In this study, we conducted semi-structured interviews with 21 IIR researchers to investigate their data reuse practices. This study aims to expand upon current findings by exploring IIR researchers’ information obtaining behaviors regarding data reuse. We identified the information about shared data characteristics that IIR researchers needed when evaluating data reusability, as well as the sources they typically consulted to obtain this information. We consider this work to be an initial step towards revealing IIR researchers’ data reuse practices and find out what the community need to do to promote data reuse. We hope that this study, as well as future research, will inspire more individuals to contribute to the ongoing efforts aimed at designing the standards, infrastructures, and policies, as well as fostering a sustainable culture for data sharing and reuse in this field.

Abstract Reusing research data can effectively reduce efforts in data collection and enhance the replicability of evaluation experiments, especially for small laboratories and research teams studying human‐centered systems. Building a sustainable data reuse process and culture relies on frameworks that encompass policies, standards, roles, and responsibilities, all of which must address the diverse needs of data providers, curators, and reusers. This study investigated data reuse practices of experienced researchers in Interactive Information Retrieval (IIR), a field where data reuse has been strongly advocated but still remains a challenge. We conducted 21 semi‐structured in‐depth interviews with IIR researchers from varying demographic backgrounds, institutions, and career stages about their motivations, experiences, and concerns regarding data reuse. We uncovered the rationales, criteria, and strategies they used in reusability assessments, as well as the challenges they faced when attempting to reuse research data in their studies. These empirical findings enrich ongoing discussions about the reusability of user‐generated data and research resources and help promote community‐level data reuse culture and standards in both traditional and emerging IIR research fields.

3D reconstruction methods such as Neural Radiance Fields (NeRFs) are capable of optimizing high-quality 3D representation from images. However, NeRF is limited by the requirement for a large number of multi-view images, making its application to real-world scenarios challenging. In this work, we propose a method that can reconstruct real-world scenes from a few input images and a simple text prompt. Specifically, we fine-tune a pretrained diffusion model to constrain its powerful priors to the visual inputs and generate 3D-aware images, leveraging the coarse renderings obtained from input images as the image condition, along with the text prompt as the text condition. Our fine-tuning method saves a significant amount of training time and GPU memory usage while also generating credible results. Moreover, to enable our method to have self-evaluation capabilities, we design a semantic switch to filter out generated images that do not match real scenes, ensuring that only informative priors from the fine-tuned diffusion model are distilled into the 3D model. The semantic switch we designed can be used as a plug-in and improve performance by 13%. We perform our approach on a real-world dataset and demonstrate competitive results compared to existing sparse-view 3D reconstruction methods. Please see our project page for more visualizations and code: https://bityia.github.io/FDfusion.

Satellite networking has been a very active research area in both academia and industry recently. Starlink provides high-speed, low-latency Internet access. More companies have claimed to provide similar services soon. It is expected that different industries will embrace satellite network business in the future. This paper reviews the achievements in satellite-related works in standard organizations (IETF and 3GPP) from the networking perspective (Layer 2/3 and above). The issues and challenges in different areas are analyzed, such as IP networking for massive satellite constellations, wireless network architecture for Non-Terrestrial Network (NTN) integration, etc. Based on the latest developments, the paper envisions the evolution direction and outlines the study items for satellite networks in 6G.

This document proposes a method of addressing and routing for massive Low Earth Orbit (LEO) satellite constellations. It is based on the concepts and technologies of New IP. LEO satellite networks can be used for Internet access and for the Non-Terrestrial Network (NTN) integration with 5G and beyond. Our new addressing method leverages the characteristics of satellites with known orbit elements; and simplifies the satellite identification by using limited indexes. The new routing method combines semantic addressing with source routing and generates a new semantic routing scheme. Compared with traditional methods, the new proposal dramatically reduces the workload in satellite, such as table size, TCAM (Ternary Content-addressable Memory) lookups, and packet header size. Thus, it is more suitable to network in space where the harsh environment will restrict the hardware performance, power consumption, link bandwidth and system complexity.

Differentiated services (DiffServ) are a set of technologies used to enable the provisioning of class-based, differentiated quality of services. One of the essential building blocks to realize DiffServ is the use of traffic conditioning mechanisms to support the required forwarding behaviors. In this paper, a generic model for traffic conditioning is proposed. The generic traffic conditioner (GTC) can be used to provide the traffic control functionalities required in support of various defined per-hop forwarding behaviors. To demonstrate this capability, a configuration of GTC for an expedited forwarding (EF) service that guarantees low packet loss, delay and jitter bounds is presented. Per-hop delay due to traffic conditioning is briefly analyzed. The GTC is currently implemented in a Linux platform Experimental results show that the GTC can achieve minimal packet loss with bounded jitter and delay.

Multicast applications can involve a large number of receivers with heterogeneous data reception capabilities. In a traditional single-rate multicast session, the transmission rate at the source is chosen to match the lowest capacity path to a receiver in the session. This can cause an under-utilization of higher capacity paths to other receivers. We have previously defined an inter-receiver fairness measure in order to quantify the effect of this underutilization. We also developed protocols that use this measure to guide the choice of the source rate for a single-rate session. In this paper we design and develop a multi-rate protocol in the context of an ATM ABR service to achieve better inter-receiver fairness for a multicast session. The multi-rate protocol we investigate is based on the use of destination set grouping (DSG) where the set of receivers in a multicast session is partitioned into disjoint subgroups. The transmitter carries a separate conversation with each subgroup. Based on a number of grouping heuristics, the DSG protocol attempts to find the partitioning of the receivers that maximizes the inter-receiver fairness of the session. The DSG protocol can result in a session receiving a higher bandwidth allocation when it is split into multiple connections. We address this issue by proposing a mechanism in which the connections split from a single multicast session are treated as a single aggregated-allocation connection (AAC). A set of examples demonstrate the effectiveness of the DSG scheme incorporating the AAC technique on improving inter-receiver fairness for multicast ABR sessions.

In a multicast ABR service, a connection is typically restricted to the rate allowed on the bottleneck link in the distribution tree from the source to the set of receivers. Because of this, receivers in the connection can experience inter-receiver unfairness, when the preferred operating rates of the receivers are different. In this paper we explore the issue of improving the inter-receiver fairness in a multicast ABR connection by allowing the connection to operate at a rate higher than what is allowed by the multicast tree's bottleneck link. Since this can result in cell loss to some receivers, we operate with the knowledge of each receiver's application-specific loss tolerance. The multicast connection rate is not allowed to increase beyond the point where the cell loss on a path to a receiver exceeds this receiver's loss tolerance. Based on these ideas we develop an inter-receiver fairness measure and a technique for determining the rate that maximizes this measure. We show possible switch algorithms that can be used to convey the parameters needed to compute the function to the connection's source. In addition we develop a global network measure that helps us assess the effect of increasing inter-receiver fairness on the total network delivered throughput. We also briefly explore improving inter-receiver fairness through the use of multiple virtual circuits to carry traffic for a single multicast session. A set of examples demonstrate the use of the inter-receiver fairness concept in various network scenarios.