Energy Efficient Network Selection in Heterogeneous Network using TOPSIS

Due to integration of heterogeneous wireless technology demand of seamless communication is increases. Various approaches have been proposed for network selection in vertical handoff. Here we propose a new energy efficient network selection algorithm by considering three networks (CDMA, WIMAX &WLAN) for network selection .In this work, based on the power consumption, traffic class and current battery level of each network interface card , the mobile terminal lifetime is to be calculated. As the lifetime of mobile terminal decreases, we reduce the number of attributes and networks by eliminating the particular network form network list. AHP (Analytic hierarchical process) and TOPSIS (Technique for order of Preference by similarity to the Ideal Solution) are used for network selection

A hybrid intelligent model for network selection in the industrial Internet of Things

Industrial Internet of Things (IIoT) plays an important role in increasing productivity and efficiency in heterogeneous wireless networks. However, different domains such as industrial wireless scenarios, small cell domains and vehicular ad hoc networks (VANET) require an efficient machine learning/intelligent algorithm to process the vertical handover decision that can maintain mobile terminals (MTs) in the preferable networks for a sufficient duration of time. The preferred quality of service parameters can be differentiated from all the other MTs. Hence, in this paper, the problem with the vertical handoff (VHO) decision is articulated as the process of the Markov decision aimed to maximize the anticipated total rewards as well as to minimize the handoffs’ average count. A rewards function is designed to evaluate the QoS at the point of when the connections take place, as that is where the policy decision for a stationary deterministic handoff can be established. The proposed hybrid model merges the biogeography-based optimization (BBO) with the Markov decision process (MDP). The MDP is utilized to establish the radio access technology (RAT) selection’s probability that behaves as an input to the BBO process. Therefore, the BBO determines the best RAT using the described multi-point algorithm in the heterogeneous network. The numerical findings display the superiority of this paper’s proposed schemes in comparison with other available algorithms. The findings shown that the MDP-BBO algorithm is able to outperform other algorithms in terms of number of handoffs, bandwidth availability, and decision delays. Our algorithm displayed better expected total rewards as well as a reduced average account of handoffs compared to current approaches. Simulation results obtained from Monte-Carlo experiments prove validity of the proposed model