Mobile edge computing (MEC) sinks computing power to the edge of networks and integrate mobile access networks and Internet services in 5G and beyond. With the continuous development of services, it is extremely important of privacy protection in a heterogeneous MEC system for multi- server collaboration. However, most of the existing schemes only consider the privacy of users or services other than privacy of network topology. For the purpose of topology privacy protection, this paper employs blockchain to construct heterogeneous MEC systems and adopts accommodative bloom filter as a carrier for multi-domain collaborative routing consensus without exposing topology privacy. Blockchain is used to implement multiplex mutual trust networking and collaborative routing verification through the membership service and consensus mechanism. Experiments are conducted to evaluate the feasibility and performances of our scheme. The results indicate that the proposed scheme can highly improve the credibility and efficiency of MEC collaboration.

Quantum key distribution (QKD) networking over wavelength division multiplexing (WDM) network infrastructure provides a new paradigm for secure communications across the networks. With limited wavelength resources in existing WDM networks, how to efficiently schedule QKD to provision sufficient secret keys over WDM networks becomes a new challenge. This study proposes a new time-scheduled scheme in combination with quantum key pool (QKP) technique to overcome this challenge. A new architecture of QKD-over-WDM networks is presented, in which QKPs are constructed to decouple secret-key resources from the underlying infrastructure for timely secret-key provisioning. In the time-scheduled scheme, routing, wavelength and time-slot allocation (RWTA) problem is proposed for efficient QKP construction (QKPC) over WDM networks, in which three sub-problems (i.e., secret-key consumption, time-slot allocation, and time-slot continuity) are discussed respectively. An integer linear programming (ILP) model and a novel joint path-and-link -based RWTA (JPL-RWTA) heuristic algorithm are designed to solve the RWTA problem, in which the three sub-problems are addressed together. Simulation results indicate that the ILP model and JPL-RWTA algorithm are effective approaches to obtain the positive balance between resource utilization of QKPC (RUQKPC) and successful probability of QKPC (SPQKPC). Moreover, the SPQKPC can be increased at the cost of reducing the flexibility of secret-key consumption, the uniformity of time-slot allocation, and the proportion of time-slot continuous QKPC (TC-QKPC) to time-slot discrete QKPC (TD-QKPC) requests.

The development of reusable rockets makes it possible to launch a massive number of low earth orbit satellites for Internet access. These satellites are expected to be connected by inter-satellite links (ISLs) to provide global Internet service to end-users on the surface of the earth. From the infrastructure’s perspective, the ISLs can be implemented with lasers, forming the optical satellite networks. The design of terrestrial optical networks is usually traffic-driven, meaning more links/bandwidth are deployed to the traffic-intensive areas. But, the orbiting nature of satellites determines that laser ISLs are also moving at high velocities, making the presence of corresponding bandwidth loosed coupled with a specific area. As a result, the traffic-driven network design methodology will be inapplicable to the optical satellite networks. In this work, we model the optical satellite networks and define the laser ISL planning problem, Accordingly, we propose an ISL removal algorithm to remove parts of the ISLs from the grid-mesh topology to improve the average bandwidth utilization ratio (i.e., bandwidth efficiency) while maintaining networks’ reliability and availability. We conduct a simulation study based on the Starlink constellation to evaluate the grid-mesh topology and to investigate the proposed algorithm’s impact on the network performance. Results show that the bandwidth resource in the grid-mesh topology can hardly be used efficiently and removing certain ISLs properly can improve the bandwidth efficiency of optical satellite networks significantly. We also gain another interesting insight that maintaining too many ISLs will not improve, but degrade the network availability.

This scoping review examined racial and ethnic bias in artificial intelligence health algorithms (AIHA), the role of stakeholders in oversight, and the consequences of AIHA for health equity. Using the PRISMA-ScR guidelines, databases were searched between 2020 and 2024 using the terms racial and ethnic bias in health algorithms resulting in a final sample of 23 sources. Suggestions for how to mitigate algorithmic bias were compiled and evaluated, roles played by stakeholders were identified, and governance and stewardship plans for AIHA were examined. While AIHA represent a significant breakthrough in predictive analytics and treatment optimization, regularly outperforming humans in diagnostic precision and accuracy, they also present serious challenges to patient privacy, data security, institutional transparency, and health equity. Evidence from extant sources including those in this review showed that AIHA carry the potential to perpetuate health inequities. While the current study considered AIHA in the US, the use of AIHA carries implications for global health equity.

Edge computing provides computing capability at close-user proximity to reduce service latency for end users. To improve the efficiency of edge computing infrastructures, geographically-distributed edge datacenters can co-work with each other and with cloud datacenters, forming a new paradigm referred to as cooperative edge-cloud computing. In this context, applications typically run on a virtual machine (VM) that can be replicated at multiple sites, and thus user traffic can be served at all the sites where corresponding VMs reside. For the performance of many applications, latency is a critical parameter. In this work, taking applications latencies as the primary constraint, we model the problem of VM placement and workload assignment as a mixed integer linear program and develop heuristic algorithms accordingly. The goal is to minimize the consumption of information technology (IT) infrastructures for placing VMs in cooperative edge-cloud computing, while meeting the heterogeneous latency demands of different applications. Some preliminary results indicate that edge datacenters resource efficiency can be optimized by proper cross-site VM placement and workload re-direction.