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47
Theoretical Results on Base Station Movement Problem for Sensor Network
- In Proc. IEEE INFOCOM
, 2008
"... The benefits of using mobile base station to prolong sensor network lifetime have been well recognized. However, due to the complexity of the problem (time-dependent network topology and traffic routing), theoretical performance limit and provably optimal algorithms remain difficult to develop. This ..."
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Cited by 46 (5 self)
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The benefits of using mobile base station to prolong sensor network lifetime have been well recognized. However, due to the complexity of the problem (time-dependent network topology and traffic routing), theoretical performance limit and provably optimal algorithms remain difficult to develop. This paper fills this important gap by contributing theoretical results regarding the optimal movement of a mobile base station. Our main result hinges upon a novel transformation of the joint base station movement and flow routing problem from time domain to space domain. Based on this transformation, we first show if the base station is allowed to be present only on a set of pre-defined points, then we can find the optimal time duration for the base station on each of these points so that the overall network lifetime is maximized. Based on this finding, we show that when the location of the base station is un-constrained (i.e., can move to any point in the two-dimensional plane), we can develop an approximation algorithm for the joint mobile base station location and flow routing problem such that the network lifetime is guaranteed to be at least of the maximum network lifetime, where can be made arbitrarily small depending on required precision.
Extending Network Lifetime for PrecisionConstrained Data Aggregation
- in Wireless Sensor Networks,” Proc. IEEE INFOCOM
, 2006
"... Abstract — This paper exploits the tradeoff between data quality and energy consumption to extend the lifetime of wireless sensor networks. We consider the applications that require some aggregate form of sensed data with precision guarantees. Our key idea is to differentiate the precisions of data ..."
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Cited by 38 (8 self)
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Abstract — This paper exploits the tradeoff between data quality and energy consumption to extend the lifetime of wireless sensor networks. We consider the applications that require some aggregate form of sensed data with precision guarantees. Our key idea is to differentiate the precisions of data collected from different sensor nodes to balance their energy consumption. This is achieved by partitioning the precision constraint of data aggregation and allocating error bounds to individual sensor nodes in a coordinated fashion. Three factors affecting the lifetime of sensor nodes are identified: (1) the changing pattern of sensor readings; (2) the residual energy of sensor nodes; and (3) the communication cost between the sensor nodes and the base station. We analyze the optimal precision allocation in terms of network lifetime and propose an adaptive precision allocation scheme that dynamically adjusts the error bounds of sensor nodes. Experimental results using real data traces show that the proposed scheme significantly improves network lifetime compared to existing methods. I.
On the Construction of a Maximum-Lifetime Data Gathering Tree in Sensor Networks: NP-Completeness and Approximation Algorithm
"... Energy efficiency is critical for wireless sensor networks. The data gathering process must be carefully designed to conserve energy and extend the network lifetime. For applications where each sensor continuously monitors the environment and periodically reports to a base station, a tree-based top ..."
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Cited by 37 (6 self)
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Energy efficiency is critical for wireless sensor networks. The data gathering process must be carefully designed to conserve energy and extend the network lifetime. For applications where each sensor continuously monitors the environment and periodically reports to a base station, a tree-based topology is often used to collect data from sensor nodes. In this work, we study the construction of a data gathering tree to maximize the network lifetime, which is defined as the time until the first node depletes its energy. The problem is shown to be NP-complete. We design an algorithm which starts from an arbitrary tree and iteratively reduces the load on bottleneck nodes (nodes likely to soon deplete their energy due to high degree or low remaining energy). We show that the algorithm terminates in polynomial time and is provably near optimal.
Maximum Throughput and Fair Bandwidth Allocation in Multi-Channel Wireless Mesh Networks
, 2006
"... Wireless mesh network is designed as an economical solution for last-mile broadband Internet access. In this paper, we study bandwidth allocation in multi-channel multihop wireless mesh networks. Our optimization goals are to maximize the network throughput and, at the same time, to enhance fairnes ..."
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Cited by 35 (2 self)
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Wireless mesh network is designed as an economical solution for last-mile broadband Internet access. In this paper, we study bandwidth allocation in multi-channel multihop wireless mesh networks. Our optimization goals are to maximize the network throughput and, at the same time, to enhance fairness. First, we formulate and present an Linear Programming (LP) formulation to solve the Maximum throughput Bandwidth Allocation (MBA) problem. However, simply maximizing the throughput may lead to a severe bias on bandwidth allocation among wireless mesh nodes. In order to achieve a good tradeoff between fairness and throughput, we consider a simple max-min fairness model which leads to high throughput solutions with guaranteed maximum minimum bandwidth allocation values, and the well-known Lexicographical Max-Min (LMM) model. Correspondingly, we formulate the Max-min guaranteed Maximum throughput Bandwidth Allocation (MMBA) problem and the Lexicographical Max-Min Bandwidth Allocation (LMMBA) problem. For the former one, we present an LP formulation to provide optimal solutions and for the later one, we propose a polynomial time optimal algorithm.
Link scheduling with power control for throughput enhancement in multihop wireless networks
- IEEE Transactions on Vehicular Technology
, 2006
"... Abstract — Throughput is an important performance consideration for multihop wireless networks. In this paper, we study the joint link scheduling and power control problem, focusing on maximizing the network throughput. We formulate the MAximum THroughput link Scheduling with Power Control (MATH-SPC ..."
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Cited by 35 (3 self)
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Abstract — Throughput is an important performance consideration for multihop wireless networks. In this paper, we study the joint link scheduling and power control problem, focusing on maximizing the network throughput. We formulate the MAximum THroughput link Scheduling with Power Control (MATH-SPC) problem, and present a Mixed Integer Linear Programming (MILP) formulation to provide optimal solutions. However, simply maximizing the throughput leads to a severe bias on bandwidth allocation among all links. In order to enhance both throughput and fairness, we define a new parameter, the Demand Satisfaction Factor (DSF), to characterize the fairness of bandwidth allocation. We formulate the MAximum Throughput fAir link Scheduling with Power Control (MATA-SPC) problem and present an MILP formulation for this problem. We also present an effective polynomial time heuristic algorithm, namely, the Serial LP Rounding (SLPR) heuristic. Our numerical results show that bandwidth can be fairly allocated among all links/flows by solving our MATA-SPC formulation or using our heuristic algorithm at the cost of a minor reduction of network throughput.
Minimizing Delay and Maximizing Lifetime for Wireless Sensor Networks With Anycast
"... In this paper, we are interested in minimizing the delay and maximizing the lifetime of event-driven wireless sensor networks, for which events occur infrequently. In such systems, most of the energy is consumed when the radios are on, waiting for a packet to arrive. Sleep-wake scheduling is an effe ..."
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Cited by 27 (3 self)
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In this paper, we are interested in minimizing the delay and maximizing the lifetime of event-driven wireless sensor networks, for which events occur infrequently. In such systems, most of the energy is consumed when the radios are on, waiting for a packet to arrive. Sleep-wake scheduling is an effective mechanism to prolong the lifetime of these energy-constrained wireless sensor networks. However, sleep-wake scheduling could result in substantial delays because a transmitting node needs to wait for its next-hop relay node to wake up. An interesting line of work attempts to reduce these delays by developing “anycast”-based packet forwarding schemes, where each node opportunistically forwards a packet to the first neighboring node that wakes up among multiple candidate nodes. In this paper, we first study how to optimize the anycast forwarding schemes for minimizing the expected packet-delivery delays from the sensor nodes to the sink. Based on this result, we then provide a solution to the joint control problem of how to optimally control the system parameters of the sleep-wake scheduling protocol and the anycast packet-forwarding protocol to maximize the network lifetime, subject to a constraint on the expected endto-end packet-delivery delay. Our numerical results indicate that the proposed solution can outperform prior heuristic solutions in the literature, especially under practical scenarios where there are obstructions, e.g., a lake or a mountain, in the coverage area of the wireless sensor network.
A Utility-based Distributed Maximum Lifetime Routing Algorithm for Wireless Networks
"... 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, ..."
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Cited by 18 (0 self)
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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.
Deploying Long-lived and Cost-effective Hybrid Sensor Networks
- In Proceedings of the First Workshop on Broadband Advanced Sensor Networks (BaseNets 2004
, 2004
"... In this paper, we study the problem of network deployment in hybrid sensor networks, consisting of both resource-rich and resource-impoverished sensor devices. The resource-rich devices, called micro-servers, are more expensive but have significantly greater bandwidth and energy capabilities compare ..."
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Cited by 18 (3 self)
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In this paper, we study the problem of network deployment in hybrid sensor networks, consisting of both resource-rich and resource-impoverished sensor devices. The resource-rich devices, called micro-servers, are more expensive but have significantly greater bandwidth and energy capabilities compared to the low-cost, low-powered sensors. Such hybrid sensor networks have the potential to support the higher bandwidth communications of broadband sensor networking applications, as well as the fine-grained sensing that is made possible by smaller sensor devices. We propose several techniques to investigate some fundamental questions on hybrid sensor network deployment — for a given number of micro-servers, what is the maximum lifetime of a sensor network and the optimal micro-server placement? What benefit can additional micro-servers add to the network, and how financially costeffective is it to introduce these micro-servers? For our investigation, we propose a cost model for energy usage in hybrid sensor networks, which is then formulated into an integer linear optimization problem and solved optimally. The integer linear problem solution does not scale with network size thus we introduce an approximation algorithm using tabu-search technique. Our studies show that network life time can be extended by more than 100 % by adding an extra micro-server to the network; the network life time of optimized micro-servers ’ placement can be seven times longer than the worst case life time. We also propose a normalized cost model that balances the benefits with deployment costs, and show how to achieve an optimal deployment. 1
Joint spectrum allocation and scheduling for fair spectrum sharing in cognitive radio wireless networks,”Comput
- Netw. J
, 2008
"... Cognitive radio and Dynamic Spectrum Access (DSA) enable wireless users to share a wide range of available spectrums. In this paper, we study joint spectrum alloca-tion and scheduling problems in cognitive radio wireless networks with the objec-tives of achieving fair spectrum sharing. A novel Multi ..."
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Cited by 14 (1 self)
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Cognitive radio and Dynamic Spectrum Access (DSA) enable wireless users to share a wide range of available spectrums. In this paper, we study joint spectrum alloca-tion and scheduling problems in cognitive radio wireless networks with the objec-tives of achieving fair spectrum sharing. A novel Multi-Channel Contention Graph (MCCG) is proposed to characterize the impact of interference under the protocol model in such networks. Based on the MCCG, we present an optimal algorithm to compute maximum throughput solutions. As simply maximizing throughput may result in a severe bias on resource allocation, we take fairness into consideration by presenting optimal algorithms as well as fast heuristics to compute fair solutions based on a simplified max-min fairness model and the well-known proportional fair-ness model. Numerical results show that the performance given by our heuristic algorithms is very close to that of the optimal solution, and our proportional fair algorithms achieve a good tradeoff between throughput and fairness. In addition, we extend our research to the physical interference model, and propose effective heuristics for solving the corresponding problems. Key words: Cognitive radio, dynamic spectrum access, spectrum allocation, scheduling, fairness.
Algorithm design for base station placement problems in sensor networks
- 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 ..."
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Cited by 11 (1 self)
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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.
