer operating system 1.14
Multicomputer Operating Systems (2) • Alternatives for blocking and buffering in message passing. 1.15
Multicomputer Operating Systems (3) • Relation between blocking, buffering, and reliable communications.
Distributed Shared Memory Systems (1/3) • Programming multicomputers is much harder than programming multiprocessors • Reasons: buffering, blocking, and reliable communication, etc. • Solution: Emulating shared-memory on multicomputers system • Using virtual memory capability, which is referred to Distributed Shared Memory (DSM) • DSM is achieved by page-based distributed shared memory • Some problems caused by DSM • Data consistency • The trade-off of page size • Larger page size causes commun. cost when memory access false • Smaller page size may cause low memory hitting ratio • False sharing • Having data belonging to two independent processes in the same page
Distributed Shared Memory Systems (2/3) • Pages of address space distributed among four machines • Situation after CPU 1 references page 10 • Situation if page 10 is read only and replication is used
Distributed Shared Memory Systems (3/3) • False sharing of a page between two independent processes.
Network Operating System (2/4) • NOS • Contrast with DOS, NOS does not assume that the underlying hardware are homogeneous and that it should be managed as if it were a single system. • Different operating systems • Different kernels • Different hardware • More primitive than DOS • Compared to DOS • Drawbacks: hard to use • Login from on machine to another. • Copy files from one machine to another. • Changing a configuration such as password or settings. • Advantages: • Easy to add or remove a machine in NOS (they are highly independent of each other).
Network Operating System (2/4) • General structure of a network operating system. 1-19
Network Operating System (3/4) • Two clients and a server in a network operating system.
Network Operating System (4/4) • Different clients may mount the servers in different places.
Positioning Middleware • A synthetic solution between DOS and NOS: • Middleware: To place an additional layer of software between applications and the network operating system, offering a higher level of abstraction. • General structure of a distributed system as middleware.
Middleware Models • Remote Procedure Calls (RPCs) • Hiding network communication by allowing aprocess to call a procedure of which an implementation is located on a remote machine. • When calling a such procedure, parameters are transparently shipped to the remote machine where the procedure is subsequently executed, after which the results are sent back to the caller. • Distributed objects • Object itself located in a single machine • Making its interface available on other machines • Distributed documents • World wide web (WWW)
Middleware and Openness • In an open middleware-based distributed system, the protocols used by each middleware layer should be the same, as well as the interfaces they offer to applications. Fig. 1-23
Comparison between Systems • A comparison between multiprocessor operating systems, multicomputer operating systems, network operating systems, and middleware-based distributed systems.
Clients and Servers • General interaction between a client and a server.
An Example Client and Server (1) • The header.h file used by the client and server.
An Example Client and Server (2) • A sample server.
An Example Client and Server (3) • A client using the server to copy a file. 1-27 b
Processing Level • The general organization of an Internet search engine into three different layers 1-28
Multitiered Architectures (1) • Alternative client-server organizations (a) – (e). 1-29
Multitiered Architectures (2) • An example of a server acting as a client. 1-30
Modern Architectures • An example of horizontal distribution of a Web service. 1-31