The significant development of mobile cloud computing allows a mobile user to access resources of the nearby mobile devices, i.e., Cloudlets, for processing tasks by using the offloading mechanism. However, due to the mobility of the user and cloudlets, the connection between the user's device and cloudlets may be interrupted since cloudlets move out of transmission range of the user's device. Consequently, the task transmission may fail, forcing the user to re-offload the task to another cloudlet or process on the local device. In this paper, we propose a dynamic opportunistic offloading algorithm which allows the user to make the decision of offloading or deferring the processing of each task in a set of parallel tasks. We formulate and solve a Markov Decision Process (MDP) model for the mobile user to obtain an optimal offloading policy while minimizing the offloading and processing cost. We extend the MDP model to a constrained MDP to solve the offloading problem when the user has a processing deadline. Numerical studies and simulations were carried out to evaluate the performance of the proposed model. The results show that the proposed model outperforms conventional baseline schemes.