The power quality nowadays of the low voltage distribution system is vital for the utility and the consumer at the same time. One disturbing issue affected the quality conditions in the radial distribution system is load balancing. This survey paper is looking most the articles that deal with the phase nodal and lateral phase swapping because it is the efficient and direct method to maintain the current and voltage in balance situation, lead to a suitable reduction in the losses and preventing the wrong tripping of the protective relays.
Computer network routing is performed based on routing protocol decisions. Open Shortest Path First OSPF is the most known routing protocol. It suffers from congestion problem since it generally uses single (least cost) path to deliver information. Some times OSPF delivers information using more than one path in the case of more than one path have the same cost value. This condition is rarely achieved in normal cases. In this work OSPF is developed to distribute information load across multiple paths and makes load distribution as general case for the routing protocol. The modification supposes no protocol replacement and uses the existing protocol facilities. This makes faster information delivery, load balancing, less congestion, and with little modification on the built in OSPF functions. Disjoint paths are calculated then the costs of the best set of them are adapted using approporate ratio.
In this paper, a modified wavelet neural network (WNN) (or wavenet)-based predictor is introduced to predict link status (congestion with load indication) of each link in the computer network. On the contrary of previous wavenet-based predictors, the proposed modified wavenet-based link state predictor (MWBLSP) generates two indicating outputs for congestion and load status of each link based on th e premeasured power burden (square values) of utilization on each link in the previous time intervals. Fortunately, WNNs possess all learning and generalization capabilities of traditional neural networks. In addition, the ability of such WNNs are efficiently enhanced by the local characteristics of wavelet functions to deal with sudden changes and burst network load. The use of power burden utilization at the predictor input supports some non-linear distri butions of the predicted values in a more efficient manner. The proposed MWBLSP pre dictor can be used in the context of active congestion control and link load balancing techniques to improve the performance of all links in the network with best utilization of network resources.