Distributed System Models Most concepts are drawn from

Distributed System Models Most concepts are drawn from Chapter 2 © Pearson Education Most concepts are drawn from Chapter 1 © Pearson Education Dr. Christian Vecchiola Postdoctoral Research Fellow csve@unimelb. edu. au Cloud Computing and Distributed Systems (CLOUDS) Lab Dept. of Computer Science and Software Engineering The University of Melbourne

Distributed System Models Distributed Systems Principles and Paradigms Outline Ø Introduction Ø Architectural Models – – Characterization Software Layers System Architectures Design Challenges/Requirements Ø Fundamental Models – Interaction – Failure – Security Ø Summary

Distributed System Models Distributed Systems Principles and Paradigms Introduction

Distributed System Models Distributed Systems Principles and Paradigms Introduction Ø Overview – Distributed system models helps in… • . . classifying and understanding different implementations • . . identifying their weaknesses and their strengths • . . crafting new systems outs of pre-validated building blocks – We will study distributed system models from different perspectives • Structure, organization, and placement of components • Interactions • Fundamental properties of systems

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø Characterization – The structure and the organization of systems and the relationship among their components should be designed with the following goals in mind: • To cover the widest possible range of circumstances. • To face the possible difficulties and threats. • To meet the current and possibly the future demands. – Architectural models provide both: • a pragmatic starting point • a conceptual view to address these challenges. In terms of implementation models and basic blocks In terms of logical view of the system, interaction flow, and components

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø Characterization – Challenges (more…) • Widely varying models of use – High variation of workload, partial disconnection of components, or poor connection. • Wide range of system environments – Heterogeneous hardware, operating systems, network, and performance. • Internal problems – Non synchronized clocks, conflicting updates, various hardware and software failures. • External threats – Attacks on data integrity, secrecy, and denial of service.

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø Characterization – Observations • Widely varying models of use – The structure and the organization of systems allow for distribution of workloads, redundant services, and high availability. • Wide range of system environments – A flexible and modular structure allows for implementing different solutions for different hardware, OS, and networks. • Internal problems – The relationship between components and the patterns of interaction can resolve concurrency issues, while structure and organization of component can support failover mechanisms. • External threats – Security has to be built into the infrastructure and it is fundamental for shaping the relationship between components.

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø Characterization – What is an architectural model? An architectural model of a distributed system is concerned with the placement of its parts and the relationship between them. It defines the way in which the components of systems interact with one another and the way in which they are mapped onto an underlying network of computers.

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø Characterization – A Distributed System is ultimately composed by processes communicating over a network. – A first (rough) classification can be done by discriminating the process types: • • Server processes Client-Server Systems Client processes Peer-to-Peer Systems Peer processes (Possible variations and compositions) – Such classification leads to a first categorization of architectural models.

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø Characterization – Some Examples: • Client Server Model – Placement: two distinct roles (1 server, multiple clients) – Relationship: the server provide services, the clients consume them – Communication: asymmetric client • Peer-to-Peer Model server – Placement: one single role, the peer – Relationship: all the peer have the same responsibilities – Communication: symmetric peer

Distributed System Models Distributed Systems Principles and Paradigms Architectural Model Ø Characterization – Other models • Mobile Code based Systems – Code is dynamically moved among hosts » Web applets (Java, Flash) » Mobile agents – Security is a concern • Ad-hoc Systems (based on proximity networks) – High dynamism and volatility of system components – More heterogeneity in the devices connected to the system – Limited capabilities (often)

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø Software Layers – Despite the specific model used for describing/implementing a system a reference software architecture can be defined. – A software architecture. . • . . identifies the organization of a software system (single or multi-computer) • . . can be expressed in terms of cooperating – layers (very general, applicable to all the systems) – modules (for component-based systems) – services (more appropriate for DS and SOA)

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø Software Layers – Why layers? • Breaking up complexity • Decomposition of Layer N – functions – responsibilities • Different levels of abstraction • Well proven model – TCP/IP Stack – ISO/OSI Architecture Layer 1 Layer 0

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø Software Layers Middleware - Masks heterogeneity - Provides convenient programming model - Composed of distributed processes or objects - Communication support & resource sharing – Layers in Distributed Systems Application & Services Middleware Operating System Computer and Network Hardware - RPC / RMI - Event notification - Shared data placement/retrieval/replication -Examples - CORBA / Microsoft DCOM - Java RMI /. NET Remoting - Web Services - ISO/ITU-T RM-ODP Platform - Comprises mostly hardware and OS - Provides basic services to upper level: - Process communication - Process coordination and management - Resource management - Examples: - Intel x 86/Windows - Intel x 86/Solaris - Power. PC/Mac OS X, Intel x 86/MAC OS X - Intel x 86/Unix(Linux)….

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø Software Layers – Middleware • Common stratus for developing application services • Infrastructure component that ties together the different parts of the distributed system • Modern examples – – – Sun J 2 EE Microsof. NET IBM Web. Sphere IBM Blue. Cloud Manjrasoft Aneka Google App. Engine Cloud Computing Platforms (Paa. S)

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø System Architectures – Middleware is the layer where most of the architectural model realizations take place. – A layered architecture allows for a partition of responsibilities among the different layers of the system. – At the middleware level a further distribution of responsibilities and functions between components takes place.

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø System Architectures – Different architectural models partition such responsibilities in different ways. – This partitioning has an impact on: • Performance • Reliability • Security – In deciding how to make this partitioning several tradeoffs apply. – We will investigate the different advantages/disadvantages of the most common models.

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø Software Architectures – Client Server Model • Mostly cited in the case of distributed systems. • Most widely employed. • Based on: – Two roles: server and client – Communication pattern: » asymmetric » request (client) – response (server) • Examples – HTTP, SMTP, DNS, NNTP

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø Software Architectures – Client Server Model t 4 Client t 2 Server t 1 t 3 Time t 1: request time t 2: server process time t 3: response time t 4: roundtrip time

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø System Architectures – Client-Server • Two-tier model (classic) client server • Three-tier (when the server, becomes a client) client server Server/client • Multi-tier (cascade model) server client Server/client server

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø System Architectures – Peer-to-Peer Model • All the processes play a similar role. • No distinction between server and client that are played by each component. • Cooperative interaction. • Avoids centralization and potential SPOF • More difficult to manage • Provides a better scalable infrastructure (1000 s hosts) • Examples – P 2 P File sharing (Open. NAP, e. Mule, etc. . ) – Distributed Hash tables

Distributed System Models Distributed Systems Principles and Paradigms Architectural Model Ø System Architectures – Peer-to-Peer model peer peer

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø System Architecture – Variations of the previous two models • • Multiple Server (kind of multi-tiers) Cache and Proxy architectures Mobile Code Mobile Agents Network Computers Thin Clients Mobile devices and ad-hoc networking

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø System Architectures – Services provided by multiple servers • Extension of the Client-Server Model • A server response can be the result of – a cascade request-response (multi-tier model) – the collaboration of several processes which might be » partitioned in several nodes » replicated in several nodes • Examples: – Web page content as composition of… » Database queries » Static content embedding » Web Service calls

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø System Architectures – Proxy Servers and Caches • A cache is a store of recently used data object that is closer than the object themselves. • Proxy servers uses caches to maintain a copy of the content that is frequently accessed, in order to – – increase availability of content increase the performance of requests serving reduce the traffic load on a wider scale make accessible content, not accessible otherwise (e. g. firewalls)

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø System Architectures – Proxy Servers and Caches • Examples – Web Browser cache » The web browser maintains copies of the recently visited pages on a local store » This version of the pages is returned to the use r when he or she looks for the same page » Specific HTML tags can control the validity of the cached web pages – Web Proxy Server » The caching mechanism is similar. .

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø System Architectures – Proxy Servers and Caches • Caching in action! 1 st Request 2 nd Request

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø System Architectures – Mobile Code • Mobile code generally refers to an application, component, or a program that can migrate during its life cycle. • To certain extent, it is also considered mobile code, a software component that is dynamically downloaded and integrated to an existing application. – Example: » Applet or Flash in a browser. » Dynamic plug-ins.

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø System Architectures – Mobile Code – Applet model Browser process space Server Client

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø System Architectures – Mobile Agents • Mobile Agents incarnate a better example of mobile code. • They are programs that can migrate among different hosts, during their life cycle and carry their computation along the way. • Main problem with mobility: – reconstruction of state • Two main models: – Strong mobility full state persistence (stack frame) – Weak mobility partial state persistence (checkpointing)

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø System Architectures – Mobile Agents • Possible uses of mobile agents: – Information collection – Computation locality » Mobile agents can move computation in situ » This approach is useful when the data size is huge • Disadvantages – Security threats (host and guest) – Compatibility of the hosting environment

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø System Architectures – Network Computer and Thin Clients • Network computers provide terminals – whit the minimum required software installed locally – that download operating systems and application software from a remote file server • In this model: – Applications are run locally – Files (and data in general) are managed remotely – A minimal computational capacity (memory and CPU) is required.

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø System Architectures – Network Computer and Thin Clients • Thin Client constitute a software layer that provide a GUI access to a remote machine where application are executed. • Comparison with Network Computers – Same management costs – No download of OS and software locally • Disadvantage: – Low performance for highly demanding graphical applications. • Example: – X-11, VNC, Remote Desktop. .

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø System Architectures – Mobile devices and spontaneous interoperation • Mobile devices involve mobile hardware and not mobile software. • Mobile devices – migrate among different computing environments – adapt themselves/ integrate with existing environment • Main problems – – Mobnility Trasparency Variable connectivity Relocation of services Transition between different networks Context Awareness & Discoverability of services Spontaneous Interaction

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø Interfaces and Objects – A distributed systems is a set of cooperating processes. – Processes communicate among each others • At low level – Message passing – Raw communication with sockets • At high level – By using specific and well defined interfaces – Remote Objects This patterns provides a more flexible and dynamic partitioning of the responsibilities if compared to the static Client-Server model.

Distributed System Models Distributed Systems Principles and Paradigms Design Requirements

Distributed System Models Distributed Systems Principles and Paradigms Design Requirements Ø Distributed Architectures Challenges – Main goal of DS: Sharing Resources – History: • • • 1960 – First Timesharing systems 60 s – Multiuser operating systems (UNIX) 70 s – 80 s First Distributed Systems (devices sharing) 80 s Clusters 90 s Grids …. Clouds – Still today… Sharing data & resources on a large scale is still a challenge!

Distributed System Models Distributed Systems Principles and Paradigms Design Requirements Ø Distributed Architecture Challenges – In particular the following aspects have to be considered: • • Performance Quality of Service Data and Replica management (caching) Dependability

Distributed System Models Distributed Systems Principles and Paradigms Design Requirements Ø Performance Issues – They arise from the limited processing and communicating capacities of computers and networks. – What to consider: • Responsiveness – Interactive application need to be responsive – Bottlenecks can be at each level of the communication stack • Throughput – This is a common measure for DS – Heterogeneity in a DS may affect throughput • Load-balancing – DS allow for concurrent execution without competition – Lack of competition can be obtained by » decentralizing processing » data & services replication

Distributed System Models Distributed Systems Principles and Paradigms Design Requirements Ø Quality of Service – Qo. S concerns non-functional properties of the system. – By non-functional we mean that: • A Qo. S evaluation is not intended to verify whether a operates correctly from a logical point of view. • A Qo. S evaluation provides insights on the behavior of the system from the point of view of parameters that characterize how a service operating correctly performs its task. – Example - File Server: • a functional parameter might be the capability of retrieving a file • Qo. S parameters are: guaranteed bandwidth, reliability

Distributed System Models Distributed Systems Principles and Paradigms Design Requirements Ø Quality of Service – Parameters of interest for Distributed Systems • Reliability & Security: – How much the system is robust? – What are the security measures put in place (protocols, standards, encryption level)? • Performance – Throughput, load balancing, responsiveness. • Adaptability – How much the system is able to meet the changing requirements?

Distributed System Models Distributed Systems Principles and Paradigms Design Requirements Ø Data Replication and Caching – Performance is the major issue in DS deployment – How can we address performance loss? • Data replication and load balancing – We can increase throughput • Data caching – We can reduce the service time Data caching poses the problem of obsolete information and different strategies can be implied to avoid the use of content not anymore valid.

Distributed System Models Distributed Systems Principles and Paradigms Design Requirements Ø Data Replication and Caching – Obsolete content detection and management • The web caching protocol uses two strategies – Cache validation – Expiration time on cache content • How they work – Each content maintained in the cache has an expiry date. – The expiry date of a cached item can be checked against the server, which will return a fresh copy in case of expiration. – The browser or the proxy do not need to check every time: » Server sends current time and expiry time for response » Browser (proxy) can estimate whether to request a fresh copy or not.

Distributed System Models Distributed Systems Principles and Paradigms Design Requirements Ø Dependability – What is dependability? “The value showing the reliability of a person to others because of his/her integrity, truthfulness, and trustfulness, traits that can encourage someone to depend on him/her. ” – In systems engineering… “. . the trustworthiness of a computing system which allows reliance to be justifiably placed on the service it delivers. . ” [IFIP 10. 4 Working Group on Dependable Computing] “ dependability (is) the collective term used to describe the availability performance and its influencing factors : reliability performance, maintainability performance and maintenance support performance” [Technical Committee 56 Dependability – IEC]

Distributed System Models Distributed Systems Principles and Paradigms Design Requirements Ø Dependability – In other words… How much we can trust, rely on a system? – How can we measure dependability? • Attributes: Availability, Reliability, Safety, Integrity, Confidentiality, Maintainability. – What tampers dependability? • Threats: Faults, Errors, Failures. – What can we do to ensure dependability? • Means: Prevention, Fault-tolerance, Forecasting.

Distributed System Models Distributed Systems Principles and Paradigms Design Requirements Ø Dependability – In particular… • Fault tolerance: – Dependable application in order to be reliable should keep operating in the presence of hardware, software, and network faults. – In order to achieve reliability, redundancy (i. e. data & services replication, message retransmission) is applied. • Security: – Sensitive data must be placed only on hosts that can actively respond to attacks, and safely protect information.

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø A different perspective… – Architectural Models • Internal organization, placement of components, and interaction patterns – Design Requirements • Thoughts on performance and reliability characteristics of distributed systems – Fundamental Models • Based on the fundamental properties that can give insights on – characteristics of the system – associated failure an security risks it might exhibit

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø What is a model? – It provides only essential elements to consider for reasoning and understanding the system behavior. – Addresses the following questions: • What are the main entities in the system? • How do they interact? • What are the characteristic that affect their individual and collective behavior? – We use a model for… • Making relevant assumptions about the system modeled. • Making generalizations concerning what is possible or not possible. These generalization assume the form of algorithms or properties that are guaranteed (i. e. dependent on logical analysis or mathematical proof)

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Aspect to consider for DS – Interaction • DS are constituted by interacting processes • Interaction can be: – Communication (message passing) – Coordination (information flow) – Failure • Faults occurs usually in distributed environment • A classification of them helps understanding the weakness of the systems and the possible counter-actions. – Security • Modularity and openness expose the system to threats • It is necessary to classify the attacks and devises potential resistance measures.

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Interaction Model – Facts: • Communication takes place with delays (often of considerable duration) • Delays and the absence of global time limit the accuracy with which we can coordinate processes. – What are the element of interest? • • Performance Communication Channels Computer Clocks and Timing Events Synchronous vs Asynchronous models Event Ordering

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Interaction Model – Performance Communication Channels • Various implementations • In general the following elements are important: – Latency » Time taken for transmitting the first bit of a string of bytes » Delay in accessing the network (varies according to load) » Time taken by communication service and OS for processing – Bandwidth » Total amount of information transmissible in the unit of time – Jitter » Variation in the time taken to deliver a message

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Interaction Model – Computer Clocks and Timing Events • Each computer has its own internal clock. • Two processes running on different computers will end up to have a different clock (and timestamps for events) • Computer clocks drift from the perfect time at different rates. • Without corrections such clocks will vary considerably over a long period of time. • Possible solutions: – GPS (ok for open spaces) – Timing protocols (variable to message delays)

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Interaction Model – Synchronous vs Asynchronous Models • Synchronous Systems (Assumptions) – Process step execution time has known lower and upper bounds. – Each message transmission over a channel has a bounded time. – Local clock drift rate from real time has a known bound. • Asynchronous Systems – None of the previous assumptions are valid. – Heterogeneity in all of the three aspects. • Observations: – It is possible to suggest likely upper and lower bound. – It is very difficult to provide accurate realistic values. – The use of synchronous system models is not realistic but might be helpful in designing initial versions of the system.

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Interaction Model – Event Ordering • Sequence of events is important • The execution of a system can be described in terms of the sequence of events that occur in it • Clocks cannot be synchronized perfectly across a distributed system. • It is possible to order events in the absence of global clock?

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Interaction Model – Event Ordering – The meeting problem send X m 1 Y send receive m 2 receive Z A send receive Z X Y Re: Meeting Can A reconstruct the proper sequence? m 3 receive t 1 Inbox of A: … 23 24 25 receive …. t 2 t 3 receive

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Interaction Model – Event Ordering • Logical Time (Lamport 1978) can help reconstruct the sequence ordering of events in absence of global clock. • A number is assigned to each event. • This number represents the logical order of the event in the sequence.

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Failure Model – What is failure? • Process and communication may depart from what is the expected behavior. – What is a failure model? • Defines the ways in which failure may occur in order to provide understanding of the effects it can cause. – Observations • Different kinds of failures can be addressed differently • Different kinds of failures denote different (major or minor) problems • Classification of failures is then important.

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Failure Model – Taxonomy of Failures • Applies to Processes and Communication • [Hadzilacos and Tueg, 1994] – Categorization: • Omission Failures • Arbitrary or Byzantine Failures • Timing Failures

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Failure Model – Omission Failures • Characterization – A process or a communication channel fails in performing what it is supposed to do. • Possible Types: – Process omission Failures » Process crashes (fail-stop if can be detected, complete crash or abnormal residual behavior? ) – Communication channel Omission Failures » Dropping messages (channel omission) » Send-omission failures » Receive-omission failures

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Failure Model – Arbitrary Failures or Byzantine Failures • Characterization – Worst possible failure semantics. – Any type of any error can occur. • Types: – Process arbitrary failures » Insertion of invalid data. » Invalid execution paths. – Channel arbitrary failures » Message content corruption » Unintended messages delivered » Duplication Difficult to detect by simply checking whether the process responds to the invocation. . Easily detectable by the communication software.

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Failure Model – Timing Failures • Synchronous Systems – An operation executes beyond its time limits. • Asynchronous Systems – Difficult to characterize, since there are no bounds on the time. • Solutions: – Real-time operating systems • Where to: – Multimedia computer with audio and video channels.

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Failover Model – Masking Failures • It is possible to construct reliable services from components that exhibit failures. • Failure detection is important to identify the wrong behavior and then provide a counter-measure – Data replication – Checksums and error correction – Message retransmissions • A failure can be … – … completely masked – … turned into an acceptable failure

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Security Model – The security of a distributed system can be achieved by • Securing the processes composing the system. • Securing the channels they use to communicate. • Protecting the objects they encapsulate by unauthorized access.

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Security Model – Protecting objects • Avoiding unauthorized access • Identifying – who is accessing what – what permission does he/she have on the object • Each service request operating on sensitive objects has to occur under a specific authority – Concept of Security Principal – Concept of Access Rights.

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Security Model – Protecting objects • Example Request + Credentials Sensitive Object User Internet <Untrusted Zone> Security Service Principal + Access Rights Server

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Security Model – Securing Processes and their Interactions • Process interact through – Message passing – Publicly available interfaces • Assumptions – The communication channel is untrusted – Potential misuses of the services exposed by the process • Observations – How can we protect processes from the enemy? – What are the potential threats?

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Security Model – Identifying the Enemy • Malicious entity (user or program) capable of – sending message through the network to any process – reading or copying any message between a pair of processes – impersonating one end point of the communication m 1 m 1’

Distributed System Models Distributed Systems Principles and Paradigms Architectural Models Ø Security Model – Classification of Threats • Threats to Processes – Impersonation (generation, alteration of network packets) – Threats to both servers (requests) and clients (responses) • Threats to Communication Channels – – Injection, alteration of messages Message copy Threats for privacy and integrity Countermeasure: secure channels • Denial of Service: generation of false request • Mobile Code: untrusted, unknown, potentially harmful

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Security Model – Countermeasures • Cryptography and shared secrets – Processes shared a secret helping them communicating safely – The shared secret can be used as key to encrypt messages over an unsecure channel – Cryptography: science of keeping message secures – Encryption: process of altering a message so that its content cannot be read by unintended receivers. • Authentication – The knowledge of the secret ensures the identity of both endpoints – The secret can be used to identify the sender

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Security Model – Countermeasures • Secure Channels – Encryption and Authentication can be used to build a secure channel. – A secure channel can be considered as a service layer on top of existing communication services. – It is a communication channel that connects a pair of processes, each of which acts on behalf of a principal. • Channel properties. – Each end point knows who resides on the other end point. – The channel ensures privacy and integrity of messages. – Each message includes a physical and logical time-stamp to prevent copies.

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Security Model – Use of Security Models • The techniques discussed in this section constitute the fundamental blocks to build a security infrastructure. • Additional issues arises in a real system – Performance vs Security: security measure introduce processing costs. – Other threats beyond the ones listed can be considered » Human factor » Geo-location • A careful analysis of all the aspects of a DS (hardware, software, network, and human) allows to build a threat model.

Distributed System Models Distributed Systems Principles and Paradigms Fundamental Models Ø Security Model – Use of Security Models • The threat model lists all the potential attacks that the systems might be exposed to. • Security costs have to be balanced against these attacks • Bottom line: – “how much your enemy is willing to pay to break your security? ”

Distributed System Models Distributed Systems Principles and Paradigms Summary

Distributed System Models Distributed Systems Principles and Paradigms Summary Ø What do we have learnt? – Architectural Models • An architectural model of a distributed system is concerned with the placement of its parts and the relationship between them. • It defines the way in which the components of systems interact with one another and the way in which they are mapped onto an underlying network of computers. – Design Requirements • Focus on performance, quality of service, dependability and security – Fundamental models • What is a model and its characteristics • 3 Fundamental models – Interaction model – Communication model – Security model

Distributed System Models Distributed Systems Principles and Paradigms Questions?