Contact Ratio Aware Mobile Edge Computing for Content Offloading Content offloading in mobile edge computing is one of the effective ways to alleviate network congestion. This paper studies the content offloading problem in bufferconstraint edge scenarios. First, the content offloading problem is transformed into the maximum delivery rate and minimum transmission delay problem integrating the heterogeneous contact rate between users and small base stations. Second, a Lagrangian multiplier method is employed to compute the optimal numbers of offloading copy for each file, and then a greedy algorithm which can achieve the optimality with a probability 1  1e is proposed, followed by a distributed algorithm with the same performance as the greedy one. Finally, the proposed schemes are compared with the classical algorithms, and the simulation results show that they enhance the content delivery rate and reduce the transmission delay in different popularity distributions and buffer sizes.

CrossServer Computation Offloading for MultiTask Mobile Edge Computing As an emerging network architecture and technology, mobile edge computing (MEC) can alleviate the tension between the computationintensive applications and the resourceconstrained mobile devices. However, most available studies on computation offloading in MEC assume that the edge severs host various applications and can cope with all kinds of computation tasks, ignoring limited computing resources and storage capacities of the MEC architecture. To make full use of the available resources deployed on the edge servers, in this paper, we study the crossserver computation offloading problem to realize the collaboration among multiple edge servers for multitask mobile edge computing, and propose a greedy approximation algorithm as our solution to minimize the overall consumed energy. Numerical results validate that our proposed method can not only give nearoptimal solutions with much higher computational efficiency, but also scale well with the growing number of mobile devices and tasks.