Bi-adjusting duty cycle for green communications in wireless sensor networks

Abstract

Green communications is a challenging issue for communications and networking. In order to save energy, nodes of the wireless sensor networks (WSNs) usually adopt the low duty cycle mode which brings a large delay to the event detection and data transmission to the sink and deteriorates the network's timely processing of the event. In this paper, bi-adjusting duty cycle schedule (BADCS) scheme is proposed to reduce event detection latency as well as data routing delay for low duty cycle wireless sensor networks. BADCS scheme consists mainly of two duty cycle adjustment algorithms: (a) active slot asynchronous adjustment algorithm for nodes in the same sensing area; (b) the continuous adjustment algorithm for two adjacent nodes on the routing path with one active slot interval. Specifically, the operations are 2-fold. First, perform asynchronous operations on the active slots of the nodes in the same sensing area, so that the active slots of the nodes in the same sensing area are distributed as evenly as possible without overlapping. In this way, it is possible to reduce the latency by the time the event is perceived after its occurrence. Secondly, active slots of the nodes on the routing path are adjusted to be with pipeline style, so that when the nodes receive the data packet, they can route through the continuous active slots, thus greatly reducing the delay of data routing. Two adjustment algorithms of active slot are given in detail in this paper. The performance of BADCS mode is discussed in detail, and its performance is better than the previous strategy. Comprehensive experiments are conducted, and the results demonstrate that the proposed BADCS scheme significantly improves event detection performance in terms of detection latency, detection probability, and routing delay. Detection delay and routing delay are reduced as high as 3.91% and 56.22% respectively.

An Efficient Data Aggregation Scheme Based on Differentiated Threshold Configuring Joint Optimal Relay Selection in WSNs

“…With the development of artificial intelligence technology, more potential value can be obtained from a large amount of data, which promotes the widespread application of IoT devices [31], [32]. However, data collection in WSNs is not an easy task, and many factors affect the performance of data collection [13], [16]. In addition to the common security attacks in data collection, the energy consumption and delay in the data collection process are the most important issues in data collection [40].…”

“…Because sensor nodes are powered by batteries, due to economic cost and volume constraints, the batteries are not very large, and their power is limited [22]. In general, sensor nodes are difficult to replace and recharge once deployed [13], [16]. Therefore, how to be energy efficient in various applications of WSNs is an important research issue [22], [24], [26].…”

Parameter analysis and optimization of polling-based medium access control protocol for multi-sensor communication

“…With the development of microprocessor technology, the volume of sensor devices has become smaller while their functions are more powerful. 31,32 The computing ability of current mobile phones has surpassed that of personal computers 10 years ago. Massive devices connected to the IoT have caused huge changes in the current network architecture.…”

Fast Multicast With Adjusting Transmission Power and Active Slots in Software Define IoT

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“…Therefore, in such applications, the network has two flows, one is data flow, and its flow direction is from sensor devices to data collection centers (such as sinks or other mobile vehicles, etc.) [57], [58]. In data collection, it can be directly connected to the Internet through the sink node like the traditional network, or it can be collected through mobile vehicles like the opportunistic routing method proposed by Bonola et al [47].…”