Author
Samir R. Das
Other affiliations: University of Texas at San Antonio, University of Cincinnati, Georgia Institute of Technology ...read more
Bio: Samir R. Das is an academic researcher from Stony Brook University. The author has contributed to research in topics: Wireless network & Physics. The author has an hindex of 58, co-authored 186 publications receiving 29007 citations. Previous affiliations of Samir R. Das include University of Texas at San Antonio & University of Cincinnati.
Papers published on a yearly basis
Papers
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21 Nov 2013TL;DR: The vision of an all-wireless inter-rack datacenter fabric that can offer operator the ability to dynamically reconfigure the network topology to adapt to future traffic demands while eliminating concerns related to cabling complexity is explored.
Abstract: We explore the vision of an all-wireless inter-rack datacenter fabric. Such a fabric, if realized, can offer operator the ability to dynamically reconfigure the network topology to adapt to future traffic demands while eliminating concerns related to cabling complexity. A key enabler for our vision is the use of free space optical (FSO) technology which, in contrast to traditional wireless/RF technologies, has lower interference footprint, can support longer range, and offers higher bandwidths. While FSO is an enabler, there are several significant practical challenges that need to be addressed before this vision turns into reality. We demonstrate the early promise of addressing these challenges and the potential benefits that this offers in comparison to state-of-the-art datacenter architectures.
30 citations
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01 Apr 2015TL;DR: This work addresses the problem of network-side localization where cellular operators are interested in localizing cellular devices by means of signal strength measurements alone by using semi-supervised and unsupervised machine learning techniques.
Abstract: We address the problem of network-side localization where cellular operators are interested in localizing cellular devices by means of signal strength measurements alone. While fingerprinting-based approaches have been used recently to address this problem, they require significant amount of geo-tagged (‘labeled’) measurement data that is expensive for the operator to collect. Our goal is to use semi-supervised and unsupervised machine learning techniques to reduce or eliminate this effort without compromising the accuracy of localization. Our experimental results in a university campus (6 sq. km) demonstrate that sub-100m median localization accuracy is achievable with very little or no labeled data so long as enough training is possible with ‘unlabeled’ measurements. This provides an opportunity for the operator to improve the model with time. We present extensive analysis of the error characteristics to gain insight and improve performance, including understanding spatial properties and developing confidence measures.
28 citations
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21 Jun 2010TL;DR: This work model the 802.11 MAC as a Hidden Markov Model (HMM), and uses a machine learning approach to learn the state transition probabilities in this model using the observed trace, and coupled with an estimation of collision probabilities helps to deduce the interference relationships.
Abstract: Wireless interference is the major cause of degradation of capacity in 802.11 wireless networks. We present an approach to estimate the interference between nodes and links in a live wireless network by passive monitoring of wireless traffic. This does not require any controlled experiments, injection of probe traffic in the network, or even access to the network nodes. Our approach requires deploying multiple sniffers across the network to capture wireless traffic traces. These traces are then analyzed to infer the interference relations between nodes and links. We model the 802.11 MAC as a Hidden Markov Model (HMM), and use a machine learning approach to learn the state transition probabilities in this model using the observed trace. This coupled with an estimation of collision probabilities helps us to deduce the interference relationships. We show the effectiveness of this method against simpler heuristics, and also a profiling-based method that requires active measurements. Experimental results demonstrate that the proposed approach is significantly more accurate than heuristics and quite competitive with active measurements. We also validate the approach in a real WLAN environment.
28 citations
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01 Jul 1993
TL;DR: An improved version of the skew heap that allows dequeueing of arbitrary elements at low cost and the possibility of de queues will improve memory utilization is presented, which is also important in applications where frequent rescheduling may occur.
Abstract: The implementation of the pending event set (PES) is crucial to the execution speed of discrete event simulation programs. This paper studies the implementation of the PES in the context of simulations executing on parallel computers using the Time Warp mechanism. We present a scheme for implementing Time Warsp's PES based on well-known data structures for priority queues. This scheme supports efficient management of future and past events, especially for rollback and fossil collection operations. A comparative study of several queue implementations is presented. Experiments with a Time Warp system executing on a Kendall Square Research multiprocessor (KSR1) demonstrate that the implementation of the input queue can have a dramatic impact on performance, as large as an order of magnitude, that is much greater than what can be accounted for by simply the reduced execution time to access the data structure. In particular, it is demonstrated that an efficient input queue implementation can also significantly reduce the number of rollbacks, and the efficiency of memory management policies such as Jefferson's cancelback protocol. In the context of this work we also present an improved version of the skew heap that allows dequeueing of arbitrary elements at low cost. In particular, the possibility of dequeueing arbitrary elements will improve memory utilization. This ability is also important in applications where frequent rescheduling may occur, as in ready queues used to select the next logical process to execute.
28 citations
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19 Apr 2009TL;DR: This work uses commodity WiFi hardware for a comprehensive study of interference modeling for transmission scheduling on a mesh network setup, and proposes use of the "graded" version of the model where feasibility of a link is probabilistic, as opposed to using the more traditional "thresholded" version, where feasibility is binary.
Abstract: The demand for capacity in WiFi networks is driving a new look at transmission scheduling-based link layers. One basic issue here is the use of accurate interference models to drive transmission scheduling algorithms. However, experimental work in this space has been limited. In this work, we use commodity WiFi hardware (specifically, 802.11a) for a comprehensive study of interference modeling for transmission scheduling on a mesh network setup. We focus on the well-known physical interference model for its realism. We propose use of the "graded" version of the model where feasibility of a link is probabilistic, as opposed to using the more traditional "thresholded" version, where feasibility is binary. We show experimentally that the graded model is significantly more accurate (80 percentile error 0.2 vs. 0.55 for thresholded model). We develop transmission scheduling experiments using greedy scheduling algorithms for the evacuation model for both interference models. We also develop similar experiments for optimal scheduling performance for the simplified one-shot scheduling. The scheduling experiments demonstrate clearly superior performance for the graded model, often by a factor of 2. We conclude by promoting use of this model for scheduling studies.
27 citations
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TL;DR: This work develops and analyzes low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality.
Abstract: Networking together hundreds or thousands of cheap microsensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. These networks require robust wireless communication protocols that are energy efficient and provide low latency. We develop and analyze low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality. LEACH includes a new, distributed cluster formation technique that enables self-organization of large numbers of nodes, algorithms for adapting clusters and rotating cluster head positions to evenly distribute the energy load among all the nodes, and techniques to enable distributed signal processing to save communication resources. Our results show that LEACH can improve system lifetime by an order of magnitude compared with general-purpose multihop approaches.
10,296 citations
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01 Aug 2000TL;DR: This paper explores and evaluates the use of directed diffusion for a simple remote-surveillance sensor network and its implications for sensing, communication and computation.
Abstract: Advances in processor, memory and radio technology will enable small and cheap nodes capable of sensing, communication and computation. Networks of such nodes can coordinate to perform distributed sensing of environmental phenomena. In this paper, we explore the directed diffusion paradigm for such coordination. Directed diffusion is datacentric in that all communication is for named data. All nodes in a directed diffusion-based network are application-aware. This enables diffusion to achieve energy savings by selecting empirically good paths and by caching and processing data in-network. We explore and evaluate the use of directed diffusion for a simple remote-surveillance sensor network.
6,061 citations
01 Jan 2000
TL;DR: This work introduces Epidemic Routing, where random pair-wise exchanges of messages among mobile hosts ensure eventual message delivery and achieves eventual delivery of 100% of messages with reasonable aggregate resource consumption in a number of interesting scenarios.
Abstract: Mobile ad hoc routing protocols allow nodes with wireless adaptors to communicate with one another without any pre-existing network infrastructure. Existing ad hoc routing protocols, while robust to rapidly changing network topology, assume the presence of a connected path from source to destination. Given power limitations, the advent of short-range wireless networks, and the wide physical conditions over which ad hoc networks must be deployed, in some scenarios it is likely that this assumption is invalid. In this work, we develop techniques to deliver messages in the case where there is never a connected path from source to destination or when a network partition exists at the time a message is originated. To this end, we introduce Epidemic Routing, where random pair-wise exchanges of messages among mobile hosts ensure eventual message delivery. The goals of Epidemic Routing are to: i) maximize message delivery rate, ii) minimize message latency, and iii) minimize the total resources consumed in message delivery. Through an implementation in the Monarch simulator, we show that Epidemic Routing achieves eventual delivery of 100% of messages with reasonable aggregate resource consumption in a number of interesting scenarios.
4,355 citations
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TL;DR: This paper presents a detailed study on recent advances and open research issues in WMNs, followed by discussing the critical factors influencing protocol design and exploring the state-of-the-art protocols for WMNs.
4,205 citations