arXiv subjects

Benjamin Finley

Publications and source records attributed to Benjamin Finley.

14 recordsLinked to original sources

arXiv2022

Towards User-Centered Metrics for Trustworthy AI in Immersive Cyberspace

AI plays a key role in current cyberspace and future immersive ecosystems that pinpoint user experiences. Thus, the trustworthiness of such AI systems is vital as failures in these systems can cause serious user harm. Although there are related works on exploring trustworthy AI (TAI) metrics in the current cyberspace, ecosystems towards user-centered services, such as the metaverse, are much more complicated in terms of system performance and user experience assessment, thus posing challenges for the applicability of existing approaches. Thus, we give an overlook on fairness, privacy and robustness, across the historical path from existing approaches. Eventually, we propose a research agenda towards systematic yet user-centered TAI in immersive ecosystems.

cs.CY↗

arXiv2021

AICP: Augmented Informative Cooperative Perception

Connected vehicles, whether equipped with advanced driver-assistance systems or fully autonomous, require human driver supervision and are currently constrained to visual information in their line-of-sight. A cooperative perception system among vehicles increases their situational awareness by extending their perception range. Existing solutions focus on improving perspective transformation and fast information collection. However, such solutions fail to filter out large amounts of less relevant data and thus impose significant network and computation load. Moreover, presenting all this less relevant data can overwhelm the driver and thus actually hinder them. To address such issues, we present Augmented Informative Cooperative Perception (AICP), the first fast-filtering system which optimizes the informativeness of shared data at vehicles to improve the fused presentation. To this end, an informativeness maximization problem is presented for vehicles to select a subset of data to display to their drivers. Specifically, we propose (i) a dedicated system design with custom data structure and lightweight routing protocol for convenient data encapsulation, fast interpretation and transmission, and (ii) a comprehensive problem formulation and efficient fitness-based sorting algorithm to select the most valuable data to display at the application layer. We implement a proof-of-concept prototype of AICP with a bandwidth-hungry, latency-constrained real-life augmented reality application. The prototype adds only 12.6 milliseconds of latency to a current informativeness-unaware system. Next, we test the networking performance of AICP at scale and show that ACIP effectively filters out less relevant packets and decreases the channel busy time.

cs.MM↗

arXiv2021

5G MEC Computation Handoff for Mobile Augmented Reality

The combination of 5G and Multi-access Edge Computing (MEC) can significantly reduce application delay by lowering transmission delay and bringing computational capabilities closer to the end user. Therefore, 5G MEC could enable excellent user experience in applications like Mobile Augmented Reality (MAR), which are computation-intensive, and delay and jitter-sensitive. However, existing 5G handoff algorithms often do not consider the computational load of MEC servers, are too complex for real-time execution, or do not integrate easily with the standard protocol stack. Thus they can impair the performance of 5G MEC. To address this gap, we propose Comp-HO, a handoff algorithm that finds a local solution to the joint problem of optimizing signal strength and computational load. Additionally, Comp-HO can easily be integrated into current LTE and 5G base stations thanks to its simplicity and standard-friendly deployability. Specifically, we evaluate Comp-HO through a custom NS-3 simulator which we calibrate via MAR prototype measurements from a real-world 5G testbed. We simulate both Comp-HO and several classic handoff algorithms. The results show that, even without a global optimum, the proposed algorithm still significantly reduces the number of large delays, caused by congestion at MECs, at the expense of a small increase in transmission delay.

cs.NI↗

arXiv2020

How does enterprise IoT traffic evolve? Real-world evidence from a Finnish operator

The adoption of Internet of Things (IoT) technologies in businesses is increasing and thus enterprise IoT (EIoT) is seemingly shifting from hype to reality. However, the actual use of EIoT over significant timescales has not been empirically analyzed. In other words, the reality remains unexplored. Furthermore, despite the variety of EIoT verticals, the use of IoT across vertical industries has not been compared. This paper uses a two-year EIoT dataset from a major Finnish mobile network operator to investigate device use across industries, cellular traffic patterns, and mobility patterns. We present a variety of novel findings: EIoT traffic volume per device has increased three-fold over the last two years, the share of LTE-enabled devices has remained low at around 2% and that 30% of EIoT devices are still 2G only, and there are order of magnitude differences between different industries' EIoT traffic and mobility. We also show that daily traffic can be clustered into only three patterns, differing mainly in the presence and timing of a peak hour. Beyond these descriptive results, modeling and forecasting is conducted for both traffic and mobility. We forecast the total daily EIoT traffic through a temporal regression model and achieve an error of about 15% over medium-term (30 to 180 day) horizons. We also model device mobility through a Markov mixture model and quantify the upper bound of predictability for device mobility.

cs.NI↗

arXiv2020

Evaluating Transport Protocols on 5G for Mobile Augmented Reality

Mobile Augmented Reality (MAR) mixes physical environments with user-interactive virtual annotations. Immersive MAR experiences are supported by computation-intensive tasks which rely on offloading mechanisms to ease device workloads. However, this introduces additional network traffic which in turn influences the motion-to-photon latency (a determinant of user-perceived quality of experience). Therefore, a proper transport protocol is crucial to minimise transmission latency and ensure sufficient throughput to support MAR performance. Relatedly, 5G, a potential MAR supporting technology, is widely believed to be smarter, faster, and more efficient than its predecessors. However, the suitability and performance of existing transport protocols in MAR in the 5G context has not been explored. Therefore, we present an evaluation of popular transport protocols, including UDP, TCP, MPEG-TS, RTP, and QUIC, with a MAR system on a real-world 5G testbed. We also compare with their 5G performance with LTE and WiFi. Our evaluation results indicate that TCP has the lowest round-trip-time on 5G, with a median of $15.09\pm0.26$ ms, while QUIC appears to perform better on LTE. Through an additional test with varying signal quality (specifically, degrading secondary synchronisation signal reference signal received quality), we discover that protocol performance appears to be significantly impacted by signal quality.

cs.NI↗

arXiv2020

Russian trolls speaking Russian: Regional Twitter operations and MH17

The role of social media in promoting media pluralism was initially viewed as wholly positive. However, some governments are allegedly manipulating social media by hiring online commentators (also known as trolls) to spread propaganda and disinformation. In particular, an alleged system of professional trolls operating both domestically and internationally exists in Russia. In 2018, Twitter released data on accounts identified as Russian trolls, starting a wave of research. However, while foreign-targeted English language operations of these trolls have received significant attention, no research has analyzed their Russian language domestic and regional-targeted activities. We address this gap by characterizing the Russian-language operations of Russian trolls. We first perform a descriptive analysis, and then focus in on the trolls' operation related to the crash of Malaysia Airlines flight MH17. Among other things, we find that Russian-language trolls have run 163 hashtag campaigns (where hashtag use grows abruptly within a month). The main political sentiments of such campaigns were praising Russia and Putin (29%), criticizing Ukraine (26%), and criticizing the United States and Obama (9%). Further, trolls actively reshared information with 76% of tweets being retweets or containing a URL. Additionally, we observe periodic temporal patterns of tweeting suggesting that trolls use automation tools. Further, we find that trolls' information campaign on the MH17 crash was the largest in terms of tweet count. However, around 68% of tweets posted with MH17 hashtags were likely used simply for hashtag amplification. With these tweets excluded, about 49% of the tweets suggested to varying levels that Ukraine was responsible for the crash, and only 13% contained disinformation and propaganda presented as news. Interestingly, trolls promoted inconsistent alternative theories for the crash.

cs.SI↗

arXiv2020

Marketplace for AI Models

Artificial intelligence shows promise for solving many practical societal problems in areas such as healthcare and transportation. However, the current mechanisms for AI model diffusion such as Github code repositories, academic project webpages, and commercial AI marketplaces have some limitations; for example, a lack of monetization methods, model traceability, and model auditabilty. In this work, we sketch guidelines for a new AI diffusion method based on a decentralized online marketplace. We consider the technical, economic, and regulatory aspects of such a marketplace including a discussion of solutions for problems in these areas. Finally, we include a comparative analysis of several current AI marketplaces that are already available or in development. We find that most of these marketplaces are centralized commercial marketplaces with relatively few models.

cs.CY↗

arXiv2020

Distributed Vehicular Computing at the Dawn of 5G: a Survey

Recent advances in information technology have revolutionized the automotive industry, paving the way for next-generation smart vehicular mobility. Vehicles, roadside units, and other road users can collaborate to deliver novel services and applications. These services and applications require 1) massive volumes of heterogeneous and continuous data to perceive the environment, 2) reliable and low-latency communication networks, 3) real-time data processing that provides decision support under application-specific constraints. Addressing such constraints introduces significant challenges for current communication and computing technologies. Relatedly, the fifth generation of cellular networks (5G) was developed to respond to communication challenges by providing for low-latency, high-reliability, and high bandwidth communications. As a major part of 5G, edge computing allows data offloading and computation at the edge of the network, ensuring low-latency and context-awareness, and 5G efficiency. In this work, we aim at providing a comprehensive overview of the state of research on vehicular computing in the emerging age of 5G and big data.

cs.DC↗

arXiv2019

Cellular IoT Traffic Characterization and Evolution

The adoption of Internet of Things (IoT) technologies is increasing and thus IoT is seemingly shifting from hype to reality. However, the actual use of IoT over significant timescales has not been empirically analyzed. In other words the reality remains unexplored. Furthermore, despite the variety of IoT verticals, the use of IoT across vertical industries has not been compared. This paper uses a two-year IoT dataset from a major Finnish mobile network operator to investigate different aspects of cellular IoT traffic including temporal evolution and the use of IoT devices across industries. We present a variety of novel findings. For example, our results show that IoT traffic volume per device increased three-fold over the last two years. Additionally, we illustrate diversity in IoT usage among different industries with orders of magnitude differences in traffic volume and device mobility. Though we also note that the daily traffic patterns of all devices can be clustered into only three patterns, differing mainly in the presence and timing of a peak hour. Finally, we illustrate that the share of LTE-enabled IoT devices has remained low at around 2% and 30% of IoT devices are still 2G only.

cs.NI↗

arXiv2019

In Search of Lost QoS

The area of quality of service (QoS) in communications networks has been the target of research for already several decades with tens of thousands of published journal and conference papers. However, the practical introduction of QoS systems in commercial networks has been limited (with a preference for simple overprovisioning). Despite this dissonance, most influential QoS papers do not discuss this lack of penetration or challenge any of the common assumptions used to argue for QoS systems. So far, the few critical QoS papers have had only a minor effect on QoS research and standardization. Therefore, there is a serious risk that QoS will remain an academic research topic without significant practical relevance. To help elucidate these issues, in this work, we first perform a comprehensive review of QoS including a general overview and an analysis of both influential and critical work from the past 30 years. We examine properties such as citations, keywords, and author traits to show that QoS has passed through several distinct phases with different topics while maintaining the overall attitude towards the role and objective of QoS systems. We then discuss QoS as a social phenomenon and in the context of current networking standards. Finally, we propose a QoS scheme based on incentives that avoids some of the problems identified in critical work, and we provide simple recommendations for network operators. Overall, we hope to spark the community to take a fresh look at QoS.

cs.NI↗

arXiv2018

Does network quality matter? A field study of mobile user satisfaction

Mobile quality of experience and user satisfaction are growing research topics. However, the relationship between a user's satisfaction with network quality and the networks real performance in the field remains unexplored. This paper is the first to study both network and non-network predictors of user satisfaction in the wild. We report findings from a large sample (2224 users over 12 months) combining both questionnaires and network measurements. We found that minimum download goodput and device type predict satisfaction with network availability. Whereas for network speed, only download factors predicted satisfaction. We observe that users integrate over many measurements and exhibit a known peak-end effect in their ratings. These results can inform modeling efforts in quality of experience and user satisfaction.

cs.NI↗

arXiv2018

Multidevice mobile sessions: A first look

The increasing number of users with multiple mobile devices underscores the importance of understanding how users interact, often simultaneously, with these multiple devices. However, most device based monitoring studies have focused only on a single device type. In contrast, we study the multidevice usage of a US-based panel through device based monitoring on panelist's smartphone and tablet devices. We present a broad range of results from characterizing individual multidevice sessions to estimating device usage substitution. For example, we find that for panelists, 50% of all device interaction time can be considered multidevice usage.

cs.HC↗

arXiv2018

Mobile Device Type Substitution

Mobile users today interact with a variety of mobile device types including smartphones, tablets, smartwatches, and others. However research on mobile device type substitution has been limited in several respects including a lack of detailed and robust analyses. Therefore, in this work we study mobile device type substitution through analysis of multidevice usage data from a large US-based user panel. Specifically, we use regression analysis over paired user groups to test five device type substitution hypotheses. We find that both tablets and PCs are partial substitutes for smartphones with tablet and PC ownership decreasing smartphone usage by about 12.5 and 13 hours/month respectively. Additionally, we find that tablets and PCs also prompt about 20 and 57 hours/month respectively of additional (non-substituted) usage. We also illustrate significant inter-user diversity in substituted and additional usage. Overall, our results can help in understanding the relative positioning of different mobile device types and in parameterizing higher level mobile ecosystem models.

cs.HC↗

arXiv2017

Benefits of Mobile End User Network Switching and Multihoming

Mobile users have not been able to exploit spatio-temporal differences between individual mobile networks operators for a variety of reasons. End user network switching and multihoming are two promising mechanisms that could allow such exploitation. However these mechanisms have not been thoroughly explored at a general system level with QoE metrics. Therefore, in this work we analyze these mechanisms in a variety of diverse scenarios through a system level model based on an agent based modeling framework. In terms of results, we find that in all scenarios end user network switching provides significant benefits in terms of both throughput and mean opinion score as the number of available networks increases. However, contrastingly, end user multihoming in most scenarios does not provide significant benefits over network switching given the same number of available networks. The major reason is inefficient radio resource allocation resulting from individual networks not taking the multihoming nature of end users into account. Though, in low user density situations this inefficiency is not a problem and multihoming does provide increased throughput though not increased mean opinion scores. Finally, scenarios that vary the fraction of users adopting multihoming suggests that both early and late adopters will have similar gains over users not adopting multihoming. Thus the adoption dynamics of multihoming appear favorable. Overall, the results support the applicability of end user network switching for improving mobile user experience and the applicability of end user multihoming in more limited situations.

cs.NI↗