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82
A minimum cost heterogeneous sensor network with a lifetime constraint
 IEEE Transactions on Mobile Computing
, 2005
"... Abstract—We consider a heterogeneous sensor network in which nodes are to be deployed over a unit area for the purpose of surveillance. An aircraft visits the area periodically and gathers data about the activity in the area from the sensor nodes. There are two types of nodes that are distributed ov ..."
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Cited by 108 (1 self)
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Abstract—We consider a heterogeneous sensor network in which nodes are to be deployed over a unit area for the purpose of surveillance. An aircraft visits the area periodically and gathers data about the activity in the area from the sensor nodes. There are two types of nodes that are distributed over the area using twodimensional homogeneous Poisson point processes; type 0 nodes with intensity (average number per unit area) 0 and battery energy E0; and type 1 nodes with intensity 1 and battery energy E1. Type 0 nodes do the sensing while type 1 nodes act as the cluster heads besides doing the sensing. Nodes use multihopping to communicate with their closest cluster heads. We determine the optimum node intensities ( 0, 1) and node energies (E0, E1) that guarantee a lifetime of at least T units, while ensuring connectivity and coverage of the surveillance area with a high probability. We minimize the overall cost of the network under these constraints. Lifetime is defined as the number of successful data gathering trips (or cycles) that are possible until connectivity and/or coverage are lost. Conditions for a sharp cutoff are also taken into account, i.e., we ensure that almost all the nodes run out of energy at about the same time so that there is very little energy waste due to residual energy. We compare the results for random deployment with those of a grid deployment in which nodes are placed deterministically along grid p ffiffiffiffiffi points. We observe that in both cases 1 scales approximately as 0. Our results can be directly extended to take into account unreliable nodes.
Crosslayer design for lifetime maximization in interferencelimited wireless sensor networks
, 2006
"... We consider the joint optimal design of the physical, medium access control (MAC), and routing layers to maximize the lifetime of energyconstrained wireless sensor networks. The problem of computing lifetimeoptimal routing flow, link schedule, and link transmission powers for all active time slots ..."
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Cited by 88 (6 self)
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We consider the joint optimal design of the physical, medium access control (MAC), and routing layers to maximize the lifetime of energyconstrained wireless sensor networks. The problem of computing lifetimeoptimal routing flow, link schedule, and link transmission powers for all active time slots is formulated as a nonlinear optimization problem. We first restrict the link schedules to the class of interferencefree time division multiple access (TDMA) schedules. In this special case, we formulate the optimization problem as a mixed integerconvex program, which can be solved using standard techniques. Moreover, when the slots lengths are variable, the optimization problem is convex and can be solved efficiently and exactly using interior point methods. For general nonorthogonal link schedules, we propose an iterative algorithm that alternates between adaptive link scheduling and computation of optimal link rates and transmission powers for a fixed link schedule. The performance of this algorithm is compared to other design approaches for several network topologies. The results illustrate the advantages of load balancing, multihop routing, frequency reuse, and interference mitigation in increasing the lifetime of energyconstrained networks. We also briefly discuss computational approaches to extend this algorithm to large networks.
DFTMSN: The Delay/FaultTolerant Mobile Sensor Network for Pervasive Information Gathering
 INFOCOM 2006
, 2006
"... Abstract — This paper focuses on the Delay/FaultTolerant Mobile Sensor Network (DFTMSN) for pervasive information gathering. We develop simple and efficient data delivery schemes tailored for DFTMSN, which has several unique characteristics such as sensor mobility, loose connectivity, fault toler ..."
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Cited by 74 (6 self)
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Abstract — This paper focuses on the Delay/FaultTolerant Mobile Sensor Network (DFTMSN) for pervasive information gathering. We develop simple and efficient data delivery schemes tailored for DFTMSN, which has several unique characteristics such as sensor mobility, loose connectivity, fault tolerability, delay tolerability, and buffer limit. We first study two basic approaches, namely, direct transmission and flooding. We analyze their performance by using queuing theory and statistics. Based on the analytic results that show the tradeoff between data delivery delay/ratio and transmission overhead, we introduce an optimized flooding scheme that minimizes transmission overhead in flooding. Then, we propose a simple and effective DFTMSN data delivery scheme, which consists of two key components for data transmission and queue management, respectively. The former makes decision on when and where to transmit data messages based on the delivery probability, which reflects the likelihood that a sensor can deliver data messages to the sink. The latter decides which messages to transmit or drop based on the fault tolerance, which indicates the importance of the messages. The system parameters are carefully tuned on the basis of thorough analyses to optimize network performance. Extensive simulations are carried out for performance evaluation. Our results show that the proposed DFTMSN data delivery scheme achieves the highest message delivery ratio with acceptable delay and transmission overhead. I.
Distributed algorithms for maximum lifetime routing in wireless sensor networks
 IEEE Trans. Wireless Commun
"... Abstract — A sensor network of nodes with wireless transceiver capabilities and limited energy is considered. We propose distributed algorithms to compute an optimal routing scheme that maximizes the time at which the first node in the network drains out of energy. The problem is formulated as a li ..."
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Cited by 71 (6 self)
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Abstract — A sensor network of nodes with wireless transceiver capabilities and limited energy is considered. We propose distributed algorithms to compute an optimal routing scheme that maximizes the time at which the first node in the network drains out of energy. The problem is formulated as a linear programming problem and subgradient algorithms are used to solve it in a distributed manner. The resulting algorithms have low computational complexity and are guaranteed to converge to an optimal routing scheme that maximizes the network lifetime. The algorithms are illustrated by an example in which an optimal flow is computed for a network of randomly distributed nodes. We also show how our approach can be used to obtain distributed algorithms for many different extensions to the problem. Finally, we extend our problem formulation to more general definitions of network lifetime to model realistic scenarios in sensor networks. Index Terms — routing, linear programming, dual decomposition, subgradient algorithm, sensor networks, network lifetime. I.
Principles and protocols for power control in wireless ad hoc networks
 IEEE Journal on Selected Areas in Communications, Special Issue on Wireless Ad Hoc Networks (Part I
, 2005
"... Abstract—Transmit power control is a prototypical example of a crosslayer design problem. The transmit power level affects signal quality and, thus, impacts the physical layer, determines the neighboring nodes that can hear the packet and, thus, the network layer affects interference which causes c ..."
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Cited by 68 (0 self)
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Abstract—Transmit power control is a prototypical example of a crosslayer design problem. The transmit power level affects signal quality and, thus, impacts the physical layer, determines the neighboring nodes that can hear the packet and, thus, the network layer affects interference which causes congestion and, thus, affects the transport layer. It is also key to several performance measures such as throughput, delay, and energy consumption. The challenge is to determine where in the architecture the power control problem is to be situated, to determine the appropriate power level by studying its impact on several performance issues, to provide a solution which deals properly with the multiple effects of transmit power control, and finally, to provide a software architecture for realizing the solution. We distill some basic principles on power control, which inform the subsequent design process. We then detail the design of a sequence of increasingly complex protocols, which address the multidimensional ramifications of the power control problem. Many of these protocols have been implemented, and may be the only implementations for power control in a real system. It is hoped that the approach in this paper may also be of use in other topical problems in crosslayer design. Index Terms—Design principles, Linux implementation, power control.
Rate Allocation in Wireless Sensor Networks with Network Lifetime Requirement
, 2004
"... An important performance consideration for wireless sensor networks is the amount of information collected by all the nodes in the network over the course of network lifetime. Since the objective of maximizing the sum of rates of all the nodes in the network can lead to a severe bias in rate allocat ..."
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Cited by 47 (5 self)
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An important performance consideration for wireless sensor networks is the amount of information collected by all the nodes in the network over the course of network lifetime. Since the objective of maximizing the sum of rates of all the nodes in the network can lead to a severe bias in rate allocation among the nodes, we advocate the use of lexicographical maxmin (LMM) rate allocation for the nodes. To calculate the LMM rate allocation vector, we develop a polynomialtime algorithm by exploiting the parametric analysis (PA) technique from linear programming (LP), which we call serial LP with Parametric Analysis (SLPPA). We show that the SLPPA can be also employed to address the socalled LMM node lifetime problem much more efficiently than an existing technique proposed in the literature. More important, we show that there exists an elegant duality relationship between the LMM rate allocation problem and the LMM node lifetime problem. Therefore, it is sufficient to solve any one of the two problems and important insights can be obtained by inferring duality results for the other problem.
Multipath Routing Algorithms for Congestion Minimization
, 2005
"... Unlike traditional routing schemes that route all traffic along a single path, multipath routing strategies split the traffic among several paths in order to ease congestion. It has been widely recognized that multipath routing can be fundamentally more efficient than the traditional approach of rou ..."
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Cited by 32 (1 self)
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Unlike traditional routing schemes that route all traffic along a single path, multipath routing strategies split the traffic among several paths in order to ease congestion. It has been widely recognized that multipath routing can be fundamentally more efficient than the traditional approach of routing along single paths. Yet, in contrast to the singlepath routing approach, most studies in the context of multipath routing focused on heuristic methods. We demonstrate the significant advantage of optimal (or near optimal) solutions. Hence, we investigate multipath routing adopting a rigorous (theoretical) approach. We formalize problems that incorporate two major requirements of multipath routing. Then, we establish the intractability of these problems in terms of computational complexity. Finally, we establish efficient solutions with proven performance guarantees.
Crosslayer energy and delay optimization in smallscale sensor networks
 IEEE Trans.Wirel. Commun
"... Abstract — The general joint design of the physical, MAC, and routing layers to minimize network energy consumption is complex and hard to solve. Heuristics to compute approximate solutions and highcomplexity algorithms to compute exact solutions have been previously proposed. In this paper, we foc ..."
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Cited by 32 (1 self)
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Abstract — The general joint design of the physical, MAC, and routing layers to minimize network energy consumption is complex and hard to solve. Heuristics to compute approximate solutions and highcomplexity algorithms to compute exact solutions have been previously proposed. In this paper, we focus on synchronous smallscale networks with interferencefree link scheduling and practical MQAM link transmission schemes. We show that the crosslayer optimization problems can be closely approximated by convex optimization problems that can be efficiently solved. There are two main contributions of this paper. First of all, we minimize the total network energy that includes both transmission and circuit energy consumptions, where we explore the tradeoff between the two energy elements. Specifically, we use interferencefree TDMA as the medium access control scheme. We optimize the routing flow, TDMA slot assignment, and MQAM modulation rate and power on each link. The results demonstrate that the minimum energy transmission scheme is a combination of multihop and singlehop transmissions for general networks; including circuit energy favors transmission schemes with fewer hops. Secondly, based on the solved optimal transmission scheme, we quantify the best tradeoff curve between delay and energy consumption, where we derive a scheduling algorithm to minimize the worstcase packet delay. Index Terms — Crosslayer, energy efficiency, routing, link scheduling, link adaptation, convex programming, minimum
Power aware routing for sensor databases
 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 ..."
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Cited by 25 (0 self)
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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 NPcomplete. 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.
Maximizing Lifetime of Sensor Surveillance Systems
 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 ..."
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Cited by 23 (3 self)
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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 targetwatching 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