Computer
Sanaa Ali Jabber; Soukaena H. Hashem; Shatha H Jafer
Abstract
Finding an optimal solution to some problem, like minimizing andmaximizing the objective function, is the goal of Single-Objective Optimization (SOP).Real-world problems, on the other hand, are more complicated and involve a widerrange of objectives, several objectives should be maximized in such problems. ...
Read More ...
Finding an optimal solution to some problem, like minimizing andmaximizing the objective function, is the goal of Single-Objective Optimization (SOP).Real-world problems, on the other hand, are more complicated and involve a widerrange of objectives, several objectives should be maximized in such problems. No singlesolution could be enhanced in all objectives without deteriorating at least one othergoal, which is the definition of Pareto-optimality. Understanding the idea of MultiObjective Optimization (MOP) is thus necessary to find the optimum solution. Multiobjective evolutionary algorithm (MOEA) are made to simultaneously assess manyobjectives and find Pareto-optimal solutions, MOEA can resolve multi-objective andsingle-objective optimization problems.This paper aims to introduce a survey study for optimization problem solutions bycomparing techniques, advantages, and disadvantages of SOP and MOP withmetaheuristics and evolutionary algorithms. From this study, we conduct that theefficiency of MOP lies in the present more than one SOP, but it takes a longer time toprocess and train and is not suitable for all applications, While SOP is faster and moreuseful in stock and profit maximization applications. And the posterior techniques areconsidered the dominant approach to solving multi-objective problems by the use of thefield of metaheuristics.
Sarah Ammar Rafea; Abdulkareem Abdulrahman Kadhim
Volume 19, Issue 1 , January 2019, , Page 71-81
Abstract
Internet of Things (IoT) enables things to have connectivity throughthe internet. The number of things is growing fast and has to be uniquelyidentified through the Internet to communicate with other things. In WirelessSensor Networks (WSNs) each node can be considered as a thing. WSN noderesources are ...
Read More ...
Internet of Things (IoT) enables things to have connectivity throughthe internet. The number of things is growing fast and has to be uniquelyidentified through the Internet to communicate with other things. In WirelessSensor Networks (WSNs) each node can be considered as a thing. WSN noderesources are very limited due to the need to communicate using low power andusually through unreliable links. Such limitations need an energy efficientrouting protocol. WSN is considered as a type of Low power and LossyNetwork (LLN). The routing protocol for low power and lossy network (RPL)is being adopted for LLN and has been standardized to enable connectivity ofWSN over IoT. RPL constricted a topology similar to tree topology. Nodes inRPL optimized its path using an objective function (OF). OF depends ondifferent node/link metrics in the optimization process. In this paper, an EnergyThreshold RPL (ETRPL) protocol is proposed. ETRPL depends on a newobjective function to enhance energy consumption of RPL protocol by takinginto account the remaining energy of the preferred parent node. ETRPL isimplemented using Cooja simulator. The results show that ETRPL provides anincrease in the remaining energy of at least 87.4% for a small area with highnumber of nodes. ETRPL also performed better with regards to Time Delay,Packet Reception Ratio, and the number of dead nodes in a small area. For alarge area, the performance is not encouraging. Thus the proposed ETRPLprotocol is useful for IoT networks with relatively small areas.
