Efficient collection of sensor data via a new accelerated random walk

Angelopoulos, Constantinos Marios; Nikoletseas, Sotiris; Patroumpa, Dimitra; Raptopoulos, Christoforos

doi:10.1002/cpe.3108

Cited by 5 publications

(5 citation statements)

References 22 publications

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“…To illustrate the effectiveness and performance of the proposed MSPO-ABC algorithm, we test and compare its performance with a number of competing clustering design protocols, namely, Rendezvous-based Data Collection algorithm (RDCA) [35] and Indegree-based Path Design for Mobile Sink algorithm (IPDMS) [36]. The parameter values for these approaches are selected in accordance with the values specified in [15] and [31], and the following simulation parameters are used in Table 1.…”

Section: Results and Analysismentioning

confidence: 99%

“…In [14], a novel swarm Intelligence-based sensor selection algorithm is presented to meets predefined quality of service (QoS) constraint with uncontrollable sink's mobility. In [15], a random geometric graphs (RGG) model is introduced to deal with spatial proximity for wireless sensor network, and conduct the random walk with inertia to traverse distant neighbor nodes towards reducing area overlap as well as accelerate the coverage time.…”

Section: Related Workmentioning

confidence: 99%

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Mobile Sink-Based Path Optimization Strategy in Wireless Sensor Networks Using Artificial Bee Colony Algorithm

Sun

Pan

2019

IEEE Access

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In traditional static wireless sensor networks (WSNs), the unbalanced communication overhead in different regions will result in premature death of some monitoring nodes. The introduction of mobile sink in WSNs can not only balance the node traffic load, but also obtain even energy consumption of nodes, thus effectively avoiding the ''hot spot'' problem and prolonging the network lifetime. However, the mobility of the sink will lead to frequent changes in the aspect of network topology, which can aggravate the overhead of the node's reorganization in hierarchical WSNs. Therefore, it is essential to obtain the optimal trajectory design of the mobile sink so as to improve the ability of data gathering. In this paper, a mobile sink-based path optimization strategy in WSNs using artificial bee colony algorithm is proposed. First, the problem of overall energy consumption in the network can be transformed into the minimization of the total hops between all subnodes and the rendezvous points of the mobile sink. The objective function and the constraint criterion should be established. Second, an improved artificial bee colony algorithm is proposed to solve the problem. On the one hand, the cumulative factor is introduced to the position update of the employed bee stage to speed up the convergence of the algorithm. On the other hand, the Cauchy mutation operator is presented to increase the diversity of the feasible solution and enhance the global search ability of the algorithm. The simulation results show that the proposed algorithm is better than the traditional methods in the aspects of energy efficiency and the real-time performance of data collection.INDEX TERMS Wireless sensor networks, mobile sink, path optimization, artificial bee colony algorithm.

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Section: Results and Analysismentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Mobile Sink-Based Path Optimization Strategy in Wireless Sensor Networks Using Artificial Bee Colony Algorithm

Sun

Pan

2019

IEEE Access

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“…Experiments show that this method can improve the data collection rate and energy efficiency of the network. Angelopoulos et al 12 used random geometric graph model to better capture the geometric proximity of WSNs and proposed a gstretched random movement strategy which favors traversing far neighbor nodes to reduce area overlap and accelerate coverage time. Zhang et al 13 presented a compressed sensing data acquisition strategy based on ring topology.…”

Section: Related Workmentioning

confidence: 99%

Evolutionary game–based trajectory design algorithm for mobile sink in wireless sensor networks

Gong

Panpan

Chen

et al. 2020

International Journal of Distributed Sensor Networks

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In wireless sensor networks, if sink node is stationary, the nodes close to sink will deplete energy faster than those in other areas. The unbalanced energy consumption among the nodes will lead to the energy hole problem, which shortens the network lifetime. To solve the problem, evolutionary game–based trajectory design algorithm for mobile sink in wireless sensor networks is proposed in this article. In evolutionary game model, the average residual energy of each cluster, average intra-cluster energy consumption, and average inter-cluster energy consumption are used to design utility function. The sink will select the cluster with more utility value as its new location and move to the cluster head which has the largest residual energy and the shortest distance to other cluster heads. The simulation results show that the algorithm can effectively balance network load, reduce network energy consumption, prolong the network lifetime, and increase the number of data packets that sink receives.

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“…Collecting the gathered information efficiently is a key issue for wireless sensor networks. A great deal of work has been devoted to this field [16,17,18,19,20,21]. Li et al [22] studied the time complexity, message complexity, and energy cost complexity of some data collection, data aggregation, and queries for a multi-hop wireless sensor network of n nodes.…”

Section: Related Workmentioning

confidence: 99%

A Delay-Aware and Reliable Data Aggregation for Cyber-Physical Sensing

Zhang

Long

Zhang

et al. 2017

Sensors

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Physical information sensed by various sensors in a cyber-physical system should be collected for further operation. In many applications, data aggregation should take reliability and delay into consideration. To address these problems, a novel Tiered Structure Routing-based Delay-Aware and Reliable Data Aggregation scheme named TSR-DARDA for spherical physical objects is proposed. By dividing the spherical network constructed by dispersed sensor nodes into circular tiers with specifically designed widths and cells, TSTR-DARDA tries to enable as many nodes as possible to transmit data simultaneously. In order to ensure transmission reliability, lost packets are retransmitted. Moreover, to minimize the latency while maintaining reliability for data collection, in-network aggregation and broadcast techniques are adopted to deal with the transmission between data collecting nodes in the outer layer and their parent data collecting nodes in the inner layer. Thus, the optimization problem is transformed to minimize the delay under reliability constraints by controlling the system parameters. To demonstrate the effectiveness of the proposed scheme, we have conducted extensive theoretical analysis and comparisons to evaluate the performance of TSR-DARDA. The analysis and simulations show that TSR-DARDA leads to lower delay with reliability satisfaction.

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Efficient collection of sensor data via a new accelerated random walk

Cited by 5 publications

References 22 publications

Mobile Sink-Based Path Optimization Strategy in Wireless Sensor Networks Using Artificial Bee Colony Algorithm

Mobile Sink-Based Path Optimization Strategy in Wireless Sensor Networks Using Artificial Bee Colony Algorithm

Evolutionary game–based trajectory design algorithm for mobile sink in wireless sensor networks

A Delay-Aware and Reliable Data Aggregation for Cyber-Physical Sensing

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