Heterogeneous networks are designed to offload or route some of data traffics of mobile networks through other co‐located wireless access networks. This technique apparently increases the capacity of mobile network. In such networks, a vertical handover process plays an important role in providing seamless and uninterrupted connectivity as well as the required level of quality‐of‐service along with a wide coverage for all mobile nodes. Traditional vertical handover algorithms that are based on single criterion (eg, received signal strength) are not performing well in terms of excess handover rates, ping‐pong effects, handover delays, handover cost, etc. This research presents an efficient multicriteria‐based vertical handover decision‐making algorithm for heterogeneous networks. This algorithm uses a two‐step execution procedure, the first step evaluates whether the handover is needed or not before initiating a handover process, if needed, then a set of feasible solutions are generated for the vertical handover problem formulated as a multi‐objective optimization problem with two objective functions such as quality factor of networks and handover processing cost. In the second step, an optimal solution (ie, an appropriate access network) for handover is obtained using a hybrid approach of fuzzy analytic hierarchy process (FAHP) and technique for order preference by similarity to ideal solution (TOPSIS). Our simulation study shows that the proposed algorithm performs well as compared to some other existing algorithms (ie, single‐criterion based, multicriteria with AHP, multicriteria with TOPSIS, and multicriteria with both AHP and TOPSIS) in terms of performance metrics such as handover rate, delay, cost, and energy consumption.
For this present research investigation, hybrid natural fiber reinforced Nano SiC particles composite was fabricated and their mechanical properties has been studied. Experiments have been planned as per Taguchi’s Method. After preparing the composite material by hand layup technique and then the mechanical characterizations are performed. Multi-response optimization has been carried out by employment of a recently developed method for multi-criteria decision making (MCDM), i.e. combined compromise solution (CoCoSo) method. For defining the relative significance of measured norms, pairwise comparison matrix was used. Optimal results have been verified through confirmatory experiments. Based on the experimental observations ultimate tensile strength (UTS), density and flexural strength, ANOVA result indicated that density has highest impact for a better mechanical behaviour. This can be useful in different field of application for fabrication of different structures, parts etc.
In this investigation, the influence of WEDM process constraints on tool wear rate, kerf width, surface roughness of SS 304 grade stainless steel was studied. Fifteen experimental runs were carried out based on Box-Behnken method of Response surface methodology and TOPSIS method was used for finding an optimum parameter setting. From the ANOVA results, pulse ON time was found as most significant factor for tool wear rate, kerf width and surface roughness. Genetic Algorithm and Simulated Annealing was also used for the calculation of the optimum setting along with the forecast of fitness values. It was found that every optimization technique gives similar factor setting.
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