Wireless sensor networks have grown rapidly with the innovation in Information Technology. Sensor nodes are distributed and deployed over the area for gathering requisite information. Sensor nodes possess a negative characteristic of limited energy which pulls back the network from exploiting its peak capabilities. Hence, it is necessary to gather and transfer the information in an optimized way which reduces the energy dissipation. Ant Colony Optimization (ACO) is being widely used in optimizing the network routing protocols. Ant Based Routing can play a significant role in the enhancement of network life time. In this paper, Intercluster Ant Colony Optimization algorithm (IC-ACO) has been proposed that relies upon ACO algorithm for routing of data packets in the network and an attempt has been made to minimize the efforts wasted in transferring the redundant data sent by the sensors which lie in the close proximity of each other in a densely deployed network. The IC-ACO algorithm was studied by simulation for various network scenarios. The results depict the lead of IC-ACO as compared to LEACH protocol by indicating higher energy efficiency, prolonged network lifetime, enhanced stability period, and the elevated amount of data packets in a densely deployed wireless sensor network.

Software development with minimum effort has become a challenging task for the software de-velopers. Software effort may be defined as the prediction process of the effort required to de-velop any software. Many software effort estimation models have been developed in the past, but it is observed that none of them can be applied successfully in all kinds of projects in differ-ent environments that raise the problem of the software effort estimation model selection. To se-lect the suitable software effort estimation model, many conflicting selection criteria must be con-sidered in the decision process. The present study emphasizes on the development of a fuzzy multi-criteria decision making approach by integrating Fuzzy Set Theory and Weighted Distance Based Approximation. To show the consistency of the proposed approach, methodology valida-tion is also performed by making comparison with existing methodologies and to check the criti-cality of the selection criterion, sensitivity analysis is also performed

As Sensor networks are being used in remote environment monitoring, healthcare, machine automation, security of these networks is becoming a central concern. Till now main concern was to make sensor networks useful and deployable and little emphasis was placed on security. This paper analyses security issues and vulnerabilities in wireless sensor networks. The paper gives an overview of various security protocols used for wireless sensor networks and finally a comparison is done for the various security protocols available.

Earthquake Early Warning Systems (EEWS) needless to mention is an essential tool in mitigating the effects of earthquakes by passing a warning to the affected region. The functionality of these systems presupposes the real-time identification and evaluation of seismic activity, and the modern development of automated detection protocols is considered to have boosted this factor significantly. This paper provides a critical analysis of the current approaches, tools, and platforms used in the detection and prevention of earthquakes. It also focuses on the advancements in the sensor systems like high sensitivity seismic sensors, fibre optic sensors, etc which were effectively incorporated and enhanced the capabilities of the seismic data acquisition. Further, the paper explores the machine learning technologies such as deep learning models and the hybrid model strategies used in the analysis of seismic data and prediction of earthquakes with higher efficiency. These algorithms help to detect those extremely subtle patterns and deviations that may characterize certain periods before the seismic activity, bringing the warnings earlier and more accurately. Data processing in real-time is also another and important emphasis of this class of reviews. Some of the developments highlighted in the paper include parallel computing, cloud computing, edge computing that make it easier to perform analysis and disseminate the warnings. Thus, employing these technologies, EEWS can give more prompt responses and accurate alerts, which contributes to increasing public safety and improving disaster readiness. The paper also consolidates a collection of case studies of different countries and zones containing Japan, Mexico, California, and Turkey. The present practical examples are intended to show the application of the automated detection procedures and to point out the working experience and problem fields connected with the use of the methods at different geographical and technological conditions.