Volume-11 ~ Issue-4
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Abstract: This paper is based on analysis of the performance of load balancing and route optimization in computerized networks. The complete system model shows the scenario of Packet distribution between nodes, and if congestion occurs due to traffic then Packet to be failed. The model used the AntNet system for simulate the network. The simulation runs on the ant's behavior for the load balancing of the network. The ants travel across the network between alternative chosen pairs of nodes; as they travel they deposit pheromones from their source node, collect the information of the route and the traffic congestion encountered on their journey. They select their path at each next node according the distribution of pheromones at each node. Packets between nodes are routed of the pheromone distributions at each next node. The performance of the network is proportional to packets which are failed. This model also shows the adaptivity of the system; the nodes are removed from the network, system finds the alternative chosen paths without system degradation and controls the performance of routing.
Keywords- AntNet Algorithm, Ant Colony Optimization (ACO), Routing, Load Balancing, Dynamic, Adaptive, Simulation, Communication Networks.
[1] G. Di Caro, M. Dorigo: AntNet: A Mobile Agents Approach to Adaptive Routing. Technical Report, IRIDIA, 1997.
[2] G. Di Caro, M. Dorigo: An adaptive multi-agent routing algorithm inspired by ants behavior. IRIDIA, Belgium, 1998.
[3] Benjamin Baran, Ruben Sosa: AntNet routing algorithm for data networks based on Mobile Agents. Inteligencia Artificial, 2001.
[4] G. Di Caro: Ant Colony Optimization and its Application to Adaptive Routing in Telecommunication Networks, IRIDIA, 2004
[5] G. Di Caro, M. Dorigo: AntNet: Distributed Stigmergetic Control for Communication Networks, Journal of Artificial Intelligence Research, 9, Vol. 9, PP. 317-365, IRIDIA, 1998. [6] Benjamin Baran, Ruben Sosa: A New approach for AntNet Routing, Presented at the Proc. 9th Int. Conf. Computer Communications Networks, Las Vegas, NV, 2000.
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[9] V. Verstraete, M. Strobbe, E. Breusegem, Jan Coppens, Mario, Pickavet, and Piet Demeester: AntNet: ACO routing algorithm in practice, Ghent University, Belgium, 2002.
[10] M. Dorigo, G. Di Caro and L. M. Gambardella: Ant Algorithms for Discrete Optimization. Artificial Life, MIT Press, 1999
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| Paper Type | : | Research Paper |
| Title | : | Deniable Encryption Key |
| Country | : | India |
| Authors | : | P.Lokesh Kumar Reddy, B.Rama Bhupal Reddy, S.Rama Krishna |
| : | 10.9790/0661-1140812 ![]() |
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Abstract: Deniable encryption is an important that allows a user (a sender and/or a receiver) to escape a coercion attempted by a coercive adversary. Such an adversary approaches the coerced user after transmission forcing him to reveal all his random inputs used during encryption or decryption. Since traditional encryption schemes commit the user to his random inputs, the user is forced to reveal the true values of all his random inputs (including the encrypted/decrypted messages and the encryption/decryption keys) which are verifiable by this coercer using the intercepted cipher text. In this scenario, a coercer may force the user to perform actions against his wish. An appealing property in the mediated RSA, PKI was introduced that, the user has no information, neither about his full private (decryption) key, nor the factorization of the RSA public modulus, which represents an excellent step toward achieving in forcibility in public key encryption, since, a coercer cannot ask the user to reveal such unknown information. In this pa- per we present a scheme for receiver-deniable public-key encryption, by which, the receiver is able to lie about the decrypted message to a coercer and hence, escape a coercion. On one hand, the receiver is able to decrypt for the correct message, on the other hand, all the information held by the receiver, when opened to a coercer, do not allow this coercer to verify the encrypted message and consequently, approaching this user becomes useless from the very beginning.
Keywords: Deniable encryption, mediated PKI, oblivious transfer, public-key encryption, RSA
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Abstract: In today's civilized society, the people are betrayed with proper healthcare facilities. In order to minimize the cost and complexity involved in processing traditional billing system, Electronic health records (EHR) and electronic billing systems have been proposed as mechanisms to help curb the rising costs of healthcare and also helps to detect the fraudulent practices in healthcare system. The introduction of Cloud computing concept in electronic healthcare systems is the solution for better utilization of healthcare facilities. It uses open-source cloud computing technologies as the mechanism to build an affordable, secure, and scalable platform that supports billing as well as EHR operations. We call this platform as "MedBook" which is a cloud solution that provides patients, healthcare providers, and healthcare payers a platform for exchange of information about EHR, billing activities, and benefits inquiries. MedBook serves as an integration point between the various participants in the healthcare delivery system. This paper presents the architecture and implementation status of this system. The developed system has been evaluated using the Jelastic cloud service. MedBook is a Software-as-a-Service (SaaS) application built on top of open source cloud technologies and running on an Infrastructure-as-a-Service (IaaS) platform. The client applications are mobile apps run from Google's Android enabled devices.
Keywords - Cloud Computing, EHR, Mobile apps, Open source Cloud, REST-based API, SaaS
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