Task Resource Allocation in Grid using Swift Scheduler

In nature, Grid computing is the combination of parallel and distributed computing where running computationally intensive applications like sequence alignment, weather forecasting, etc are needed a proficient scheduler to solve the problems awfully fast. Most of the Grid tasks are scheduled based on the First come first served (FCFS) or FCFS with advanced reservation, Shortest Job First (SJF) and etc. But these traditional algorithms seize more computational time due to soar waiting time of jobs in job queue. In Grid scheduling algorithm, the resources selection is NPcomplete. To triumph over the above problem, we proposed a new dynamic scheduling algorithm which is the combination of heuristic search algorithm and traditional SJF algorithm called swift scheduler. The proposed algorithm takes care of Job’s memory and CPU requirements along with the priority of jobs and resources. Our experimental results shows that our scheduler reduces the average waiting time in the job queue and reduces the over all computational time

Maximizing Service Reliability in Distributed Computing Systems with Random Node Failures: Theory and Implementation

In distributed computing systems (DCSs) where server nodes can fail permanently with nonzero probability, the system performance can be assessed by means of the service reliability, defined as the probability of serving all the tasks queued in the DCS before all the nodes fail. This paper presents a rigorous probabilistic framework to analytically characterize the service reliability of a DCS in the presence of communication uncertainties and stochastic topological changes due to node deletions. The framework considers a system composed of heterogeneous nodes with stochastic service and failure times and a communication network imposing random tangible delays. The framework also permits arbitrarily specified, distributed load-balancing actions to be taken by the individual nodes in order to improve the service reliability. The presented analysis is based upon a novel use of the concept of stochastic regeneration, which is exploited to derive a system of difference-differential equations characterizing the service reliability. The theory is further utilized to optimize certain load-balancing policies for maximal service reliability; the optimization is carried out by means of an algorithm that scales linearly with the number of nodes in the system. The analytical model is validated using both Monte Carlo simulations and experimental data collected from a DCS testbed

Performance and Reliability of Non-Markovian Heterogeneous Distributed Computing Systems

Average service time, quality-of-service (QoS), and service reliability associated with heterogeneous parallel and distributed computing systems (DCSs) are analytically characterized in a realistic setting for which tangible, stochastic communication delays are present with nonexponential distributions. The departure from the traditionally assumed exponential distributions for event times, such as task-execution times, communication arrival times and load-transfer delays, gives rise to a non-Markovian dynamical problem for which a novel age dependent, renewal-based distributed queuing model is developed. Numerical examples offered by the model shed light on the operational and system settings for which the Markovian setting, resulting from employing an exponential-distribution assumption on the event times, yields inaccurate predictions. A key benefit of the model is that it offers a rigorous framework for devising optimal dynamic task reallocation (DTR) policies systematically in heterogeneous DCSs by optimally selecting the fraction of the excess loads that need to be exchanged among the servers, thereby controlling the degree of cooperative processing in a DCSs. Key results on performance prediction and optimization of DCSs are validated using Monte-Carlo (MC) simulation as well as experiments on a distributed computing testbed. The scalability, in the number of servers, of the age-dependent model is studied and a linearly scalable analytical approximation is derived

Distributed Task Management in Cyber-Physical Systems: How to Cooperate under Uncertainty?

We consider the problem of task allocation in a network of cyber-physical systems (CPSs). The network can have different states, and the tasks are of different types. The task arrival is stochastic and state-dependent. Every CPS is capable of performing each type of task with some specific state-dependent efficiency. The CPSs have to agree on task allocation prior to knowing about the realized network's state and/or the arrived tasks. We model the problem as a multi-state stochastic cooperative game with state uncertainty. We then use the concept of deterministic equivalence and sequential core to solve the problem. We establish the non-emptiness of the strong sequential core in our designed task allocation game and investigate its characteristics including uniqueness and optimality. Moreover, we prove that in the task allocation game, the strong sequential core is equivalent to Walrasian equilibrium under state uncertainty; consequently, it can be implemented by using the Walras' tatonnement process

Maximizing service reliability in distributed computing systems with random failures: Theory and implementation,”

Abstract-In distributed computing systems (DCSs) where server nodes can fail permanently with nonzero probability, the system performance can be assessed by means of the service reliability, defined as the probability of serving all the tasks queued in the DCS before all the nodes fail. This paper presents a rigorous probabilistic framework to analytically characterize the service reliability of a DCS in the presence of communication uncertainties and stochastic topological changes due to node deletions. The framework considers a system composed of heterogeneous nodes with stochastic service and failure times and a communication network imposing random tangible delays. The framework also permits arbitrarily specified, distributed load-balancing actions to be taken by the individual nodes in order to improve the service reliability. The presented analysis is based upon a novel use of the concept of stochastic regeneration, which is exploited to derive a system of difference-differential equations characterizing the service reliability. The theory is further utilized to optimize certain load-balancing policies for maximal service reliability; the optimization is carried out by means of an algorithm that scales linearly with the number of nodes in the system. The analytical model is validated using both Monte Carlo simulations and experimental data collected from a DCS testbed

Determining the set of the most important components for system reliability

Mere značajnosti (Importance measures) predstavlјaju načine merenja, tj. brojčanog iskazivanja značajnosti pojedinih komponenata u sistemu sa aspekta ukupne pouzdanosti sistema. Merama značajnosti je moguće odrediti (izdvojiti) komponente najznačajnije za pouzdanost sistema. Od šezdesetih godina, kada je koncept mera značajnosti prvi put uveden, do danas postoji neprekidno interesovanje za ovu oblast, tako da se, pored primene tradicionalnih mera značajnosti, neprestano uvode i definišu nove mere radi njihove primene na specifične sisteme. Opšti nedostatak mera značajnosti, nezavisno od kategorije kojoj pripadaju, je taj što se one utvrđuju za svaku pojedinačnu komponentu, a tek nakon toga se može izdvojiti skup najznačajnijih komponenata zadate kardinalnosti...Importance measures are numerical representations of the importance of each system’s component considering total system reliability. Using importance measures, the most important components for system reliability can be determined. Since the sixties, when the concept of importance measures was first introduced, there is a constant interest in this area, so that, in addition to the traditional importance measures, new measures for specific systems observed are continually introduced and defined. The general weak point of importance measures, irrespective of the category they belong to, is that they are determined for each individual component, and only afterwards a certain number of most important components can be set aside..

Availability and Reliability Analysis of Computer Software Systems Considering Maintenance and Security Issues

Ph.DDOCTOR OF PHILOSOPH