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Journal ArticleDOI

A Data Gathering Algorithm Based on Energy-Aware Connected Dominating Sets to Minimize Energy Consumption and Maximize Node Lifetime in Wireless Sensor Networks

TL;DR: Performance comparison studies involving well-known LEACH and PEGASIS algorithms indicate that ECDS-DG incurs the lowest energy consumption per round and sustains the largest number of rounds before first node failure.
Abstract: This paper develops an energy-aware connected dominating set based data gathering ECDS-DG algorithm for wireless sensor networks. The algorithm includes only nodes that have a relatively higher energy level in ECDS. For every round, a data gathering tree ECDS-DG tree rooted at the ECDS Leader, that is, the node with the largest available energy, which transmits the data packet to the sink, is formed by considering only the nodes in the ECDS as the intermediate nodes of the tree. The non-ECDS nodes are leaf nodes of the tree, and the upstream node of an intermediate ECDS node in the ECDS-DG tree is the closest ECDS node that is also relatively closer to the ECDS Leader. Performance comparison studies involving well-known LEACH and PEGASIS algorithms indicate that ECDS-DG incurs the lowest energy consumption per round and sustains the largest number of rounds before first node failure.
Citations
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Book
26 Oct 2010
TL;DR: This issue contains three research papers and a comprehensive survey article on mobile ad hoc networks, describing the main characteristics of those networks and how they are being used, and discussing the most pressing issues and challenges associated with these temporary wireless networks.
Abstract: Welcome to the second installment of IJBDCN. This issue contains three research papers and a comprehensive survey article on mobile ad hoc networks. We would like to publish a couple of survey or tutorial articles per year as we believe this to be of value to our readers. Many research papers are necessarily focused and do not allow for a " panoramic " view of a particular subject. This is the gap that well-written survey or tutorial papers can fill. We are also planning a guest-edited special issue for the last quarter of this year and welcome your suggestions for future special issues of the journal. This second issue starts with a paper entitled " An Approach to Solving the Surviv-able Capacitated Network Design Problem " where Sridhar and Park studied the problem of selecting links of a network to construct primary and secondary routes for transfer of commodity traffic between nodes of the network. Their technique allows the design of survivable and cost-effective networks. In the second paper, " Query Processing Strategies for Location-Dependent Information Services " , Jayaputera and Taniar propose a new approach to generate a query result for location-dependent information services (LDIS). They argue that choosing a square as the scope of a query and dividing it into four equal regions, where a user is a center point of the scope, results in a faster searching time to find targets queried and brings a bigger chance to get rare targets. In addition, by avoiding resubmitting the same queries when the query results missed, the approach reduced bandwidth use at both the server and client sides. The third paper, " Addressing SPAM E-Mail Using Hashcash " by Curran and Honan tackles a problem experienced by most of us. The authors present the Hashcash proof-of-work approach and investigate the feasibility of implementing a solution based on that mechanism along with what they called a " cocktail " of antispam measures designed to keep junk mail under control. Finally , in the last paper, entitled " MANET: Applications, Issues, and Challenges for the Future " , Dhar presents an informative survey of mobile ad hoc networks, describing the main characteristics of those networks and how they are being used, and discussing the most pressing issues and challenges associated with these temporary wireless networks. We hope that you enjoy this and the upcoming issues of IJBDCN. Our goal is to …

262 citations

Journal ArticleDOI
TL;DR: This paper presents a comprehensive description of two broad categories of data gathering algorithms for wireless sensor networks-the classical algorithms that are not energy-aware and modern energy- aware data gatheringgorithms.
Abstract: Wireless sensor networks comprise of vast numbers of sensor nodes deployed to monitor a particular event fire, intrusion, etc. or measure a parameter like temperature, pressure value representative of the physical condition of the ambient environment. There is a growing need of using energy-efficient data gathering algorithms that can effectively aggregate the monitored/measured data from the individual sensor nodes through a properly constructed communication topology and transmit a single representative data to a control center sink that is typically located far away from the network field. In order to maximize node lifetime and be fair to all nodes in the network, such a communication topology has to be dynamically constructed for every round of data gathering by taking into consideration available energy levels of sensor nodes. This paper presents a comprehensive description of two broad categories of data gathering algorithms for wireless sensor networks-the classical algorithms that are not energy-aware and modern energy-aware data gathering algorithms. These algorithms can also be classified based on the communication topology they choose to construct and use for data gathering. The authors also present an extensive simulation study that demonstrates the individual as well as the comparative performance of these data gathering algorithms.

32 citations


Cites background or methods from "A Data Gathering Algorithm Based on..."

  • ...• Next, we present two grid block energy based hierarchical data gathering (GBEDG) algorithms (Meghanathan, 2010a) that differ from each other depending on whether the nodes within a grid are arranged as a cluster or as a chain....

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  • ...• Afterwards, a spanning-tree based energyaware maximal leaf nodes data gathering (EMLN-DG) algorithm (Meghanathan, 2010c) that prefers to include only nodes that have a relatively larger number of uncovered neighbors as well as a higher energy level as the intermediate nodes of the tree and in…...

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  • ...• We describe an algorithm to construct an energy-aware connected dominating set (ECDS)-based data gathering tree (Meghanathan, 2010b) that prefers to include nodes with higher energy level as the intermediate aggregating nodes of the tree....

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  • ...The data gathering algorithms differ in the communication topology used for data aggregation and forwarding: clusters (Heinzelman et al., 2000), chain (Lindsey et al., 2002), grid (Meghanathan, 2010a), connected dominating set (Meghanathan, 2010b) and spanning trees (Meghanathan, 2010c)....

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Journal ArticleDOI
TL;DR: The authors examine the impact of wireless technology on gatekeeping practices in the context of EU news markets using the Shoemaker/ReeseGatekeeping Model.
Abstract: Mediation in news industries has received significant attention by researchers for more than half a century. Gatekeepers decide which information should be delivered to different audiences. The Shoemaker/ReeseGatekeeping Model identifies five different filters of content processing: individual influences, professional routines, the organization, extra-media influences and ideology. Journalism practices, intra-organization and extra-media-related procedures and strategic alliances, including culture and ideology, add more complexity in the contemporary globalized media landscape. Gatekeeping is being processed through out all the above mentioned pillars. ICT technologies related to the media have influenced the interactivity among the pillars and wireless technologies have influenced the digital media landscape. The European Union has experienced dramatic changes in its regulation environment and spectrum resources allocation. In this article, the authors examine the impact of wireless technology on gatekeeping practices in the context of EU news markets.

26 citations

Journal ArticleDOI
TL;DR: This work modeled the cost based on distance, bandwidth, geographical terrain and technology simultaneously using a parametric cost estimation methodology applied to real data obtained from the Indian Telecom Company, BSNL and shows how a cost optimized network can be designed given the real world constraints.
Abstract: The parametric cost estimation approach has proved to be an efficient method for analyzing complex systems such as spacecraft, missiles, ships, buildings, etc where cost varies according to a number of parameters. The cost to provision a telecom network also depends on a number of parameters; but little research effort has been applied to estimate cost using this approach. In estimating the cost of a telecom network, most published research has considered two parameters; distance and bandwidth of a link and ignored the effects of other parameters. We have modeled the cost based on distance, bandwidth, geographical terrain and technology simultaneously using a parametric cost estimation methodology applied to real data obtained from the Indian Telecom Company, BSNL. Using the model, we show how a cost optimized network can be designed given the real world constraints. The applicability of our model to determine revenue sharing mechanism for an international call is also demonstrated.

11 citations

Journal ArticleDOI
TL;DR: An algorithm to determine a stable Connected Dominating Set CDS for Mobile Ad hoc Networks MANETs based on the notion of a metric called the Node Stability Index NSI of a node, defined as the sum of the predicted expiration times of the links LETs with the neighbor nodes that are not yet covered by a CDS node.
Abstract: In this paper, the author proposes an algorithm to determine a stable Connected Dominating Set CDS for Mobile Ad hoc Networks MANETs based on the notion of a metric called the Node Stability Index NSI of a node, defined as the sum of the predicted expiration times of the links LETs with the neighbor nodes that are not yet covered by a CDS node. The proposed algorithm prefers, to include to the CDS, a covered node that has the largest NSI value. A covered node is eligible for inclusion into the NSI-CDS if it has at least one uncovered neighbor node. Through extensive simulations, the author observes that the NSI-CDS is significantly stable the tradeoff being a modest increase in the CDS Node Size and its lifetime is about 2.5-3.5 times more than the lifetime of a maximum-density based CDS MaxD-CDS and 1.5-2 times more than the lifetime of an ID-based CDS.

10 citations

References
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Book
01 Jan 1990
TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
Abstract: From the Publisher: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures. Like the first edition,this text can also be used for self-study by technical professionals since it discusses engineering issues in algorithm design as well as the mathematical aspects. In its new edition,Introduction to Algorithms continues to provide a comprehensive introduction to the modern study of algorithms. The revision has been updated to reflect changes in the years since the book's original publication. New chapters on the role of algorithms in computing and on probabilistic analysis and randomized algorithms have been included. Sections throughout the book have been rewritten for increased clarity,and material has been added wherever a fuller explanation has seemed useful or new information warrants expanded coverage. As in the classic first edition,this new edition of Introduction to Algorithms presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers. Further,the algorithms are presented in pseudocode to make the book easily accessible to students from all programming language backgrounds. Each chapter presents an algorithm,a design technique,an application area,or a related topic. The chapters are not dependent on one another,so the instructor can organize his or her use of the book in the way that best suits the course's needs. Additionally,the new edition offers a 25% increase over the first edition in the number of problems,giving the book 155 problems and over 900 exercises thatreinforcethe concepts the students are learning.

21,651 citations

Proceedings ArticleDOI
04 Jan 2000
TL;DR: The Low-Energy Adaptive Clustering Hierarchy (LEACH) as mentioned in this paper is 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.
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.

12,497 citations

01 Jan 2000
TL;DR: 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, is proposed.
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.

11,412 citations

Book
Andrew J. Viterbi1
01 Jan 1995
TL;DR: Generating Pseudorandom Signals (Pseudonoise) from PseudOrandom Sequences by Modulation and Demodulation of Spread Spectrum Signals in Multipath and Multiple Access Interference.
Abstract: 1. Introduction. Definition and Purpose. Basic Limitations of the Conventional Approach. Spread Spectrum Principles. Organization of the Book. 2. Random and Pseudorandom Signal Generation. Purpose. Pseudorandom Sequences. Maximal Length Linear Shift Register Sequences. Randomness Properties of MLSR Sequences. Conclusion. Generating Pseudorandom Signals (Pseudonoise) from Pseudorandom Sequences. First- and Second-Order Statistics of Demodulator Output in Multiple Access Interference. Statistics for QPSK Modulation by Pseudorandom Sequences. Examples. Bound for Bandlimited Spectrum. Error Probability for BPSK or QPSK with Constant Signals in Additive Gaussian Noise and Interference. Appendix 2A: Optimum Receiver Filter for Bandlimited Spectrum. 3. Synchronization of Pseudorandom Signals. Purpose. Acquisition of Pseudorandom Signal Timing. Hypothesis Testing for BPSK Spreading. Hypothesis Testing for QPSK Spreading. Effect of Frequency Error. Additional Degradation When N is Much Less Than One Period. Detection and False Alarm Probabilities. Fixed Signals in Gaussian Noise (L=1). Fixed Signals in Gaussian Noise with Postdetection Integration (L>1). Rayleigh Fading Signals (L>/=1). The Search Procedure and Acquisition Time. Single-Pass Serial Search (Simplified). Single-Pass Serial Search (Complete). Multiple Dwell Serial Search. Time Tracking of Pseudorandom Signals. Early-Late Gate Measurement Statistics. Time Tracking Loop. Carrier Synchronization. Appendix 3A: Likelihood Functions and Probability Expressions. Bayes and Neyman-Pearson Hypothesis Testing. Coherent Reception in Additive White Gaussian Noise. Noncoherent Reception in AWGN for Unfaded Signals. Noncoherent Reception of Multiple Independent Observations of Unfaded Signals in AWGN. Noncoherent Reception of Rayleigh-Faded Signals in AWGN. 4. Modulation and Demodulation of Spread Spectrum Signals in Multipath and Multiple Access Interference. Purpose. Chernoff and Battacharyya Bounds. Bounds for Gaussian Noise Channel. Chernoff Bound for Time-Synchronous Multiple Access Interference with BPSK Spreading. Chernoff Bound for Time-Synchronous Multiple Access Interference with QPSK Spreading. Improving the Chernoff Bound by a Factor of 2. Multipath Propagation: Signal Structure and Exploitation. Pilot-Aided Coherent Multipath Demodulation. Chernoff Bounds on Error Probability for Coherent Demodulation with Known Path Parameters. Rayleigh and Rician Fading Multipath Components. Noncoherent Reception. Quasi-optimum Noncoherent Multipath Reception for M-ary Orthogonal Modulation. Performance Bounds. Search Performance for Noncoherent Orthogonal M-ary Demodulators. Power Measurement and Control for Noncoherent Orthogonal M-ary Demodulators. Power Control Loop Performance. Power Control Implications. Appendix 4A: Chernoff Bound with Imperfect Parameter Estimates. 5. Coding and Interleaving. Purpose. Interleaving to Achieve Diversity. Forward Error Control Coding - Another Means to Exploit Redundancy. Convolutional Code Structure. Maximum Likelihood Decoder - Viterbi Algorithm. Generalization of the Preceding Example. Convolutional Code Performance Evaluation. Error Probability for Tailed-off Block. Bit Error Probability. Generalizations of Error Probability Computation. Catastrophic Codes. Generalization to Arbitrary Memoryless Channels - Coherent and Noncoherent. Error Bounds for Binary-Input, Output-Symmetric Channels with Integer Metrics. A Near-Optimal Class of Codes for Coherent Spread Spectrum Multiple Access. Implementation. Decoder Implementation. Generating Function and Performance. Performance Comparison and Applicability. Orthogonal Convolutional Codes for Noncoherent Demodulation of Rayleigh Fading Signals. Implementation. Performance for L-Path Rayleigh Fading. Conclusions and Caveats. Appendix 5A: Improved Bounds for Symmetric Memoryless Channels and the AWGN Channel. Appendix 5B: Upper Bound on Free Distance of Rate 1/n Convolutional Codes. 6. Capacity, Coverage, and Control of Spread Spectrum Multiple Access Networks. General. Reverse Link Power Control. Multiple Cell Pilot Tracking and Soft Handoff. Other-Cell Interference. Propagation Model. Single-Cell Reception - Hard Handoff. Soft Handoff Reception by the Better of the Two Nearest Cells. Soft Handoff Reception by the Best of Multiple Cells. Cell Coverage Issues with Hard and Soft Handoff. Hard Handoff. Soft Handoff. Erlang Capacity of Reverse Links. Erlang Capacity for Conventional Assigned-Slot Multiple Access. Spread Spectrum Multiple Access Outage - Single Cell and Perfect Power Control. Outage with Multiple-Cell Interference. Outage with Imperfect Power Control. An Approximate Explicit Formula for Capacity with Imperfect Power Control. Designing for Minimum Transmitted Power. Capacity Requirements for Initial Accesses. Erlang Capacity of Forward Links. Forward Link Power Allocation. Soft Handoff Impact on Forward Link. Orthogonal Signals for Same-Cell Users. Interference Reduction with Multisectored and Distributed Antennas. Interference Cancellation. Epilogue. References and Bibliography. Index.

2,795 citations


"A Data Gathering Algorithm Based on..." refers methods in this paper

  • ...For Code Division Multiple Access, CDMA, (Viterbi, 1995) systems, PEGASIS has been later improved using a chain-based binary scheme to minimize the delay incurred and to reduce the energy*delay metric (Lindsey et al., 2001)....

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Journal ArticleDOI
TL;DR: This paper presents an improved scheme, called PEGASIS (power-efficient gathering in sensor information systems), which is a near-optimal chain-based protocol that minimizes energy, and presents two new schemes that attempt to balance the energy and delay cost for data gathering from sensor networks.
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.

1,194 citations


Additional excerpts

  • ...Well-known among these are the Low-Energy Adaptive Clustering Hierarchy, LEACH, (Heinelman et al., 2000) and the Power-Efficient Gathering in Sensor Information Systems, PEGASIS, (Lindsey et al., 2002) algorithms....

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