Distributed connectivity restoration in multichannel wireless sensor networks

The single-channel wireless sensor networks (WSNs) exists the problem of low efficiency of monitoring data transmission, however the multi-channel WSNs exists the problem of communication collision caused by the sensor node’s wireless channel competition. The paper at first introduces the causes of the above problems and selects a reasonable wireless channel resources allocation method of the multi-channel WSNs. Then to solve these questions, the theory of compressive sensing and spectrum sensing are adopted to improve the existing multi-channel WSNs. Finally, a new sensor node of the multi-channel WSNs is designed based on the above improvement. By analyzing the monitoring data of the field test, the improved multi-channel WSNs could complete monitoring mission efficiently and accurately, meanwhile it reduced power consumption of the WSNs effectively.

Fault tolerance is one of the most important requirements in the Wireless Sensors Networks (WSNs). In fact, the performance and the reliability of a RCSF degrade because of several factors. On one hand, the interferences between simultaneous transmissions generate infinite phenomena of collision / retransmission. On the other hand, the failure of some components of the network may introduce the failure of the whole network. In this fact, the integration of the mechanisms which prevent or reduce the impacts of these two problems (interferences and failures) becomes an obligation. In this work, we propose the Connectivity Restoration for wireless sensor networks in Routing based Multi-Channel Context approach (CR-RMC) to improve the WSN reliability. This solution uses multi-channel communications to reduce the interference ratio, as well as network reorganization to recover from a critical node and restore the connectivity. We evaluate the obtained results regarding the fixed objectives.

We develop a novel collision-free channel assignment and scheduling mechanism (CFCS) for multichannel wireless sensor networks. Firstly, each node is assigned with a quiescent channel to reduce hidden terminal beforehand and then it makes channel adjustment according to dynamic traffic. Secondly, a scalable multichannel scheduling is designed to make a tradeoff between overhead and fairness. We have implemented simulation to evaluate the performance of CFCS by comparing with other relevant protocols. The results show that our protocol exhibits more prominent ability, which utilizes multichannel to make parallel transmission and reduce hidden terminal problems effectively in resource-constrained wireless sensor networks.

Wireless Sensor Network (WSN) is one of the active research topics in the field of computer network since it provides three types of basic services: sensing, processing, and disseminating. Ad-hoc and multi-hop WSNs are commonly used in many applications; therefore, maintaining stability of WSN is an essential issue in present days. However, node failures are not exceptions in WSN. Many factors may cause sensor nodes to fail, such as energy exhaustion, out of communication range, or node module damage. These damages are usual incidents in practical WSN applications. Except node module damages that we are unable to look after, we propose an energy-efficient routing algorithm to prolong the lifetime of nodes in WSN. Another feature of the proposed algorithm is that each node routes network packets independently throughout the entire WSN. It makes that algorithm to provide autonomic management of the links in WSN.

This survey covers schedulability analysis approaches that have been recently proposed for multi-hop and multi-channel wireless sensor and actuator networks in the industrial control process domain. It reviews results with a focus on WirelessHART-like networks. The paper address the mapping of multi-channel transmission scheduling to multiprocessor scheduling theory, and recognize it as the key aspect of the research direction covered by this survey. It also provides a taxonomy of the existing approaches concerning this direction, and discuss its main features and evolution. The survey identifies open issues, key research challenges, and future directions.

In wireless sensor networks, MAC protocol is used to achieve efficient, fair and balanced allocation of wireless channel resources and access control of nodes in the network, and to control the communication process of nodes in the network. The energy consumption of wireless sensor nodes is mainly concentrated in the communication unit, including: data transceiver, idle listening, protocol control overhead, etc. A good MAC protocol is beneficial to reduce unnecessary energy consumption and enhance node life time. At the same time, MAC protocol, as the bottom protocol of wireless sensor network, provides a stable and reliable communication foundation for the realization of the upper protocol. Therefore, a large number of scholars at home and abroad have carried out extensive and in-depth research on MAC layer protocol of network. In this paper, the research process and progress of MAC layer protocol in wireless sensor networks are analyzed, and the research progress of MAC layer protocol in multi-radio frequency and multi-channel wireless sensor networks is analyzed.

Node failures are inevitable in wireless sensor networks (WSNs) because sensor nodes in WSNs are miniature and equipped with small and often irreplaceable batteries. Due to battery drainage, sensor nodes can fail at any instance. Moreover, WSNs operate in hostile environments and environmental factors may also contribute to nodes failure. Failure of nodes leads to disruption of inter-node connectivity and might also lead to network partitioning. Failure to communicate with each other and with the base station can compromise the basic operation of the sensor network. For restoration of connectivity, a robust recovery mechanism is required. The existing connectivity restoration mechanisms suffer from shortcomings because they do not focus on energy-efficient operation and coverage-aware mechanisms while performing connectivity restoration. As a result, most of these mechanisms lead to the excessive mobility of nodes, which itself causes the utilization of excessive battery. In this work, we propose a novel technique called smart node relocation (SNR). SNR is capable of detecting and restoring the connectivity caused by either single or multiple node failures. For achieving energy efficiency, SNR relies on transmitting a lesser number of control packets. For achieving the goal of being coverage-aware, it tries to relocate only essential nodes while trying to restore connectivity. By performing extensive simulations, we prove that SNR outperforms the existing approaches concerning multiple performance metrics including but not limited to the total number of packets transmitted, total distance moved for connectivity restoration, the percentage reduction in field coverage.

In this paper we propose a routing protocol with integrated routing metric for multi-channel wireless sensor networks. We improve the existing multi-channel AODV protocol to adapt to multi-channel wireless sensor networks. We consider link cost and the delivery cost of remaining energy in route selection. The simulation results show that, we can increase the network lifetime using the integrated routing metric.

Wireless sensor networks(WSNs) have many applications in recent years, especially in some harsh environment, such as battlefield reconnaissance. WSNs may suffer from a large scale damage which causes many nodes to fail and the network to get partitioned into disjoint segments. So in order to avoid negative effects on the application, restoring network connectivity is crucial in such case. In this paper, we study connectivity restoration of wireless sensor networks (WSNs), analyze and summarize the related main direction and the research results in recent years, and classify connectivity restoration solution of WSN, point out the deficiency and future research direction.

This article investigates the high-reliable data transmission for multihop and multichannel wireless sensor networks (WSNs), which jointly optimizes the channel allocation and channel access mechanisms. We propose a novel wireless paradigm empowered by mobile-edge computing (MEC) and deep reinforcement learning (DRL) to improve the data process ability of WSNs and formulate the joint resource allocation problem for reliability maximization as a partially observable Markov decision process (POMDP). Meanwhile, we introduce the distributed decision-making (DDM) framework to decouple channel optimization into two subproblems: 1) channel allocation and 2) channel access. Correspondingly, we present an asynchronous channel allocation algorithm for multiagent scenario and enable the neighbor cooperation to tackle the nonstationary problem, which can significantly improve the network convergence speed. Besides, we present a collision-free channel access algorithm including three submodules that can simultaneously eliminate vanishing nodes, hidden terminal, and exposed terminal problems in large-scale WSNs. Simulation results demonstrate that the proposed algorithm significantly improves network performance in terms of convergence, throughput, collision, and packet delivery ratio (PDR).

Recently, there is a growing interest in the applications of wireless sensor networks (WSNs). A set of sensor nodes is deployed in order to collectively survey an area of interest and/or perform specific surveillance tasks in some of the applications, such as battlefield reconnaissance. Due to the harsh deployment environments and limited energy supply, nodes may fail, which impacts the connectivity of the whole network. Since a single node failure (cut-vertex) will destroy the connectivity and divide the network into disjoint blocks, most of the existing studies focus on the problem of single node failure. However, the failure of multiple nodes would be a disaster to the whole network and must be repaired effectively. Only few studies are proposed to handle the problem of multiple cut-vertex failures, which is a special case of multiple node failures. Therefore, this paper proposes a comprehensive solution to address the problems of node failure (single and multiple). Collaborative Single Node Failure Restoration algorithm (CSFR) is presented to solve the problem of single node failure only with cooperative communication, but CSFR-M, which is the extension of CSFR, handles the single node failure problem more effectively with node motion. Moreover, Collaborative Connectivity Restoration Algorithm (CCRA) is proposed on the basis of cooperative communication and node maneuverability to restore network connectivity after multiple nodes fail. CSFR-M and CCRA are reactive methods that initiate the connectivity restoration after detecting the node failure(s). In order to further minimize the energy dissipation, CCRA opts to simplify the recovery process by gridding. Moreover, the distance that an individual node needs to travel during recovery is reduced by choosing the nearest suitable candidates. Finally, extensive simulations validate the performance of CSFR, CSFR-M and CCRA.

Due to high data traffic and resource-constrained nature of the wireless sensor network (WSN), congestion occurs which leads to severe packet loss and high energy consumption. Since an efficient route discovery procedure can avoid congestion and balance the traffic load, a reliable congestion-aware routing is important and requires careful design consideration. In this paper, a novel route discovery procedure for congestion avoidance (RDCA) in multi-hop WSNs has been proposed. RDCA is based on an objective function that incorporates the implicit behaviour of traffic load and consumed energy of the sensor nodes and signal strength between them along with the hop count. The results show that RDCA has a significant impact over energy, traffic load, and link quality aware ad hoc routing (ETLAODV) and energy efficient and QoS based routing (EQSR) in terms of packet delivery ratio (PDR), end-to-end (ETE) delay, energy consumption, and throughput.

In this paper, we present a class of cooperative beamforming algorithms for information relaying in wireless multihop sensor networks. We focus on networks whereby the source is communicating to the destination via a set of multihop relay nodes organized via hierarchical clustering. In particular, at each hop, a set of clusters are formed using a number of relay nodes where for each cluster, the relay nodes employ two different relaying strategies: i) amplify-and-forward via beamforming, ii) decode-and-forward via beamforming. For both strategies, we present algorithms that systematically select the beamforming weights for the relays at each cluster that optimize the uncoded bit error rates at the destination.

Packet dropping and modification are common attacks that can be launched by an adversary to disrupt communication in wireless multihop sensor networks. Many schemes have been proposed to mitigate or tolerate such attacks, but very few can effectively and efficiently identify the intruders. To address this problem, we propose a simple yet effective scheme, which can identify misbehaving forwarders that drop or modify packets. Extensive analysis and simulations have been conducted to verify the effectiveness and efficiency of the scheme.

In this study, the authors present an energy-efficient data compression protocol for data collection in wireless sensor networks (WSNs). WSNs are essentially constrained by motes’ limited battery power and networks bandwidth. The authors focus on data compression algorithms and protocol development to effectively support data compression for data gathering in WSNs. Their design of compressed data-stream protocol (CDP) is generic in the sense that other lossless or lossy compression algorithms can be easily ‘plugged’ into the proposed protocol system without any changes to the rest of the CDP. This design intends to support various different WSN applications where users may prefer more specific compression algorithms, tailored to the sensing data characteristics in question, to their general algorithm. CDP is not only able to significantly reduce energy consumptions of data gathering in multi-hop WSNs, but also able to reduce sensor network traffic and thus avoid congestion accordingly. The proposed CDP is implemented on the tinyOS platform using the nesC programming language. To evaluate their work, the authors conduct simulations via TOSSIM and PowerTOSSIM-z with real-world sensor data. The results demonstrate the significance of CDP.