P. Dhavachelvan

An application perspective evaluation of multi-agent system in versatile environments

Multi-agent systems (MAS) based computing is the most appropriate paradigm for the problem domain, where data, control, expertise or resources are distributed and also it is interesting to the user only if the technologies address the issues of interest to the user. The MAS has the hypothesis that the agent based computing offers better approach to manage the complex systems and process. They are large-scale systems and collaborate with one another to achieve their functions in a highly modular and flexible way. In this point of view, the work presented in this paper is an enhanced attempt to validate the MAS based on application perspective. As a test-bed, a distributed MAS for software testing is constructed such that to provide a hybrid testing environment based on variety of agents, which possibly incorporate several testing techniques. The developed framework is validated on two perspectives namely, efficiency of the application domain, i.e. software testing using MAS and efficiency of the proposed framework. The validation of the later case has been carried out on two conditions: regular working environment and exceptional working environment. The second type of validation provided the guidelines for implementing proper exception handling mechanism in the enhanced MAS, which is being developed for software testing Purpose.

MSRCC - Mitigation of Security Risks in Cloud Computing

Cloud computing represents the latest phase in the evolution of Internet-based computing. In spite of the attractive properties it provides, security and privacy issues loom large for cloud computing. In this paper, we concentrate on the security threats involved in cloud by providing an Authenticated Key Exchange Protocol (AKExP). In this protocol, we make use of the identity management scheme and symmetric key encryption algorithm so that unauthorized users cannot get access to the sensitive data stored in the cloud. This proposed approach minimizes the computation cost and communication cost when compared with another authentication protocol, Identity-based Authentication Protocol. This paper provides an efficient and secure way to authenticate the user in the cloud both by the owner and cloud service provider.

HPPC-Hierarchical Petri-Net based Privacy nominal model approach for Cloud

This paper focusing on the data collected ubiquitously and conserved by cloud providers are assured that, the clients and users can assess that information globally as per their versatility, where as the cloud providers should gave some limited transparency policy to maintain clients secrecy. Usually the private data collected by the service providers can be shared with in their other platforms. Highest risk of data exposure occurs for cloud providers due to the breach of clients secrecy. In cloud architecture privacy policies and its standards is one of the main issues of cloud computing. Many researchers have been vigorously working in these issues. We studied these researchers work, frontward us to propose HPBP (Hierarchical Petri-net based Privacy nominal model for Cloud) architecture. Our proposed model facilitates clients, to have an augment trust on cloud providers as a pledge to maintain their high secrecy. The privacy of the proposed technique is analyzed briefly.

A Privacy Preserving Representation for Web Service Communicators’ in the Cloud

The present paper focuses on maintaining one’s data secrecy in cloud storage area and it may depend on their privacy policy and standards. The effectiveness and efficiency of preserved data from different cloud providers should maintain the integrity of original data stored in it. In the era of could computing, stored information’s value, proficiency and optimization of data retrieving spotlights the importance of maintaining cloud users data, privacy, identity, reliability and maintainability it may vary for different Cloud providers (CP). Giant CP ensures their user proprietary information’s are sustained more secretly using cloud technologies. During third party cloud services and exodus between inter cloud providers may lead to data portability privacy issue. More remarkable event in this case, even the cloud providers don’t have implication about the information and records where it’s stored and maintained in their own cloud. This is one of the obligatory research issue in cloud computing. We came frontward by proposing (EMPPC) an Evolutionary model based privacy Preserving technique and try to hold user’s, to have trust in providers for maintaining their confidentiality in cloud. This proposal helps the CR (Cloud Requester and Users) to mark trust on their proprietary information and data’s stored in cloud.

Hybrid Algorithm for Job Scheduling: Combining the Benefits of ACO and Cuckoo Search

Job scheduling problem is a combinatorial optimization problem in computer science in which ideal jobs are assigned to resources at particular times. Our approach is based on heuristic principles and has the advantage of both ACO and Cuckoo search. In this paper, we present a Hybrid algorithm, based on ant colony optimization (ACO) and Cuckoo Search which efficiently solves the Job scheduling problem, which reduces the total execution time. In ACO, pheromone is chemical substances that are deposited by the real ants while they walk. When it comes to solving optimization problems it acts as if it lures the artificial ants. To perform a local search, we use Cuckoo Search where there is essentially only a single parameter apart from the population size and it is also very easy to implement.

A krill herd optimization based fault tolerance strategy in MANETs for dynamic mobility

Mobile ad hoc network (MANET) is the multi-hop network, infrastructure less network with autonomously self-organizing in the distributed network. In case of node failure or link failure, MANET has the capacity to self-heal by changing the topology dynamically. There are many issues due to its dynamic nature, with the change in topology which leads to more routing. In multi-hop networking it uses the routing protocols such as AODV and DSR are due to its dynamic infrastructure and high mobility. The krill herd bio - inspired optimization algorithm in MANET is proposed for the dynamic network for the efficient power saver and reducing the routing process by the local and global optimization. The local search can be calculated by the sensing distance in KH algorithm to find the nearest neighbors with in the infrastructure. The local optimization uses AODV protocol and in global optimization, the DSR protocol is used for the power consumption. The node failure or node link failure can be detected by the KH algorithm as random diffusion and motion influencing other node.

Hybrid Ant Colony Optimization and Cuckoo Search Algorithm for Job Scheduling

Job scheduling is a type of combinatorial optimization problem. In this paper, we propose a Hybrid algorithm which combines the merits of ACO and Cuckoo Search. The major problem in the ACO is that, the ant will walk through the path where the chemical substances called pheromone is deposited. This acts as if it lures the artificial ants. Cuckoo search can perform the local search more efficiently and there is only a single parameter apart from the population size. It minimizes the makespan and the scheduling can be used in scientific computing and high power computing.

Lifetime enhancement by Cluster Head Cooperative Trustworthy Energy Efficient MIMO routing algorithm based on game theory for WSN

Energy-constrained wireless sensor network (WSN) has attained considerable research attention in recent years and requires robust and energy efficient routing protocols for communication in fading environments to minimise the energy consumption. To mitigate the fading effects in wireless channel, multi-input multi-output (MIMO) scheme is utilised for energy efficient communication and to route the data in WSN. This paper proposes a Cluster Head Cooperative Trustworthy Energy Efficient MIMO (CH-C-TEEM) routing algorithm based on game theory for WSN and the performances are analysed in terms of energy consumption. In this scheme the cluster head nodes cooperate transmit data cooperatively rather than selecting the cooperative sending and receiving groups in each cluster. Game theory is used to elect healthier cluster heads having sufficient residual energy and high trust level. Further the game theory is used to select the cooperative nodes for MIMO communication. The outcome of the simulation results show that the CH-C-TEEM routing algorithm provides more than 50% increase in residual energy as compared to TEEM.

FEWSS — FRAMEWORK TO EVALUATE THE SERVICE SUITABILITY AND PRIVACY IN A DISTRIBUTED WEB SERVICE ENVIRONMENT

This paper focuses on addressing the problem of web service monitoring by evaluating its suitability and privacy in a distributed web service environment (DWS). The need for web services monitoring and evaluation is necessary because the quantity and quality of retrieved web services generally does not fulfill the demands or requirements of the web service requesters. In the literature, many authors proposed suitable solutions for checking the quality of web service in an ad hoc scenario but there is no available testbed for this purpose. In this work, it is proposed to develop a framework as a testbed for evaluating the web service for its suitability and privacy. In order to verify, the retrieved web services fulfill the demands and requirements of the requester in a DWS environment. The Framework to Evaluate the Web Service Suitability (FEWSS) supports service providers in modeling the services with testbed and to design service behavior to comply the service suitability. It generates run-time instances of web services, clients requests, service registries and other entities in order to emulate realistic SOA environments. By generating a real testbed, our approach assists in runtime test for provider system/services. Particular focus has been put on the privacy policy extensibility to allow the service providers and users in a complex environment. FEWSS also provides an intuitive interface for testing all services under SOA control.

Energy-aware scheduling using Hybrid Algorithm for cloud computing

Cloud computing are becoming an important platform for scientific applications. Using virtualization in cloud computing it is possible to provide an on-demand provision of virtualized resources as a service, without any additional waiting time. Scheduling the tasks based on the deadline-constraint reduces the energy consumption, leading to a considerable decrease in energy cost. Energy consumption is the blue eye of task scheduling. But all the applications are not based on the deadline-constraint, so complexity of the problem arises. Hence the task scheduling need to be focused by considering the energy consumption and it has to be evaluated based on the quality of the schedules. This paper puts forth a hybrid algorithm which focuses on the reduction of energy consumption. This method is based on the voltage scaling factor to reduce the energy consumption. The result proves that by using this method, energy consumption can be minimized while scheduling the tasks.