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Energy consumption is one of the critical challenges in designing wireless sensor network (WSN) since it is typically composed of resource-constrained devices. Many studies have been proposed clustering to deal with energy conservation in WSN. Due to its predominance in coordinating the behaviors of many players, game theory has been considered for improving energy efficiency in WSN. In this paper, we evaluate the performance of cooperative game theoretic clustering (CGC) algorithm which employs cooperative game theory in a form of 3-agent cost sharing game for energy-efficient clustering in WSN. Furthermore, we compared its performance to a well-known traditional clustering method, low-energy adaptive clustering hierarchy (LEACH), in terms of network lifetime and stability, and total residual energy. The simulation results show that CGC has better performance compared to LEACH due to the cooperation among cluster heads in coalition. CGC has higher alive nodes with stability improvement of first node dies (FND) by 65%, and the improvement by 52.4% for half node dies (HND). However, with the increasing of the number of nodes, the performance of LEACH is getting better compared to CGC.

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COVID-19, which has become a global pandemic since March 2020, has tremendously affected human life globally. The negative impact of COVID-19 affects societies in almost all aspects. Implementing quarantine monitoring, also social distancing, and contact tracing are a series of processes that can suppress the new infected COVID-19 cases in various countries. Prior works have proposed different monitoring systems to assist the monitoring of individuals in quarantines, as well as many methods are offered for social distancing and contact tracing. These methods focus on one function to provide a reliable system. In this paper, we propose IoT-based quarantine monitoring by implementing a geofence equipped with social distancing features to offer an integrated system that provides more benefits than one system carrying one particular function. We propose a system consisting of a low cost, low complexity, and reusable wristband design and mobile apps to support the quarantine monitoring system. For the geofencing, we propose a GPS-based geofence system that was developed by taking advantage of the convenience offered by the Traccar application. Meanwhile, we add the notification for social distancing feature with adaptive distance measurement RSSI-based set up in the android application. Based on the experiment we did to validate the system, in terms of wristband-to-smartphone communication, scanning interval in smartphone and advertising interval in wristband is best to set in 7 s for both. For social distancing notification and geofence, we measure the system performance through precision, recall, accuracy, and F-measure.