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DM Rasanjalee Himali CSc8320 – Advanced Operating Systems (SECTION 2.6) FALL 2009
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The Basics
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A distributed system consist of concurrent processes accessing distributed resources Resources are shared through message passing in a network environment that may be unreliable and contain untrusted components.
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1. Object Models and Naming Schemes 2. Distributed Coordination 3. Interprocess Communication 4. Distributed Resources 5. Fault Tolerance and Security
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Objects in Computer System: ◦ Ex: Processes, data files, memory, devices, processors, networks ◦ Are represented by set of allowable operations of the object ◦ Physical details of the object are transparent to other objects Object Servers: ◦ Is the process that manages the object ◦ Objects are encapsulated in servers ◦ Only visible entities in the system are servers ◦ Ex: process servers, file servers, memory servers etc. ◦ A client is a null server that accesses the object server
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Identifying Server: ◦ To contact a server, server must be identifiable. ◦ Three identification methods: 1.Identification by name 2.Identification by physical or logical address 3.Identification by service that servers provide
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1. Identification by Name: ◦ Names are generally assumed to be unique ◦ But multiple addresses for same server may exist, and needs to change if server moves ◦ Names are more intuitive than addresses 2. Identification by physical or logical address ◦ Name to logical address mapping is done by name server in OS. ◦ logical address to physical address mapping is a network service ◦ The PORT used by many systems is a logical address. ◦ Associating more than one port to server provide multiple entry points to server 3. Identification by service that servers provide ◦ Multiple servers can share the same port ◦ This can be used for service identification in distributed system. ◦ Client is only interested in requested service ◦ Who provide the service is irrelevant ◦ Multiple servers can provide the same service ◦ This approach is critical to implement an autonomous system. ◦ A resolution protocol is needed to translate service to server
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Object models and naming : ◦ Must be addressed early in the system design as many things depend on the naming scheme: ◦ Ex: Structure of the system Management of the namespace Name resolution Access methods
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Interacting concurrent processes require coordination to achieve synchronization. Types of Synchronization Requirements: ◦ In general there are three types of synchronization requirements: 1.Barrier Synchronization ◦ A set of processes or events must reach a common synchronization point before they can continue 2.Condition coordination ◦ A process or event must wait for a condition that will be set asynchronously by other interacting processes to maintain some ordering of execution 3.Mutual Exclusion ◦ Concurrent processes must have mutual exclusion when accessing a critical shared resource
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Synchronization Implies the need for the knowledge of state information about other processes Problems with Synchronization: 1.Complete State of information is difficult to obtain ◦ Ex: ◦ no shared memory environment ◦ Solution: ◦ Use message passing to convey state information 2.Inaccurate or Incomplete information ◦ Ex: ◦ message transfer delays ◦ Solution: ◦ Use centralized coordinator that move from one process to another (no single point of failure)
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3.Deadlock of Processes Interacting processes can lead to deadlock Deadlock :Circular waiting of processors Problem: Sometimes it is not practical to implement deadlock prevention or avoidance strategies in a distributed system Solution: Detect and recover from deadlocks Problem: Detection of deadlocks in a distributed system is non-trivial (b’s global state of the system is not available) Who should initiate the detection algorithm? How the algorithm be implemented in distributed fashion by message passing? Who should be the victim in order to abort and resolve the deadlock? How the victim can be recovered? Efficiency of the of deadlock resolution and recovery seems more than that of detection
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Distributed solutions to synchronization and deadlock problems: ◦ Use partial global state for decision making Many applications do not need absolute global knowledge of the system ◦ Exchange of local knowledge among cooperating sites
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Communication: ◦ Most important issue in any distributed system ◦ In OSs, interaction between processes and information flow between objects depend on communication ◦ Message passing is the only means of communication in distributed system ◦ Goal: Have transparency in communication by providing higher level communication methods that hide the physical details of the message passing ◦ Two concepts are used to achieve this goal: Client/Server model Remote Procedure Calls (RPC)
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Client/Server model: ◦ Programming paradigm for structuring processing in distributed systems ◦ All system interactions are viewed as a pair of message exchanges Client process send request to server Server responds with a reply message Remote Procedure Calls: ◦ Client/Server request/reply message exchange is represented as a procedure call in programming languages ◦ RPC: Procedure call to a remote server
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Multicast and Broadcast: ◦ Client/Server, RPC : Unicast (point-to-point) ◦ Notion of “groups” is inherent to distributed systems ◦ Processes cooperate in group activities ◦ Group communication in distributed systems is logical multicast (perhaps without broadcasting hardware) ◦ Communication needs to go through several layers of protocols and be propagated to a no. of physically distributed nodes. ◦ Thus it is more susceptible to failures in the system ◦ Reliable and atomic group broadcast remains an open issue in distributed systems
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Only resource needed for computation are data and processing Data: may reside physically in distributed memory or secondary storage Processing Capacity: Aggregate processing power of all processors Goal: Achieve transparency in allocating processing capacity processes (distributing processes/load to the processors )
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Static Load Distribution: Also called multiprocessor scheduling Goal: minimize completion time of a set of related processes Issue: Communication overhead on design of scheduling strategies Dynamic Load Distribution: Also called load sharing Goal: Maximize utilization of set of processes Issue: Process migration
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Distributed Shared Memory: Transparent memory system Assume data resides in distributed memory modules Present single shared memory view of physically distributed memories Goal: Maximize transparency Other issues (for distributed file systems & distributed shared memory): Sharing & replication of data Need protocols to maintain consistency & coherency of data Existence of replicas should be transparent to the user
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Distributed systems are vulnerable to failures and security threats Failures: Faults due to unintentional intrusion Security Violations: Faults due to intentional intrusion Dependable Distributed System: Fault tolerant system System faults are transparent to the user
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Solution for Failures: Redundancy in the system: Is an inherent property of distributed systems as data and resources can be replicated Rollback: Recovery from failures requires rolling back the execution of failed process and other affected processes The execution state must be kept for rollback recovery (difficult task in distributed systems) Solution for Security: Issues : Trustworthiness of the communicating processes Confidentiality and integrity of messages & data Authentication & Authorization Solutions: Authentication : Clients, servers & messages must be authenticated Authorization : access control across physical network with heterogeneous components under different administrative units, using different security models
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Related Work
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Peer-to-Peer Networks: distributed network architecture composed of participants that make a portion of their resources available directly to their peers without intermediary network hosts or servers. Peers are both suppliers and consumers of resources ◦ Research: Security and privacy in P2P systems Resource discovery/management in P2P systems
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Peer-to-Peer Search BFS – Breadth First Search Random BFS (-) sacrifices performance and network utilization for simplicity (+) guarantees high hit rates at the expense of a large no. of messages (-) RBFS algorithm is probabilistic and the query might not reach some large network segments (+) does not require global knowledge
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Future Work
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Develop a model for P2P Search Bayesian Inferencing Value of Information Extend P2P search for P2P Web Search Most centralized Web search engines currently find it harder to catch up with the growth in information needs Local & decentralized global directory Semantic P2P Overlay Networks Node connections be influenced by content / existence of multiple overlay networks based on content Dynamic restructuring of overlay
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Randy Chow, Theodore Johnson, “Distributed Operating Systems & Algorithms”, Addison Wesley, 1997 Semantic Overlay Networks for P2P Systems, Arturo Crespo and Hector Garcia-Molina, 2002 Random walks in peer-to-peer networks: algorithms and evaluation, Christos Gkantsidis, Milena Mihail, Amin Saberi, 2006 www.en.wikipedia.com www.en.wikipedia.com
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