Maximizing data extraction in energy-limited sensor networks. (2004)

by SK04 Sadagopan, N, B Krishnamachari
Venue:INFOCOM 2004. Twenty-third Annual Joint Conference of the IEEE Computer and Communications Societies,
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Data aggregation techniques in sensor networks: A survey

by Ramesh Rajagopalan, Pramod K. Varshney - Comm. Surveys & Tutorials, IEEE , 2006
"... Wireless sensor networks consist of sensor nodes with sensing and communication capabilities. We focus on data aggregation problems in energy constrained sensor networks. The main goal of data aggregation algorithms is to gather and aggregate data in an energy efficient manner so that network lifeti ..."
Abstract - Cited by 138 (0 self) - Add to MetaCart
Wireless sensor networks consist of sensor nodes with sensing and communication capabilities. We focus on data aggregation problems in energy constrained sensor networks. The main goal of data aggregation algorithms is to gather and aggregate data in an energy efficient manner so that network lifetime is enhanced. In this paper, we present a survey of data aggregation algorithms in wireless sensor networks. We compare and contrast different algorithms on the basis of performance measures such as lifetime, latency and data accuracy. We conclude with possible future research directions. 1.
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Power aware routing for sensor databases

by Chiranjeeb Buragohain, Divyakant Agrawal, Subhash Suri - in Proc. IEEE Infocom’05 , 2005
"... Abstract — Wireless sensor networks offer the potential to span and monitor large geographical areas inexpensively. Sensor network databases like TinyDB [1] are the dominant architectures to extract and manage data in such networks. Since sensors have significant power constraints (battery life), an ..."
Abstract - Cited by 25 (0 self) - Add to MetaCart
Abstract — Wireless sensor networks offer the potential to span and monitor large geographical areas inexpensively. Sensor network databases like TinyDB [1] are the dominant architectures to extract and manage data in such networks. Since sensors have significant power constraints (battery life), and high communication costs, design of energy efficient communication algorithms is of great importance. The data flow in a sensor database is very different from data flow in an ordinary network and poses novel challenges in designing efficient routing algorithms. In this work we explore the problem of energy efficient routing for various different types of database queries and show that in general, this problem is NP-complete. We give a constant factor approximation algorithm for one class of query, and for other queries give heuristic algorithms. We evaluate the efficiency of the proposed algorithms by simulation and demonstrate their near optimal performance for various network sizes. Index Terms — sensor networks, graph theory, mathematical programming/optimization I.
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Data gathering tours in sensor networks

by Alexandra Meliou, David Chu, Carlos Guestrin, Joseph Hellerstein, Wei Hong - IN IPSN , 2006
"... A basic task in sensor networks is to interactively gather data from a subset of the sensor nodes. When data needs to be gathered from a selected set of nodes in the network, existing communication schemes often behave poorly. In this paper, we study the algorithmic challenges in efficiently routing ..."
Abstract - Cited by 24 (6 self) - Add to MetaCart
A basic task in sensor networks is to interactively gather data from a subset of the sensor nodes. When data needs to be gathered from a selected set of nodes in the network, existing communication schemes often behave poorly. In this paper, we study the algorithmic challenges in efficiently routing a fixed-size packet through a small number of nodes in a sensor network, picking up data as the query is routed. We show that computing the optimal routing scheme to visit a specific set of nodes is NP-complete, but we develop approximation algorithms that produce plans with costs within a constant factor of the optimum. We enhance the robustness of our initial approach to accommodate the practical issues of limited-sized packets as well as network link and node failures, and examine how different approaches behave with dynamic changes in the network topology. Our theoretical results are validated via an implementation of our algorithms on the TinyOS platform and a controlled simulation study using Matlab and TOSSIM.
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Maximizing Lifetime of Sensor Surveillance Systems

by Hai Liu, Xiaohua Jia, Peng-jun Wan, Chih-wei Yi, S. Kami Makki, Niki Pissinou - IEEE/ ACM Trans. Networking , 2006
"... Abstract—This paper addresses the maximal lifetime scheduling problem in sensor surveillance systems. Given a set of sensors and targets in an area, a sensor can watch only one target at a time, our task is to schedule sensors to watch targets and forward the sensed data to the base station, such th ..."
Abstract - Cited by 23 (3 self) - Add to MetaCart
Abstract—This paper addresses the maximal lifetime scheduling problem in sensor surveillance systems. Given a set of sensors and targets in an area, a sensor can watch only one target at a time, our task is to schedule sensors to watch targets and forward the sensed data to the base station, such that the lifetime of the surveillance system is maximized, where the lifetime is the duration that all targets are watched and all active sensors are connected to the base station. We propose an optimal solution to find the target-watching schedule for sensors that achieves the maximal lifetime. Our solution consists of three steps: 1) computing the maximal lifetime of the surveillance system and a workload matrix by using the linear programming technique; 2) decomposing the workload matrix into a sequence of schedule matrices that can achieve the maximal lifetime; and 3) determining the sensor surveillance trees based on the above obtained schedule matrices, which specify the active sensors
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Balanced Data Gathering in Energy-Constrained Sensor Networks

by Emil Falck, Patrik Floréen, Petteri Kaski, Jukka Kohonen, Pekka Orponen
"... We consider the problem of gathering data from a wireless multi-hop network of energy-constrained sensor nodes to a common base station. Speci cally, we aim to balance the total amount of data received from the sensor network during its lifetime against a requirement of sucient coverage for all ..."
Abstract - Cited by 16 (1 self) - Add to MetaCart
We consider the problem of gathering data from a wireless multi-hop network of energy-constrained sensor nodes to a common base station. Speci cally, we aim to balance the total amount of data received from the sensor network during its lifetime against a requirement of sucient coverage for all the sensor locations surveyed. Our main contribution lies in formulating this balanced data gathering task and in studying the eects of balancing. We give an LP network ow formulation and present experimental results on optimal data routing designs also with impenetrable obstacles between the nodes. We then proceed to consider the eect of augmenting the basic sensor network with a small number of auxiliary relay nodes with less stringent energy constraints.

Scalable and Robust Aggregation Techniques for Extracting Statistical Information in Sensor Networks

by Hongbo Jiang, Shudong Jin , 2006
"... Wireless sensor networks have stringent constraints on system resources and data aggregation techniques are critically important. However, accurate data aggregation is difficult due to the variation of sensor readings and due to the frequent communication failures. To address these difficulties, we ..."
Abstract - Cited by 14 (2 self) - Add to MetaCart
Wireless sensor networks have stringent constraints on system resources and data aggregation techniques are critically important. However, accurate data aggregation is difficult due to the variation of sensor readings and due to the frequent communication failures. To address these difficulties, we propose a scalable and robust data aggregation algorithm. The novelty of our work includes two aspects. First, our algorithm exploits the mixture model and the Expectation Maximization (EM) algorithm for parameter estimation. Hence, it captures the effects of aggregation over different scales while keeping the communication cost low. Second, our algorithm exploits loss-tolerant multi-path routing schemes. Hence, it obtains accurate statistical information even in the presence of high link and node failure rates. We demonstrate that our techniques reduce communication cost while retaining the precious statistical information otherwise neglected by other aggregation techniques. Our evaluation shows the proposed techniques are robust against link and node failures, and perform consistently well.

Algorithm design for base station placement problems in sensor networks

by Yi Shi, Y. Thomas Hou - in Proc. the 3rd international , 2006
"... Base station placement has significant impact on sensor network performance. Despite its significance, results on this problem remain limited, particularly theoretical results that can provide performance guarantee. This paper proposes a set of procedure to design  �approximation algorithms for base ..."
Abstract - Cited by 11 (1 self) - Add to MetaCart
Base station placement has significant impact on sensor network performance. Despite its significance, results on this problem remain limited, particularly theoretical results that can provide performance guarantee. This paper proposes a set of procedure to design  �approximation algorithms for base station placement problems under any desired small error bound��. It offers a general framework to transform infinite search space to a finite-element search space with performance guarantee. We apply this procedure to solve two practical problems. In the first problem where the objective is to maximize network lifetime, an approximation algorithm designed through this procedure offers��complexity reduction when compared to a stateof-the-art algorithm. This represents the best known result to this problem. In the second problem, we apply the design procedure to address base station placement problem for maximizing network capacity. Our �approximation algorithm is the first theoretical result on this problem. 1.
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Analysis of wired short cuts in wireless sensor networks

by Rohan Chitradurga - In Proc. of IEEE International Conference on Pervasive Svcs , 2004
"... In this paper we investigate the use of wired short cuts in sensor networks. This new paradigm augments a sensor network with a very limited wired infrastructure to improve its overall energy-efficiency. Energy-efficiency is obtained by reduction in average path length. We have developed an analytic ..."
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In this paper we investigate the use of wired short cuts in sensor networks. This new paradigm augments a sensor network with a very limited wired infrastructure to improve its overall energy-efficiency. Energy-efficiency is obtained by reduction in average path length. We have developed an analytical model to analyze the gain in path length reduction by using short cuts. We have also conducted extensive simulations to validate our analysis. Our results show that there is an optimal wire length for which the path length reduction is at its maximum, beyond which it decreases. The optimal length is only a small fraction (37.8-50%) of the network diameter. In a network with 1000 nodes uniformly distributed on a disk the path length reduction saturates at 60-70 % with 5-24 wires, depending on the location of the sink. Also, we find that restricting the knowledge about the wires to 2 hops does not degrade the performance from the case when we have global knowledge of all wires. These results show promise of the new paradigm. 1.
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Optimal traffic-oblivious energyaware routing for multihop wireless networks

by Yuxi Li, Janelle Harms, Robert Holte - In Proceedings of INFOCOM’06 , 2006
"... Abstract — Energy efficiency is an important issue in multihop wireless networks with energy concerns. Usually it is achieved with accurate knowledge of the traffic pattern and/or the current network information such as the remaining energy level. We investigate the problem of designing a routing sc ..."
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Abstract — Energy efficiency is an important issue in multihop wireless networks with energy concerns. Usually it is achieved with accurate knowledge of the traffic pattern and/or the current network information such as the remaining energy level. We investigate the problem of designing a routing scheme to minimize the maximum energy utilization of a multihop wireless network with weak assumption of the traffic pattern and without ongoing collection of network information. We develop polynomial size LP models to design such a routing scheme. We discuss generalizations of the LP models to various radio transmission models. In an interference-limited scenario, we show how to guarantee schedulability of the oblivious routing. We present an extension to consider lossy links. We also discuss implementation issues. The LP models achieve performance close to what an oracle can achieve in the performance study. The results for multihop wireless networks with a single sink are especially good. We make a first stride in designing a traffic-oblivious energy-aware routing framework in multihop wireless networks. I.
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Constrained Flow Optimization with Applications to Data Gathering

by Bo Hong, Viktor K. Prasanna - in Sensor Networks,” First International Workshop on Algorithmic Aspects of Wireless Sensor Networks (ALGOSENSORS 2004 , 2004
"... Abstract. We focus on data gathering problems in energy-constrained wireless sensor networks. We study store-and-gather problems where data are locally stored on the sensors before the data gathering starts, and continuous sensing and gathering problems that model time critical applications. We show ..."
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Abstract. We focus on data gathering problems in energy-constrained wireless sensor networks. We study store-and-gather problems where data are locally stored on the sensors before the data gathering starts, and continuous sensing and gathering problems that model time critical applications. We show that these problems reduce to maximization of network flow under vertex capacity constraint, which reduces to a standard network flow problem. We develop a distributed and adaptive algorithm to optimize data gathering. This algorithm leads to a simple protocol that coordinates the sensor nodes in the system. Our approach provides a unified framework to study a variety of data gathering problems in sensor networks. The efficiency of the proposed method is illustrated through simulations. 1
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