Summary
Designing an efficient, short, and secure authentication algorithm for resource‐constrained sensor nodes of wireless sensor networks (WSNs) is a challenging task. Authentication in WSNs is mainly performed by the digital signature algorithm. In this paper, we propose an efficient, short, and secure pairing computation‐free ID‐based authentication algorithm (signature scheme) ESS‐IBAA for WSNs which completely follows the rule of identity‐based cryptosystem. Identity‐based schemes, unlike traditional public‐key infrastructure (PKI)‐based schemes, remove the need for public‐key certificates for public‐key validation. It also removes extra costs associated with the public‐key certificate and traffic management. Further, due to the requirement of low power and fast authentication, bilinear pairing computation‐free identity‐based signature schemes are applicable in WSNs. Keeping this in mind, ESS‐IBAA scheme is proposed, which is pairing computation free and uses a general cryptographic hash function in the place of a costly map‐to‐point hash function. The proposed scheme ESS‐IBAA is secure against existential forgery on adaptive chosen message and ID attack in the random oracle model under the hardness of the elliptic curve discrete logarithm problem (ECDLP). Moreover, comparative performance analysis shows that the proposed scheme ESS‐IBAA is much more efficient in both communication cost and computation cost from the existing related schemes.
Background:
Wireless Sensor Network (WSN) is an arising field for research and development. It has various
applications ranging from environmental monitoring to battlefield surveillance and more. WSN is a collection of multiple
sensor nodes used for sensing the environment. But these sensing nodes are deployed in such areas where it is not that
easy to reach, so battery used in these nodes becomes quite impossible to change, so we need to utilize this energy to get
the maximum sensing for a long time.
Objective:
To use the Fuzzy approach in the clustering algorithm. Clustering is a key approach to prolong the network
lifetime with minimum energy utilization. In this paper, our main concern is on the Cluster Head (CH) selection. So, we
are proposing a clustering algorithm which is based on some of the attributes: Average Residual Energy of CHs, Average
Distance from nodes to CHs, Standard Deviation of member nodes, and Average Distance from CH to Base Station(BS).
Methods:
Initially, some of the nodes are found having greater residual energy than the average network energy, and
fifteen populations are made each having an optimum number of CHs. The final and best CHs set is chosen by
determining the maximum fitness value using a fuzzy approach.
Result:
The result positively supports the energy-efficient utilization with lifetime maximization, which is compared with
the Base algorithm [1] and LEACH [2] protocol based on residual energy and the number of nodes that die after
performing some rounds.
Conclusion:
The proposed algorithm determines a fuzzy-based fitness value, provides load-balancing among all the
networking nodes, and performs a selection of best Cluster Heads, resulting in prolonged network lifetime and maximized
efficiency.
Coronavirus disease 2019 (COVID19), the outbreak of the novel coronavirus, has posed an unprecedented public health threat to China and many other countries in the world at present, with a significant effect on health and public health systems, individual lives and national and world economic. COVID-19 has been declared by the WHO as a pandemic. The structures of public contact significantly determine spread of this infection and, in the absence of vaccines, the control of these structures through extensive social distancing measures have appeared to be the most effective means of mitigation. In this paper, to examine the impact of social distancing in COVID 19 distribution, we propose mathematical model using direct correlation between social exposure and reproduction number. We show that the calculation of social distance is an efficient way of monitoring the spread of COVID-19 in the absence of vaccines. In India, we have also calculated that the basic reproduction number is 2.5.
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