A generic framework for optimizing performance metrics by tuning parameters of clustering protocols in WSNs

2019-04-01
Alchihabi, Abdullah
Dervis, Ates
Ever, Enver
Al-Turjman, Fadi
Wireless sensor network (WSN) is a key technology trend in emerging internet of things paradigms which are commonly used for application areas such as smart-cities, smart-grids, wearables, and connected health. There is a wealth of literature which considers various cluster-based routing protocols such as LEACH, HEED, and UHEED where these protocols are compared in terms of the network lifetime and/or the total number of packets successfully received by the base station under various operational conditions. While existing studies present various approaches to form WSN clusters in the most efficient way, various parameters are manually-assigned their values such as the radius of the cluster, the number of nodes in the cluster, and the number of clusters that should be formed to reach the base station. The choice of correct parameters is essential for reaching the most efficient configuration, however existing studies do not specify a systematic way for tuning these parameters. In other words, the optimization of cluster-based WSNs through fine tuning of related system parameters is not considered in the existing studies. We believe that presenting a generic approach to tune the parameters of clustering algorithms in order to optimize the performance metrics of WSNs is a significant contribution. In this study a systematic and an efficient method is presented to tune the parameters of clustering and routing protocols. Instead of brute force, or trial and error approaches, simulated annealing and K-beams algorithms are adopted together with discrete event system simulator OMNET++ with Castalia Framework. Results are presented comparatively with brute force approach in order to show the efficiency of the new approach in finding the optimum configuration in terms of energy efficiency as well as the rate of successfully received packets.

Suggestions

A Novel SDN Dataset for Intrusion Detection in IoT Networks
Sarica, Alper Kaan; Angın, Pelin (2020-11-04)
The number of Internet of Things (IoT) devices and the use cases they aim to support have increased sharply in the past decade with the rapid developments in wireless networking infrastructures. Despite many advantages, the widespread use of IoT has also created a large attack surface frequently exploited by cyber criminals, requiring real-time, automated detection and mitigation of various attacks in the high-volume network traffic generated. Software-defined networking (SDN) and machine learning (ML) base...
A Cloud Based Architecture for Distributed Real Time Processing of Continuous Queries
Gökalp, Mert Onuralp; Koçyiğit, Altan; Department of Information Systems (2015)
The technological advancements in Internet of Things (IoT) domain have enabled us to reshape the physical world through smart devices, sensors and actuators. The data collected by IoT devices has become a valuable asset to extract knowledge about the environment and other nearby devices. Existing IoT applications mostly store collected data in a central server and allow users to query stored data to notice and react to changes in the environment. Usually cloud and big data technologies are utilized in those...
A complex event processing framework implementation using heterogeneous devices in smart environments
Kaya, Muammer Özge; Eren, Pekin Erhan; Department of Information Systems (2012)
Significant developments in microprocessor and sensor technology make wirelessly connected small computing devices widely available; hence they are being used frequently to collect data from the environment. In this study, we construct a framework in order to extract high level information in an environment containing such pervasive computing devices. In the framework, raw data originating from wireless sensors are collected using an event driven system and converted to simple events for transmission over a...
An Effective Forest Fire Detection Framework Using Heterogeneous Wireless Multimedia Sensor Networks
Kizilkaya, Burak; Ever, Enver; Yatbaz, Hakan Yekta; Yazıcı, Adnan (2022-05-01)
With improvements in the area of Internet of Things (IoT), surveillance systems have recently become more accessible. At the same time, optimizing the energy requirements of smart sensors, especially for data transmission, has always been very important and the energy efficiency of IoT systems has been the subject of numerous studies. For environmental monitoring scenarios, it is possible to extract more accurate information using smart multimedia sensors. However, multimedia data transmission is an expensi...
A visual programming framework for distributed Internet of Things centric complex event processing
Gökalp, Mert Onuralp; Koçyiğit, Altan; Eren, Pekin Erhan (2019-03-01)
Complex Event Processing (CEP) is a promising approach for real-time processing of big data streams originating from Internet of Things (IoT) devices. Even though scalability and flexibility are key issues for IoT applications, current studies are mostly based on centralized solutions and restrictive query languages. Moreover, development, deployment and operation of big-data applications require significant amount of technical expertise. Hence, a framework that provides a higher abstraction level programmi...
Citation Formats