Title:
Optimal Allocation of Clients to Replicated Multicast Servers
Optimal Allocation of Clients to Replicated Multicast Servers
Author(s)
Ammar, Mostafa H.
Zegura, Ellen W.
Fei, Zongming
Zegura, Ellen W.
Fei, Zongming
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Abstract
Server replication is an approach that is often used to improve the
scalability of a service. One of the important factors in the efficient
utilization of replicated servers is the ability to direct client requests
to the `best" server, according to some optimality criteria. Recently, there
have been several proposals for multicast services in which a server
delivers information to multiple clients simultaneously. Such proposals
include multicasting of web content, multicast-based video services
(on-demand and pay-per-view style services), multicasting of database
content and broadcast disks. The goal of many of these proposals is to use
multicast to enhance the ability of the service to handle a large number of
clients economically. Multicast servers may be replicated for several
reasons: to distribute the load among on-demand multicast servers, to
balance the `feedback" load on the servers or on entities along the
multicast tree from the servers, or to select the server that is at the root
of the `best" multicast routing tree. In this paper we first give a
definition of the static multicast server selection problem, in which we
assume a set of static clients and multicast servers and consider how one
might produce an optimalallocation of the clients to the servers. We propose
a transformation method for deriving multicast server selection algorithms
from the traditional multicast routing algorithms. To investigate the
dynamic behavior of client join and leave and the cost incurred during the
process, we next define the dynamic multicast server selection problem, in
which the potential clients join and leave the multicast session
dynamically, and the goal is to produce an optimal allocation of clients to
servers with an emphasis on how this allocation behaves over time. We
formulate the problem as a Markovian Decision Process (MDP) and analyze the
tradeoff between the cost of the multicast tree(s) and the transition cost
of establishing and removing links from the tree(s). We also explore the
effect of join/leave frequency on optimal policy. Our analysis leads to two
heuristics which we use to propose a selection algorithm. The algorithm
uses a very simple join and leave strategy yet still can generate low cost
trees. Our simulation compares the performance of our proposed algorithm
with various other multicast server selection algorithms.
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Date Issued
1999
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346081 bytes
Resource Type
Text
Resource Subtype
Technical Report