  In this paper, an energy efficient IoT virtualization framework with P2P
networking and edge computing is proposed. In this network, the IoT task
processing requests are served by peers. The peers in our work are represented
by IoT objects and relays that host virtual machines (VMs). We have considered
three scenarios to investigate the saving in power consumption and the system
capabilities in terms of task processing. The first scenario is the relays only
scenario, where the task requests are processed using relays only. The second
scenario is the objects only scenario, where the task requests are processed
using the IoT objects only. The last scenario is a hybrid scenario, where the
task requests are processed using both IoT objects and VMs. We have developed a
mixed integer linear programming (MILP) model to maximize the number of
processing tasks served by the system and minimize the total power consumed by
the IoT network. We investigated our framework under the impact of VMs
placement constraints, fairness constraints between the objects, tasks number
limitations, uplink and downlink limited capacities, and processing capability
limitations. Based on the MILP model principles, we developed an energy
efficient virtualized IoT P2P networks heuristic (EEVIPN). The heuristic
results were comparable to those of the MILP in terms of energy efficiency and
tasks processing. Our results show that the hybrid scenario serves up to 77%
(57% on average) processing task requests, but with higher energy consumption
compared to the other scenarios. The relays only scenario can serve 74% (57% on
average) of the processing task requests with 8% saving in power consumption
compared to the hybrid scenario. In contrast, 28% (22% on average) of task
requests can be successfully handled by applying the objects only scenario with
up to 62% power saving compared to the hybrid scenario.
