Self Reconfigurable Distributed Load
Balancing For Secure and PrivacyPreserving Information Brokering.
Jyoti More.
ME student
Dept of Computer Engg G.H.Raisoni College of Engineering,Savitribai Phule
University of Pune, Pune, Maharashtra Email: jyotimore2283@gmail.com
Urmila Biradar
Asst Professor
Dept of Computer Engg G.H.Raisoni College of Engineering, Savitribai Phule
University of Pune, Pune, Maharashtra Email: urmilakb@gmail.com
Abstract—This paper describes concept of Self Reconfigurable Distributed Load Balancing
as well as secure and privacy preserving information brokering. To implement concept of Self
Reconfigurable Distributed Load Balancing, Packet redirection by the server Algorithm is used.
To preserve sensitive information Privacy Preserving is used. Information sharing through
on-demand access has been increased in organizations (e.g. libraries, enterprise). Information
Brokering System (IBS) is distributed system providing data access through set of brokers.
The set of brokers are used to make decisions to locate data sources for client queries. A solution
to preserve privacy in Information Brokering process of multiple stakeholder is Privacy
Preserving Information Brokering(PPIB).To integrates security with query routing have been
achieved by automaton segmentation and query segment encryption. The attacker could infer the
privacy by two attacks named as correlation attack and inference attack. Load balancing has
important impact on performance. In distributed system, load balancing is applied among nodes
for redistributing the workload. Load balancing improves resource utilization and response time.
Index TermsPrivacy,
PPIB,
Balancing, distributed system.
Automaton
segmentation, query segment encryption, Load
I. INTRODUCTION
Information sharing is becoming increasingly important in recent years, but also within many field
ranging from business to other agencies that are becoming more globalized and distributed. To
provide efficient large-scale information sharing, to reconcile data heterogeneity and provide
interoperability across geographically distributed data sources. The systems work on two extremes of
the spectrum: (1) in the query-answering model, peers are fully autonomous but there is no systemwide communication; so that user creates one-to-one client-server connections for information sharing;
(2) in the distributed database systems, all the user lost autonomy and are managed by a unified
DBMS. In distributed system providing data access through a set of brokers is referred to as
Information Brokering System (IBS).This system provide server autonomy and scalability In IBS
infrastructure given broker as well as coordinator structure.
Fig. 1. overview of the IBS infrastructure
There is increasing need for information sharing in recent years, in different organization. In the
Information brokering system, there are mainly three types of stakeholder data owner, data provider
and data requester. The information is may be different from one another. The main problem has
been created by attacker. Attacker could infer privacy of data owner, data provider and data
requester. Also introduce problem of system performance. There are mainly two types of attacks:
Inference attack and Attribute-correlation attack.
• Attribute-correlation attack
This attack is depending on predicates. Attacker prevents query, which contain predicates. To infer
sensitive information, the attacker correlate attributes. This attack is called as the attribute correlation
attack.
• Inference attack
This attack is totally based on the guessing the query. if the guess is matches, the query will be
inferred. This attack is occurred by finding the location of the data server or the data owner by using
the IP address.
• Need for improving Performance Solution:
PPIB has been provided for overcome these attacks. In this way, privacy is preserved. And also Dynamic
load balancing algorithm is implemented for improving performance of system.
PPIB has been provided for overcome these attacks. In this way, privacy is preserved. And also Dynamic
load balancing algorithm is implemented for improving performance of system.
II. LITERATURE SURVEY
Bo Luo et al.[1] study the privacy protection in information brokering process. they first focus on two
attacks: inference attack as well as attribute-correlation attack . Then, they propose a brokercoordinator s t r u c t u r e , as well as two schemes,query segment encryption scheme and automaton
segmentation scheme, to share among a set of brokering servers the secure query routing function.
With analysis on privacy and scalability, end-to- end performance, they show that the proposed system
can integrate query routing while preserving system-wide privacy and security enforcement.they achieve
load balancing. A more detailed quantitative comparison of the various architectures would be
necessary to have major insights on the tradeoffs of the different mechanisms discussed in this paper.
Ms. Pradnya Kamble[8] provides study in Distributed Information Sharing through an automaton
segmentation scheme and query segment encryption and data management issues for processing
XML data in a p2p setting, namely indexing, replication and query routing and processing.
Privacy issues of data and user during the design stage is considered and concluded that existing
information brokering systems suffer from a vulnerabilities associated with data privacy, and metadata
privacy as well as user privacy,. In this paper, PPIB proposed architecture is discussed, a new approach
to preserve privacy in XML information brokering.
A. Banu Prabha[3], a new approach propose PPIB ,to preserve privacy in XML information brokering,. To
preserve privacy of stakeholders involved in information brokering process. The system defines two
privacy attacks, namely inference attack and attribute-correlation attack. The Privacy-Preserving
Information Brokering in Distributed Information Sharing is achieved by an automaton segmentation
scheme and query segment encryption scheme .
Valeria Cardellini [9] proposed a classification of existing solutions based on the entity that dispatches
the client requests among the distributed Web-servers: client-based, dispatcher-based and DNS-based,
server-based. The different techniques are evaluated primarily with respect to compatibility to Web
standards, geographical scalability.
III. IMPLEMENTATION
A. Existing System
1) Privacy Preserving Information Brokering (PPIB):
Architecture of PPIB:
Fig. 2. Architecture of PPIB
PPIB has mainly three types of brokering components: (a) Brokers (b) Coordinators and (c) Central
authority (CA).
• Broker:
Brokers are attached through coordinators. The main function of brokers is for user authentication and
query forwarding.
• Coordinator:
Coordinator is responsible for access control and content based query routing.
• Central Authority:
Central Authority is responsible for metadata maintenance and key management.
B. Problem of existing System
In this system has some existing problem as like site distribution and load balancing. PPIB can suffer
from certain load imbalances due to data storing and query routing, load imbalance caused by these
factors can be efficiently tackled without substantial performance degradation. However, no load
balancing is considered and no explicit results showing query processing costs are reported. [9].
Another problem is drawing an automatic scheme which performs dynamic site distribution. There
is a need of consider several other factors such as the workload and trust level of each peer, and
privacy disagreement between automaton segments. A scheme that can strike a balance among
these factors is a point of consideration.
C. Proposed Method
1) Load balancing: Load balancing is the process of redistributing the work load among nodes of
the distributed system for improve both job response time and resource utilization.And also avoiding a
situation where some nodes are heavily loaded while others are idle or doing little work.
Algorithm: The automaton segmentation
Deploy Segment ()
Input: Automaton State St Output: Segment Address: addr
1: for each symbol k in St:StateT ransT able do
2:
addr=deploySegment(St:StateT ransT able(k):nextState)
3:
DS=createDummyAcceptState()
4:
DS:nextState addr
5:
St:StateT ransT able(k):nextState DS
6: end for
7: Seg = createSegment()
8: Seg:addSegment(S)
9: Coordinator = getCoordinator()
10: Coordinator:assignSegment(Seg)
11: return Coordinator:address
Server-based approach
Packet redirection by the server
Distributed Packet Rewriting (DPR) uses a round robin DNS mechanism to carry out the first
scheduling of the requests among the Web-servers. The server reached by a client request is able
to reroute the connection to another server through a packet rewriting mechanism that, unlike
HTTP redirection, is quite transparent to the client. Figure shows the initial request distribution
achieved through the DNS (step 1, 1’, 2, 3, 3’) and the case Where the server 1 decides to redirect the
received request (step 5, 6) to the server 2 without affecting the client. Two load balancing algorithms
are proposed to spread clients requests. The first policy uses a static (stateless) routing function,
where the destination server of each packet is determined by a hash function applied to both the
sender’s IP address and the port number. However, this simple policy is not practicable because IP
packet fragmentation does not provide the port information in each fragment. The second stateful
algorithm relies on periodic communications among servers about their current load. It tends to
redirect the requests to the least loaded server. DPR can be applied to both LAN and WAN distributed
Web-server systems. However, the packet rewriting and redirecting mechanism causes a delay that can
be high in WAN distributed Web-server systems.
D. MATHEMATICAL MODEL
MATHEMATICAL MODEL FOR AUTOMATION SEGMENTATION:
DS =Dummy accept state
Addr =segment address
For each K,
Create new dummy accept state DS,
Addr1 =DS1
Addr2 =DS2
…………..
Addrk = DSk
[S.StateTransTable] i=1 to k =Addr i
For each Addr,
Create segment S,
S=Si
Si(coordinator)= S(coordinator)
Addr= Si(coordinator).Addr
MATHEMATICAL MODEL FOR LOAD BALANCING:
Let A (i) be the set of jobs assigned to machine Mi; hence the machine Mi needs total computing time
Which is known as (Li) load on machine Mi. to minimize makespan is objective of load balancing ; maximum
loads on any machine is defined as (T = maxi Ti). This is known as linear programming problem, with objective to
Minimize L (load of the corresponding assignment)
Minimize L
Where Mj⊆ M; set of machines to which the job j can be assigned.
The finding an assignment of minimum makespan is NP-hard. The solutions can be obtained using a dynamic
programming algorithm
Where L is the minimum makespan.
RESULT
We test the system using the application of hospital.The application also containing dataset of Health
Dieseas and related information. Following graphs show result of security and Self reconfigurable Load
Balancing. Following figure shows that when both servers are busy then user request is wait in waiting
queue.
Figure : user request wait in waiting queue.
Following figure shows the Name of user request which are request to server1.
Figure : Name of user request which are request to server1.
Following figure shows the Responce of user request.
Figure : Responce of user request
IV. CONCLUSION
This system proposes a new approach for Self reconfigurable load Balancing concept. self
reconfigurable load balancing algorithm is implemented for improving performance of system. Load
Balancing means redistribute workload among the nodes of distribute system to improve resource
utilization and response time. For implementing concept of self reconfigurable load balancing, Packet
redirection by the server. This system gives different ways for privacy and security issues. We studied
how the privacy and security is maintained. Attacker could infer privacy of data owner, data provider
and data requester. Also introduce problem of system performance. There are two types of attacks:
inference attack and Attribute-correlation attack are studied. In this paper, we studied PPIB architecture,
two novel scheme, and phases of PPIB.
V. REFERENCES
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INFORMATION FORENSICS AND SECURITY, 2013.
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efficient end-to-end performance of information brokerage systems, in Proc. IEEE SUTC, 2006.
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Information Sharing IOSR-JCE,Issue 2, Vol 16,Ver.XI Mar-Apr 2014
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INFORMATION BROKERING IJCSMC, Vol.3, Issue.4 April 2014.
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Ajanta De Sarkar,Soumya Ray, EXECUTION ANALYSIS OF LOAD BALANCING
ALGORITHMS IN CLOUD COMPUTING ENVIRON- MENT ,in IJCCSA, Vol.2, No.5, October 2012.
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Distributed System using Qualitative Parameters Volume-1,Issue-3,August-2012.
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Information Brokering In Distributed Information Sharing.
[9] Valeria Cardellini and Michele Colajanni, Dynamic Load Balancing on Web-server Systems.