EDBT 2026 Demo / reviewers in the wild / expert
Mark D. Yarvis
dblp:00/1863
· DBLP profile ↗
12ranked-venue papers
2as first author
0since 2021 · last 2013
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 10 · 2 first-authorSystems, architecture and hardware · 2
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer networks
6 papers |
Internet of things and sensor networks · 44% Wireless networking · 28% Internet architecture and protocols · 15% | |
| Computer architecture, parallel and distributed computing, and storage systems
3 papers |
Embedded and real-time systems · 57% Parallel and multicore computing · 43% |
Topics — the 18 heaviest of 18, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Internet architecture and protocols
quality of service |
0.2 | 2 | 2008 | BodyQoS: Adaptive and Radio-Agnostic QoS for Body Sensor Networks · INFOCOM 2008 Aggregator-centric QoS for body sensor networks · IPSN 2007 |
Internet of things and sensor networks
wireless body area network |
0.2 | 2 | 2008 | BodyQoS: Adaptive and Radio-Agnostic QoS for Body Sensor Networks · INFOCOM 2008 Aggregator-centric QoS for body sensor networks · IPSN 2007 |
Wireless networking
medium access control |
0.1 | 2 | 2008 | BodyQoS: Adaptive and Radio-Agnostic QoS for Body Sensor Networks · INFOCOM 2008 Exploiting heterogeneity in sensor networks · INFOCOM 2005 |
Wireless networking › WLAN
wireless home networks |
0.1 | 1 | 2006 | Experimental Characterization of Home Wireless Networks and Design Implications · INFOCOM 2006 |
Network measurement and analytics
wireless network measurement |
0.1 | 1 | 2006 | Experimental Characterization of Home Wireless Networks and Design Implications · INFOCOM 2006 |
Wireless networking
WLAN |
0.1 | 1 | 2006 | Experimental Characterization of Home Wireless Networks and Design Implications · INFOCOM 2006 |
Internet of things and sensor networks › wireless sensor network
heterogeneous sensor networks |
0.1 | 1 | 2005 | Exploiting heterogeneity in sensor networks · INFOCOM 2005 |
Internet of things and sensor networks › industrial iot
industrial sensor networks |
0.1 | 1 | 2005 | Design and deployment of industrial sensor networks: experiences from a semiconductor plant and the north sea · SenSys 2005 |
Software-defined and programmable networks
resource-aware deployment |
0.1 | 1 | 2005 | Exploiting heterogeneity in sensor networks · INFOCOM 2005 |
Internet of things and sensor networks › wireless sensor network
sensor deployment |
0.1 | 1 | 2005 | Design and deployment of industrial sensor networks: experiences from a semiconductor plant and the north sea · SenSys 2005 |
Internet of things and sensor networks
wireless sensor network |
0.1 | 1 | 2005 | Exploiting heterogeneity in sensor networks · INFOCOM 2005 |
Internet of things and sensor networks › wireless sensor network
wireless sensor network platform |
0.1 | 1 | 2005 | Intel mote 2: an advanced platform for demanding sensor network applications · SenSys 2005 |
Parallel and multicore computing › parallel scheduling
adaptive scheduling |
0.0 | 1 | 2008 | BodyQoS: Adaptive and Radio-Agnostic QoS for Body Sensor Networks · INFOCOM 2008 |
Internet of things and sensor networks › wireless sensor network
data aggregation |
0.0 | 1 | 2007 | Aggregator-centric QoS for body sensor networks · IPSN 2007 |
Wireless networking
wireless mesh network |
0.0 | 1 | 2006 | Experimental Characterization of Home Wireless Networks and Design Implications · INFOCOM 2006 |
Routing and switching
routing protocol |
0.0 | 1 | 2005 | Exploiting heterogeneity in sensor networks · INFOCOM 2005 |
Embedded and real-time systems
cyber-physical system platforms |
0.0 | 1 | 2005 | Design and deployment of industrial sensor networks: experiences from a semiconductor plant and the north sea · SenSys 2005 |
Embedded and real-time systems › cyber-physical system platforms › industrial automation
industrial monitoring |
0.0 | 1 | 2005 | Design and deployment of industrial sensor networks: experiences from a semiconductor plant and the north sea · SenSys 2005 |
Methods — techniques the papers use, named apart from their topics
virtual MAC · 0.2adaptive scheduling · 0.2vibration signature sensing · 0.1state preservation · 0.1oversampling · 0.1testbed deployment · 0.1link quality measurement · 0.1testbed measurement · 0.1simulation · 0.1analysis · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | Experiences with context management in emergency medicineabstractIn emergency medicine, patient care is intense and stressful, often requiring paramedics to consult with remote physicians to convey the patient's condition. We present a framework for context-management in telemedicine developed in collaboration between engineers, physicians, and paramedics. We describe a mobile platform and embedded wireless sensors to capture physiological and audio context into a comprehensive patient record, accessible locally and remotely. We describe a first evaluation of this technology by trained paramedics in simulated scenarios and evaluate key aspects of system performance. Early results suggest that wireless sensing can provide reliable and low latency data both locally and to remote physicians. In addition, audio context capture is a promising approach to capturing a comprehensive patient record, with a low rate of medically important errors. Rita H. Wouhaybi, Mark D. Yarvis, Sangita Sharma, Philip Muse, Chieh-Yih Wan, Sai Prasad, Lenitra Durham, Ritu Sahni, Robert Norton, Merlin Curry, Holly Brügge Jimison, Richard Harper 0002, Robert A. Lowe |
ACM Trans. Embed. Comput. Syst. | 2 |
| 2011 | Adaptive and Radio-Agnostic QoS for Body Sensor NetworksabstractAs wireless devices and sensors are increasingly deployed on people, researchers have begun to focus on wireless body-area networks. Applications of wireless body sensor networks include healthcare, entertainment, and personal assistance, in which sensors collect physiological and activity data from people and their environments. In these body sensor networks, quality of service is needed to provide reliable data communication over prioritized data streams. This article proposes BodyQoS, the first running QoS system demonstrated on an emulated body sensor network. BodyQoS adopts an asymmetric architecture, in which most processing is done on a resource-rich aggregator, minimizing the load on resource-limited sensor nodes. A virtual MAC is developed in BodyQoS to make it radio-agnostic, allowing a BodyQoS to schedule wireless resources without knowing the implementation details of the underlying MAC protocols. Another unique property of BodyQoS is its ability to provide adaptive resource scheduling. When the effective bandwidth of the channel degrades due to RF interference or body fading effect, BodyQoS adaptively schedules remaining bandwidth to meet QoS requirements. We have implemented BodyQoS in NesC on top of TinyOS, and evaluated its performance on MicaZ devices. Our system performance study shows that BodyQoS delivers significantly improved performance over conventional solutions in combating channel impairment. Gang Zhou 0002, Qiang Li 0025, Jingyuan Li 0006, Yafeng Wu, Shan Lin 0001, Chieh-Yih Wan, Mark D. Yarvis, John A. Stankovic |
ACM Trans. Embed. Comput. Syst. | 8 |
| 2008 | BodyQoS: Adaptive and Radio-Agnostic QoS for Body Sensor NetworksabstractAs wireless devices and sensors are increasingly deployed on people, researchers have begun to focus on wireless body-area networks. Applications of wireless body sensor networks include healthcare, entertainment, and personal assistance, in which sensors collect physiological and activity data from people and their environments. In these body sensor networks, quality of service is needed to provide reliable data communication over prioritized data streams. This paper proposes BodyQoS, the first running QoS system demonstrated on an emulated body sensor network. BodyQoS adopts an asymmetric architecture, in which most processing is done on a resource rich aggregator, minimizing the load on resource limited sensor nodes. A virtual MAC is developed in BodyQoS to make it radio-agnostic, allowing a BodyQoS to schedule wireless resources without knowing the implementation details of the underlying MAC protocols. Another unique property of BodyQoS is its ability to provide adaptive resource scheduling. When the effective bandwidth of the channel degrades due to RF interference or body fading effect, BodyQoS adaptively schedules remaining bandwidth to meet QoS requirements. We have implemented BodyQoS in NesC on top of TinyOS, and evaluated its performance on MicaZ devices. Our system performance study shows that BodyQoS delivers significantly improved performance over conventional solutions in combating channel impairment. Gang Zhou 0002, Chieh-Yih Wan, Mark D. Yarvis, John A. Stankovic |
INFOCOM | 4 |
| 2008 | Exploiting Heterogeneity for Sensor Network SecurityabstractMany sensor network deployments are heterogeneous: a large number of regular nodes perform sensing, while some nodes have better energy resources and/or more computational capacity. Whereas the effect of heterogeneous nodes on network reliability and lifetime has been studied [3], we here focus on exploiting heterogeneity for security. For security and privacy, the identity of nodes must be authenticated and keys have to be distributed. In our lightweight end-middle-end security framework, every node has a public/private key pair, but only resource-rich gateway nodes use public key cryptography to compute digital signatures. Since gateway nodes vouch for regular nodes, regular nodes can use symmetric cryptography until a gateway is reached. On regular nodes, this reduces energy consumption and processing delays by more than a factor of 3000. Re-encryption on the gateways is typically not the bottleneck, since gateways are often line-powered and typically more than 100 times faster than regular nodes (e.g. Stargate vs. Mica). An additional advantage of our end-middle-end architecture is that only gateways are affected by changes in user privileges. Jens Mache, Chieh-Yih Wan, Mark D. Yarvis |
SECON | 3 |
| 2008 | Ad hoc networks: Special issue on energy efficient design in wireless ad hoc and sensor networks
Mark D. Yarvis, Michele Zorzi |
Ad Hoc Networks | 1 |
| 2007 | Aggregator-centric QoS for body sensor networksabstractNo abstract available. Gang Zhou 0002, Chieh-Yih Wan, Mark D. Yarvis, John A. Stankovic |
IPSN | 3 |
| 2007 | Guaranteed on-demand discovery of node-disjoint paths in ad hoc networks
Changwen Liu, Mark D. Yarvis, W. Steven Conner, Xingang Guo |
Comput. Commun. | 2 |
| 2006 | Experimental Characterization of Home Wireless Networks and Design ImplicationsabstractAbstract — Anecdotal evidence suggests that home wireless networks may be unpredictable despite their limited size. In this work, we deploy six-node wireless testbeds in three houses in the United States and the United Kingdom. We examine the quality of links in home wireless networks and the effect of (i) transmission rate, (ii) transmission power, (iii) node location, (iv) type of house, and (v) 802.11 technology. We provide empirical evidence suggesting that homes are challenging environments for wireless communication. Wireless links in the home are highly asymmetric and heavily influenced by precise node location, transmission power, and encoding rate, rather than physical distance between nodes. In our measurements, many links were unable to utilize the maximum transmission rate of the deployed 802.11 technology, and a few provided no connectivity at all. These results suggest that creating an AP-based topology with maximum coverage and throughput in this environment is challenging. Our findings have implications on the design of future home wireless networks and requirements for future wifi-enabled consumer electronic devices. We show that coverage and performance can be improved using a multi-hop topology, implying that mesh capabilities may actually be needed in consumer electronics for seamless connectivity across the home. I. Konstantina Papagiannaki, Mark D. Yarvis, W. Steven Conner |
INFOCOM | 2 |
| 2005 | Exploiting heterogeneity in sensor networksabstractThe presence of heterogeneous nodes (i.e., nodes with an enhanced energy capacity or communication capability) in a sensor network is known to increase network reliability and lifetime. However, questions of where how many, and what types of heterogeneous resources to deploy remain largely unexplored. We focus on energy and link heterogeneity in ad hoc sensor networks and consider resource-aware MAC and routing protocols to utilize those resources. Using analysis, simulation, and real testbed measurements, we evaluate the impact of number and placement of heterogeneous resources on performance in networks of different sizes and densities. While we prove that optimal deployment is very hard in general, we also show that only a modest number of reliable, long-range backhaul links and line-powered nodes are required to have a significant impact. Properly deployed, heterogeneity can triple the average delivery rate and provide a 5-fold increase in the lifetime (respectively) of a large batten-powered network of simple sensors. Mark D. Yarvis, Nandakishore Kushalnagar, Harkirat Singh, Anand Rangarajan 0002, York Liu, Suresh Singh 0001 |
INFOCOM | 1 |
| 2005 | Intel mote 2: an advanced platform for demanding sensor network applicationsabstractNo abstract available. Robert Adler, Mick Flanigan, Jonathan Huang, Ralph Kling, Nandakishore Kushalnagar, Lama Nachman, Chieh-Yih Wan, Mark D. Yarvis |
SenSys | 8 |
| 2005 | Design and deployment of industrial sensor networks: experiences from a semiconductor plant and the north seaabstractSensing technology is a cornerstone for many industrial applications. Manufacturing plants and engineering facilities, such as shipboard engine rooms, require sensors to ensure product quality and efficient and safe operation. We focus on one representative application, preventative equipment maintenance, in which vibration signatures are gathered to predict equipment failure. Based on application requirements and site surveys, we develop a general architecture for this class of industrial applications. This architecture meets the application's data fidelity needs through careful state preservation and over-sampling. We describe the impact of implementing the architecture on two sensing platforms with differing processor and communication capabilities. We present a systematic performance comparison between these platforms in the context of the application. We also describe our experience and lessons learned in two settings: in a semiconductor fabrication plant and onboard an oil tanker in the North Sea. Finally, we establish design guidelines for an ideal platform and architecture for industrial applications. This paper includes several unique contributions: a study of the impact of platform on architecture, a comparison of two deployments in the same application class, and a demonstration of application return on investment. Lakshman Krishnamurthy, Robert Adler, Philip Buonadonna, Jasmeet Chhabra, Mick Flanigan, Nandakishore Kushalnagar, Lama Nachman, Mark D. Yarvis |
SenSys | 8 |
| 2005 | Experimental Evaluation of Topology Control and Synchronization for In-Building Sensor Network Applications
W. Steven Conner, Jasmeet Chhabra, Mark D. Yarvis, Lakshman Krishnamurthy |
Mob. Networks Appl. | 3 |