Mitigating Hotspot Problem Using Chaotic Salp Swarm Algorithm for Energy Efficient IoT Assisted Wireless Sensor Networks

Wireless Sensor Networks (WSN) and Internet of Things (IoT) continued to be pro-active study due to their far reaching applications and also a crucial technology for ubiquitous living. In WSN, energy awareness becomes a significant design problem. Clustering can be defined as a renowned energy-efficient method and renders a lot of benefits like energy competence, less delay, scalability, and lifetime; but it resulted in hot spot problems. To sort out this problem a method called unequal clustering is designed. In unequal clustering, the cluster size differs with the Base Station (BS) distance. In this study, a new Chaotic Salp Swarm Algorithm Based Unequal Clustering Approach (CSSA-UCA) methodology to resolve hot spot issues in IoT-assisted WSN is proposed. The major objective of the CSSA-UCA methodology lies in the effectual identification of CHs and unequal cluster sizes. To accomplish this, the CSSA-UCA technique initially derives the CSSA by the incorporation of chaotic notions into the conventional SSA. At the same time, a fitness function incorporating multiple input parameters was considered for unequal cluster construction. A wide range of experimental result analyses is performed to exhibit the supremacy of the CSSA-UCA technique. The experimental results stated that the CSSA-UCA technique proficiently balances energy accretion and improves the network lifetime

Extending the Lifetime of Wireless Sensor Networks Based on an Improved Multi-objective Artificial Bees Colony Algorithm

Reducing the sensors\u27 energy expenditure to prolong the network lifespan as long as possible remains a fundamental problem in the field of wireless networks. Particularly in applications with inaccessible environments, which impose crucial constraints on sensor replacement. It is, therefore, necessary to design adaptive routing protocols, taking into account the environmental constraints and the limited energy of sensors. To have an energy-efficient routing protocol, a new cluster heads’ (CHs) selection strategy using a modified multi-objective artificial bees colony (MOABC) optimization is defined. The modified MOABC is based on the roulette wheel selection over non-dominated solutions of the repository (hyper-cubes) in which a rank is assigned to each hypercube based on its density in dominated solutions of the current iteration and then a random food source is elected by roulette from the densest hypercube. The proposed work aims to find the optimal set of CHs based on their residual energies to ensure an optimal balance between the nodes\u27 energy consumption. The achieved results proved that the proposed MOABC-based protocol considerably outperforms recent studies and well-known energy-efficient protocols, namely: LEACH, C-LEACH, SEP, TSEP, DEEC, DDEEC, and EDEEC in terms of energy efficiency, stability, and network lifespan extension

An Improved Energy-Aware Distributed Unequal Clustering Protocol using BBO Algorithm for Heterogeneous Load Balancing

With the rapid extension of IoT-based applications various distinct challenges are emerging in this area Among these concerns the node s energy efficiency has a special importance since it can directly affect the functionality of IoT-Based applications By considering data transmission as the most energy-consuming task in IoT networks clustering has been proposed to reduce the communication distance and ultimately overcome node energy wastage However cluster head selection as a non-deterministic polynomial-time hard problem will be challenging notably by considering node s heterogeneity and real-world IoT network constraints which usually have conflicts with each other Due to the existence of conflict among the main system parameters various solutions have been proposed in recent years that each of which only considered a few real-world limitations and parameter

WICC 2017 : XIX Workshop de Investigadores en Ciencias de la Computación

Actas del XIX Workshop de Investigadores en Ciencias de la Computación (WICC 2017), realizado en el Instituto Tecnológico de Buenos Aires (ITBA), el 27 y 28 de abril de 2017.Red de Universidades con Carreras en Informática (RedUNCI

Untangling the Web: A Guide To Internet Research

[Excerpt] Untangling the Web for 2007 is the twelfth edition of a book that started as a small handout. After more than a decade of researching, reading about, using, and trying to understand the Internet, I have come to accept that it is indeed a Sisyphean task. Sometimes I feel that all I can do is to push the rock up to the top of that virtual hill, then stand back and watch as it rolls down again. The Internet—in all its glory of information and misinformation—is for all practical purposes limitless, which of course means we can never know it all, see it all, understand it all, or even imagine all it is and will be. The more we know about the Internet, the more acute is our awareness of what we do not know. The Internet emphasizes the depth of our ignorance because our knowledge can only be finite, while our ignorance must necessarily be infinite. My hope is that Untangling the Web will add to our knowledge of the Internet and the world while recognizing that the rock will always roll back down the hill at the end of the day