Hassaan Hydher, Dushantha Nalin K Jayakody, Kasun T. Hemachandra, Tharaka Samarasinghe
Conference
INFOCOM IEEE INFOCOM 2022-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) , pp. 1-6 · 2022 · Cited by 19
Internet of Things and Sensor NetworksNetwork Optimization and IntelligenceUAVs and Aerial Robotics
Abstract
This paper addresses the problem of deploying unmanned aerial vehicles (UAVs) to assist data collection and transmission in wireless sensor networks (WSNs). A multi-UAV deployment algorithm is proposed for an energy-constrained network to minimize the maximum transmit power of the sensor node (SN), while satisfying data rate and transmit power constraints. The problem is divided into two subproblems, namely, UAV-SN association, and UAV positioning. First, the UAV-SN association is addressed using a customized Gale-Shapley algorithm. Then, the 2D positions of the UAVs are decided using a modified pattern search algorithm. The two subproblems are solved alternatively in an iterative manner to obtain a near-optimal solution. Compared to baseline algorithms, the proposed solution results in at least 4-fold and 4.5-fold reductions in the number of iterations required for convergence, and the maximum …
Rakshitha De Silva, Yushan Siriwardhana, Tharaka Samarasinghe, Madhusanka Liyanage, Mika Ylianttila
Journal
De Silva, Rakshitha, Yushan Siriwardhana, Tharaka Samarasinghe, Madhusanka Liyanage, and Mika Ylianttila.“Deployment Options of 5G Network Slicing for Smart Healthcare.” IEEE, January 11, 2022. https://doi. org/10.1109/ccnc49033. 2022.9700516. · 2022 · Cited by 9
Mobile and Next-Generation NetworksNetwork Optimization and IntelligencePhysiological Monitoring and Digital Health
Abstract
Network slicing enables the creation of multiple logical independent networks on physical networking infrastructure. Network slice deployment in a Fifth Generation (5G) mobile network can be classified as vertical and horizontal slicing. The paper compares the performance of the two slicing methods through solving two convex optimization problems, considering several smart hospital scenarios that differ from each other based on their medical speciality. The results are used to draw insights on the most appropriate slicing approach for each setup.
