We evaluate a Bluetooth-based mobile contact-confirming app, COVID-19 Contact-Confirming Application (COCOA), which is being used in Japan to contain the spread of COVID-19, the disease caused by the novel virus termed SARS-COV-2. The app prioritizes the protection of users’ privacy from a variety of parties (eg, other users, potential attackers, and public authorities), enhances the capacity to balance the current load of excessive pressure on health care systems (eg, local triage of exposure risk and reduction of in-person hospital visits), increases the speed of responses to the pandemic (eg, automated recording of close contact based on proximity), and reduces operation errors and population mobility. The peer-to-peer framework of COCOA is intended to provide the public with dynamic and credible updates on the COVID-19 pandemic without sacrificing the privacy of their information. However, cautions must be exercised to address critical concerns, such as the rate of participation and delays in data sharing. The results of a simulation imply that the participation rate in Japan needs to be close 90% to effectively control the spread of COVID-19.
This paper introduces a novel scheduling problem called the active interval scheduling problem in hierarchical wireless sensor networks for long-term periodical monitoring applications. To improve the report sensitivity of the hierarchical wireless sensor networks, an efficient scheduling algorithm is desired. In this paper, we propose a compact genetic algorithm (CGA) to optimize the solution quality for sensor network maintenance. The experimental result shows that the proposed CGA brings better solutions in acceptable calculation time. . In this architecture, the sensor network is partitioned into several clusters. Each cluster contains several sensor nodes and a local control center (LCC). A sensor node has capability to detect and then reports the detection results to its LCC. The detection results are then routed back to the sink through the Core Network constructed by only the LCCs. The sink may communicate with the global control center (GCC) via Internet or satellite. The sensor nodes are immobile in this study. In each cluster, the LCC applies the polling protocol to communicate with all its sensor nodes.In [1], each cluster is assumed to be active periodically and the entire clusters apply the same period. The period for all the clusters is said to be the detection cycle and the length of detection cycle is denoted as ldc. Each cluster is allowed to be active in the same period in all the detection cycle, and the period is called the active interval of the cluster.
THE ACTIVE INTERVAL SCHEDULING PROBLEMWe adopt the following definitions proposed in [1] as following. D 1: CL = {C 1 , C 2 , …, C n } be the set of all clusters, where n is the number of cluster nodes in the core network. Since ldc min = min{ t e (i) | C i ∈ CL}, and the network requires adjacent clusters should not be active simultaneously. Therefore, in [1], the cost model for ldc min minimization is stated as follow.
Minimize ldc min(1) Subject to
THE PROPOSED COMPACT GENETIC ALGORITHMThe methodology of the algorithm design is to classified all the clusters into m sets V 1 , …, V m . The set V i is called the i th selection of the solution. The clusters in the same selection can be active simultaneously. The active interval of each cluster in the i th selection is a sub-interval of (t i-1 , t i ), and hence ldc min = t m .
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