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PANEL: Position-based Aggregator Node Election in Wireless Sensor Networks

by Levente Buttyán, et al.
"... In this paper, we introduce PANEL, a position-based aggregator node election protocol for wireless sensor networks. The novelty of PANEL with respect to other aggregator node election protocols is that it supports asynchronous sensor network applications where the sensor readings are fetched by the ..."
Abstract - Cited by 20 (2 self) - Add to MetaCart
In this paper, we introduce PANEL, a position-based aggregator node election protocol for wireless sensor networks. The novelty of PANEL with respect to other aggregator node election protocols is that it supports asynchronous sensor network applications where the sensor readings are fetched by the base stations after some delay. In particular, the motivation for the design of PANEL was to support reliable and persistent data storage applications, such as TinyPEDS [13]. PANEL ensures load balancing, and it supports intraand inter-cluster routing allowing sensor to aggregator, aggregator to aggregator, base station to aggregator, and aggregator to base station communications. We also compare PANEL with HEED [42] in the simulation environment provided by TOSSIM, and show that, on the one hand, PANEL creates more cohesive clusters than HEED, and, on the other hand, that PANEL is more energy efficient than HEED.

Fundamental scaling laws for energy-efficient storage and querying in wireless sensor networks

by Joon Ahn, Bhaskar Krishnamachari - in MobiHoc ’06: Proceedings of the seventh ACM international symposium on Mobile , 2006
"... We use a constrained optimization framework to derive fundamen-tal scaling laws for both unstructured sensor networks (which use blind sequential search for querying) and structured sensor net-works (which use efficient hash-based querying). We find that the scalability of a sensor network’s perform ..."
Abstract - Cited by 19 (3 self) - Add to MetaCart
We use a constrained optimization framework to derive fundamen-tal scaling laws for both unstructured sensor networks (which use blind sequential search for querying) and structured sensor net-works (which use efficient hash-based querying). We find that the scalability of a sensor network’s performance depends upon whether or not the increase in energy and storage resources with more nodes is outweighed by the concomitant application-specific increase in event and query loads. Let m be the number of events sensed by a network over a finite period of deployment, q the num-ber of queries for each event, and N the size of the network. Our key finding is that q1/2 ·m must be O(N1/4) for unstructured net-works, and q2/3 ·m must be O(N1/2) for structured networks, to ensure scalable network performance. These conditions determine (i) whether or not the energy requirement per node grows without bound with the network size for a fixed-duration deployment, (ii) whether or not there exists a maximum network size that can be operated for a specified duration on a fixed energy budget, and (iii) whether the network lifetime increases or decreases with the size of the network for a fixed energy budget. We discuss the practical implications of these results for the design of hierarchical two-tier wireless sensor networks.
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Latency constrained aggregation in sensor networks

by Luca Becchetti, Peter Korteweg, Alberto Marchetti-spaccamela, Martin Skutella, Leen Stougie, Andrea Vitaletti - IN PROC. OF THE 14TH EUROPEAN SYMPOSIUM ON ALGORITHMS (ESA 06), LNCS , 2006
"... A sensor network consists of sensing devices which may exchange data through wireless communication; sensor networks are highly energy constrained since they are usually battery operated. Data aggregation is a possible way to save energy consumption: nodes may delay data in order to aggregate them ..."
Abstract - Cited by 18 (1 self) - Add to MetaCart
A sensor network consists of sensing devices which may exchange data through wireless communication; sensor networks are highly energy constrained since they are usually battery operated. Data aggregation is a possible way to save energy consumption: nodes may delay data in order to aggregate them into a single packet before forwarding them towards some central node (sink). However, many applications impose constraints on data freshness; this translates into latency constraints for data arriving at the sink. We study the problem of data aggregation to minimize maximum energy consumption under latency constraints on sensed data delivery and we assume unique transmission paths that form a tree rooted at the sink. We prove that the off-line problem is strongly NP-hard and we design a 2-approximation algorithm. The latter uses a novel rounding technique. Almost all real life sensor networks are managed on-line by simple distributed algorithms in the nodes. In this context we consider both the case in which sensor nodes are synchronized or not. We consider distributed on-line algorithms and use competitive analysis to assess their performance.
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A Utility-based Distributed Maximum Lifetime Routing Algorithm for Wireless Networks

by Yuan Xue, Yi Cui, Klara Nahrstedt
"... Energy efficient routing is a critical problem in multihop wireless networks due to the severe power constraint of wireless nodes. Despite its importance and many research efforts towards it, a distributed routing algorithm that maximizes network lifetime is still missing. To address this problem, ..."
Abstract - Cited by 18 (0 self) - Add to MetaCart
Energy efficient routing is a critical problem in multihop wireless networks due to the severe power constraint of wireless nodes. Despite its importance and many research efforts towards it, a distributed routing algorithm that maximizes network lifetime is still missing. To address this problem, we propose a novel utility-based nonlinear optimization formulation to the maximum lifetime routing problem. Based on this formulation, we further present a fully distributed, localized routing algorithm, which is proved to converge to the optimal point, where the network lifetime is maximized. Solid theoretical analysis and simulation results are presented to validate our solution.
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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.

Optimal base station selection for anycast routing in wireless sensor networks

by Y. Thomas Hou, Senior Member, Yi Shi, Student Member, Hanif D. Sherali - IEEE Trans. on Vehicular Technology , 2006
"... Abstract—Energy constraints have a significant impact on the design and operation of wireless sensor networks. This paper investigates the base station (BS) selection (or anycast) problem in wireless sensor networks. A wireless sensor network having multiple BSs (data sink nodes) is considered. Each ..."
Abstract - Cited by 13 (4 self) - Add to MetaCart
Abstract—Energy constraints have a significant impact on the design and operation of wireless sensor networks. This paper investigates the base station (BS) selection (or anycast) problem in wireless sensor networks. A wireless sensor network having multiple BSs (data sink nodes) is considered. Each source node must send all its locally generated data to only one of the BSs. To maximize network lifetime, it is essential to optimally match each source node to a particular BS and find an optimal routing solution. A polynomial time heuristic is proposed for optimal BS selection and anycast via a sequential fixing procedure. Through extensive simulation results, it is shown that this algorithm has excellent performance behavior and provides a near-optimal solution. Index Terms—Anycast, energy constraint, network lifetime, optimization, routing, wireless sensor networks. I.
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CSN: A Network Protocol for Serving Dynamic Queries in Large-Scale Wireless Sensor Networks

by Muneeb Ali, Zartash Afzal Uzmi - 2nd Annual Conference on Communication Networks and Services Research (CNSR 2004 , 2004
"... A fundamental problem that confronts future applications of sensor networks is how to efficiently locate the sensor node that stores a particular data item. It is known that distributed hash table (DHT) based Internet peer-topeer (P2P) protocols provide near-optimum data lookup times for queries mad ..."
Abstract - Cited by 11 (1 self) - Add to MetaCart
A fundamental problem that confronts future applications of sensor networks is how to efficiently locate the sensor node that stores a particular data item. It is known that distributed hash table (DHT) based Internet peer-topeer (P2P) protocols provide near-optimum data lookup times for queries made on networks of distributed nodes [2, 23-25]. A generic mapping of these protocols to sensor networks is, however, perceived as difficult [1]. We present a novel DHT based network protocol for sensor networks—Chord for Sensor Networks (CSN)—for which bounded times for data lookup, in the order of O(logN) messages, can be achieved in an energy efficient manner. CSN makes system lifetime of the sensor network proportional to its effective use. Furthermore, CSN scales well to large-scale sensor networks when the information about other nodes logarithmically increases with an increase in the number of sensor nodes. 1.

Distributed Data Gathering in Multi-Sink Sensor Networks With Correlated Sources

by Kevin Yuen, Baochun Li, Ben Liang - PROC. OF IFIP NETWORKING , 2006
"... In this paper, we propose an effective distributed algorithm to solve the minimum energy data gathering (MEDG) problem in sensor networks with multiple sinks. The problem objective is to find a rate allocation on the sensor nodes and a transmission structure on the network graph, such that the d ..."
Abstract - Cited by 10 (1 self) - Add to MetaCart
In this paper, we propose an effective distributed algorithm to solve the minimum energy data gathering (MEDG) problem in sensor networks with multiple sinks. The problem objective is to find a rate allocation on the sensor nodes and a transmission structure on the network graph, such that the data collected by the sink nodes can reproduce the field of observation, and the total energy consumed by the sensor nodes is minimized. We formulate the problem as a linear optimization problem. The formulation exploits

Scheduling Algorithms for Tree-Based Data Collection in Wireless Sensor Networks

by Ozlem Durmaz Incel, Amitabha Ghosh, Bhaskar Krishnamachari
"... Data collection is a fundamental operation in wireless sensor networks (WSN) where sensor nodes measure attributes about a phenomenon of interest and transmit their readings to a common base station. In this chapter, we survey contention-free Time Division Multiple Access (TDMA) based scheduling pr ..."
Abstract - Cited by 7 (0 self) - Add to MetaCart
Data collection is a fundamental operation in wireless sensor networks (WSN) where sensor nodes measure attributes about a phenomenon of interest and transmit their readings to a common base station. In this chapter, we survey contention-free Time Division Multiple Access (TDMA) based scheduling protocols for such data collection applications over tree-based routing topologies. We classify the algorithms according to their common design objectives, identifying the following four as the most fundamental and most studied with respect to data collection in WSNs: (i) minimizing schedule length, (ii) minimizing latency, (iii) minimizing energy consumption, and (iv) maximizing fairness. We also describe the pros and cons of the underlying design constraints and assumptions, and provide a taxonomy according to these metrics. Finally, we discuss some open problems together with future research directions. Data collection from a set of sensors to a common sink over a tree-based routing topology is a fundamental traffic pattern in wireless sensor networks (WSNs). This

Energy-aware Routing to Maximize Lifetime in Wireless Sensor Networks with Mobile Sink

by Ioannis Papadimitriou, Leonidas Georgiadis - Journal of Communications Software and Systems , 2006
"... In this paper we address the problem of maximizing the lifetime in a wireless sensor network with energy and power constrained sensor nodes and mobile data collection point (sink). Information generated by the monitoring sensors needs to be routed efficiently to the location where the sink is curren ..."
Abstract - Cited by 7 (0 self) - Add to MetaCart
In this paper we address the problem of maximizing the lifetime in a wireless sensor network with energy and power constrained sensor nodes and mobile data collection point (sink). Information generated by the monitoring sensors needs to be routed efficiently to the location where the sink is currently located across multiple hops with different transmission energy requirements. We exploit the capability of the sink to be located in different places during network operation in order to maximize network lifetime. We provide a novel linear programming formulation of the problem. We show that maximum lifetime can be achieved by solving optimally two joint problems: a scheduling problem that determines the sojourn times of the sink at different locations, and a routing problem in order to deliver the sensed data to the sink in an energy-efficient way. Our model provides the optimal solution to both of these problems and gives the best achievable network lifetime. We evaluate numerically the performance of our model by comparing it with the case of static sink and with previously proposed models that focus mainly on the sink movement patterns and sojourn times, leaving the routing problem outside the linear programming formulation. Our approach always achieves higher network lifetime, as expected, leading to a lifetime up to more than twice that obtained with models previously proposed as the network size increases. It also results in a fair balancing of the energy depletion among the sensor nodes. The optimal lifetime provided by the theoretical analysis of our model can be used as
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