Ravi Shankar Singh

Real-time recognition of cattle using animal biometrics

With the advent of efficient recognition techniques, animal biometric systems have gained more proliferation for the identification and monitoring of cattle. A cattle biometric system is a pattern recognition-based system for the identification of livestock. In this paper, we propose a novel muzzle point recognition based on Fisher locality preserving projection algorithm for the recognition of cattle in real time. We have captured images of animals using a surveillance camera and transferred them to the server by wireless network technology. The major contributions are as follows: (1) preparation of muzzle point database, (2) extraction of the salient set of features using proposed muzzle point recognition approach, and (3) evaluation and comparison analysis of the introduced method and several existing recognition algorithms on a standard benchmark protocol. The efficacy of proposed muzzle point recognition approach for cattle evaluates under identification settings and yields

Error-tolerant graph matching using homeomorphism

96.87\,\%

Dynamic and adaptive load balancing in transaction oriented grid service

96.87% recognition accuracy for identifying individual cattle. The proposed approach also valued the 10.25 sec recognition time for enrollment and identified individual cattle on different sizes of muzzle point images.

Secure and privacy enhanced authentication framework for cloud computing

Adaptability is the ability of a system to adapt itself efficiently to changed circumstances. Adaptability in transaction oriented grid service is a challenge due to the extreme complexity and the occurrence of failures in the grid system. This paper presents the design, implementation, and evaluation of an adaptive model, ATOGS, using adaptive fault-tolerance (i.e., checkpointing and replication) during the execution of services. We evaluate our adaptive model experimentally comparing with the Dynasa and the experimental results have demonstrated that ATOGS enables the application itself to handle the failure problems efficiently and it achieves better performance in terms of execution time, network bandwidth, load, resulting in up to a lower overhead. The results indicate that the performance of transaction oriented grid service is better than the performance of general grid service when replication technique is used. This model is based on a modeling and simulation tool, Coloured petri nets (CPNs).

On maximizing reliability of grid transaction processing system considering balanced task allocation using social spider optimization

Graph matching is the task of computing the resemblance of graphs. While in exact matching, a strict one-to-one correspondence should exist between two graphs or among their subgraphs, on the other hand in error-tolerant matching a strict correspondence is not necessary, and some similarity measure should be exhibited between two graphs or their subgraph depending on some tolerance value or noise. In this paper, we present a new approach to error-tolerant matching using graph homeomorphism to measure the structural resemblance of two graphs.

Privacy preserving security using biometrics in cloud computing

Balanced task allocation is one of the methods that can be used to maximize the performance and reliability in the on‐demand computing‐based transaction processing system. On‐demand computing is an increasingly popular enterprise model. It provides computing resources to the user as needed, which may be maintained within the users enterprise, or made available by a service provider. The balanced task allocation in such environment is known to be an NP hard. The reliability is a measure of trustworthiness of the system while executing the task. So we derive the reliability formula for the on‐demand computing‐based transaction processing system considering resource availability. We propose the balanced task allocation based on social spider optimization (LBTA_SSO) method for this problem. The LBTA_SSO is based on the cooperative behavior of social‐spiders to find a collection of task allocation solutions. We modified five existing algorithms to obtain the task allocation algorithms; Honey Bee Optimization (HBO), Ant Colony Optimization (ACO), Hierarchical Load Balanced Algorithm (HLBA), Dynamic and Decentralized Load Balancing (DLB), and Randomized Algorithm respectively. Then, we compared the proposed algorithm with these modified algorithms. The results show that our algorithm works better than the modified existing algorithms.

On scheduling transactions in a grid processing system considering load through Ant Colony Optimization

Dynamic and decentralized load balancing in transaction oriented grid service is a challenge due to its heterogeneous, real-time, autonomous and adaptive nature. The execution of these services increases the loads on the processing nodes or the required resources at the time of task recovery from failures. The task recovery may be of two types: local level and replicated level. In both the cases, the job queues at global nodes and local nodes are crowded with incoming new and older failed tasks. This paper presents a sender-initiated dynamic and adaptive load balancing approach (SI-DALB) based model using hypercube topology. The proposed model is based on Coloured Petri Nets (CPNs) and uses decentralized approach to balance and manage the load distributions among resources. Experimental results are validated and compared with the model consisting NoLB (No load balancing) approach. The experimental results show that the proposed algorithm is better and effective in distributing and balancing the loads of transaction oriented grid service.

Spatial modeling of SPAD values for different type of crops using LISS-IV satellite imagery

Cloud computing is a revolution in information technology. The cloud consumer outsources their sensitive data and personal information to cloud providers servers which is not within the same trusted domain of data-owner so most challenging issues arises in cloud are data security users privacy and access control. In this paper we also have proposed a method to achieve fine grained security with combined approach of PGP and Kerberos in cloud computing. The proposed method provides authentication, confidentiality, integrity, and privacy features to Cloud Service Providers and Cloud Users.