scholarly journals Speeding Up Exact Algorithms for Maximizing Lifetime of WSNs Using Multiple Cores

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Pengyuan Cao ◽  
Xiaojun Zhu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Exact Algorithms ◽  
Wireless Sensor ◽  
Np Hard ◽  
Desktop Computer ◽  
Exponential Time ◽  
The Third ◽  
Multiple Cores ◽  
Speed Up

Maximizing the lifetime of wireless sensor networks is NP-hard, and existing exact algorithms run in exponential time. These algorithms implicitly use only one CPU core. In this work, we propose to use multiple CPU cores to speed up the computation. The key is to decompose the problem into independent subproblems and then solve them on different cores simultaneously. We propose three decomposition approaches. Two of them are based on the notion that a tree does not contain cycles, and the third is based on the notion that, in any tree, a node has at most one parent. Simulations on an 8-core desktop computer show that our approach can speed up existing algorithms significantly.

scholarly journals Parameterized Algorithms for Power-Efficiently Connecting Wireless Sensor Networks: Theory and Experiments

2021 ◽  
Author(s):  
Matthias Bentert ◽  
René van Bevern ◽  
André Nichterlein ◽  
Rolf Niedermeier ◽  
Pavel V. Smirnov
Keyword(s):  
Communication Network ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Network ◽  
Polynomial Time ◽  
Exact Algorithms ◽  
Wireless Sensor ◽  
Connected Components ◽  
Np Hard ◽  
Transmission Power

We study a problem of energy-efficiently connecting a symmetric wireless communication network: given an n-vertex graph with edge weights, find a connected spanning subgraph of minimum cost, where the cost is determined by each vertex paying the heaviest edge incident to it in the subgraph. The problem is known to be NP-hard. Strengthening this hardness result, we show that even o(log n)-approximating the difference d between the optimal solution cost and a natural lower bound is NP-hard. Moreover, we show that under the exponential time hypothesis, there are no exact algorithms running in 2o(n) time or in [Formula: see text] time for any computable function f. We also show that the special case of connecting c network components with minimum additional cost generally cannot be polynomial-time reduced to instances of size cO(1) unless the polynomial-time hierarchy collapses. On the positive side, we provide an algorithm that reconnects O(log n)-connected components with minimum additional cost in polynomial time. These algorithms are motivated by application scenarios of monitoring areas or where an existing sensor network may fall apart into several connected components because of sensor faults. In experiments, the algorithm outperforms CPLEX with known integer linear programming (ILP) formulations when n is sufficiently large compared with c. Summary of Contribution: Wireless sensor networks are used to monitor air pollution, water pollution, and machine health; in forest fire and landslide detection; and in natural disaster prevention. Sensors in wireless sensor networks are often battery-powered and disposable, so one may be interested in lowering the energy consumption of the sensors in order to achieve a long lifetime of the network. We study the min-power symmetric connectivity problem, which models the task of assigning transmission powers to sensors so as to achieve a connected communication network with minimum total power consumption. The problem is NP-hard. We provide perhaps the first parameterized complexity study of optimal and approximate solutions for the problem. Our algorithms work in polynomial time in the scenario where one has to reconnect a sensor network with n sensors and O(log n)-connected components by means of a minimum transmission power increase or if one can find transmission power lower bounds that already yield a network with O(log n)-connected components. In experiments, we show that, in this scenario, our algorithms outperform previously known exact algorithms based on ILP formulations.

scholarly journals Adaptive Source Location Estimation Based on Compressed Sensing in Wireless Sensor Networks

2012 ◽  
Vol 8 (1) ◽  
pp. 592471 ◽  
Author(s):  
Lei Liu ◽  
Jin-Song Chong ◽  
Xiao-Qing Wang ◽  
Wen Hong
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Compressed Sensing ◽  
Source Parameters ◽  
Location Estimation ◽  
Multiple Source ◽  
Wireless Sensor ◽  
Multiple Sources ◽  
Redundant Dictionary ◽  
Speed Up

Source localization is an important problem in wireless sensor networks (WSNs). An exciting state-of-the-art algorithm for this problem is maximum likelihood (ML), which has sufficient spatial samples and consumes much energy. In this paper, an effective method based on compressed sensing (CS) is proposed for multiple source locations in received signal strength-wireless sensor networks (RSS-WSNs). This algorithm models unknown multiple source positions as a sparse vector by constructing redundant dictionaries. Thus, source parameters, such as source positions and energy, can be estimated by [Formula: see text]-norm minimization. To speed up the algorithm, an effective construction of multiresolution dictionary is introduced. Furthermore, to improve the capacity of resolving two sources that are close to each other, the adaptive dictionary refinement and the optimization of the redundant dictionary arrangement (RDA) are utilized. Compared to ML methods, such as alternating projection, the CS algorithm can improve the resolution of multiple sources and reduce spatial samples of WSNs. The simulations results demonstrate the performance of this algorithm.

The Development of Mobile Wireless Sensor Networks

2015 ◽  
pp. 257-286 ◽  
Author(s):  
Yuenong Zhu ◽  
Kun Hua
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Mobile Networks ◽  
Wireless Sensor ◽  
General Context ◽  
Cross Layer Design ◽  
Mobile Wireless ◽  
Mobile Wireless Sensor Networks ◽  
The Third ◽  
Mobile Wireless Sensor

In this chapter, the authors mainly discuss mobile wireless sensor networks (MWSNs). First, the authors are introduce the evolution of MWSNs from sensor networks to wireless sensor networks, and finally to mobile networks. Second, to provide a general context of MWSNs the authors then compare the peer work of MWSNs in chronological order. The third section discusses typical issues including localization, deployment, resource/energy efficiency and coverage issues. Cross-layer design is considered as one of the most useful ways to improve MWSNs in the future.

scholarly journals Exact algorithms to minimize interference in wireless sensor networks

2011 ◽  
Vol 412 (50) ◽  
pp. 6913-6925 ◽  
Author(s):  
Haisheng Tan ◽  
Tiancheng Lou ◽  
Yuexuan Wang ◽  
Qiang-Sheng Hua ◽  
Francis C.M. Lau
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Exact Algorithms ◽  
Wireless Sensor

Connectivity Estimation Approaches for Internet of Things-Enabled Wireless Sensor Networks

2022 ◽  
pp. 104-122
Author(s):  
Zuleyha Akusta Dagdeviren ◽  
Vahid Akram
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Exact Algorithms ◽  
Estimation Problem ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Estimation Algorithms ◽  
Communication Layer ◽  
Main Ideas

Internet of things (IoT) envisions a network of billions of devices having various hardware and software capabilities communicating through internet infrastructure to achieve common goals. Wireless sensor networks (WSNs) having hundreds or even thousands of sensor nodes are positioned at the communication layer of IoT. In this study, the authors work on the connectivity estimation approaches for IoT-enabled WSNs. They describe the main ideas and explain the operations of connectivity estimation algorithms in this chapter. They categorize the studied algorithms into two divisions as 1-connectivity estimation algorithms (special case for k=1) and k-connectivity estimation algorithms (the generalized version of the connectivity estimation problem). Within the scope of 1-connectivity estimation algorithms, they dissect the exact algorithms for bridge and cut vertex detection. They investigate various algorithmic ideas for k connectivity estimation approaches by illustrating their operations on sample networks. They also discuss possible future studies related to the connectivity estimation problem in IoT.

The Development of Mobile Wireless Sensor Networks

2016 ◽  
pp. 365-394
Author(s):  
Yuenong Zhu ◽  
Kun Hua
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Mobile Networks ◽  
Wireless Sensor ◽  
General Context ◽  
Cross Layer Design ◽  
Mobile Wireless ◽  
Mobile Wireless Sensor Networks ◽  
The Third ◽  
Mobile Wireless Sensor

In this chapter, the authors mainly discuss mobile wireless sensor networks (MWSNs). First, the authors are introduce the evolution of MWSNs from sensor networks to wireless sensor networks, and finally to mobile networks. Second, to provide a general context of MWSNs the authors then compare the peer work of MWSNs in chronological order. The third section discusses typical issues including localization, deployment, resource/energy efficiency and coverage issues. Cross-layer design is considered as one of the most useful ways to improve MWSNs in the future.

scholarly journals Secure and Efficient Three-Factor Protocol for Wireless Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4481 ◽  
Author(s):  
Jihyeon Ryu ◽  
Hakjun Lee ◽  
Hyoungshick Kim ◽  
Dongho Won
Keyword(s):  
Health Care ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Security Analysis ◽  
Security Protocols ◽  
User Anonymity ◽  
Wireless Sensor ◽  
Speed Up ◽  
Inherent Nature ◽  
Three Factor

Wireless sensor networks are widely used in many applications such as environmental monitoring, health care, smart grid and surveillance. Many security protocols have been proposed and intensively studied due to the inherent nature of wireless networks. In particular, Wu et al. proposed a promising authentication scheme which is sufficiently robust against various attacks. However, according to our analysis, Wu et al.’s scheme has two serious security weaknesses against malicious outsiders. First, their scheme can lead to user impersonation attacks. Second, user anonymity is not preserved in their scheme. In this paper, we present these vulnerabilities of Wu et al.’s scheme in detail. We also propose a new scheme to complement their weaknesses. We improve and speed up the vulnerability of the Wu et al. scheme. Security analysis is analyzed by Proverif and informal analysis is performed for various attacks.

scholarly journals The Application of Improved Sparrow Search Algorithm in Sensor Networks Coverage Optimization of Bridge Monitoring

2020 ◽  
Author(s):  
Yueqi Peng ◽  
Yunqing Liu ◽  
Qi Li
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Initial Population ◽  
Bridge Monitoring ◽  
Speed Up ◽  
Point Set

Aiming at the uneven random coverage distribution of wireless sensor networks sensor nodes, the sparrow search algorithm (SSA) is used to optimize the node coverage of wireless sensor networks. To improve the global search capability of SSA, the algorithm is improved and applied to the wireless sensor networks of bridge monitoring. For enhancing the coverage of the wireless sensor networks, this article uses two improved methods. One is to use the good point set theory to make the initial population evenly distributed; another is to introduce a weight factor to speed up its convergence. The experiments have proved the reliability and rationality of the algorithm. The improved algorithm is superior to other meta-heuristic algorithms and provides a new idea for optimizing bridge monitoring wireless sensor networks coverage.

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