Cauligi S. Raghavendra

Bio: Cauligi S. Raghavendra is an academic researcher from University of Southern California. The author has contributed to research in topics: Wireless sensor network & Hypercube. The author has an hindex of 48, co-authored 275 publications receiving 20869 citations. Previous affiliations of Cauligi S. Raghavendra include University of California, Los Angeles & Washington State University.

PEGASIS: Power-efficient gathering in sensor information systems

Abstract: Sensor webs consisting of nodes with limited battery power and wireless communications are deployed to collect useful information from the field. Gathering sensed information in an energy efficient manner is critical to operate the sensor network for a long period of time. In W. Heinzelman et al. (Proc. Hawaii Conf. on System Sci., 2000), a data collection problem is defined where, in a round of communication, each sensor node has a packet to be sent to the distant base station. If each node transmits its sensed data directly to the base station then it will deplete its power quickly. The LEACH protocol presented by W. Heinzelman et al. is an elegant solution where clusters are formed to fuse data before transmitting to the base station. By randomizing the cluster heads chosen to transmit to the base station, LEACH achieves a factor of 8 improvement compared to direct transmissions, as measured in terms of when nodes die. In this paper, we propose PEGASIS (power-efficient gathering in sensor information systems), a near optimal chain-based protocol that is an improvement over LEACH. In PEGASIS, each node communicates only with a close neighbor and takes turns transmitting to the base station, thus reducing the amount of energy spent per round. Simulation results show that PEGASIS performs better than LEACH by about 100 to 300% when 1%, 20%, 50%, and 100% of nodes die for different network sizes and topologies.

Spray and wait: an efficient routing scheme for intermittently connected mobile networks

Abstract: Intermittently connected mobile networks are sparse wireless networks where most of the time there does not exist a complete path from the source to the destination. These networks fall into the general category of Delay Tolerant Networks. There are many real networks that follow this paradigm, for example, wildlife tracking sensor networks, military networks, inter-planetary networks, etc. In this context, conventional routing schemes would fail.To deal with such networks researchers have suggested to use flooding-based routing schemes. While flooding-based schemes have a high probability of delivery, they waste a lot of energy and suffer from severe contention, which can significantly degrade their performance. Furthermore, proposed efforts to significantly reduce the overhead of flooding-based schemes have often be plagued by large delays. With this in mind, we introduce a new routing scheme, called Spray and Wait, that "sprays" a number of copies into the network, and then "waits" till one of these nodes meets the destination.Using theory and simulations we show that Spray and Wait outperforms all existing schemes with respect to both average message delivery delay and number of transmissions per message delivered; its overall performance is close to the optimal scheme. Furthermore, it is highly scalable retaining good performance under a large range of scenarios, unlike other schemes. Finally, it is simple to implement and to optimize in order to achieve given performance goals in practice.

Power-aware routing in mobile ad hoc networks

Abstract: b this paper we present a case for using new power-aware metn.cs for determining routes in wireless ad hoc networks. We present five ~erent metriw based on battery power consumption at nodw. We show that using th=e metrics in a shortest-cost routing algorithm reduces the cost/packet of routing packets by 5-30% over shortwt-hop routing (this cost reduction is on top of a 40-70% reduction in energy consumption obtained by using PAMAS, our MAC layer prtocol). Furthermore, using these new metrics ensures that the mean time to node failure is increased si~cantly. An interesting property of using shortest-cost routing is that packet delays do not increase. Fintiy, we note that our new metrim can be used in most tradition routing protocols for ad hoc networks.

PAMAS—power aware multi-access protocol with signalling for ad hoc networks

Abstract: In this paper we develop a new multiaccess protocol for ad hoc radio networks. The protocol is based on the original MACA protocol with the adition of a separate signalling channel. The unique feature of our protocol is that it conserves battery power at nodes by intelligently powering off nodes that are not actively transmitting or receiving packets. The manner in which nodes power themselves off does not influence the delay or throughput characteristics of our protocol. We illustrate the power conserving behavior of PAMAS via extensive simulations performed over ad hoc networks containing 10-20 nodes. Our results indicate that power savings of between 10% and 70% are attainable in most systems. Finally, we discuss how the idea of power awareness can be built into other multiaccess protocols as well.

Data gathering algorithms in sensor networks using energy metrics

Abstract: Gathering sensed information in an energy efficient manner is critical to operating the sensor network for a long period of time. The LEACH protocol presented by Heinzelman et al. (2000) is an elegant solution where clusters are formed to fuse data before transmitting to the base station. In this paper, we present an improved scheme, called PEGASIS (power-efficient gathering in sensor information systems), which is a near-optimal chain-based protocol that minimizes energy. In PEGASIS, each node communicates only with a close neighbor and takes turns transmitting to the base station, thus reducing the amount of energy spent per round. Simulation results show that PEGASIS performs better than LEACH. For many applications, in addition to minimizing energy, it is also important to consider the delay incurred in gathering sensed data. We capture this with the energy /spl times/ delay metric and present schemes that attempt to balance the energy and delay cost for data gathering from sensor networks. We present two new schemes to minimize energy /spl times/ delay using CDMA and non-CDMA sensor nodes. We compared the performance of direct, LEACH, and our schemes with respect to energy /spl times/ delay using extensive simulations for different network sizes. Results show that our schemes perform 80 or more times better than the direct scheme and also outperform the LEACH protocol.

Energy-efficient communication protocol for wireless microsensor networks

Abstract: Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our findings that the conventional protocols of direct transmission, minimum-transmission-energy, multi-hop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show the LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional outing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated.

Energy-efficient communication protocols for wireless microsensor networks

Abstract: Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have signicant impact on the overall energy dissipation of these networks. Based on our ndings that the conventional protocols of direct transmission, minimum-transmission-energy, multihop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster base stations (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show that LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional routing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated.

An application-specific protocol architecture for wireless microsensor networks

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.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.