AUTOMATIC
RECONFIGURATION FOR LARGE-SCALE RELIABLE
STORAGESYSTEMS
ABSTRACT:
Byzantine-fault-tolerant replication
enhances the availability and reliability of Internet services that store
critical state and preserve it despite attacks or software errors. However,
existing Byzantine-fault-tolerant storage systems either assume a static set of
replicas, or have limitations in how they handle reconfigurations (e.g., in
terms of the scalability of the solutions or the consistency levels they
provide). This can be problematic in long-lived, large-scale systems where
system membership is likely to change during the system lifetime.
In this paper, we present a complete
solution for dynamically changing system membership in a large-scale
Byzantine-fault-tolerant system. We present a service that tracks system
membership and periodically notifies other system nodes of membership changes.
The membership service runs mostly automatically, to avoid human configuration
errors; is itself Byzantine fault- tolerant and reconfigurable; and provides
applications with a sequence of consistent views of the system membership.
We demonstrate the utility of this
membership service by using it in a novel distributed hash table called dBQS
that provides atomic semantics even across changes in replica sets. dBQS is
interesting in its own right because its storage algorithms extend existing
Byzantine quorum protocols to handle changes in the replica set, and because it
differs from previous DHTs by providing Byzantine fault tolerance and offering
strong semantics.
We implemented the membership service
and dBQS. Our results show that the approach works well, in practice: the
membership service is able to manage a large system and the cost to change the
system membership is low.
EXISTING
SYSTEM:
In Existing System, replication enhanced
the reliability of internet services to store the data’s the preserved data to
be secured from software errors. But, existing Byzantine-fault tolerant systems
is a static set of replicas. It has no limitations. So, scalability is
inconsistency. So, these data’s are not came for long-lived systems. The
existence of the following cryptographic techniques that an adversary cannot subvert:
a collision resistant hash function, a public key cryptography scheme, and forward-secure
signing key and the existence of a proactive threshold signature protocol.
PROPOSED
SYSTEM:
In Proposed System, has two parts. The
first is a membership service (MS) that tracks and responds to membership
changes. The MS works mostly automatically, and requires only minimal human
intervention; this way we can reduce manual configuration errors, which are a
major cause of disruption in computer systems periodically, the MS publishes a
new system membership; in this way it provides a globally consistent view of the
set of available servers. The choice of strong consistency makes it easier to implement
applications, since it allows clients and servers to make consistent local decisions
about which servers are currently responsible for which parts of the service. The
second part of our solution addresses the problem of how to reconfigure applications
automatically as system membership changes. We present a storage system, dBQS
that provides Byzantine-fault-tolerant replicated storage with strong
consistency.
HARDWARE
& SOFTWARE REQUIREMENTS:
HARDWARE
REQUIREMENTS:
· System : Pentium
IV 2.4 GHz.
· Hard Disk : 40
GB.
· Floppy Drive : 1.44 Mb.
· Monitor : 15
VGA Color.
· Mouse :
Logitech.
· RAM : 512 Mb
SOFTWARE
REQUIREMENTS:
· Operating system : Windows
XP.
· Coding Language : C#.Net
· Database :
SQL Server 2005
MODULES:
1.
RELIABLE AUTOMATIC RECONFIGURATION
2.
TRACKING MEMBERSHIP SERVICE
3.
BYZANTINE FAULT TOLERANCE
4.
DYNAMIC REPLICATION
RELIABLE
AUTOMATIC RECONFIGURATION:
In this Module, it provides the
abstraction of a globally consistent view of the system membership. This
abstraction simplifies the design of applications that use it, since it allows
different nodes to agree on which servers are responsible for which subset of
the service. It is designed to work at large scale, e.g., tens or hundreds of
thousands of servers. Support for large scale is essential since systems today
are already large and we can expect them to scale further. It is secure against
Byzantine (arbitrary) faults. Handling Byzantine faults is important because it
captures the kinds of complex failure modes that have been reported for our
target deployments.
TRACKING
MEMBERSHIP SERVICE:
In this Module, is only part of what is
needed for automatic reconfiguration we assume nodes are connected by an
unreliable asynchronous network like the Internet, where messages may be lost,
corrupted, delayed, duplicated, or delivered out of order. While we make no
synchrony assumptions for the system to meet its safety guarantees, it is
necessary to make partial synchrony assumptions for livens. The MS describes
membership changes by producing a configuration, which identifies the set of
servers currently in the system, and sending it to all servers. To allow the
configuration to be exchanged among nodes without possibility of forgery, the
MS authenticates it using a signature that can be verified with a well-known
public key.
BYZANTINE
FAULT TOLERANCE:
In this Module, to provide Byzantine
fault tolerance for the MS, we implement it with group replicas executing the
PBFT state machine replication protocol. These MS replicas can run on server
nodes, but the size of the MS group is small and independent of the system
size. So, to implement from tracking service,
1. Add – It takes a certificate signed
by the trusted authority describing the node adds the node to the set of system
members.
2. Remove – It also takes a certificate
signed by the trusted authority that identifies the node to be removed and
removes this node from the current set of members.
3. Freshness – It receives a freshness
challenge, the reply contains the nonce and current epoch number signed by the
MS.
4. PROBE – The MS sends probes to
servers periodically. It serves respond with a simple ack, or, when a nonce is
sent, by repeating the nonce and signing the response.
5. New EPOCH – It informs nodes of a new
epoch. Here certificate vouching for the configuration and changes represents
the delta in the membership.
DYNAMIC
REPLICATION:
In this Module, to prevent attacker from
predicting,
1. Choose the random number.
2. Sign the configuration using the old
shares
3. Carry out are sharing of the MS keys
with the new MS members.
4. Discard the old shares
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