Wireless communication is one of the most attractive and fast growing fields in technology nowadays. The accessibility of wireless access technologies has become an essential aspect of mobile communication. Owing to the ubiquity of divergent access networks, user satisfaction, significantly affected by the factors such as roaming (frequent handover), security association, quality of service provision, seamless connectivity to the best-connected network, has gained a significant importance of designing the future generation wireless networks. Emerging applications tends to demand high-speed networks and much better throughput improvement at a reasonable cost. Mobile cloud computing (MCC) is a mixture of cloud and mobile networks, which brings extra benefits to mobile clients, network operators, and cloud providers. This thesis addresses the challenging issue related to the security in MCC technology, especially in the authentication process during the handover. Most existing vertical handover authentication protocols still suffer from some barriers, for example, undesirable delay in real-time applications, the man in the middle attack, and replay attack. In this thesis, a new authentication protocol for heterogeneous mobile cloud networks is proposed. The proposed protocol is based on the view of the 3GPP Access Network Discovery and Selection Function (ANDSF), which uses the capacities given by the IEEE 802.11 and the 3GPP Long Term Evolution– Advanced (LTE-A) Standards interconnection. To solve the problems experienced by cloud computing during authentication in the handover process, a prediction scheme is used which adds no additional load over the network or the user. The proposed handover authentication protocol outperformed existing protocols in terms of key confidentiality, powerful security, and efficiency which used to reduce bandwidth consumption. Providing complete mobility along with minimizing the poor quality of service (QoS) is one of the highest essential challenges in mobile wireless networks. Handover prediction can overcome these challenges. In this thesis, two novel prediction schemes are proposed. The first prediction scheme depends on scanning the quality of all signals among mobile station and all nearby stations in the surrounding area, while the second one is based on a multi-criteria prediction decision using both the signal-to-noise ratio SNR value and station’s bandwidth. Moreover, the prediction efficiency is improved by reducing the number of redundant/ unnecessary handovers. The proposed schemes are evaluated using different scenarios with several mobile stations’ numbers, different WLAN access points, LTE-base station number & location, and random mobile station movement manner. The proposed schemes achieved a success rate of 99% with the different scenarios using LTE-WLAN architecture. The performance of the proposed prediction schemes outperformed the performance of the existing prediction schemes in terms of the accuracy percentage. Fog Computing is clearly foresee able in future and might replace several different computing paradigms existent today. The over whelming nature of data generated is evident during the past few years and the need to derive meaningful insights from this data is still apparent. The proposed handover prediction schemes are examined and experienced in fog environment using LTE-Wi-Fi heterogeneous networks. The proposed schemes enhanced the handover mechanisms accuracy in Fog networks as well as minimized the overall computation overhead in switching connection in handover process.