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MOBILE EDGECOMPUTATIONOFFLOADING BASEDIN IOT DEVICES

An Academic presentation byDr. Nancy Agens, Head, Technical Operations, PhdassistanceGroup  www.phdassistance.comEmail: info@phdassistance.com

In Brief

Introduction

Contributions

System Model

System Architecture

Conclusion

Future Scopes

Outline

TODAY'S DISCUSSION

Internet of Things has shown great increase in the development that leadto the evolution of the delay-sensitive and computation-intensive

functions. As the cloud computing technology is time delaying, and thereis a limitation of resources at end devices, mobile edge computing is

well-thought-out as a most promising method that could solve the time-delaying issues of such challenging applications. Mobile-edge

computing can be applied to the Internet of Things (IoT) devices toprovide the better quality for computation intensive applications and to

extend the life of battery.

In Brief

Mobile-edge Computing network implements a binary offloading strategy, so thatthe computation is either executed locally or offloaded completely to a mobile-edgecomputing server in the Wireless Devices (WD).

With the advancement in the wireless power transfer (WPT) technology, we cancharge the battery of the wireless devices continuously over the air without replacingbattery in these devices.

In the meantime, the computing power of the device can be enhanced to a greatextent due to the advancement of mobile-edge computing (MEC) technology.

Introduction

Contributions

To develop the management issues in computationoffloading across various networks with the aim ofreducing the power consumption across the network.

To efficiently solve this management issue, a frameworkhas been developed to obtain transmission powerallocation approach and computation offloading design.

The figure below shows a mobile-edge computing network possessingone cloud server with K edge servers, and N wireless devices.

Assuming that each wireless device has M independent tasks where eachtask of the device is computed by the wireless device itself or be offloadedto, and they are processed by the cloud server.

System Model

Figure 1: System Model of a Multi-User Multi-Task Mobile Edge Computing (MEC) Network

System Architecture

The MEC system consists of three layers. They are, 1. MANAGEMENT LAYER: The main role of this layer is to provide global resource allocation to assure stability in difficult computation. 2. EDGE LAYER: This layer consists of an access point (AP) and a base station (BS), and supplies the resource needed for computation. 3. DEVICE LAYER: There are a set of IoT devices which lack local computing capacity, and additionally they are expected to perform some similar tasks with the same latency constraint, such as sensors used for tracking on bicycles.

Figure 2: System architecture

Conclusion

IoT has evolved as a renowned technology for building mobile applications.

With the progress of the technology, the intricacy and balance of the data for processingalso increases.

EC model help to control the issue to a great extent by offloading computing tasks to thecloud server.

To reduce the implementation time and the power consumption of mobile devices, acomputation offloading method (COM) has been proposed.

Future Scopes

For future work, the proposed method would be extended in a real worldsituation of IoT.

Additionally, it is proposed to resolve different time requirements neededfor execution, and to find an offloading approach to reduce the energyconsumption of the IoT devices.

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