Novel reliable and dynamic energy-aware routing protocol for large scale wireless sensor networks

Wireless sensor networks (WSN) are made up of an important number of sensors, called nodes, distributed in random way in a concerned monitoring area. All sensor nodes in the network are mounted with limited energy sources, which makes energy harvesting on top of the list of issues in WSN. A poor communication architecture can result in excessive consumption, reducing the network lifetime and throughput. Centralizing data collection and the introduction of gateways (GTs), to help cluster heads (CHs), improved WSN life time significantly. However, in vast regions, misplacement and poor distribution of GTs wastes a huge amount of energy and decreases network’s performances. In this work, we describe a reliable and dynamic with energy-awareness routing (RDEAR) protocol that provides a new GT’s election approach taking into consideration CHs density, transmission distance and energy. Applied on 20 different networks, RDEAR reduced the overall energy consumption, increased stability zone and network life time as well as other compared metrics. Our proposed approach increased network’s throughput up to 75.92% , 67.7% and 9.78% compared to the low energy adaptive clustering hierarchy (LEACH), distributed energy efficient clustering (DEEC) and static multihop routing (SMR), protocols, respectively

Review of Ad Hoc Networks scenarios and challenges in years 2015-2019

A Mobile Ad-hoc Network (MANET) protocol performance analysis depends on the type of simulation tools, mobility models, and metrics used. These parameters\u27 choice is crucial to researchers because it may produce an inaccurate result if it is not well chosen. The challenges researcher is facing are on the choice of these four parameters. Our survey shows an inclination to used Ad-hoc On-Demand Distance Vector routing (AODV) for performance comparison and enhancement of it by the researcher. Network simulation 2 (NS2) was the most selected tool, but we observe a decline in its utilization in recent years. Random Waypoint Mobility model (RWPM) was the most used mobility model. We have found a high percentage of the published article did not mention the mobility models use; this will make the result difficult for performance comparison with other works. Packet Delivery Ratio (PDR), End to End Delay (E2ED) were the most used metrics. Some authors have self-developed their simulation tools; the authors have also used new metrics and protocols to get a particular result based on their research objective. However, some criteria of choosing a protocol, metrics, mobility model, and simulation tool were not described, decreasing the credibility of their papers\u27 results. Improvement needs to be done in the Ad-hoc network in terms of benchmark, acceptable scenario parameters. This survey will give the best practice to be used and some recommendations to the Ad-hoc network community

A dynamic trust and mutual authentication scheme for MANET security

MANETs are attractive technology in providing communication in the absence of a fixed infrastructure for applications such as, first responders at a disaster site or soldiers in a battlefield (Kumar, and Mishra, 2012). The rapid growth MANET has experienced in recent years is due to its Ad Hoc capabilities that have also made it prime target of cybercrimes (Jhaveri, 2012). This has raised the question of how could we embrace the benefits of MANET without the increased security risks. MANETs have several vulnerabilities such as lack of a central point, mobility, wireless links, limited energy resources, a lack of clear line of defence, cooperative nature and non-secure communication to mention a few. This research proposes a two-phase scheme. In phase-one a novel approach is suggested by using concept of exiting trust schemes and adopting the use of Dynamic Trust Threshold Scheme (DTTS) for the selection of trusted nodes in the network and using mutual trust acknowledgement scheme of neighbour nodes to authenticate two communicating nodes. The notion of trust is used for authenticating peer nodes. The trust scheme algorithm is based on real time network dynamics, relevant to MANET conditions, as opposed to pre-determined static values. The phase-one is implemented in AODV and tested in a simulated environment using NS2. The reason for using AODV is that it’s reactive and has comparatively low routing overhead, low energy consumption and relatively better performance (Morshed, et al 2010). In order to ensure data confidentiality and end-to-end security, in phase-two, the source and destination generates a shared secret key to communicate with each other using a highly efficient Diffie Hellman Elliptic Curve scheme (Wang, Ramamurthy and Zou, 2006). The shared key is used to encrypt data between the peer nodes

Personality Identification from Social Media Using Deep Learning: A Review

Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed