Integrating Software Defined Network Approach Into Wireless Sensor And Actuator Networks

Project Title: Integrating Software-Defined Networking(SDN) Approach Into Wireless Sensor And Actuator Networks(WSAN)

Team: Celal ÇEKEN,Ph.D Ali Al-Shaikhlia,Ph.D. Candidate Mohammed Al-Hubaishi,Ph.D. Candidate Kadir Erkan,Ph.D

Sponsors: TÜBİTAK, Sakarya University

Start Date: 2016

Project Overview

Energy consumption is one of the most important design constraints when building a wireless sensor and actuator network (WSAN) since each device in the network has a limited capacity of the battery and prolonging the lifetime of the network depends on saving energy. This challenge needs a smart and reconfigurable network energy management strategy. Software-Defined Networking (SDN) paradigm aims to build a flexible and dynamic network structures, especially in wired networks. In this project an SDN supported WSAN architecture is proposed. The SDN enabled WSAN system has three main components. The most critical one is SDN Controller that includes all the network intelligence and is in charge of handling all the network controlling and management operations. In addition to its other functions, SDNC also has a routing decision unit with a new fuzzy-based Dijkstra’s algorithm. The second component of this system is End Device (ED) that has an application layer and may also behave as a Routing Device (RD) according to the network and application requirements. The last com- ponent is a communication interface protocol, referred as WSANFlow in the remainder of the paper, placed between SDNC and EDs.All the controlling messages, even the ones related to routing discovery, are transmitted using this protocol.

Project Video 1.1: Simulation Model

Publications

Ali Al-Shaikhli, Celal Çeken, Mohammed Al-Hubaishi "WSANFlow: An Interface Protocol between SDN Controller and End Devices for SDN-Oriented WSAN",Wireless Personal Communications, 2018, DOI: 10.1007/s11277-018-5714-5 View
Mohammed Al-Hubaishi, Celal Çeken, Ali Al-Shaikhli "A Novel Energy-Aware Routing Mechanism for SDN-Enabled WSAN", International Journal of Communication Systems, 2018, DOI: 10.1002/dac.3724 View
Celal Çeken, Mohammed Al-Hubaishi "Integrating SDN-Enabled Wireless Sensor Networks Into The Internet", 2019

A New Routing Discovery Mechanism for SDN Enabled Clustered WSAN

Choosing the shortest distance route may not be the most appropriate decision for energy efficient network design. Power consumption ratio of any node increases when different routes use the same node, which may also shorten the network lifetime. When this aspect is considered, it is not difficult to conclude 5 of 20 that routing decision is a vital mechanism for energy-aware network structures. In this study, we proposed a new routing discovery mechanism that incorporates fuzzy based dijsktra’s algorithm into routing process in order for SDNC decision making module to be more effective. In the proposed SDNC, which is outlined in the given Figure, the End Device Status Aggregation (EDSA) unit collects ED statuses such as remaining energy and neighbor device list together with related SNR periodically. Each ED transmits a command frame including device status to SDNC in order to update its status information in SDNC. When an application running on an ED need to communicate with a destination node, it firstly sends a connection request to the SDNC to be able to get the proper path to the destination.

Simulation Environment

Two different simulation scenarios were evaluated in order to investigate the performance of the developed models and algorithms. While the SDNC in the first scenario employed the proposed fuzzy-based Dijkstra’s algorithm so that the optimum path could be established, the second scenario included an SDNC with a regular Dijkstra’s algorithm. Having these two alternatives in hand, the impact of the proposed routing discovery algorithm can be easily extracted and interpreted from the simulation results. Each scenario was simulated under varying working conditions using commercially available software called Riverbed Modeler. An illustration of the network together with the developed components and algorithms is shown in the Figure.

Simulation Results

The findings show that the proposed algorithm shows better performance for all values of the number of application, as a consequence of the developed model that considers also the battery level of the next hop device, as stated earlier. When all applications are running, the first node death time for the network with the proposed algorithm is 9500 seconds, whereas the regular Dijkstra’s algorithm the first node death time is approximately 8700 seconds.