Energy efficient IoT virtualization framework with passive optical access networks

Abstract

In this paper we design a framework for an energy efficient cloud computing platform for Internet of things (IoT) accompanied by a passive optical access network (PON). The design is evaluated using a Mixed Integer Linear Programming (MILP) model. IoT network consists of four layers. The first layer represents IoT objects and the three other layers host relays, the coordinator and the gateway, respectively. PON consists of two layers hosting the Optical Network Units (ONUs) and the Optical Line Terminal (OLT), respectively. Equipment at all layers, except the object layer, can aggregate and process the traffic generated by IoT objects. The processing is performed using distributed mini clouds that host different types of Virtual Machines (VMs). These mini clouds can be located at the three upper layers of the IoT network and the PON two layers. We aim to reduce the total power consumption resulting from the traffic delivery and data processing at the different layers. The energy efficiency can be achieved by optimizing the placement and number of the mini clouds and VMs and utilizing energy efficient routes. Our results indicate that up to 21% of total power can be saved utilizing energy efficient PONs and serving heterogeneous VMs.

Impact of Distributed Processing on Power Consumption for IoT Based Surveillance Applications

“…In addition, we assume all IoT devices communicate through the WiFi (IEEE 802.11g) protocol with a supported bit rate of 54Mbps. It is important to note that we only consider uplink traffic, as this is reported to carry a much larger proportion of the data generated by IoT networks [13]. Furthermore, we assume the number of CPU instructions required to process one bit of data remains constant throughout our evaluations.…”

Energy Efficient Service Distribution in Internet of Things

“…We consider 25 IoT devices, which are randomly and uniformly distributed among the access points and each IoT device is located between 10 -50 meters away from its respective access point. The distance is used to calculate the power consumption in the wireless domain due to amplification requirements which are distance dependant [19]. In addition, we assume all IoT devices communicate through WiFi with a supported bit rate of 150 Mbps [20].…”

“…In addition, we assume all IoT devices communicate through WiFi with a supported bit rate of 150 Mbps [20]. It is important to note that we only consider uplink traffic, as this is reported to carry a much larger proportion of the data generated by IoT networks [19]. Furthermore, we assume the number of CPU instructions required to process one bit of data remains constant throughout our evaluations.…”

Energy Efficient IoT Virtualization Framework With Peer to Peer Networking and Processing

“…Constraints (13) and (14) ensure that the summation of the whole workloads of processed tasks by each object and each relay respectively do not exceed its maximum processing workload capability 5. Traffic calculations and capacity constraints…”

“…In [13], data processing and traffic aggregation were done by VMs hosted in cloudlets, where these mini clouds are distributed over the IoT network elements. The work was extended in [14] where two separated IoT networks were considered with the deployment of a Passive Optical Access Network (PON). The main goal of our previous work is to investigate the potential energy efficiency gains that can be made if a use is made of distributed cloudlets at the edge of the network compared to centralized cloudlets at highest layer of the implemented model.…”