Prasun Sinha Assistant Professor 791 Dreese Labs 2015 Neil Avenue Deptartment of Computer Science and Engineering Ohio State University Columbus, OH 43210-1277 phone: 614-292-1531, email: prasun@cse.ohio-state.edu

About me

Education

• PhD, Computer Science, University of Illinois, Urbana-Champaign, May 2001
  Advisor: Prof. Vaduvur Bharghavan, Thesis Title: Network and Transport Layer Protocols for Wireless Networks
• MS, Computer Science, Michigan State University, Aug 1997
  Advisor: Prof. Anil Jain, Thesis Title: Cursive Script Postal Address Recognition
• B. Tech., Computer Sc. and Engg., Indian Institute of Technology, Delhi (India), May 1995
  Advisor: Prof. P.C.P. Bhatt, Thesis Title: Distributed and Object Oriented Geographic Information System
  

Research Themes

• Scalable Sensor Networking How can senor networks be designed to operate in harsh conditions under constrained resources in real deployments? Can we build reliable and energy efficient protocols for large scale sensor networks? Can the networks self-heal in presence of node failures? These are some of the questions that I am currently investigating. In the ExScal project, (funded by DARPA/NEST) a 1000 node sensor network was demonstrated in operation for the purpose of detection, classification and tracking in Avon Park, Florida in December 2004. My role was to design network protocols for a multi-hop mesh network of 200 nodes that formed the backbone of the sensor network. Both these networks were world's largest at that time.
• Efficient Wireless Mesh Networking: How can we transmit data over time-varying channels to obtain high throughput? How can we optimize routing and association in a mesh network while considering multicast traffic? These questions are becoming more important with increasing number of deployments of mesh networks around the world.

Some Recent Publications

• Supporting MAC Layer Anycasting in Sensor Networks
  Anycasting at the MAC layer can provide low delay and low overhead for packet transmissions. In sensor networks, anycasting can also be used to address the problem of sleeping forwarding nodes. We have designed algorithms and protocols to support anycasting in sensor networks.
• On Maximizing the Lifetime of Delay-Sensitive Wireless Sensor Networks with Anycast
  Joohwan Kim, Xiaojun Lin, Ness Shroff, and Prasun Sinha
  Proc. of IEEE INFOCOM, Phoenix, Arizona, Apr 2008
  
  
• CMAC: An Energy Efficient MAC Layer Protocol Using Convergent Packet Forwarding for Wireless Sensor Networks,
  Sha Liu, Kai-Wei Fan and Prasun Sinha,
  Proc. of IEEE SECON, San Diego, CA, Jun 2007 (Best Paper Finalist)
  
  
• Scalable Data Collection in Sensor Networks
  Static structures for routing and aggregation can not optimize for all possible scenarios of events that can occur in a network. Dynamic structures are very expensive to compute and maintain, and hence not suited for dynamic scenarios. The key question is - How can routing structures and data aggregation strategies with provable performance bound be devised?
• Dynamic Forwarding over Tree-on-DAG for Scalable Data Aggregation in Sensor Networks,
  Kai-Wei Fan, Sha Liu, and Prasun Sinha
  IEEE Transactions on Mobile Computing (TMC), To Appear, 2008
  (for an earlier SENSYS 2006 version, click here. For slides click here.
  
  
• Structure-free Data Aggregation in Sensor Networks
  Kai-Wei Fan, Sha Liu, and Prasun Sinha
  IEEE Transactions on Mobile Computing (TMC), Vol. 6, Number 8, pp 929-942, August 2007
  (for an earlier Infocom 2006 version, click here)
  
  
• Multicasting Support in Wireless Networks
  Signal strength based user-to-AP association is commonly used in most WLANs. In case of multicast and broadcast applications how can the association scheme be optimized? We have designed algorithms and protocols for addressing this issue in the context of WLANs and mesh networks.
• Approximation Algorithms for Scheduling Real-Time Multicast Flows in Wireless LANs
  Yigal Bejerano, Dongwook Lee, Prasun Sinha, and Lisa Zhang
  Proc. of IEEE INFOCOM Mini-Conference, Phoenix, Arizona, Apr 2008
  
  
• Optimizing Multicast Performance in Large Scale WLANs
  Ai Chen, Dongwook Lee, Prasun Sinha
  Proc. of IEEE ICDCS, Toronto, Canda, Jun 2007
  
  
• Association Management for Data Dissemination over Wireless Mesh Networks
  Dongwook Lee, Gayathri Chandrasekaran, Mukundan Sridharan and Prasun Sinha
  Elsevier Computer Networks , 2007
  
  
• Network Services for Sensor Network Backbones
For large scale sensor networks one of the design choices is to use a backbone of nodes with higher capability. We have used this design in our DARPA/NEST demonstration in end of 2004. Several interesting questions arise in the context of data forwarding and reliable data dissemination, which are critical services that a backbone must support.
• Sprinkler: A Reliable and Energy Efficient Data Dissemination Service for Extreme Scale Wireless Networks of Embedded Devices
  Vinayak Naik, Anish Arora, Prasun Sinha, and Hongwei Zhang
  IEEE Transactions on Mobile Computing (TMC), Vol. 6, Number 7, pp 777-789, July 2007
  (earlier version in RTSS 2005)
  
  
• Learn on the Fly: Beacon-free Link Estimation and Routing in Sensor Network Backbones
  Hongwei Zhang, Anish Arora and Prasun Sinha
  Proc. of IEEE INFOCOM , Barcelona, Apr 2006
  
  
• Hybrid Ad-hoc and Cellular Networks
Multi-hop networking can improve the capacity of cellular networks by making use of high capacity peer-to-peer links. We have studied the design and performance of such a hybrid architecture. With increasing number of devices that can support both WWAN and WLAN connectivity, such archtitectures are promising for higher throughput and lower delay services to end users.
• The Design and Evaluation of Unified Cellular and Ad-Hoc Networks,
  Haiyun Luo, Xiaoqiao Meng, Ram Ramjee, Prasun Sinha, and Li (Erran) Li
  IEEE Transactions on Mobile Computing (TMC), Vol. 6, Number 9, pp 1060-1074, September 2007
  (earlier version in Mobicom 2003)
  
  

Currently active grants:

• NeTS-NECO: A New Resource Management Paradigm for Sensor Networks with Energy Replacement
  Funding Agency: NSF
  PI: Ness B. Shroff, Co-PI: Can Emre Koksal, and Prasun Sinha
  Recent advances in sensor networks have resulted in a unique capability to remotely sense the environment. These networks can be used to sense natural as well as human-created phenomena (e.g., earthquake, fires, troop movements, radioactive substances). These systems could be deployed in remote or hard-to-reach areas, hence, it is critical that such networks operate unattended for long durations. To that end, new developments in the areas of renewable energy sources suggest that this is feasible. However, the design and control of sensor networks with the added dimension of renewable energy makes the problem of managing these networks challenging and substantially different from their non-replenishment counterparts. The goal of the project is to understand the performance limits of sensor networks with replenishment, to develop simple distributed algorithms and protocols that approach these limits, and validate and fine-tune the results based on experimentation. This ambitious endeavor will be accomplished by a team that brings in expertise that spans physical layer communications, distributed algorithms, control theory, resource allocation, sensor networking, and implementation. Broader Impact: Given that sensor nodes with replenishment are an emerging technology, the techniques developed in this project have the potential to make a significant impact on emerging industry sectors. The PIs will actively share their results by giving academic and industrial seminars and facilitating student internships. Students on this project will learn a wide range of theoretical and experimental methodologies to prepare them for the workforce. The PIs will continue their efforts to recruit and train under-represented students.
• NeTS-NOSS: Collaborative Research: Doing More with Less: Tracking Movements Using a Sparse Sensor Network
  Funding Agency: NSF
  PI: Santosh Kumar, Co-PI: Bela Bolobas; PI (at OSU): Prasun Sinha
  The full coverage model, where every point in the deployment region must be covered by at least one sensor, is pervasive in the wireless sensor network community. For applications that involve tracking movements at large scale such as tracking of thieves and robbers fleeing with stolen objects, tracking of animals in forests, and tracking the spread of forest fire, using the full coverage model makes sensor deployment prohibitively expensive. No sound model currently exists that can be used for systematic deployment of such large scale applications. This project proposes a novel model of coverage called Trap Coverage that can be used for systematic deployment of sparse sensor networks, while ensuring frequent tracking of movements of interest. Most existing theoretical and systems work are not applicable to this new model because of the inherent sparsity of the network implied by the trap coverage model. The overall goal of this project is to establish a strong foundation for all large scale movement tracking applications and address the key systems issues faced in such applications. The project applies rigorous mathematical analysis, experimentation on a large scale sensor network testbed, and real-life deployment of a campus-wide object tracking system called AutoWitness to design, develop, and evaluate the algorithms and protocols developed in this project. In addition to providing hands-on research experience to undergraduate and graduate students in building a real wireless sensor network, the AutoWitness system is expected to help reduce property thefts in a university campus.
• NeTS-NOSS: Collaborative Research: Energy-Efficient Distributed Sensor Network Control: Theory to Implementation
  Funding Agency: NSF
  PI: Ness B. Shroff, Co-PI: Xiaojun Lin, and Prasun Sinha
  Energy-management is essential for wireless sensor networks to prolong network lifetime and to increase the amount of useful information conveyed. There is potential to substantially improve the energy efficiency of sensor networks by exploiting cross-layer interactions among various networking layers and functionalities. However, such a cross-layer solution could also become impractically complex and difficult to implement. To address this challenge, this collaborative NSF-funded project at The Ohio State University and Purdue University aims to develop a suite of high-performance cross-layer mechanisms for sensor networks that are simple, modular, distributed, and provably energy-efficient. The key distinguishing feature of the project is that the mechanisms developed are based on a solid theoretical foundation that rigorously manages both performance and complexity with the goal of practical implementation. The PIs will investigate four major functionalities that are crucial to the efficient operation of energy-constrained wireless sensor networks, including joint medium-access and routing, sleep/wake scheduling, in-network aggregation/computation, and reliable broadcast. The theoretical solutions developed in this project will be implemented and evaluated on two testbeds: the existing Kansei testbed at OSU, and a prototype deployment (SENSE@OSU).
• CAREER: On-the-fly Protocols for Data Dissemination in Wireless Mesh Networks
  Funding Agency: NSF
  PI: Prasun Sinha
  With increasing demand for real-time multimedia services such as TV channel broadcasting, and fast download requirements by applications such as P2P, video-on-demand, and software downloads, the access network design needs to treat point-to-multipoint and multipoint-to-point traffic as first class citizens for efficient operation. The high level objective of this project is to design networking protocols over realistic time-varying channels for supporting data dissemination in wireless mesh-networks. These networks are characterized by wireless backbones as opposed to the dominant wired backbones connecting today's wireless access-points. This research is based on the novel paradigm of on-the-fly computation, where recent data-driven channel measurements are used to exploit time-variance of channels for enhanced performance. This research will enable support for emerging media-rich applications that will result in the wide-scale deployment of mesh-networks to provide ubiquitous multi-media enriched services. It will make tangible impacts to several active research areas including mesh-networks, wireless local area networks, and ad-hoc networks.

Awards and Honors

• Best Paper Finalist, IEEE SECON, Jun 2007
• NSF CAREER Award, 2006
• Nominated for ACM PhD Dissertation Award, Department of Computer Science, University of Illinois at Urbana-Champaign, 2002
• Ray Ozzie Fellowship , Department of Computer Science, University of Illinois at Urbana-Champaign, April 2000 (Established for outstanding graduate students)
• Mavis Memorial Scholarship , College of Engineering, University of Illinois at Urbana-Champaign, April 1999 (Awarded for excellence in research and teaching)
• Project CEDAR (PhD Thesis) was selected among the top 4 projects out of approx. 60 projects nationwide , by DARPA in its Quorum Integration Project, 1999
• Distinguished Academic Achievement Award , Michigan State University, 1997 (Awarded for being selected as the Outstanding Teaching Assistant by the Department of Computer Science)
• Secured All India Rank of 8th in GATE (Entrance Examination for Graduate Studies in Computer Science in India), 1995
• Vivekvir Puraskar (for academic excellence), State of Madhya Pradesh, India, 1992

Professional Activities

• Publicity Chair, Mobiquitous 2006
• Session Chair, ICCCN 2005
• Registration Chair, MobiHoc 2005
• Publicity Co-Chair, ICDCS 2005
• Panels Chair, QShine 2004
• Co-Organizer, Special Session on Actor based Sensor Networks, SANPA 2004
• Submissions Chair, ACM SenSys 2004
• Session Chair, ACM MobiDE 2003
• TPC member: ACM MOBICOM 2004-2005, 2008, IEEE INFOCOM 2004-2008; ACM MOBIHOC 2006-2008; IEEE PERCOM 2005,2007; ACM MobiDE 2003; ACM WMASH 2003; IEEE ICC 2003;
• Reviewer for various conferences/journals including INFOCOM, IWQoS, SIGCOMM, MOBICOM, ICON, Computer Networks Journal, IEEE Personal Communication Magazine, MONET, Transactions on Mobile Computing, Transactions on Sensor Networks, Transaction on Parallel and Distributed Computing

Research Group

• Ren-Shiou Liu (PhD)
  
• Zizhan Zheng (PhD)
  
• Tarali Bora (MS), jointly supervised with Ness Shroff
  

• Dongwook Lee, Postdoc (2004-2007), Samsung, Korea
  
• Kai-Wei Fan, PhD (Sp '08), MS (Au '07), Cisco, San Jose, CA
  
• Sha Liu, PhD (Sp '08), MS (Sp '08), Epic Systems, Madison, WI
  

Miscellaneous links

• How to be an effective teacher
  
• Acceptance Rates for Various Networking Related Conferences