Computer Science

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The Computer Science Department at Montana State University supports the Mission of the College of Engineering and the University through its teaching, research, and service activities. The Department educates undergraduate and graduate students in the principles and practices of computer science, preparing them for computing careers and for a lifetime of learning.

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Sex Parity in Cognitive Fatigue Model Development for Effective Human-Robot Collaboration
(IEEE, 2022-10) Kalatzis, Apostolos; Hopko, Sarah; Mehta, Ranjana K.; Stanley, Laura; Wittie, Mike P.
In recent years, robots have become vital to achieving manufacturing competitiveness. Especially in industrial environments, a strong level of interaction is reached when humans and robots form a dynamic system that works together towards achieving a common goal or accomplishing a task. However, the human-robot collaboration can be cognitively demanding, potentially contributing to cognitive fatigue. Therefore, the consideration of cognitive fatigue becomes particularly important to ensure the efficiency and safety in the overall human-robot collaboration. Additionally, sex is an inevitable human factor that needs further investigation for machine learning model development given the perceptual and physiological differences between the sexes in responding to fatigue. As such, this study explored sex differences and labeling strategies in the development of machine learning models for cognitive fatigue detection. Sixteen participants, balanced by sex, recruited to perform a surface finishing task with a UR10 collaborative robot under fatigued and non-fatigued states. Fatigue perception and heart rate activity data collected throughout to create a dataset for cognitive fatigue detection. Equitable machine learning models developed based on perception (survey responses) and condition (fatigue manipulation). The labeling approach had a significant impact on the accuracy and F1-score, where perception-based labels lead to lower accuracy and F1-score for females likely due to sex differences in reporting of fatigue. Additionally, we observed a relationship between heart rate, algorithm type, and labeling approach, where heart rate was the most significant predictor for the two labeling approaches and for all the algorithms utilized. Understanding the implications of label type, algorithm type, and sex on the design of fatigue detection algorithms is essential to designing equitable fatigue-adaptive human-robot collaborations across the sexes.
MIST: Cellular data network measurement for mobile applications
(Conference on Broadband Communications, Networks and Systems (BROADNETS), 2007-09) Wittie, Mike P.; Stone-Gross, Brett; Almeroth, Kevin C.; Belding, Elizabeth M.
The rapid growth in the popularity of cellular networks has led to aggressive deployment and a rapid expansion of mobile services. Services based on the integration of cellular networks into the Internet have only recently become available, but are expected to become very popular. One current limitation to the deployment of many of these services is poor or unknown network performance, particularly in the cellular portion of the network. Our goal in this paper is to motivate and present the Mobile Internet Services Test (MIST) platform, a new distributed architecture to measure and characterize cellular network performance as experienced by mobile devices. We have used MIST to conduct preliminary measurements; evaluate MIST’s effectiveness; and motivate further measurement research.
Exploiting Parallel Networks Using Dynamic Channel Scheduling
(Wireless Internet Conference (WICON), 2008-11) Deek, Lara B.; Almeroth, Kevin C.; Wittie, Mike P.; Harras, Khaled A.
Many researchers have been focusing on the outcomes and consequences of the rapid increase and proliferation of mobile wireless technologies. If it is not already the case, it will soon be rare for a user to be in a situation where absolutely no network connection exists. In fact, through numerous devices, users will soon expect to be connected in all places at all times. Through the great variety and increase in the capabilities of these devices, it is not a surprise to find a single user with many connection opportunities. As a result, we believe that the next major evolution of wireless mobile networks will be in the exploitation of multiple network connections in parallel. Due to network heterogeneity, the major challenge in such situations is to determine the way that these networks can be utilized to better serve different network applications. In this work, we propose a dynamic channel scheduling mechanism that adapts to the state of the available channels to provide more efficient usage of network connectivity. We do so by observing channel throughput, creating a set of channel usage combinations, and then choosing the most efficient combination. We evaluate an implementation of the proposed mechanism using emulation. Our results show that under realistic conditions our dynamic approach greatly improves cost delay metrics, and the overall user-perceived performance compared to a more static approach.
On The Implications of Routing Metric Staleness in Delay Tolerant Networks
(Elsevier, 2009) Wittie, Mike P.; Harras, Khaled A.; Almeroth, Kevin C.; Belding, Elizabeth M.
Delay Tolerant Network (DTN) routing addresses challenges of providing end-to-end service where end-to-end data forwarding paths may not exist. The performance of current DTN routing protocols is often limited by routing metric ‘‘staleness”, i.e., routing information that becomes out-of-date or inaccurate because of long propagation delays. Our previous work, ParaNets, proposed a new opportunistic network architecture in which the data channel is augmented by a thin end-to-end control channel. The control channel is adequate for the exchange of control traffic, but not data. In this paper we present Cloud Routing, a routing solution for the ParaNets architecture. We motivate the need for such a solution, not only because of stale routing metrics, but also because of congestion that can occur in DTNs. Unable to use up-to-date routing metrics to limit congestion, existing DTN routing solutions suffer from low goodput and long data delivery delays. We show how Cloud Routing avoids congestion by smart use of forwarding opportunities based on up-to-date routing metrics. We evaluate our solution using extensive OPNET simulations. Cloud Routing extends network performance past what is currently possible and motivates a new class of globally cognizant DTN routing solutions.
Internet Service in Developing Regions Through Network Coding
(IEEE, 2009) Wittie, Mike P.; Almeroth, Kevin C.; Belding, Elizabeth M.; Rimac, Ivica; Hilt, Volker
The availability of Internet services brings many benefits to developing regions, yet Internet deployment levels in these regions remain staggeringly low. In this work we investigate how existing cellular deployments, which have enjoyed more rapid and wider deployment than client Internet infrastructure, could be used to provide very low cost Internet services in underdeveloped rural areas. We propose a new service model in which traffic is delivered over multihop client-to-client connections that are coordinated by end-to-end control traffic exchanged over cellular infrastructure. To enable this scheme in low client density rural settings, we propose a novel data forwarding mechanism for opportunistic space-time paths. To explore multiple opportunistic paths, but without the high forwarding cost of replicating data on these paths, we use network coding and send only a fraction of the data on each path. Through extensive OPNET simulations we show that globally coordinated opportunistic forwarding enables service acceptable to most applications at only a fraction of cellular infrastructure load. We argue that the reduced load on the cellular infrastructure allows additional users to share services and cost of the network and has the potential to lower the per user price of data services in developing regions.
ParaNets: A parallel network architecture for challenged networks
(IEEE, 2007-03) Harras, Khaled A.; Wittie, Mike P.; Almeroth, Kevin C.; Belding, Elizabeth M.
Networks characterized by challenges, such as intermittent connectivity, network heterogeneity, and large delays, are called “challenged networks”. We propose a novel network architecture for challenged networks dubbed Parallel Networks, or, ParaNets. The vision behind ParaNets is to have challenged network protocols operate over multiple heterogenous networks, simultaneously available, through one or more devices. We present the ParaNets architecture and discuss its short-term challenges and long-term implications. We also argue, based on current research trends and the ParaNets architecture, for the evolution of the conventional protocol stack to a more flexible cross-layered protocol tree. To demonstrate the potential impact of ParaNets, we use Delay Tolerant Mobile Networks (DTMNs) as a representative challenged network over which we evaluate ParaNets. Our ultimate goal in this paper is to open the way for further work in challenged networks using ParaNets as the underlying architecture.
Mobile ad hoc networks (MANET) protocols evaluation framework
(IEEE, 2007-10) Slavin, Vadim A.; Polyakov, Michael; Quilling, Mark; Wittie, Mike P.; Andrews, Matthew
We propose a novel, robust MANET protocols evaluation framework which enables researchers to track performance metrics and evaluate theoretical predictions. This framework speeds up the research and development spirals, provides faster feedback to algorithm developers and closes the loop between theory and qualitative analysis of the protocols' performance. Our test and evaluation effort is divided into two parts. Rapid prototyping and evaluation of proposed algorithms is performed in the MATLAB environment. These tools enable us to numerically analyze performance, capabilities, convergence, and robustness of new algorithms. The second higher fidelity approach is the test and evaluation framework developed in OPNET simulation environment. Its unique features are the novel application and evaluation process including sophisticated statistics collection and an event logging architecture.
AirLab: Distributed Infrastructure for Wireless Measurements
(USENIX, 2010) Kone, Vinod; Zheleva, Mariya; Wittie, Mike P.; Zhang, Zengbin; Zhao, Xiaohan; Zhao, Ben Y.; Belding, Elizabeth M.; Zheng, Haitao; Almeroth, Kevin C.
The importance of experimental research in the field of wireless networks is well understood. So far researchers have either built their own testbeds or accessed third-party controlled testbeds (http://orbit-lab.org) or used publicly available traces (http://crawdad.cs.dartmouth.edu) for evaluation. While immensely useful, all these approaches have their drawbacks. While building own test beds requires cost and effort, third-party controlled test beds do not replicate real network deployments. On the other hand, the publicly available traces are often collected using different software and hardware platforms, making it very difficult to compare results across traces. As a result, observations are often inconsistent across different networks, leading researchers to draw potentially conflicting conclusions across their own studies. To facilitate meaningful analysis of wireless networks and protocols, we need a way to collect measurement traces across a wide variety of network deployments, all using a consistent set of measurement metrics. Widespread multi-faceted data collection will provide multiple viewpoints of the same network, enabling deeper understanding of both self and exterior interference properties, spectrum usage, network usage, and a wide variety of other factors. Furthermore, data collected in this manner across a variety of heterogeneous network types, such as university, corporate, and home environments, will facilitate cross-comparison of observed network phenomena within each of these settings. To address the critical need for comparable and consistent wireless traces, we propose AirLab, a publicly accessible distributed infrastructure for wireless measurements
Exploiting Locality of Interest in Online Social Networks
(ACM CoNEXT, 2010) Wittie, Mike P.; Pejovic, Veljko; Deek, Lara B.; Almeroth, Kevin C.; Zhao, Ben Y.
Online Social Networks (OSN) are fun, popular, and socially significant. An integral part of their success is the immense size of their global user base. To provide a consistent service to all users, Facebook, the world’s largest OSN, is heavily dependent on centralized U.S. data centers, which renders service outside of the U.S. sluggish and wasteful of Internet bandwidth. In this paper, we investigate the detailed causes of these two problems and identify mitigation opportunities. Because details of Facebook’s service remain proprietary, we treat the OSN as a black box and reverse engineer its operation from publicly available traces. We find that contrary to current wisdom, OSN state is amenable to partitioning and that its fine grained distribution and processing can significantly improve performance without loss in service consistency. Through simulations of reconstructed Facebook traffic over measured Internet paths, we show that user requests can be processed 79% faster and use 91% less bandwidth. We conclude that the partitioning of OSN state is an attractive scaling strategy for Facebook and other OSN services.
Network Optimization with Dynamic Demands and Link Prices
(Allerton Conference, 2012) Patterson, Stacy; Wittie, Mike P.; Almeroth, Kevin C.; Bamieh, Bassam
We present Overlapping Cluster Decomposition (OCD), a novel distributed algorithm for network optimization targeted for networks with dynamic demands and link prices. OCD uses a dual decomposition of the global problem into local optimization problems in each node’s neighborhood. The local solutions are then reconciled to find the global optimal solution. While OCD is a descent method and thus may converge slowly in a static network, we show that OCD can more rapidly adapt to changing network conditions than previously proposed first-order and Newton-like network optimization algorithms. Therefore, OCD yields better solutions over time than previously proposed methods at a comparable communication cost.

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