3rd Edition Chapter 1

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					Routing and Scheduling in Web
       Server Clusters




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Reference
    The State of the Art in Locally
    Distributed Web-server Systems
  Valeria Cardellini, Emiliano Casalicchio, Michele Colajanni
                       and Philip S. Yu




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 Objectives
 Routing in Distributed Web-based Servers
     DNS-based routing mechanisms
     Web server routing mechanisms
 Dispatching Algorithms
 Content-blind algorithms
     Static
     Client aware
     Server aware
     Client and Server aware
 Content-aware algorithms
     Client aware
     Client and Server aware


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Routing in Distributed Web-based
Servers
 DNS-based routing mechanisms
    Handles multiple web servers hosting a Web site
    The idea is conceived for locally distributed web
     servers but it is also applicable for geographically
     distributed web servers
 Web server routing mechanisms
      Routing mechanisms are implemented by the web
       server
      Web servers can (re)direct a client request to another
       node




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DNS-based routing
 DNS-based routing intervenes at lookup phase
 The authoritative DNS (A-DNS) server can
  select a different server for every address
  resolution
 The A-DNS replies with (IP address, TTL)




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Web server routing
 Triangulation
 HTTP redirection
 URL rewriting




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Web server routing: Triangulation

 The client sends packets to the first contacted
  server
 The first node routes packets to a second
  server
      Routing is done at the TCP/IP level
 Triangulation is based on tunneling!




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Web server routing: HTTP redirection

 HTTP protocol allows a Web server to respond
  to a client request with some redirection status
  code
      HTTP has a built-in redirection mechanism
 HTTP redirection is good for
   Medium granularity down to individual Web pages
   Allowing content-aware routing

 Drawbacks
    Extra round-trip time




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Web server routing: HTTP redirection




                                   9
Web server routing: HTTP rewriting

 The first contacted server dynamically changes
  the links for the embedded objects within the
  Web page
 This approach is used by Akamai
 This approach introduces additional load on the
  redirecting Web server
 It also cause a considerable DNS overhead




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Dispatching Algorithms
Strategies to select the target server of the web
  clusters
 Static: Fastest solution to prevent web switch bottleneck,
  but do not consider the current state of the servers
 Dynamic: Outperform static algorithms by using intelligent
  decisions, but collecting state information and analyzing them
  cause expensive overheads
Requirements:        (1) Low computational complexity (2) Full
  compatibility with web standards (3) state information must be
  readily available without much overhead




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Content blind approach
   Static Policies:
    Random
    distributes the incoming requests uniformly with equal
    probability of reaching any server
    Round Robin (RR)
    use a circular list and a pointer to the last selected server to
     make the decision
    Static Weighted RR (For heterogeneous severs)
    A variation of RR, where each server is assigned a weight Wi
    depending on its capacity




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Content blind approach (Cont.)
 Dynamic
  Client state aware
 static partitioning the server nodes and to assign group
 of clients identified through the clients information, such
 as source IP address
 Server State Aware
    Least Loaded, the server with the lowest load.
    Issue: Which is the server load index?
         Least Connection
           fewest active connection first




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Content blind approach (Cont.)
 Server State Aware Contd.
   Fastest Response
      responding fastest
   Weighted Round Robin
   Variation of static RR, associates each server with a dynamically
     evaluated weight that is proportional to the server load
 Client and server state aware
 Client affinity
 instead of assigning each new connection to a server only on the basis of
  the server state regardless of any past assignment, consecutive
  connections from the same client can be assigned to the same server




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Considerations of content blind
 Static approach is the fastest, easy to implement,
  but may make poor assignment decision
 Dynamic approach has the potential to make
  better decisions, but it needs to collect and
  analyze state information, may cause high
  overhead
 Overall, simple server state aware algorithm is the
  best choice, least loaded algorithm is commonly
  used in commercial products




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Content aware approach
 Client state aware
 Cache Affinity
    The file space is partitioned among the server nodes.
 Load Sharing
 . SITEA (Size Interval Task Assignment with Equal Load)
    The web switch determines the size of the requested file and
    select the target server based on this information
 . CAP (Client-Aware Policy)
    The web switch requests are classified based on their impact on
    system resources: such as I/O bound, CPU bound




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Content aware approach (Cont.)
 Client state aware (Cont.)
  Service Partitioning
     Employs specialized servers for certain type of requests
 Client Affinity
     Using session identifier to assign all web transactions from the
    same client to the same server




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Content aware approach (Cont.)
 Client and server state aware
 LARD (Locality aware request distribution)
     Direct all requests of the same web object to the same server
    node as long as its utilization is below a given threshold.
 Cache Manager
     A cache manager that is aware of the cache content of all web
    servers.




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20
Fair Scheduling in Web Servers




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Objectives
 Create an arbitrary number of service
  quality classes and assign a priority weight
  for each class.
 Provide service differentiation for
  different use classes in terms of the
  allocation of CPU and disk I/O capacities




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Fair Scheduling in a Web Cluster:
Objective
 Provide service differentiation (or QoS
  guarantee) for different user classes in
  terms of the allocation of CPU and disk
  I/O capacities => Scheduling
 Balance the Load among various nodes in
  the cluster to ensure maximum utilization
  and minimum execution time => Load
  Balancing



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Request Scheduling
Two decisions:
 Which request should be serviced next
  (Scheduling)
 according to each subscriber’s static resource reservation
 and dynamic resource usage
 Which RPN should service this request
 (Load Balancing)
 according to the load information on each RPN (Least Load
 First) and also exploit access locality




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