Introduction Chapter 1

Definition of a Distributed System A distributed system [Tannenbaum & Steen] can be defined as a collection of independent computers that appears to its users as a single coherent system.

Building a Distributed System –Development of powerful microprocessors –High speed computer networks –Cheap off the shelf components –The above three has resulted in feasible computer systems consisting of large number of computers connected by a high speed network

Organization of a Distributed System A distributed system organized as middleware. Note that the middleware layer extends over multiple machines. 1.1

Goals in Building a Distributed System –Connect users and resources Access and share resources in a controlled way –Transparent A system that presents itself as a single system –Open offers services according to commonly accepted standards –Scale Performance proportional to resources and system complexity

Connect Users and Resources Goals: Provide easy access to resources share costly resources in a controlled manner Challenges: security versus privacy violation

Transparency in a Distributed System Different forms of transparency in a distributed system. TransparencyDescription Access Hide differences in data representation and how a resource is accessed LocationHide where a resource is located MigrationHide that a resource may move to another location Relocation Hide that a resource may be moved to another location while in use Replication Hide that a resource may be shared by several competitive users Concurrency Hide that a resource may be shared by several competitive users FailureHide the failure and recovery of a resource Persistence Hide whether a (software) resource is in memory or on disk

Openness Goals: Interoperability: extent to which two different system implementations can work together by relying on each other’s services as specified by a common standard Portability: extent to which an application developed for system A can be executed on a system B that implements the same interfaces Extensible: easy to configure and add/replace components - separate mechanism from policy ( i.e. memory management)

Achieving Openness Services are generally specified through interfaces which are described in Interface Definition Language (IDL). For a distributed system to be inter-operable and portable the specifications should be complete and neutral

Scalabilty Scalability measured in terms of –Size: how the system scales by adding users and resources –Geography: the extent to which the users and resources are apart –Administration: the number of administrative domains

Centralized versus distributed services/algorithms Distributed services/algorithms - Machines make decision based on local information - no machine maintains complete system state - no single point of failure - no global clock Tradeoffs between centralized versus decentralized algorithms/services ConceptExample Centralized servicesA single server for all users Centralized dataA single on-line telephone book Centralized algorithmsDoing routing based on complete information

Problems in Scalability Local area networks are designed for synchronous communication Communication in WANs are unreliable and virtually point to point Many systems have centralized components Different administrative domains have conflicting policies for resource usage, management and security

Scaling Techniques –Use asynchronous communication Applications do not block Special handler needs to be set to handle interrupts on service completion Not a solution for interactive applications –Distribution splitting components and spreading them across (eg. DNS is split into domains and zones, distributing load in web servers) –Replication replicate components increases availability and balances load (Web servers, caching) Issues with consistency

Scaling Techniques (1) 1.4 The difference between letting: a)a server or b)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)A crossbar switch b)An omega switching network 1.8

Homogeneous Multicomputer Systems a)Grid b)Hypercube 1-9

Heterogeneous Multi-computer systems –Most existing distributed systems built on top of heterogeneous multi-computers –Inter-connection networks may also be heterogeneous –Sophisticated software is needed since these systems lack a global system view

Software Concepts An overview of DOS (Distributed Operating Systems) NOS (Network Operating Systems) Middleware SystemDescriptionMain Goal DOS Tightly-coupled operating system for multi- processors and homogeneous multicomputers Hide and manage hardware resources NOS Loosely-coupled operating system for heterogeneous multicomputers (LAN and WAN) Offer local services to remote clients Middleware Additional layer atop of NOS implementing general-purpose services Provide distribution transparency

Uniprocessor Operating Systems Separating applications from operating system code through a microkernel. 1.11

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. Synchronization pointSend buffer Reliable comm. guaranteed? Block sender until buffer not fullYesNot necessary Block sender until message sentNoNot necessary Block sender until message receivedNoNecessary Block sender until message deliveredNoNecessary

Distributed Shared Memory Systems (1) a)Pages of address space distributed among four machines b)Situation after CPU 1 references page 10 c)Situation if page 10 is read only and replication is used

Distributed Shared Memory Systems (2) False sharing of a page between two independent processes. 1.18

Network Operating System (1) General structure of a network operating system. 1-19

Network Operating System (2) Two clients and a server in a network operating system. 1-20

Network Operating System (3) Different clients may mount the servers in different places. 1.21

Positioning Middleware General structure of a distributed system as middleware. 1-22

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. 1.23

Comparison between Systems A comparison between multiprocessor operating systems, multicomputer operating systems, network operating systems, and middleware based distributed systems. Item Distributed OS Network OS Middleware- based OS Multiproc.Multicomp. Degree of transparencyVery HighHighLowHigh Same OS on all nodesYes No Number of copies of OS1NNN Basis for communication Shared memory MessagesFilesModel specific Resource management Global, central Global, distributed Per node ScalabilityNoModeratelyYesVaries OpennessClosed Open

Clients and Servers General interaction between a client and a server. 1.25

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

References Lecture slides of Distributed Systems principles and paradigms by Andrew Tannenbaum and Van Steen, Prentice Hall India, 2002.