CS4513 Distributed Computer Systems Introduction (Ch 1:

CS4513 Distributed Computer Systems Introduction (Ch 1: 1.1-1.2, 1.4-1.5)

Outline Overview Goals Software Client Server

The Rise of Distributed Systems Computer hardware prices falling, power increasing – If cars the same, Rolls Royce would cost 1 dollar and get 1 billion miles per gallon (with 200 page manual to open the door) Network connectivity increasing – Everyone is connected with fat pipes It is easy to connect hardware together Definition: a distributed system is – A collection of independent computers that appears to its users as a single coherent system.

Definition of a Distributed System Examples: -The Web -Processor Pool -Airline Reservation A distributed system organized as middleware. Note that the middleware layer extends over multiple machines. Users can interact with the system in a consistent way, regardless of where the interaction takes place

Transparency in a Distributed System Transparency Description Access Hide differences in data representation and how a resource is accessed Location Hide where a resource is located Migration Hide 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 Failure Hide the failure and recovery of a resource Persistence Hide whether a (software) resource is in memory or on disk Different forms of transparency in a distributed system.

Scalability Problems As distributed systems grow, centralized solutions are limited – Consider LAN name resolution vs. WAN Concept Example Centralized services A single server for all users Centralized data A single on-line telephone book Centralized algorithms Doing routing based on complete information Sometimes, hard to avoid (consider a bank) Need to collect information in distributed fashion and distributed in a distributed fashion Challenges: – geography, ownership domains, time synchronization

Scaling Techniques: Hiding Communication Latency Especially important for interactive applications If possible, do asynchronous communication - Not always possible when client has nothing to do Instead, can hide latencies

Scaling Techniques: Distribution 1.5 Example: DNS name space into zones (nl.vu.cs.fluit – z1 gives address of vu gives address of cs) Example: The Web

Scaling Techniques: Replication Copy of information to increase availability and decrease centralized load – Example: P2P networks (Gnutella ) distribute copies uniformly or in proportion to use – Example: akamai – Example: Caching is a replication decision made by client Issue: Consistency of replicated information – Example: Web Browser cache

Outline Overview Goals Software Client Server (done) (done)

Software Concepts System Description Main 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 Middlewar e Additional layer atop of NOS implementing general-purpose services Provide distribution transparency DOS (Distributed Operating Systems) NOS (Network Operating Systems) Middleware

Uniprocessor Operating Systems Separating applications from operating system code through a microkernel – Can extend to multiple computers

Multicomputer Operating Systems But no longer have shared memory – Can try to provide distributed shared memory Tough, coming up – Can provide message passing

Multicomputer Operating Systems (optional) Message passing primitives vary widely between systems – Example: consider buffering and synchronization (optional)

Multicomputer Operating Systems Synchronization point Send buffer Reliable comm. guaranteed? Block sender until buffer not full Yes Not necessary Block sender until message sent No Not necessary Block sender until message received No Necessary Block sender until message delivered No Necessary Relation between blocking, buffering, and reliable communications. These issues make synchronization harder. It was easier when we had shared memory. – So distributed shared memory

Distributed Shared Memory Systems 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 Issue: how large should page sizes be? What are the tradeoffs? Overall, DSM systems have struggled to provide efficiency and convenience (and been around 15 years) – For higher-performance, typically still do message passing – Likely will remain that way

Network Operating System OSes can be different (Windows or Linux) Typical services: rlogin, rcp – Fairly primitive way to share files

Network Operating System Can have one computer provide files transparently for others (NFS) – (try a “df” on the WPI hosts to see. Similar to a “mount network drive” in Windows)

Network Operating System Different clients may mount the servers in different places Inconsistencies in view make NOSes harder, in general for users than DOSes. – But easier to scale by adding computers

Positioning Middleware Network OS not transparent. Distributed OS not independent computers. – Middleware can help Much middleware built in-house to help use networked operating systems (distributed transactions, better comm, RPC) Unfortunately, many different standards

Middleware and Openness 1.23 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. – If different, compatibility issues – If incomplete, then users build their own or use lower-layer services (frowned upon)

Comparison between Systems Distributed OS Multiproc. Multicomp. Networ k OS Degree of transparency Very High High Low High Same OS on all nodes Yes Yes No No Number of copies of OS 1 N N N Basis for communication Shared memory Messages Files Model specific Resource management Global, central Global, distributed Per node Per node Scalability No Moderately Yes Varies Item Openness Closed Closed Open DOS most transparent, but closed and only moderately scalable NOS not so transparent, but open and scalable Middleware provides a bit more transparency than NOS Middleware -based OS Open

Outline Overview Goals Software Client Server (done) (done) (done)

Clients and Servers Thus far, have not talked about organization of processes – Again, many choices but most agree upon client-server If can do so without connection, quite simple If underlying connection is unreliable, not trivial Resend? What if receive twice Use TCP for reliable connection (apps on Internet) Not always appropriate for high-speed LAN connection (4513)

Example Client and Server: Header Used by both the client and server.

Example Client and Server: Server

Example Client and Server: Client One issue, is how to clearly differentiate

Client-Server Implementation Levels Example of an Internet search engine – UI on client – Processing can be on client or server – Data level is server, keeps consistency

Multitiered Architectures Thin client (a) to Fat client (e) – (d) and (e) popular for NOS environments

Multitiered Architectures: 3 tiers Server may act as a client – Example would be transaction monitor across multiple databases

Modern Architectures: Horizontal Rather than vertical, distribute servers across nodes – Example of Web server “farm” for load balancing – Clients, too (peer-to-peer systems)