Towards A Novel Architecture For Wide Area Data Caching And Replication Jaesoo

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  • 1. Towards a Novel Architecture for Wide-Area Data Caching and Replication presented by JaeSoo Jang Computer Communication Lab. Soongsil University Tel : 02-816-0689, Cellular : 0505-605-5858 [email_address]
  • 2. Contents
    • Introduction
    • Previous Work
    • Approach
    • Architecture
    • Example
    • Experiments
    • Conclusion and Future Work
    • Critiques
    • Question & Answer
  • 3. Introduction
    • To ensure fast and highly available access to internet services
      • Optimally locating data objects and service provision points in the network is critical.
      • Currently, caching and replication are widely used.
    • However, current caching and replication techniques should be reappraised because of the followings
      • Rapid growth of the internet
      • Increasing variety of clients demanding internet services
      • Phenomenon of hot-spots
      • Transient increases in user access patterns
  • 4. Previous Work (Con’t)
    • Caching
      • Client-pull
        • Browser-level caching
        • per-site proxy servers
        • caching hierarchies
          • increase the client latency for popular documents because the requests have to percolate through a large number of levels.
        • Some papers [WWW95, SDNE95] document the limitation of client-pull approaches.
      • Server-push (Data Dissemination)
        • This has been shown in paper [SPDP95], the authors are not aware of any such systems in wide spread use.
  • 5. Previous Work (Con’t)
    • Cache hierarchy
      • Hierarchical Web cache relation architecture
      • Each cache form peering relationship with neighboring cache
      • Kind of peering relationship
        • parent-child relationship, sibling relationship
    • Neighboring use ICP(Internet Cache Protocol) for cooperation and exchange message
  • 6. Previous Work (Con’t)
    • Replication among servers at a single location
      • DNS-based request distribution
      • Sites are forced to configure to handle the peak demand.
        • Much resources are wasted during periods of average demand.
    • Mirroring
      • require manual effort to setup and maintain the consistency of data.
      • The user has to select the mirror site to access.
    • Rent-A-Server (WebOS project [berkeley98])
      • dynamically spawn server clones and replicate the server data in response to changes in server load.
  • 7. Approach
    • Motivation
      • To minimize access time and conserve bandwidth, the dynamically replicated copies of the server must be located close to hot-spots in client access patterns.
      • But, currents approaches do not consider the client access patterns in determining the locations to spawn the server replicas.
    • We presents a dynamic caching and replication architecture that considers the temporal and geographical spikes in user demand.
      • Distributed computation of client access patterns
      • Using the access statistics for replication/migration
  • 8. Approach (Con’t)
    • Approach
      • Let’s use the network nodes
        • To compute the access patterns in a distributed fashion and sent to the server periodically
          • The network nodes can actually see the flow of client requests.
      • Let’s endow objects with intelligence
        • To make its own migration/replication decisions based on the access statistics
  • 9. Architecture
    • Design Goals
      • Design of a caching/replication system that obtains the user access patterns from the network to locate the data objects
        • The network utilization and access latency are optimized.
      • Making caching transparent
        • Clients do not have to choose proxies.
        • Caches do not have to be configured manually in a hierarchy.
  • 10. Architecture (Con’t)
    • Using Active Networks
      • In case wide-area caching and replication, network nodes are in an ideal position to determine the location of hot-spots in the access patterns of objects retrieved over the network.
  • 11. Architecture (Con’t)
    • Caching/Replication Model
  • 12. Architecture (Con’t)
    • Active Data Object (ADO)
      • Set of related files that may be transferred as a group
      • contain intelligence to make its own migration/replication decisions based on the access statistics obtained from the network.
    • Active Node
      • maintain state information about the accesses for various data objects.
      • have intelligence to periodically update server with access statistics for individual objects .
  • 13. Architecture (Con’t)
    • Process of caching/replication model
      • 1. The arrival of an update triggers the ADOs migration routine.
      • 2. ADOs migration routine analyzes the traffic information, and decides whether to migrate to the hot-spot region.
      • 3. The server transfer transfers the ADO to the corresponding cache in the hot-spot region.
      • 4. The caching server announces the presence of the ADO to its associated active node.
      • 5. Subsequent request for the object is routed to closer server by the associated active node.
  • 14. Architecture (Con’t)
    • Argument on additional overhead for active networking
      • Do the additional overhead for active networking outweigh the benefits for performance gains made by better replication?  No.
      • Requiring active processing only for requests for data objects and updates of access statistics keep the network performance penalty small.
      • The actual transfer of the data object content between client and server is performed by application-specific, non-active protocols (eq, HTTP, FTP)
  • 15. Example
    • “ ADO based Web Caching and Replication”
    • Implementation
      • Using Java applets
        • For identifying hot-spots in the client access patterns
        • For making the migration/replication decisions
      • ANTS(Active Node Transfer System)
        • Capsule based active networking toolkit written in Java
        • Capsules carry data and references to the code to be executed at active nodes
  • 16. Example (Con’t)
    • ANTS Capsule Types
      • Request Capsule
        • sent from clients to the server during connection initiations.
        • queries the active nodes it passed through.
      • Response Capsule
        • sent from the client from the active node when a hit occurs.
        • conveys the IP address of the ADO server holding the requested object.
      • Information Capsule
        • sent from the active node to the ADO server
          • when the demand for a data object held by ADO server exceeds the threshold of a server specified popularity modulus.
      • Register Capsule
        • sent from ADO servers to active nodes
          • to register an object held in the cache.
          • to refresh object entry periodically.
  • 17. Example (Con’t)
    • Capsule Processing in an Active Node
  • 18. Example (Con’t)
    • Capsule Processing (when a object is requested)
      • Common processing
        • 1. When the user input a URL, the client resolves the server name.
        • 2. The client send the IP address and the URL to a local active network daemon.
        • 3. A local active network daemon creates an request capsule and forward it towards the home server.
        • 4. When a request capsule arrives at a node, its forwarding routine queries the activity cache for the requested URL.
      • If a match is not found,
        • 5. The request capsule sets up an entry for the requested URL in the activity cache and increments the access count.
        • 6. The request capsule forwarded towards the home server.
      • If a match is found,
        • 5. A response capsule is sent back to the client with the IP address of that server holding the requested URL.
        • 6. The client proceeds to transfer the data.
  • 19. Example (Con’t)
    • Capsule Processing (which is performed periodically)
      • 1. The active node sends information capsules to the associated ADO servers with the access statistics.
      • 2. The arrival of the information capsule triggers the ADO control routine.
        • analyze the access statistics.
        • make a decision to migrate to a region of high demand.
      • 3. The server transfers the ADO to the caching server.
      • 4. The server sends an register capsule to the associated active node to create an entry for the URL in the active node’s activity cache.
  • 20. Experiments
    • Measurement
      • Client latency
      • Overheads associated with the active networking
    • Instrument of Experiments
      • Modified version of the Webpolygraph
        • polyclt
          • measure the client latency and the overheads.
          • request a single object repeatedly at rate of 1 request/second.
        • polysrv
          • response with a document selected from an exponential distribution with a mean size of 13KB.
          • simulate a wide area link by delaying the response by a normal distribution with mean 10 seconds and standard deviation 3 second.
  • 21. Experiments (Con’t)
    • Network Topology
    • Experiments
      • Caching threshold = 10
      • Number of clients = 1, 2, 5
  • 22. Experiments (Con’t)
    • Result
  • 23. Conclusion and Future Work
    • Conclusion
      • propose an Active Networks based architecture for improving caching/replication that operates by obtaining statistics from the network node to identify hot-spots in client access patterns.
    • Future Work
      • challenge the replication of dynamically generated content.
  • 24. Critiques
    • Good Points
      • Idea of using network nodes to identify hot-spots in client access patterns
    • Weak Points
      • This architecture cannot achieve good performance than a classical caching do.
      • Previous referenced work is too old.
      • Don’t consider cache consistency.
      • Don’t describe why caching threshold is a number of 10
    • Alternatives
      • Content Delivery Network (CDN)
  • 25.
    • Q&A
    Question & Answer