Decomposition algorithms for maximizing the lifetime of wireless sensor networks with mobile sinks (original) (raw)
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Energy-aware routing to maximize lifetime in wireless sensor networks with mobile sink
Journal of Communications Software and …, 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 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 a performance measure in order to test the efficiency of new heuristics that might be proposed in the future for a practical implementation of a real system.
Maximum lifetime routing to mobile sink in wireless sensor networks
Proc. IEEE SoftCOM, 2005
We address the problem of maximizing the lifetime in a wireless sensor network with energy-constrained sensor nodes and mobile data collection points (sinks). 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 and give a novel linear programming formulation that maximizes network lifetime. We show that the maximum lifetime can only 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.
Lifetime maximization of wireless sensor networks with sink costs
2017
Balanced distribution of the energy load of the sensors is important for the elongation of wireless sensor network (WSN) lifetimes. There are four main WSN design issues affecting the energy distribution among the sensors: sensor locations, sensor activity schedules, mobile sink routes, and data flow routes. Many studies try to make energy usage more efficient through optimal determination of these design issues. However, only very few studies handle these four design issues in a combined manner. Additionally, the cost of the sinks is neglected in all studies. In this study, a mixed integer linear program is first proposed, in which the cost of the sinks is taken into consideration in terms of lifetime hours and the four design issues are integrated. Next, a heuristic solution procedure for the solution of large network instances is offered and the efficiency of the heuristic is proven by comparing its performance with that of commercial solvers in extensive numerical instances.
A distributed algorithm for maximum lifetime routing in sensor networks with mobile sink
Wireless Communications, IEEE …, 2008
We consider a noise-limited wireless sensor network that consists of battery-operated nodes which can route information to a mobile sink in a multi-hop fashion. The problem of maximizing the network's lifetime, defined as the period of time during which the network can route a feasible flow to each sink location subject to power/energy constraints, is cast into a linear program, reduced into a simpler equivalent form and solved via dual decomposition. The unknowns are the sink sojourn times and the routing flow vector for each sink location. The presence of a mobile sink presents new challenges but the problem structure can still be exploited to find the optimal solution. A distributed algorithm based on the subgradient method and using the sink as leader is proposed and its performance is evaluated through simulation for random networks. The algorithm's requirements in memory are also provided.
Exploiting Sink Mobility for Maximizing Sensor Networks Lifetime
Proceedings of the 38th Annual Hawaii International Conference on System Sciences, 2005
This paper explores the idea of exploiting the mobility of data collection points (sinks) for the purpose of increasing the lifetime of a wireless sensor network with energy-constrained nodes. We give a novel linear programming formulation for the joint problems of determining the movement of the sink and the sojourn time at different points in the network that induce the maximum network lifetime. Differently from previous solutions, our objective function maximizes the overall network lifetime (here defined as the time till the first node "dies" because of energy depletion) rather than minimizing the energy consumption at the nodes. For wireless sensor networks with up to 256 nodes our model produces sink movement patterns and sojourn times leading to a network lifetime up to almost five times that obtained with a static sink. Simulation results are performed to determine the distribution of the residual energy at the nodes over time. These results confirm that energy consumption varies with the current sink location, being the nodes more drained those in the proximity of the sink. Furthermore, the proposed solution for computing the sink movement results in a fair balancing of the energy depletion among the network nodes.
Maximizing system lifetime in wireless sensor networks
European Journal of Operational Research, 2007
One of the most critical issues in wireless sensor networks is represented by the limited availability of energy on network nodes; thus, making good use of energy is necessary to increase network lifetime. In this paper, we define network lifetime as the time spanning from the instant when the network starts functioning properly, i.e., satisfying the target level of coverage of the area of interest, until the same level of coverage cannot be guaranteed any more due to lack of energy in sensors. To maximize system lifetime, we propose to exploit sensor spatial redundancy by defining subsets of sensors active in different time periods, to allow sensors to save energy when inactive. Two approaches are presented to maximize network lifetime: the first one, based on column generation, must run in a centralized way, whereas the second one is based on a heuristic algorithm aiming at a distributed implementation. To assess their performance and provide guidance to network design, the two approaches are compared by varying several network parameters. The column generation based approach typically yields better solutions, but it may be difficult to implement in practice. Nevertheless it provides both a good benchmark against which heuristics may be compared and a modeling framework which can be extended to deal with additional features, such as reliability.
Ad Hoc Networks, 2014
The longevity of Wireless Sensor Networks (WSNs) is a crucial concern that significantly influences their applicability in a specific context. Most of the related literature focuses on communication protocols aiming to reduce the energy consumption which would eventually lead to longer network lifetimes. On the other hand, a limited number of studies concentrate on providing a unifying frame to investigate the integrated effect of the important WSN design decisions such as sensor places, activity schedules, data routes, trajectory of the mobile sink(s), along with the tactical level decisions including the data propagation protocols. However, a monolithic mathematical optimization model with a practically applicable, efficient, and accurate solution method is still missing. In this study, we first provide a mathematical model which integrates WSN design decisions on sensor places, activity schedules, data routes, trajectory of the mobile sink(s) and then present two heuristic methods for the solution of the model. We demonstrate the efficiency and accuracy of the heuristics on several randomly generated problem instances on the basis of extensive numerical experiments.
Lifetime Maximization of Sensor Networks Through Optimal Data Collection Scheduling of Mobile Sink
IEEE Access, 2020
The problem of maximizing lifetime of a sensor network is still challenging mainly due to the stringent delay-deadline of real-time applications and heterogeneity of sensor devices. The problem is further complicated when the network contains many obstacles. In maximizing network lifetime, existing literature works either merely address issues of application delay-deadline and presence of obstacles, or analyze primitive data collection approaches for such an environment. In this paper, we formulate optimal data collection schedule of a mobile sink in an obstructed sensor network as a mixed-integer linear programming (MILP) problem. The proposed data collection scheduling finds an optimal set of rendezvous nodes over a preformed Starfish routing backbone, and corresponding sojourn duration so as to maximize the network lifetime while maintaining delay-deadline constraint in an obstructed network. The proposed Starfish-scheduling ensures a loop-free traveling path for a mobile sink across the network. The results of performance evaluation, performed in network simulator-2, depict the suitability of Starfish scheduling as it outperforms state-of-the-art-works in terms of extending network lifetime and data delivery throughput as well as reducing average end-to-end delay.
On the use of multiple sinks to extend the lifetime in connected wireless sensor networks
Electronic Notes in Discrete Mathematics, 2013
This paper addresses the maximum network lifetime problem in wireless sensor networks. In this problem, the purpose is to schedule a set of wireless sensors, keeping them connected and guaranteeing that all targets are covered, while network lifetime is maximized. Two variants of this problem are considered; in the first case it is assumed that a single sink (base station) is available, the second case considers the presence of several sinks. To solve the problem, a hybrid Column Generation-GRASP heuristic is proposed. The method is shown to be able to find optimal or near optimal solutions efficiently in both cases.
Efficient Approach for Maximizing Lifespan in Wireless Sensor Networks by Using Mobile Sinks
ETRI Journal, 2017
Recently, sink mobility has been shown to be highly beneficial in improving network lifetime in wireless sensor networks (WSNs). Numerous studies have exploited mobile sinks (MSs) to collect sensed data in order to improve energy efficiency and reduce WSN operational costs. However, there have been few studies on the effectiveness of MS operation on WSN closed operating cycles. Therefore, it is important to investigate how data is collected and how to plan the trajectory of the MS in order to gather data in time, reduce energy consumption, and improve WSN network lifetime. In this study, we combine two methods, the cluster-head election algorithm and the MS trajectory optimization algorithm, to propose the optimal MS movement strategy. This study aims to provide a closed operating cycle for WSNs, by which the energy consumption and running time of a WSN is minimized during the cluster election and data gathering periods. Furthermore, our flexible MS movement scenarios achieve both a long network lifetime and an optimal MS schedule. The simulation results demonstrate that our proposed algorithm achieves better performance than other well-known algorithms. This is an Open Access article distributed under the term of Korea Open Government License (KOGL) Type 4: Source Indication + Commercial Use Prohibition + Change Prohibition (http://www.kogl.or.kr/news/dataView.do?dataIdx=97).