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The increasingly wide utilization of Wireless Sensor Networks (WSNs) in industrial applications outstands the significance of the Delay Constrained Relay Node Placement (DCRNP) problem. Existing algorithms to the DCRNP problem are designed based on the ideal geometric disk wireless channel model, and no real-world deployments are performed to verify the effectiveness of these algorithms. However, the unreliable and unpredictable wireless links in WSNs may lead these algorithms to fail in practice. Therefore, we first conduct extensive real-world deployments under the guidance of existing algorithms to evaluate their performance and to gain some insights for designing practical deployment algorithms. The results exhibit that the WSNs built by existing algorithms have a favorable performance in end-to-end delay but a poor performance in reliability, which is mainly due to the lack of methods ensuring high-quality links. To this end, we first devise a Set-Covering-based Algorithm (SCA) which figures out the DCRNP problem while ensuring the quality of each link better than a given threshold. As our experiments also show that the fault-tolerant topology can significantly improve network reliability, we then design a $k$ k -Set-Covering-based Algorithm ($k$ k SCA) to build fault-tolerant WSNs based on the methodology of SCA. Furthermore, the elaborate analysis proves that both SCA and $k$ k SCA are polynomial-time algorithms, and their approximation ratios are both O($\ln n$ ln n ), where $n$ n is the number of sensor nodes. Finally, extensive experiments are performed under the guidance of SCA and $k$ k SCA to demonstrate the effectiveness of these two algorithms. [ABSTRACT FROM AUTHOR]

Wireless sensor networks are gradually employed in many applications that require reliable and real-time data transmission. As hop count is an important factor affecting end-to-end delay and reliability, we investigate the hop constrained relay node placement (HCRNP) problem in this paper. First, to achieve connectivity requirement, we study the connected HCRNP problem. Then, to design survivable network topologies against node failures, we study the 2-connected HCRNP problem. Correspondingly, two polynomial-time algorithms: cover-based 1-connected node placement (C1NP) and cover-based 2-connected node placement (C2NP) are proposed, respectively, to address the above two problems. Through rigorous analysis, we show that 1) C1NP has an approximation ratio better than existing algorithms for the connected HCRNP problem (i.e., O(1) for special settings and O($\ln n$) for arbitrary settings, where $n$ is the number of SNs) and 2) C2NP is the first algorithm that can provide an explicit performance guarantee for the 2-connected HCRNP problem, i.e., whenever C2NP finds a feasible solution, the ratio of this solution to the optimal solution is guaranteed to be O($\ln n$). Finally, we verify the effectiveness of the proposed algorithms through extensive simulations. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSNs) are applied in many time-critical applications, e.g., industrial automation and smart grid. This highlights the importance of Delay Constrained Relay Node Placement (DCRNP) problem that builds a path fulfilling a specified delay constraint between each sensor and the sink by using a minimum number of relays. Due to the NP-hardness of the DCRNP problem, in this paper, a polynomial time Subtree-and-Mergence-based Algorithm (SMA) is proposed to approximately solve the DCRNP problem. First, a shortest path tree rooted at the sink and connecting all sensors is built to check the feasibility of the DCRNP problem. If the DCRNP problem is feasible, then the paths of this tree are progressively merged at some relays, which are not limited to those relays lying in the originally the originally built shortest path tree, to save deployed relays while maintaining the obedience of delay constraints. With the repetition of this mergence, the number of deployed relays is gradually reduced. Furthermore, the approximation ratio and the time complexity of the proposed SMA are elaborately analyzed. Finally, extensive simulations are conducted to demonstrate the effectiveness of this work. Simulation results show that SMA can significantly save deployed relays comparing with existing algorithms. [ABSTRACT FROM AUTHOR]

In two-tiered wireless sensor networks (WSNs), relay node placement is one of the key factors impacting the network energy consumption and the system overhead. In this paper, a novel connectivity-aware approximation algorithm for relay node placement in the WSNs is proposed to offer a major step forward in saving system overhead. In particular, a unique local search approximation algorithm (LSAA) is introduced to solve the relay node single cover (RNSC) problem. In this proposed LSAA approach, the sensor nodes are allocated into groups and then a local set cover (SC) for each group is achieved by a local search algorithm. The union set of all the local SCs constitutes a SC of the RNSC problem. The approximation ratio and the time complexity of the LSAA are analyzed by rigorous proof. In addition, the LSAA approach has been extended to solve the relay node double cover problem. Then, a relay location selection algorithm (RLSA) is proposed to utilize the resulting SC from the LSAA in combining RLSA with the minimum spanning tree heuristic to build the high-tier connectivity. As the RLSA searches for a nearest location to the sink node for each relay node, the high-tier network built by the RLSA becomes denser than that by existing works. As a result, the number of added relay nodes for building the connectivity of the high-tier WSN can be significantly saved. Simulation results clearly demonstrate that the proposed LSAA outperforms the approaches reported in literature and the RLSA-based algorithm can noticeably save relay nodes newly deployed for the high-tier connectivity. [ABSTRACT FROM PUBLISHER]