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1 Fast Data Collection in TreeBased Wireless Sensor Networks
"... Abstract—We investigate the following fundamental question how fast can information be collected from a wireless sensor network organized as tree? To address this, we explore and evaluate a number of different techniques using realistic simulation models under the manytoone communication paradigm ..."
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Abstract—We investigate the following fundamental question how fast can information be collected from a wireless sensor network organized as tree? To address this, we explore and evaluate a number of different techniques using realistic simulation models under the manytoone communication paradigm known as convergecast. We first consider time scheduling on a single frequency channel with the aim of minimizing the number of time slots required (schedule length) to complete a convergecast. Next, we combine scheduling with transmission power control to mitigate the effects of interference, and show that while power control helps in reducing the schedule length under a single frequency, scheduling transmissions using multiple frequencies is more efficient. We give lower bounds on the schedule length when interference is completely eliminated, and propose algorithms that achieve these bounds. We also evaluate the performance of various channel assignment methods and find empirically that for moderate size networks of about 100 nodes, the use of multifrequency scheduling can suffice to eliminate most of the interference. Then, the data collection rate no longer remains limited by interference but by the topology of the routing tree. To this end, we construct degreeconstrained spanning trees and capacitated minimal spanning trees, and show significant improvement in scheduling performance over different deployment densities. Lastly, we evaluate the impact of different interference and channel models on the schedule length. Index Terms—Convergecast, TDMA scheduling, multiple channels, powercontrol, routing trees. 1
MCLMAC: A multichannel MAC protocol for wireless sensor networks,” Ad Hoc Networks
, 2011
"... Abstract—In traditional wireless sensor network (WSN) applications, energy efficiency is considered to be the most important concern whereas utilizing the use of bandwidth and maximizing the throughput are of secondary importance. However, recent applications, such as structural health monitoring, r ..."
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Abstract—In traditional wireless sensor network (WSN) applications, energy efficiency is considered to be the most important concern whereas utilizing the use of bandwidth and maximizing the throughput are of secondary importance. However, recent applications, such as structural health monitoring, require high amounts of data to be collected at a faster rate. We present a multichannel MAC protocol, MCLMAC, designed with the objective of maximizing the throughput of WSN by coordinating transmissions over multiple channels. MCLMAC takes the advantage of interference and contention free parallel transmissions on different channels. It is based on scheduled access which eases the coordination of nodes dynamically switching their interfaces between channels and makes the protocol to operate effectively free of collisions during peak traffic. Time is organized into timeslots and each node shall be assigned control over a timeslot to transmit on a particular channel. We analyze the performance of MCLMAC with extensive simulations. MCLMAC exhibits significant bandwidth utilization and high throughput while ensuring an energyefficient operation. Moreover, MCLMAC outperforms the contentionbased multichannel MMSN protocol, cluster based channel assignment and singlechannel CSMA in terms of data delivery ratio and throughput for high data rate, moderatesize networks of 100 nodes. I.
Game Theoretical Approach for Channel Allocation in Wireless Sensor and Actuator Networks
"... Abstract—In this paper, multichannel allocation in wireless sensor and actuator networks is formulated as an optimization problem which is NPhard. In order to efficiently solve this problem, a distributed game based channel allocation (GBCA) Algorithm is proposed by taking into account both networ ..."
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Abstract—In this paper, multichannel allocation in wireless sensor and actuator networks is formulated as an optimization problem which is NPhard. In order to efficiently solve this problem, a distributed game based channel allocation (GBCA) Algorithm is proposed by taking into account both network topology and routing information. For both tree/forest routing and nontree/forest routing scenarios, it is proved that there exists at least one Nash Equilibrium for the problem. Furthermore, the suboptimality of Nash Equilibrium and the convergence of the Best Response dynamics are also analyzed. Simulation results demonstrate that GBCA significantly reduces the interference and dramatically improves the network performance in terms of delivery ratio, throughput, channel access delay, and energy consumption. Index Terms—Channel allocation, game theory, wireless sensor and actuator networks (WSANs), wireless sensor networks (WSNs). I.
Scheduling Algorithms for TreeBased Data Collection in Wireless Sensor Networks
"... 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 contentionfree Time Division Multiple Access (TDMA) based scheduling pr ..."
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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 contentionfree Time Division Multiple Access (TDMA) based scheduling protocols for such data collection applications over treebased 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 treebased routing topology is a fundamental traffic pattern in wireless sensor networks (WSNs). This
MultiChannel Scheduling and Spanning Trees: ThroughputDelay Tradeoff for Fast Data Collection in Sensor Networks
 University of Aeronautics and Astronautics in 2005, and B.S. degree in mathematics from Jiangxi Normal University in
, 2012
"... Abstract—We investigate the tradeoff between two mutually conflicting performance objectives—throughput and delay—for fast, periodic data collection in treebased sensor networks arbitrarily deployed in 2D. Two primary factors that affect the data collection rate (throughput) and timeliness (delay) ..."
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Abstract—We investigate the tradeoff between two mutually conflicting performance objectives—throughput and delay—for fast, periodic data collection in treebased sensor networks arbitrarily deployed in 2D. Two primary factors that affect the data collection rate (throughput) and timeliness (delay) are: 1) efficiency of the link scheduling protocol, and 2) structure of the routing tree in terms of its node degrees and radius. In this paper, we utilize multiple frequency channels and design an efficient link scheduling protocol that gives a constant factor approximation on the optimal throughput in delivering aggregated data from all the nodes to the sink. To minimize the maximum delay subject to a given throughput bound, we also design an ()bicriteria approximation algorithm to construct a BoundedDegree MinimumRadius Spanning Tree, with the radius of the tree at most times the minimum possible radius for a given degree bound 1, and the degree of any node at most 1 +, where and are positive constants. Lastly, we evaluate the efficiency of our algorithms on different types of spanning trees and show that multichannel scheduling, combined with optimal routing topologies, can achieve the best of both worlds in terms of maximizing the aggregated data collection rate and minimizing the maximum packet delay. Index Terms—Approximation algorithms, convergecast, multiple channels, routing trees, timedivision multiple access (TDMA) scheduling. I.
1Maximum Achievable Throughput in a Wireless Sensor Network Using Innetwork Computation for Statistical Functions
"... Abstract—Many applications require the sink to compute a function of the data collected by the sensors. Instead of sending all the data to the sink, the intermediate nodes could process the data they receive to significantly reduce the volume of traffic transmitted: this is known as innetwork compu ..."
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Abstract—Many applications require the sink to compute a function of the data collected by the sensors. Instead of sending all the data to the sink, the intermediate nodes could process the data they receive to significantly reduce the volume of traffic transmitted: this is known as innetwork computation. Instead of focusing on asymptotic results for large networks as is the current practice, we are interested in explicitly computing the maximum achievable throughput of a given network when the sink is interested in the first M statistical moments of the collected data. Here, the kth statistical moment is defined as the expectation of the kth power of the data. Flow models have been routinely used in multihop wireless networks when there is no innetwork computation and they are typically tractable for relatively large networks. However, deriving such models is not obvious when innetwork computation is allowed. We develop a discretetime model for the realtime network operation and perform two transformations to obtain a flow model that keeps the essence of innetwork computation. This gives an upper bound on the maximum achievable throughput. To show its tightness, we derive a numerical lower bound by computing a solution to the discretetime model based on the solution to the flow model. This lower bound turns out to be close to the upper bound proving that the flow model is an excellent approximation to the discretetime model. We then provide several engineering insights on these networks. Index Terms—Sensor networks, innetwork computation, throughput, flow model. I.
MultiChannel Scheduling for Fast Convergecast in Wireless Sensor Networks
"... Abstract — We explore the following fundamental questionhow fast can information be collected from a wireless sensor network? We consider a number of design parameters such as, power control, time and frequency scheduling, and routing. There are essentially two factors that hinder efficient data co ..."
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Abstract — We explore the following fundamental questionhow fast can information be collected from a wireless sensor network? We consider a number of design parameters such as, power control, time and frequency scheduling, and routing. There are essentially two factors that hinder efficient data collection interference and the halfduplex singletransceiver radios. We show that while power control helps in reducing the number of transmission slots to complete a convergecast under a single frequency channel, scheduling transmissions on different frequency channels is more efficient in mitigating the effects of interference (empirically, 6 channels suffice for most 100node networks). With these observations, we define a receiverbased channel assignment problem, and prove it to be NPcomplete on general graphs. We then introduce a greedy channel assignment algorithm that efficiently eliminates interference, and compare its performance with other existing schemes via simulations. Once the interference is completely eliminated, we show that with halfduplex singletransceiver radios the achievable schedule length is lowerbounded by max(2nk − 1, N), where nk is the maximum number of nodes on any subtree and N is the number of nodes in the network. We modify an existing distributed time slot assignment algorithm to achieve this bound when a suitable balanced routing scheme is employed. Through extensive simulations, we demonstrate that convergecast can be completed within up to 50 % less time slots, in 100node networks, using multiple channels as compared to that with singlechannel communication. Finally, we also demonstrate further improvements that are possible when the sink is equipped with multiple transceivers or when there are multiple sinks to collect data. I.
MultiChannel Assignment in Wireless Sensor Networks: A Game Theoretic Approach
"... Abstract—In this paper, we formulate multichannel assignment in Wireless Sensor Networks (WSNs) as an optimization problem and show it is NPhard. We then propose a distributed Game Based Channel Assignment algorithm (GBCA) to solve the problem. GBCA takes into account both the network topology in ..."
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Abstract—In this paper, we formulate multichannel assignment in Wireless Sensor Networks (WSNs) as an optimization problem and show it is NPhard. We then propose a distributed Game Based Channel Assignment algorithm (GBCA) to solve the problem. GBCA takes into account both the network topology information and transmission routing information. We prove that there exists at least one Nash Equilibrium in the channel assignment game. Furthermore, we analyze the suboptimality of Nash Equilibrium and the convergence of the Best Response in the game. Simulation results are given to demonstrate that GBCA can reduce interference significantly and achieve satisfactory network performance in terms of delivery ratio, throughput, channel access delay and energy consumption. I.
1 MultiChannel Scheduling and Spanning Trees: ThroughputDelay Tradeoff for Fast Data Collection in Sensor Networks
"... Abstract—We investigate the tradeoff between two mutually conflicting performance objectives – throughput and delay – for fast, periodic data collection in treebased sensor networks arbitrarily deployed in 2D. Two primary factors that affect the data collection rate (throughput) and timeliness (d ..."
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Abstract—We investigate the tradeoff between two mutually conflicting performance objectives – throughput and delay – for fast, periodic data collection in treebased sensor networks arbitrarily deployed in 2D. Two primary factors that affect the data collection rate (throughput) and timeliness (delay) are: (i) efficiency of the link scheduling protocol, and (ii) structure of the routing tree in terms of its node degrees and radius. In this paper, we utilize multiple frequency channels and design an efficient link scheduling protocol that gives a constant factor approximation on the optimal throughput in delivering aggregated data from all the nodes to the sink. To minimize the maximum delay subject to a given throughput bound, we also design an (α,β)bicriteria approximation algorithm to construct a BoundedDegree MinimumRadius Spanning Tree, with the radius of the tree at most β times the minimum possible radius for a given degree bound ∆ ∗ , and the degree of any node at most ∆ ∗ +α, where α and β are positive constants. Lastly, we evaluate the efficiency of our algorithms on different types of spanning trees, and show that multichannel scheduling, combined with optimal routing topologies, can achieve the best of both worlds in terms of maximizing the aggregated data collection rate and minimizing the maximum packet delay. Index Terms—Convergecast, TDMA scheduling, multiple channels, routing trees, approximation algorithms. I.
1 Networked Computing in Wireless Sensor Networks for Structural Health Monitoring
"... Abstract—This paper studies the problem of distributed computation over a network of wireless sensors. While this problem applies to many emerging applications, to keep our discussion concrete, we will focus on sensor networks used for structural health monitoring. Within this context, the heaviest ..."
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Abstract—This paper studies the problem of distributed computation over a network of wireless sensors. While this problem applies to many emerging applications, to keep our discussion concrete, we will focus on sensor networks used for structural health monitoring. Within this context, the heaviest computation is to determine the singular value decomposition (SVD) to extract mode shapes (eigenvectors) of a structure. Compared to collecting raw vibration data and performing SVD at a central location, computing SVD within the network can result in significantly lower energy consumption and delay. Using recent results on decomposing SVD, a wellknown centralized operation, we seek to determine a nearoptimal communication structure that enables the distribution of this computation and the reassembly of the final results, with the objective of minimizing energy consumption subject to a computational delay constraint. We show that this reduces to a generalized clustering problem, and establish that it is NPhard. By relaxing the delay constraint, we derive a lower bound. We then propose an integer linear program (ILP) to solve the constrained problem exactly as well as an approximate algorithm with a proven approximation ratio. We further present a distributed version of the approximate algorithm. We present both simulation and experimentation results to demonstrate the effectiveness of these algorithms.