Energy Balanced Model for Lifetime Maximization in Randomly Distributed Wireless Sensor Networks

Dohare, Upasana; Lobiyal, D. K.; Kumar, Sushil

doi:10.1007/s11277-014-1759-2

Cited by 23 publications

(11 citation statements)

References 19 publications

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“…A solution of the MLB problem (11), when the data is broadcasted by the k-th node, will be given by an optimal set of trees fT k;r g , which satisfy (10) and minimize the objective function (4). The following lemma describes relation between the local minima of the objective function (4) and global solutions of (11).…”

Section: Definition Of the Problemmentioning

confidence: 99%

“…Proof We reduce the partition problem to the MLB problem (11). To solve the MLB problem in Z þ 0 we must find the set of integer numbers fq k r g r2½1;N NÀ2 for all trees from G T k , satisfying the constraint P r q k r ¼ Q k and which minimizes the objective function (4).…”

Section: Lemmamentioning

confidence: 99%

“…The solution of the maximum lifetime broadcasting problem (11), with the data cost energy matrix of the form (12), when the data is broadcasted by the k-th node, k 2 ½2; N À 1, is an equal energy solution and it is given by the N transmission trees T r , r 2 ½1; N …”

Section: Theoremmentioning

confidence: 99%

“…Namely, if each node of the network has a battery with the initial energy E 0 , then by finding the optimal energy utilization of each node in one cycle of network lifetime E opt i we can determine the number of cycles N cycles ¼ ½ E 0 E opt i 0 the network can perform its functions until the most overloaded node i 0 runs out of its energy. Various aspects of the lifetime problem in wireless sensor networks were discussed in the literature [6][7][8][9][10][11][12]. In [6] the maximum lifetime broadcasting problem in sensor networks with mobile nodes was analyzed.…”

Section: Introductionmentioning

confidence: 99%

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Routing Algorithm for Maximizing Lifetime of Wireless Sensor Network for Broadcast Transmission

Lipiński

2018

Wireless Pers Commun

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In the article we discuss solutions of the maximum lifetime broadcasting problem in wireless sensor networks. Due to limited energy resources of the network nodes to find an optimal transmission route of the broadcasted data we minimize the maximum energy consumed by the nodes. We give an analytical solution of the problem in one dimensional regular sensor network for the point-to-point and point-to-multipoint data transmission scheme. We show that in such a network, when the cost of data transmission is a polynomial function of distance between transmitter and receiver, there exist solutions with an equal energy, i.e., all nodes of the network consume the same amount of energy. We assume that in the networks with sensors evenly distributed over some d-dimensional area there always exists an equal energy solution of the problem. To solve the maximum lifetime broadcasting problem in such networks we propose two algorithms. By means of the first algorithm the set of minimum node weight spanning trees in a given network is determined. The second algorithm allows to balance the energy consumption of the sensors for data transmitted along given minimum node weight spanning tree. We show, that the proposed algorithms find an approximate solution of the discussed problem in polynomial time.

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Section: Definition Of the Problemmentioning

confidence: 99%

Section: Lemmamentioning

confidence: 99%

Section: Theoremmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Routing Algorithm for Maximizing Lifetime of Wireless Sensor Network for Broadcast Transmission

Lipiński

2018

Wireless Pers Commun

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“…Another relevant WSN dynamic management strategy is the load balancing. Works commonly face the load balancing in this domain as a problem of communication among nodes, presenting methods to better routing the data traffic through the network [13][14][15][16]. It happens because they consider that the network senses the environment in a proactive way, which means that all nodes have the same tasks to process.…”

Section: Load Balancingmentioning

confidence: 99%

Efficiency Evaluation of Strategies for Dynamic Management of Wireless Sensor Networks

Gonzalez

Brisolara

Ferreira

2017

Wireless Communications and Mobile Computing

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This paper presents and evaluates dynamic management strategies to improve efficiency in event-triggered wireless sensor networks. We are considering mobility, where nodes move themselves to maximize the coverage, and load balancing state-of-the-art techniques, by which the number of nodes sensing the same area is reduced. To explore mobility, we present a simple method by which nodes can dynamically reorganize themselves based on the force fields approach of mobile robotics. Firstly, the strategies are evaluated separately through experiments with different network configurations and, afterwards, a joint evaluation has been conducted to observe the impact of mobility on the efficiency of load balancing techniques. We show that mobile nodes significantly contribute to keeping the coverage as nodes die in mesh and powerfully improving it in random deployments. Load balancing techniques achieve important results, increasing lifetime and the number of sensed events. However, in random deployments, these techniques lose efficiency and become unsuitable strategies. Combining these strategies with mobility, we observe that PS-based technique keeps its contribution in mesh and random deployments, as well as improving its performance for not so dense networks. Ant-based technique when combined with mobile nodes loses performance significantly in mesh and keeps its good performance in random deployed and less dense networks.

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Energy-Efficient Superframe Scheduling in Industrial Wireless Networked Control System

Chung

Ibrahim

Hussin

et al. 2020

Lecture Notes in Electrical Engineering

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Energy Balanced Model for Lifetime Maximization in Randomly Distributed Wireless Sensor Networks

Cited by 23 publications

References 19 publications

Routing Algorithm for Maximizing Lifetime of Wireless Sensor Network for Broadcast Transmission

Routing Algorithm for Maximizing Lifetime of Wireless Sensor Network for Broadcast Transmission

Efficiency Evaluation of Strategies for Dynamic Management of Wireless Sensor Networks

Energy-Efficient Superframe Scheduling in Industrial Wireless Networked Control System

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