Cloud computing a relatively recent term builds on decades of research in virtualization, distrib... more Cloud computing a relatively recent term builds on decades of research in virtualization, distributed computing, utility computing, and networking, web and s/w services. The consequence of network based cloud computing model which is rapidly increasing in delivering computing as a utility to users worldwide is that cloud data centers have high deployment and operational costs, as well as significant carbon footprints for the environment. So attention should be paid to the need of managing energy consumption across the entire Information and Communication Technology (ICT) sector because of its large amount of CO2 emission. Despite ecological issues, the interest of the low power research has critical economical needs. We need to develop Green Cloud Computing (GCC) solutions that reduces these deployment and operational costs and thus save energy, hence, reduces adverse environmental impacts. In this paper, we aim to implement practically a Green Scheduling Algorithm integrating a neu...
Cloud Computing is a very recent term which is mainly based on distributed computing, virtualizat... more Cloud Computing is a very recent term which is mainly based on distributed computing, virtualization, utility computing, networking and web and software services. This kind of service oriented architecture reduces information technology overhead for end user, total cost of ownership, supports flexibility and on-demand services. KeywordsCloud Computing, Grid Computing, IaaS, PaaS, SaaS.
This paper addresses the issues concerning the rescheduling of a static timetable in case of a di... more This paper addresses the issues concerning the rescheduling of a static timetable in case of a disaster encountered in a large and complex railway network system. The proposed approach tries to modify the schedule so as to minimise the overall delay of trains. This is achieved by representing the rescheduling problem in the form of a Petri-Net and the highly uncertain disaster recovery times in such a model is handled as Markov Decision Processes (MDP ). For solving the rescheduling problem, a istributed Constraint Optimisation (DCOP ) based strategy involving the use of autonomous agents is used to generate the desired schedule. The proposed approach is evaluated on the actual schedule of the Eastern Railways, India by constructing vari- ous disaster scenarios using the Java Agent DEvelopment Framework (JADE). When compared to the existing approaches, the proposed framework substantially reduces the delay of trains after rescheduling.
Abstract Advancement in intelligent transportation systems with complex operations requires auton... more Abstract Advancement in intelligent transportation systems with complex operations requires autonomous planning and management to avoid collisions in day-to-day traffic. As failures and/or inadequacy in traffic safety systems are life-critical, such collisions must be detected and resolved in an efficient way to manage continuously rising traffic. In this paper, we address different types of collision scenarios along with their early detection and resolution techniques in a complex railway system. In order to handle collisions dynamically, a novel agent-based solution approach is proposed using the idea of max-sum algorithm, where each agent communicates and cooperates with others to generate a good feasible solution that keeps the system safe, i.e. collision free. We implement the proposed mechanism in Java Agent DEvelopment Framework (JADE). The simulation results are evaluated with exhaustive experiments and compared with different existing methods to show the efficiency of our proposed approach.
Advances in Intelligent Systems and Computing, 2014
Multi-Agent system, which is relatively a recent term, can be viewed as a sub-field of Distribute... more Multi-Agent system, which is relatively a recent term, can be viewed as a sub-field of Distributed AI. In order to construct and solve complex real world problems like task allocation in an organization, a number of agents can perform work cooperatively and collaboratively. To achieve the maximum system utility through the proper task allocation among agents, there is a notion of dynamic team formation. In this paper we focus on task allocation mechanism to agents with dependencies among various tasks to agents either individually or by forming a team whenever needed according to their capability to do a particular task. We propose few algorithms which dynamically filter the capable agents for performing task and hence allocating them with the help of synergy value and their individual utility. We also simulate the task allocation mechanism done by our proposed algorithms and show the performance of the system by defining some metrics like, agent utility, team utility, system utility.
TENCON 2014 - 2014 IEEE Region 10 Conference, 2014
This paper proposes a multi agent based timetable scheduling algorithm for railway system which h... more This paper proposes a multi agent based timetable scheduling algorithm for railway system which handles the in-between time delay of the newly introduced train. The delay management indeed optimizes the total journey time, hence increases the total utility of the whole railway system as well. Here we show that schedule generated by our proposed algorithm is the most optimized schedule. It is done by using the notion of DCOP(Distributed Constraint Optimization Problem), where we define some metric to analyze the system to achieve our goals. We use JADE(Java Agent DEvelopment Framework) platforms to simulate our work and test it using a small network. We also take a small case study to compare our proposed work with the existing one and the results are therefore presented.
Cloud computing a relatively recent term builds on decades of research in virtualization, distrib... more Cloud computing a relatively recent term builds on decades of research in virtualization, distributed computing, utility computing, and networking, web and s/w services. The consequence of network based cloud computing model which is rapidly increasing in delivering computing as a utility to users worldwide is that cloud data centers have high deployment and operational costs, as well as significant carbon footprints for the environment. So attention should be paid to the need of managing energy consumption across the entire Information and Communication Technology (ICT) sector because of its large amount of CO2 emission. Despite ecological issues, the interest of the low power research has critical economical needs. We need to develop Green Cloud Computing (GCC) solutions that reduces these deployment and operational costs and thus save energy, hence, reduces adverse environmental impacts. In this paper, we aim to implement practically a Green Scheduling Algorithm integrating a neu...
Cloud Computing is a very recent term which is mainly based on distributed computing, virtualizat... more Cloud Computing is a very recent term which is mainly based on distributed computing, virtualization, utility computing, networking and web and software services. This kind of service oriented architecture reduces information technology overhead for end user, total cost of ownership, supports flexibility and on-demand services. KeywordsCloud Computing, Grid Computing, IaaS, PaaS, SaaS.
This paper addresses the issues concerning the rescheduling of a static timetable in case of a di... more This paper addresses the issues concerning the rescheduling of a static timetable in case of a disaster encountered in a large and complex railway network system. The proposed approach tries to modify the schedule so as to minimise the overall delay of trains. This is achieved by representing the rescheduling problem in the form of a Petri-Net and the highly uncertain disaster recovery times in such a model is handled as Markov Decision Processes (MDP ). For solving the rescheduling problem, a istributed Constraint Optimisation (DCOP ) based strategy involving the use of autonomous agents is used to generate the desired schedule. The proposed approach is evaluated on the actual schedule of the Eastern Railways, India by constructing vari- ous disaster scenarios using the Java Agent DEvelopment Framework (JADE). When compared to the existing approaches, the proposed framework substantially reduces the delay of trains after rescheduling.
Abstract Advancement in intelligent transportation systems with complex operations requires auton... more Abstract Advancement in intelligent transportation systems with complex operations requires autonomous planning and management to avoid collisions in day-to-day traffic. As failures and/or inadequacy in traffic safety systems are life-critical, such collisions must be detected and resolved in an efficient way to manage continuously rising traffic. In this paper, we address different types of collision scenarios along with their early detection and resolution techniques in a complex railway system. In order to handle collisions dynamically, a novel agent-based solution approach is proposed using the idea of max-sum algorithm, where each agent communicates and cooperates with others to generate a good feasible solution that keeps the system safe, i.e. collision free. We implement the proposed mechanism in Java Agent DEvelopment Framework (JADE). The simulation results are evaluated with exhaustive experiments and compared with different existing methods to show the efficiency of our proposed approach.
Advances in Intelligent Systems and Computing, 2014
Multi-Agent system, which is relatively a recent term, can be viewed as a sub-field of Distribute... more Multi-Agent system, which is relatively a recent term, can be viewed as a sub-field of Distributed AI. In order to construct and solve complex real world problems like task allocation in an organization, a number of agents can perform work cooperatively and collaboratively. To achieve the maximum system utility through the proper task allocation among agents, there is a notion of dynamic team formation. In this paper we focus on task allocation mechanism to agents with dependencies among various tasks to agents either individually or by forming a team whenever needed according to their capability to do a particular task. We propose few algorithms which dynamically filter the capable agents for performing task and hence allocating them with the help of synergy value and their individual utility. We also simulate the task allocation mechanism done by our proposed algorithms and show the performance of the system by defining some metrics like, agent utility, team utility, system utility.
TENCON 2014 - 2014 IEEE Region 10 Conference, 2014
This paper proposes a multi agent based timetable scheduling algorithm for railway system which h... more This paper proposes a multi agent based timetable scheduling algorithm for railway system which handles the in-between time delay of the newly introduced train. The delay management indeed optimizes the total journey time, hence increases the total utility of the whole railway system as well. Here we show that schedule generated by our proposed algorithm is the most optimized schedule. It is done by using the notion of DCOP(Distributed Constraint Optimization Problem), where we define some metric to analyze the system to achieve our goals. We use JADE(Java Agent DEvelopment Framework) platforms to simulate our work and test it using a small network. We also take a small case study to compare our proposed work with the existing one and the results are therefore presented.
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Papers by Poulami Dalapati