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The present struggle with COVID 19 pandemic has necessitated strategic response in healthcare systems to decrease mortalities even with poor lab infrastructure. With improved disease surveillance, any country can handle health emergencies in a better manner. Combining wearable device technology with smartphone, self-testing can be improved and real time monitoring of various parameters such as temperature, oxygen levels and pulse rate reducing burden on healthcare and creating a vigilant environment. This also help us in contract tracing and also reduce death out of comorbities which has caused a heavy death toll out of pandemic. Here, the components of daily use are deployed with slight modification for creating real time monitoring along with auto alarm and warning transmission to local health ministry. Data collected from sensors are stored in Arduino memory and transmitted to smartphone through Wi -Fi module. Our proposed system is used to process, analyse and display patient's collected data with auto alarm. Our proposed system has been very reliable with average delay of 14s and low power consumption with standing time of nearly 4 hr.

Abstract. Several variations of rooted tree based solutions have been recently proposed for member revocation in multicast communications [18,19,20,21]. In this paper, we show that by assigning probabilities for member revocations, the optimality, correctness, and the system requirements of some of these schemes [18,19,20,21] can be systematically studied using information theoretic concepts. Specifically, we show that the optimal average number of keys per member in a rooted tree is related to the entropy of the member revocation event. Using our derivations we show that (a) the key assignments in [18,21,20,19] correspond to the maximum entropy solution, (b) and direct application of source coding will lead to member collusion (we present recently proposed solutions [21,20] as examples of this) and a general criteria that admits member collusion. We also show the relationship between entropy of member revocation event and key length.

This paper presents a theoretical framework based on Bayesian decision theory for analyzing recently reported results on implicit coscheduling of parallel applications on clusters of workstations. Using probabilistic modeling, we show that the approach presented can be applied for processes with arbitrary communication mixes. We also note that our approach can be used for deciding the additional spin times in the case of spin-yield. Finally, we present arguments for the use of a different notion of fairness than assumed by prior work.

Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. ABSTRACT This paper presents a robust, scalable extension to the recently proposed multicast Group Key Management Protocol GKMP 1 , 2 , in terms of security administration. The GKMP has two major security related problems, a lack of any mechanism to remove a compromised group administrator, b lack of scalability. We are able to remove a compromised single panel member from generating the group keys by setting the panel members with shared authority to generate the group keys. We then introduce the sub-controllers who have all the functionalities of the group control panel except the authority to generate the group keys. The subcontrol panel helps scalability of the network in terms of the security operations. The sub-controllers are chosen using a threshold based clustering algorithm.