Lifetime maximization of wireless sensor networks with sink costs (original) (raw)
Related papers
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.
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.
Network lifetime optimization in wireless sensor networks
IEEE Journal on Selected Areas in Communications, 2000
Network lifetime (NL) is a critical metric in the design of energy-constrained wireless sensor networks (WSNs). In this paper, we investigate a joint optimal design of the physical, medium access control (MAC) and routing layers to maximize NL of a multiple-sources and single-sink (MSSS) WSN with energy constraints. The problem of NL maximization (NLM) can be formulated as a mixed integer-convex optimization problem with adoption of time division multiple access (TDMA) technique. When the integer constraints are relaxed to take real values, the problem can be transformed into a convex problem and the solution achieves the upper bounds. We provide an analytical framework for the relaxed NLM problem of a WSN in general planar topology. We first restrict the topologies to the planar networks on a small scale, including triangle and regular quadrangle topologies. In this special case, we employ the Karush-Kuhn-Tucker (KKT) optimality conditions to derive analytical expressions of the globally optimal NL, which take the influence of data rate, link access and routing into account. To handle larger scale planar networks, an iterative algorithm is proposed using the D&C approach. Numerical results illustrate that the proposed algorithm can be extended to the large planar case and its performance is close to globally optimal performance.
A Hyper-Heuristic Framework for Lifetime Maximization in Wireless Sensor Networks With A Mobile Sink
IEEE/CAA Journal of Automatica Sinica, 2020
Maximizing the lifetime of wireless sensor networks (WSNs) is an important and challenging research problem. Properly scheduling the movements of mobile sinks to balance the energy consumption of wireless sensor network is one of the most effective approaches to prolong the lifetime of wireless sensor networks. However, the existing mobile sink scheduling methods either require a great amount of computational time or lack effectiveness in finding high-quality scheduling solutions. To address the above issues, this paper proposes a novel hyperheuristic framework, which can automatically construct high-level heuristics to schedule the sink movements and prolong the network lifetime. In the proposed framework, a set of low-level heuristics are defined as building blocks to construct high-level heuristics and a set of random networks with different features are designed for training. Further, a genetic programming algorithm is adopted to automatically evolve promising high-level heuristics based on the building blocks and the training networks. By using the genetic programming to evolve more effective heuristics and applying these heuristics in a greedy scheme, our proposed hyper-heuristic framework can prolong the network lifetime competitively with other methods, with small time consumption. A series of comprehensive experiments, including both static and dynamic networks, are designed. The simulation results have demonstrated that the proposed method can offer a very promising performance in terms of network lifetime and response time.
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.
2008
Sensors spend most of their limited battery energy on communicating the collected environmental information to sinks. Therefore, the determination of the optimal sink locations and sensor-to-sink information flow routes becomes important for the survivability of sensor networks. In this work, we address these important design issues using an integrated approach and propose new mixed-integer linear programming models to determine the optimal sink locations and information flow paths between sensors and sinks when sensor locations are given. The first group of proposed models is energy-aware and tries to minimize total routing energy, whereas the second group is financially driven with the objective of minimizing total cost. We do not only report computational results providing information on the solution efficiency of the new formulations, and the accuracy of their linear programming relaxations, but also propose and test new heuristics and lower bounding approaches for the most efficient formulation.
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.
Heuristic Solutions for the Lifetime Problem of Wireless Sensor Networks
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2016
In [5, 7, 8] an analytical model of the lifetime problem of wireless sensor networks is developed. The solution given by the model is not practical for WSNs. Each time, there is a change in a sensor network, the solution needs to be recalculated. Also, it is difficult to build ILP solvers inside the small sensors. Furthermore, when the number of sensor nodes and CHs increases, it quickly becomes infeasible to calculate an optimum solution. As the analytical model is not able to be used to solve complicated networks, heuristic solutions are then examined that can compute the solutions for large sensor networks. Finally, the simulation results of the heuristic solutions are presented and discussed.
Lifetime Optimization of a Multiple Sink Wireless Sensor Network through Energy Balancing
Journal of Sensors, 2015
The wireless sensor network consists of small limited energy sensors which are connected to one or more sinks. The maximum energy consumption takes place in communicating the data from the nodes to the sink. Multiple sink WSN has an edge over the single sink WSN where very less energy is utilized in sending the data to the sink, as the number of hops is reduced. If the energy consumed by a node is balanced between the other nodes, the lifetime of the network is considerably increased. The network lifetime optimization is achieved by restructuring the network by modifying the neighbor nodes of a sink. Only those nodes are connected to a sink which makes the total energy of the sink less than the threshold. This energy balancing through network restructuring optimizes the network lifetime. This paper depicts this fact through simulations done in MATLAB.
Decomposition algorithms for maximizing the lifetime of wireless sensor networks with mobile sinks
Computers & Operations Research, 2012
We address the problem of maximizing the lifetime of a wireless sensor network with energyconstrained sensors and a mobile sink. The sink travels among discrete locations to gather information from all the sensors. Data can be relayed among sensors and then to the sink location, as long as the sensors and the sink are within a certain threshold distance of each other. However, sending information along a data link consumes energy at both the sender and the receiver nodes. A vital problem that arises is to prescribe sink stop durations and data flow patterns that maximally prolong the life of the network, defined as the amount of time until any node exhausts its energy. We describe linear programming and column generation approaches for this problem, and also for a version in which data can be delayed in its transmission to the sink. Our column generation approach exploits special structures of the linear programming formulations so that all subproblems are shortest path problems with non-negative costs. Computational results demonstrate the efficiency of the proposed algorithms.