Scott Moeller
University of Southern California
23 Papers
123 Citations
Scott Moeller is an academic researcher from University of Southern California. The author has contributed to research in topics: Backpressure routing & Queueing theory. The author has an hindex of 9, co-authored 20 publications.
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Papers
Routing without routes: the backpressure collection protocol
Scott Moeller,Avinash Sridharan,Bhaskar Krishnamachari,Omprakash Gnawali +3 more
- 12 Apr 2010
TL;DR: This work demonstrates for the first time that replacing the traditional FIFO queue service in backpressure routing with LIFO queues reduces the average end-to-end packet delays for delivered packets drastically and improves backpressure scalability by introducing a new concept of floating queues into the backpressure framework.
Implementing backpressure-based rate control in wireless networks
Avinash Sridharan,Scott Moeller,Bhaskar Krishnamachari +2 more
- 29 May 2009
TL;DR: A comprehensive experimental evaluation of backpressure mechanisms for multihop wireless networks, in particular, the first such study in the context of wireless sensor networks, yields two key insights into the design of such protocols.
38
Patent
System for providing network content to wireless devices
Awele Ndili,Scott Moeller +1 more
- 15 May 2001
TL;DR: In this paper, a method for having a content engine (110) interact with a mobile device (20), the method comprising: having the content engine(110) receive (1) a wireless communication from the mobile device(120) that includes a card representing a URL and an identifier of the mobile devices, having the contents engine ( 110) signal (2) a database management system for an identification for the card to retrieve instructions (3) for assembling the content available on the URL for the mobiledevice, having content engine access (6) a network site located by the URL
34
Making distributed rate control using Lyapunov drifts a reality in wireless sensor networks
Avinash Sridharan,Scott Moeller,Bhaskar Krishnamachari +2 more
- 01 Apr 2008
TL;DR: This work shows that existing theoretical results in the field of stochastic network optimization can be directly applied to a CSMA based wireless sensor network using their novel receiver capacity model and proposes a distributed back pressure algorithm using Lyapunov drift based optimization techniques.
Trust-based backpressure routing in wireless sensor networks
TL;DR: The results show that even when 50% of network nodes are malicious, VAR trust offers approximately 73% throughput and ensures reliable routing, with a small trade-off in the end-to-end packet delay and energy consumptions.