Electrical computers and digital processing systems: multicomput – Distributed data processing
Reexamination Certificate
2000-01-10
2004-07-27
Najjar, Saleh (Department: 2157)
Electrical computers and digital processing systems: multicomput
Distributed data processing
C709S220000, C709S221000, C709S222000, C709S226000
Reexamination Certificate
active
06769008
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to computer systems and, more particularly, to improved methods and apparatus for dynamically altering configuration of clustered computer systems.
2. Description of the Related Art
In contrast to single mainframe computing models of the past, more distributed computing models have recently evolved. One such distributed computing model is known as a clustered computing system.
FIG. 1
illustrates an exemplary clustered computing system
100
including computing nodes (nodes) A, B and C, storage devices (e.g., storage disks
102
-
104
), and other computing devices
106
-
110
representing other devices such as scanners, printers, digital cameras, etc. For example, each of the nodes A, B and C can be a computer with its own processor and memory. The collection of nodes A, B and C, storage disks
102
-
104
, and other devices
106
-
110
make up the clustered computing system
100
.
Typically, the nodes in a cluster are coupled together through a “private” interconnect with redundant pathways. As shown in
FIG. 1
, nodes A, B and C are coupled together through private communication channels
112
and
114
. For example, the private communication channels
112
and
114
can adhere to Ethernet, ATM, or Scalable Coherent (SCI) standards. A client
116
can communicate with the clustered computing system
100
via a network
118
(e.g., public network) using a variety of protocols such as Transmission Control Protocol (TCP), User Datagram Protocol (UDP), etc. From the point of view of the client
116
, the clustered computing system
100
is a single entity that can provide the client
116
with a variety of computer-implemented services, e.g., web-hosting, transaction processing, etc. In other words, the client
116
is not aware of which particular node(s) of the clustered computing system
100
is (are) providing service to it.
The clustered computing system
100
provides a scalable and cost-efficient model where off-the-shelf computers can be used as nodes. The nodes in the clustered computing system
100
cooperate with each other to provide a distributed computing model that is transparent to users, e.g., the client
116
. In addition, in comparison with single mainframe computing models, the clustered computing system
100
provides improved fault tolerance. For example, in case of a node failure within the clustered computing system
100
, other nodes can take over to perform the services normally performed by the node that has failed.
Typically, nodes in the clustered computing system
100
send each other “responsive” (often referred to as “heart beat” or activation) signals over the private communication channels
112
and
114
. The responsive signals indicate whether nodes are active and responsive to other nodes in the clustered computing system
100
. Accordingly, these responsive signals are periodically sent by each of the nodes so that if a node does not receive the responsive signal from another node within a certain amount a time, a node failure can be suspected. For example, in the clustered computing system
100
, if nodes A and B do not receive a signal from node C within an allotted time, nodes A and B can suspect that node C has failed. In this case, if nodes A and B are still responsive to each other, a two-node sub-cluster (AB) results. From the perspective of the sub-cluster (AB), node C can be referred to as a “non-responsive” node. If node C has really failed then it would be desirable for the two-node sub-cluster (AB) to take over services from node C. However, if node C has not really failed, taking over the services performed by node C could have dire consequences. For example, if node C is performing write operations to the disk
104
and node B takes over the same write operations while node C is still operational, data corruption can result.
It should be noted that the fact that nodes A and B have not received responsive signals from node C does not necessarily mean that node C is not operational with respect to the services that are provided by node C. Other events can account for why responsive signals for node C have not been received by nodes A and B. For example, the private communication channels
112
and
114
may have failed. It is also possible that node C's program for sending responsive signals may have failed but node C is fully operational with respect to the services that it provides. Thus, it is possible for the clustered computing system
100
to get divided into two or more functional sub-clusters wherein the sub-clusters are not responsive to each other. This situation can be referred to as a “partition in space” or “split brain” where the cluster no longer behaves as a single cohesive entity. In this and other situations, when the clustered computing system no longer behaves as a single cohesive entity, it can be said that the “integrity” of the system has been compromised.
In addition to partitions in space, there are other potential problems that need to be addressed in managing the operation of clustered computing systems. For example, another potential problem associated with operating clustered computing systems is referred to as a “partition in time” or “amnesia.” As is known to those skilled in the art, partitions in time can occur when a clustered computing system is operated with cluster configurations that vary over time.
One problem is that the conventional methods do not provide for techniques that allow alteration of configuration of the clustered computing systems dynamically. For example, adding a new node to a clustered computing system typically requires shutting down all the existing nodes in the clustered computing system in order to guard against undesired partitions in time or space. Similarly, removing a node typically requires shutdown of all other existing nodes in the clustered computing system.
In view of the foregoing, there is a need for techniques that enable dynamic configuration changes to clustered computing systems.
SUMMARY OF THE INVENTION
Broadly speaking, the invention relates to improved techniques for dynamically altering configurations of clustered computing systems. In one aspect, the improved techniques allow alteration of an existing configuration of a clustered computing system without having to completely shutdown the clustered computing system. Accordingly, components such as nodes or other devices (e.g., peripheral devices) can be added to, or removed from, the clustered computing system while one or more existing nodes remain active. As a result, the clustered computing system can provide uninterrupted services while the configuration of the clustered computing system is being dynamically altered, yet also safeguard against unwanted partitions in time or space.
The invention can be implemented in numerous ways, including a system, an apparatus, a method or a computer readable medium. Several embodiments of the invention are discussed below.
As a method for altering configuration of a clustered computing system, one embodiment of the invention includes the acts of: identifying a first component that is to be added to or removed from the clustered computing system, and updating component vote information associated with at least one active component of the clustered computing system while the at least one active component remains active.
As a method for altering configuration of a clustered computing system having at least one active component with associated configuration vote information, another embodiment of the invention includes the acts of: receiving a configuration alteration request for addition or removal of one or more components to or from the existing configuration of the clustered computing system; selecting one of the components associated with the configuration alteration request as a selected component; obtaining a vote for the selected component; updating the configuration vote information of the active component in accordance with the vote while the at least one active comp
Hisgen Andrew L.
Kumar Krishna
Murphy Declan J.
Beyer Weaver & Thomas LLP
Najjar Saleh
Sun Microsystems Inc.
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