scholarly journals Towards an Optimal Energy Consumption for Unattended Mobile Sensor Networks through Autonomous Sensor Redeployment

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Jian Chen ◽  
Jie Jia ◽  
Yingyou Wen ◽  
Dazhe Zhao
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Mathematical Problem ◽  
Mobile Sensor Networks ◽  
Sensor Nodes ◽  
Target Area ◽  
Mobile Sensor ◽  
Energy Hole ◽  
Autonomous Sensor ◽  
Optimal Node

Energy hole is an inherent problem caused by heavier traffic loads of sensor nodes nearer the sink because of more frequent data transmission, which is strongly dependent on the topology induced by the sensor deployment. In this paper, we propose an autonomous sensor redeployment algorithm to balance energy consumption and mitigate energy hole for unattended mobile sensor networks. First, with the target area divided into several equal width coronas, we present a mathematical problem modeling sensor node layout as well as transmission pattern to maximize network coverage and reduce communication cost. And then, by calculating the optimal node density for each corona to avoid energy hole, a fully distributed movement algorithm is proposed, which can achieve an optimal distribution quickly only by pushing or pulling its one-hop neighbors. The simulation results demonstrate that our algorithm achieves a much smaller average moving distance and a much longer network lifetime than existing algorithms and can eliminate the energy hole problem effectively.

Graph Intersection-Based Benchmarking Algorithm for Maximum Stability Data Gathering Trees in Wireless Mobile Sensor Networks

2014 ◽  
pp. 433-458
Author(s):  
Natarajan Meghanathan ◽  
Philip Mumford
Keyword(s):  
Sensor Networks ◽  
Spanning Trees ◽  
Data Gathering ◽  
Mobile Sensor Networks ◽  
Sensor Nodes ◽  
Mobile Sensor ◽  
Topology Changes ◽  
Maximum Stability ◽  
Wireless Mobile ◽  
Data Gathering Tree

The authors propose a graph intersection-based benchmarking algorithm to determine the sequence of longest-living stable data gathering trees for wireless mobile sensor networks whose topology changes dynamically with time due to the random movement of the sensor nodes. Referred to as the Maximum Stability-based Data Gathering (Max.Stable-DG) algorithm, the algorithm assumes the availability of complete knowledge of future topology changes and is based on the following greedy principle coupled with the idea of graph intersections: Whenever a new data gathering tree is required at time instant t corresponding to a round of data aggregation, choose the longest-living data gathering tree from time t. The above strategy is repeated for subsequent rounds over the lifetime of the sensor network to obtain the sequence of longest-living stable data gathering trees spanning all the live sensor nodes in the network such that the number of tree discoveries is the global minimum. In addition to theoretically proving the correctness of the Max.Stable-DG algorithm (that it yields the lower bound for the number of discoveries for any network-wide communication topology like spanning trees), the authors also conduct exhaustive simulations to evaluate the performance of the Max.Stable-DG trees and compare to that of the minimum-distance spanning tree-based data gathering trees with respect to metrics such as tree lifetime, delay per round, node lifetime and network lifetime, under both sufficient-energy and energy-constrained scenarios.

scholarly journals Cognitive routing optimization protocol based on multiple channels in wireless sensor networks

2020 ◽  
Vol 16 (4) ◽  
pp. 155014772091451 ◽  
Author(s):  
Shuguang Deng ◽  
Buwen Cao ◽  
Xiang Xiao ◽  
Hua Qin ◽  
Bing Yang
Keyword(s):  
Sensor Networks ◽  
Network Lifetime ◽  
Large Scale ◽  
Mobile Sensor Networks ◽  
Network Throughput ◽  
Sensor Nodes ◽  
Multiple Channels ◽  
Mobile Sensor ◽  
Substantial Impact ◽  
Wireless Mobile

With the development of modern communication, available spectrum resources are becoming increasingly scarce, which reduce network throughput. Moreover, the mobility of nodes results in the changes of network topological structure. Hence, a considerable amount of control information is consumed, which causes a corresponding increase in network power consumption and exerts a substantial impact on network lifetime. To solve the real-time transmission problem in large-scale wireless mobile sensor networks, opportunistic spectrum access is applied to adjust the transmission power of sensor nodes and the transmission velocity of data. A cognitive routing and optimization protocol based on multiple channels with a cross-layer design is proposed to study joint optimal cognitive routing with maximizing network throughput and network lifetime. Experimental results show that the cognitive routing and optimization protocol based on multiple channels achieves low computational complexity, which maximizes network throughput and network lifetime. This protocol can be also effectively applied to large-scale wireless mobile sensor networks.

Location-Based Performance Tuning in Mobile Sensor Networks

2013 ◽  
pp. 30-38 ◽  
Author(s):  
Vladimir I. Zadorozhny
Keyword(s):  
Sensor Networks ◽  
Mobile Sensor Networks ◽  
Sensor Nodes ◽  
Performance Tuning ◽  
Mobile Sensor ◽  
Mobile Nodes ◽  
The Past ◽  
Mission Critical

The author of this chapter considers the location-based approach for performance tuning that significantly facilitates the challenge of utilizing Mobile Sensor Networks. The authors introduce mobile nodes that can be deployed in conjunction with stationary sensor nodes to perform mission critical surveillance and monitoring tasks. It details the past advances in this field and discusses other approaches to this challenge.

scholarly journals On virtual-force algorithms for coverage-optimal node deployment in mobile sensor networks via the two-dimensional Yukawa crystal

2019 ◽  
Vol 15 (9) ◽  
pp. 155014771986488
Author(s):  
Rongxin Tang ◽  
Xin Qian ◽  
Xiangyu Yu
Keyword(s):  
Sensor Networks ◽  
Crystalline Structure ◽  
Pair Correlation ◽  
Minimum Energy ◽  
Mobile Sensor Networks ◽  
Fixed Number ◽  
Sensor Nodes ◽  
Mobile Sensor ◽  
Node Deployment ◽  
Virtual Force

As theoretical proof has shown that a hexagonal topology can obtain maximal coverage with a fixed number of sensor nodes, node deployment for mobile sensor networks has the objective of forming a hexagonal network topology while consuming minimum energy. Using virtual-force algorithms to move initially randomly distributed nodes into a target topology is one of the widely studied methods for achieving this goal. In this work, a novel virtual-force algorithm based on physical laws in a dusty plasma system (i.e. VFA-DP) was applied within a mobile sensor network deployment scenario. The VFA-DP force has a central attracting force which can provide a screening effect via exponential decay. Here, to evaluate how perfect the final grids become from virtual-force algorithms, we introduce a performance metric based on the pair correlation function in a crystalline structure. Via simulation studies, we determined that the topology resulting from the VFA-DP is much closer to a hexagon. The analysis also indicated that the VFA-DP converges faster than another virtual-force algorithm based on the Lennard-Jones potential (VFA-LJ), resulting in lower communication-related energy costs in real deployment scenarios. The method developed in this article is derived from studies of crystalline structure from condensed matter physics and shows clear evidence of when the regular lattice is ready. It will provide some guidance for engineering by aiding deployment in complex geometric areas or those recovering from disaster.

Location-Based Performance Tuning in Mobile Sensor Networks

2010 ◽  
pp. 260-268
Author(s):  
Vladimir I. Zadorozhny
Keyword(s):  
Sensor Networks ◽  
Mobile Sensor Networks ◽  
Sensor Nodes ◽  
Performance Tuning ◽  
Mobile Sensor ◽  
Mobile Nodes ◽  
The Past ◽  
Mission Critical

The author of this chapter considers the location-based approach for performance tuning that significantly facilitates the challenge of utilizing Mobile Sensor Networks. The authors introduce mobile nodes that can be deployed in conjunction with stationary sensor nodes to perform mission critical surveillance and monitoring tasks. It details the past advances in this field and discusses other approaches to this challenge.

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