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API C++: jobID=job_submit(delegationId,wmp_point,jdlPath);. Parametric JOB. MASTER. API C++: JobInfo jobinfo(&jobID); while (!jobinfo.isDone()) jobinfo.QueryLB(); jobinfo.getStringStatus();. Entry names. ott. V1. V2. Vndisc. ContaFO. last. Code.
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API C++: jobID=job_submit(delegationId,wmp_point,jdlPath); Parametric JOB MASTER ........ API C++: JobInfo jobinfo(&jobID); while(!jobinfo.isDone()) jobinfo.QueryLB(); jobinfo.getStringStatus(); Entry names ott V1 V2 Vndisc ContaFO last Code .... .... 1 2 .... .... 3 .... .... .... .... .... .... .... .... .... METADATA CATALOGUE (AMGA) Grid Computing for Optimal Internet Traffic Engineering based on OSPF/IS-IS Protocols Sara Carcangiu, Alessandra Fanni, Anna Mereu Department of Electrical and Electronic Engineering University of Cagliari ABSTRACT An optimization tool for optimal traffic routing in telecommunication networks is proposed in this work, where a weight is associated to each link and the IP flows are forwarded following link state routing protocols like ISIS or OSPF. The main objective is to find the optimal link weights in order to avoid congestion and to guarantee full survivability of the network. This problem is NP-hard and a metaheuristic technique, based on Tabu Search, is proposed here to solve it. An original implementation on a Grid Computing System is proposed in order to drastically reduce the computational cost of the algorithm, and to obtain high quality results within acceptable computation time also for large dimension and complexity models such as those referred to telecommunication networks. Workflow of the algorithm. RESULTS The Tabu Search is a meta-heuristic technique that, starting from an initial configuration of the variables to be optimized, explores all the neighbor configurations looking for the best one. The neighborhood is defined as the reachable configurations changing one variable at time. The Tabu Search algorithm is indeed intrinsically sequential but, during each iteration, the exploration of the neighborhood of the current solution can be carried out by independent jobs. As the execution of cyclic jobs is not allowed in the grid, the algorithm has been design in a master-slave fashion. The optimization procedure has been applied to a real backbone network of an Italian ISP (Fig. 1). Results obtained from the optimization process have been compared with those deriving from the current ISP configuration. Results show that, in case of failure, the actual ISP configuration may fall in a congestion state (see Fig. 2). After the weights optimization process the congestion level has been reduced of 29% with respect to the ISP configuration (see Fig. 3). Slave Master Fig. 1 Italian portion of the Tiscali International network. Implementation of the algorithm in the Grid computing Infrastructure. Fig. 2 Maximum link utilization with the actual weights. Fig. 3 Maximum link utilization with the optimized weights.