Mobile Edge Computing: A Survey on Architecture and Computation Offloading

Technological evolution of mobile user equipments (UEs), such as smartphones\nor laptops, goes hand-in-hand with evolution of new mobile applications.\nHowever, running computationally demanding applications at the UEs is\nconstrained by limited battery capacity and energy consumption of the UEs.\nSuitable solution extending the battery life-time of the UEs is to offload the\napplications demanding huge processing to a conventional centralized cloud\n(CC). Nevertheless, this option introduces significant execution delay\nconsisting in delivery of the offloaded applications to the cloud and back plus\ntime of the computation at the cloud. Such delay is inconvenient and make the\noffloading unsuitable for real-time applications. To cope with the delay\nproblem, a new emerging concept, known as mobile edge computing (MEC), has been\nintroduced. The MEC brings computation and storage resources to the edge of\nmobile network enabling to run the highly demanding applications at the UE\nwhile meeting strict delay requirements. The MEC computing resources can be\nexploited also by operators and third parties for specific purposes. In this\npaper, we first describe major use cases and reference scenarios where the MEC\nis applicable. After that we survey existing concepts integrating MEC\nfunctionalities to the mobile networks and discuss current advancement in\nstandardization of the MEC. The core of this survey is, then, focused on\nuser-oriented use case in the MEC, i.e., computation offloading. In this\nregard, we divide the research on computation offloading to three key areas: i)\ndecision on computation offloading, ii) allocation of computing resource within\nthe MEC, and iii) mobility management. Finally, we highlight lessons learned in\narea of the MEC and we discuss open research challenges yet to be addressed in\norder to fully enjoy potentials offered by the MEC.\n