Resources allocation in distributed processing systems using AI/OR techniques

Resources Allocation In Distributed Processing Systems UsingAI / ()R TechniquesThis thesis aims to provide a new approach to allocate resources inthe Distributed Systems (DS), focussing on minimizing the traffic acrossthe system by exploiting data distribution scheme and allocating thelinks capacities of its communication network.A Decision Support System (DSS) has been developed that helps thedecision makers, in rationale way, to distribute the system data-base andthen, up on the deduced traffic pattern, assigns optimally the linkscapacities of the communication network under the problem constraints.The proposed system offers the following capabilities: .• It establishes and builds a repository of data for the characteristicsand attributes of the DS under study allowing dynamic adaptation to anychanges in its data such as adding, deleting and/or changing data ofnodes and/or system datasets .• It builds a starting network topology for the OS being examined,automatically using a heuristic approach, and provides a completegraphical user interface (GUI) to enable, the user to change the topology,interactively and graphically, and hence can in a user-friendly mannerkeep variations of the OS network topology for the analysis and decisionmaking process.• It provides the capability to have a given network traffic pattern or useproposed data distribution assessment fuzzy model that can reason howto locate the distributed system data-base, and hence presents a deducedt/”(~flic pattern for the DS. It shows, in a GUI, how much datadistribution affects the OS traffic.• It applies a shortest path algorithm using DP technique to determinethe network traffic flow routs (flow assignment process), based ondeterministic and shortest path routing strategy. It shows in a G U I thenetwork topology and enable the user to indicate any node-pair and then