Self Reconfigurable Distributed Load Balancing For Secure and Privacy-Preserving Information Brokering. Jyoti More. ME student, Dept of Computer Engg G.H.Raisoni College of Engineering, Savitribai Phule University of Pune, Pune, Maharashtra Urmila Biradar Asst Professor Dept of Computer Engg G.H.Raisoni College of Engineering, Savitribai Phule University of Pune, Pune, Maharashtra Abstract This paper describes concept of Self Recon figurable 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 Terms- Privacy, PPIB, Automaton segmentation, query segment encryption, Load Balancing, distributed system. 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 system-wide 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. 30 Jyoti More., Urmila Biradar 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 Attributecorrelation 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 broker-coordinator s t r uc 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, serverbased. 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): 31 Jyoti More., Urmila Biradar
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 32 Jyoti More., Urmila Biradar
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, 33 Jyoti More., Urmila Biradar
Create new dummy accept state DS, Addr 1 =DS 1 Addr 2 =DS 2.. Addr k = DS k [S.StateTransTable] i=1 to k =Addr i For each Addr, Create segment S, S=S i S i (coordinator)= S(coordinator) Addr= S i (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. 34 Jyoti More., Urmila Biradar
Figure : user request wait in waiting queue. Following figure shows the Name of user request which are request to server1. 35 Jyoti More., Urmila Biradar 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 [1] Bo Luo, Chao-Hsien Chu, Peng Liu Dongwon Lee, Fengjun Li, Enforc- ing Secure and Privacy-Preserving Information Brokering in Distributed Information Sharing,in IEEE TRANSCATIONS ON INFORMATION FORENSICS AND SECURITY, 2013. [2] F. Li, P. Liu, D. Lee, B. Luo, W. Lee, and P. Mitra, C. Chu, In-broker access control: Towards efficient end-to-end performance of information brokerage systems, in Proc. IEEE SUTC, 2006. [3] A Banu Prabha Security Enforcement with query routing Information Brokering in Distributed Information Sharing IOSR-JCE,Issue 2, Vol 16,Ver.XI Mar-Apr 2014 [4] Noe Elisa, K. Suresh Babu SURVEY ON PROTECTING PRIVACY ANDSECURITY IN XML INFORMATION BROKERING IJCSMC, Vol.3, Issue.4 April 2014. [5] Ajanta De Sarkar,Soumya Ray, EXECUTION ANALYSIS OF LOAD BALANCING ALGORITHMS IN CLOUD COMPUTING ENVIRON- MENT,in IJCCSA, Vol.2, No.5, October 2012. [6] S.S.Apte,Abhijit A. Rajguru,,A Comparative Performance Analysis of Load Balancing Algorithms in Distributed System using Qualitative Parameters Volume-1,Issue-3,August-2012. [7] Rima Lingawar,Milind Srode,Mangesh Ghonge,Survey on Load - Balancing Techniques in Cloud ComputingIJARCE,Vol.1,No.3,May 2014 [8] Ms. Pradnya Kamble, Mr. Mukesh Kawatghare, Review on Enforcing Secure And Privacy Preserving Information Brokering In Distributed Information Sharing. [9] Valeria Cardellini and Michele Colajanni, Dynamic Load Balancing on Web-server Systems. 36 Jyoti More., Urmila Biradar