Mohammed Mahyoub

Mohammed Mahyoub, Wael Jaafar, Sami Muhaidat et al.

We address cross-slice co-location risk in multi-slice low Earth orbit (LEO) satellite edge networks, where virtual network functions (VNFs) from different network slices sharing the same satellite instance create a cross-slice security exposure channel. We formulate a risk-aware service function chain (SFC) placement problem as a mixed-integer linear program (MILP) over a dynamically evolving LEO satellite constellation, jointly optimizing cross-slice co-location risk, CPU resource consumption, and VNF migration stability under satellite capacity, inter-satellite link (ISL) capacity, visibility, and end-to-end (E2E) delay constraints. The risk model employs a multiplicative co-location formulation, inspired by the risk assessment principles from ISO/NIST frameworks, with exact and coarse (slice-level)formulations that analytically establish bounds on the co-location exposure. To solve this problem, we propose a three-stage hybrid optimizer combining time epoch preprocessing, simulated annealing-based warm-start, and branch-and-bound refinement. Experimental evaluation demonstrates a 40% reduction in co-location risk and an 80% reduction in avoidable VNF migrations relative to the greedy baseline at negligible CPU overhead, and a 23x warm-start speedup from 256s cold-start to 11s per epoch, confirming real-time viability from the second epoch.

Mohammed Mahyoub

Post-discharge care management coordinates patients' referrals to improve their health after being discharged from hospitals, especially elderly and chronically ill patients. In a care management setting, health referrals are processed by a specialized unit in the managed care organization (MCO), which interacts with many other entities including inpatient hospitals, insurance companies, and post-discharge care providers. In this paper, a machine-learning-guided discrete event simulation framework to improve health referrals processing is proposed. Random-forest-based prediction models are developed to predict the LOS and referral type. Two simulation models are constructed to represent the as-is configuration of the referral processing system and the intelligent system after incorporating the prediction functionality, respectively. By incorporating a prediction module for the referral processing system to plan and prioritize referrals, the overall performance was enhanced in terms of reducing the average referral creation delay time. This research will emphasize the role of post-discharge care management in improving health quality and reducing associated costs. Also, the paper demonstrates how to use integrated systems engineering methods for process improvement of complex healthcare systems.

Mohammed Mahyoub, Wael Jaafar, Sami Muhaidat et al.

Low Earth orbit (LEO) satellite constellations are emerging as a backbone for global 6G connectivity, where independent tenant slices share orbital infrastructure, each requiring an ordered chain of security virtual network functions (VNFs). Because onboard computation and networking are scarce, slices cannot be given dedicated VNFs. They must share instances on the same satellites, enlarging the attack surface and exposing tenants to cross-slice side-channel risk. This exposure shifts continually as visibility, orbital motion, and the inter-satellite topology change in time (epochs), making VNF migration a structural necessity that couples resource efficiency, service continuity, and security isolation into a single problem. We formulate this security- and migration-aware security function chain (SFC) placement as a multi-slice mixed-integer linear programming (MILP) whose core is a co-location risk model, grounded in ISO/NIST principles and supported by analytic bounds, in which we separate avoidable migrations from those forced by orbital motion. Because the joint program scales quadratically with the cross-slice co-location terms, we develop an alternating direction method of multipliers (ADMM)-inspired penalized per-slice best response decomposition that recasts the coupling as a linear per-slice penalty, yielding independent subproblems through sequential (S-ADMM) and parallel, collision-repaired (P-ADMM) schedules. Simulations over a Walker-Delta satellite constellation show that the proposed framework eliminates co-location risk, reduces SFC migrations, and sustains full delay compliance, while remaining feasible within the per-epoch budget for slice counts where the monolithic security-aware MILP is intractable.