Evolution of grid has drawn attention from various resource intensive applications addressing domains of bio-informatics, astrology and multimedia, to name a few. Image analysis applications in both biosciences and astrophysics are explicitly built in modular fashion to exploit the potential offered by grid. In this paper we present a framework for resource allocation and task scheduling, MARS, which efficiently allocates resources for such resource intensive applications which can be represented as Task Interaction Graph (TIG), while keeping makespan as minimum as the current state of resources in grid allows. Simulation experiments with MARS show a considerable improvement in job completion time and host utilization over traditional resource management and scheduling algorithms for grid.

Computation grids and computational clouds are becoming increasingly popular in the organizations which require massive computational capabilities. Building such infrastructures makes a lucrative business case, thanks to availability of cheap hardware components and affordable software. Maintaining computational grids or cloud, however, require careful planning as in such dedicated environments, round-the-clock availability of workstations is very crucial. Ensuring uninterrupted availability, not only demands mechanism for failover redundancy but also results in constant power drainage. The tradeoff between the cost and the performance is the constant dilemma that the operations of the data centers face today. In this paper, we propose various heuristics for power-aware scheduling algorithms for scheduling jobs with dependent tasks onto the computational grid. We formulate the problem as a multi-objective function which results in various cost-performance tradeoffs each lying within the solution boundary.

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This activity aims to provide risk management training for Micro, Small and Medium Enterprises for Community Learning Equivalent Education Paket C at PKBM Cerdas Mandiri, Peureulak District in order to increase knowledge, apply in dealing with risks that arise in building Micro, Small and Medium Enterprises for residents. learn Equivalence Education Package C who are members of the PKBM Cerdas Mandiri. The location of community service activities is carried out through face-to-face meetings at the PKBM Cerdas Mandiri Peureulak. Community Service Activities use the Pre-Test and Post-test methods, providing material by mentors, presentations by participants, and discussion and product exposure. The results of the activity provide knowledge for participants while still paying attention to the development of the business world and technological developments as well as insurance in running a business, by being able to predict the risks that will occur from the start, both financial data, place of business and external influences that cannot be predicted or the emergence of a business that is unpredictable. In the same way, it will be able to minimize the risk of losses that occur to UMKM carried out by Equality Education Participants in Peureulak District, East Aceh Regency

The competitiveness of online algorithms is measured based on the correctness of the results produced and processing time efficiency. Traditionally evolutionary algorithms are not favored in online paradigms because of the large number of iterations involved in the algorithm which translates directly into processing time overhead. In this paper we describe MARS (Management Architecture for Resource Services) online scheduling algorithm which uses Simulated Annealing and concepts from Tabu Search to drastically decrease the processing time of the algorithm. The paper outlines the concepts behind MARS, the components involved and scheduling methodology used. In addition we also identify the time consuming bottlenecks in the performance of the system and how evolutionary algorithms help us soar past them.