A Cross-Layer Optimized Opportunistic Routing Scheme for Loss-and-Delay Sensitive WSNs

Wang

et al. 2019

J Wireless Com Network

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Data collection is the basic functions of the Internet of Things (IoT), in which the sensed data are concentrations from sensor nodes to the sink, with a timely style, so the smart response can be done for emergency. The goal of multi-modal sensor data fusion is to obtain simple and accurate data to enhance system reliability and fault tolerance. Energy efficiency and small delay are the most important indicators which govern the performance of IoT. Convergecast is a low-latency data collection strategy based on effective time division multiple access (TDMA), in which each sensor node generates a packet, and m packets can aggregate to a packet. However, in most practical networks, sensor nodes do not necessarily generate packets during each data collection cycle, but instead generate packets from time to time. In the previous convergecast strategy, each node was fixedly allocated a slot, which increased the delay and wasted energy. A delay and energy-efficient data collection (DEEDC) scheme-based matrix filling theory is proposed to collect data in a randomly generated WSNs with minimum delay and energy consumption. The DEEDC scheme uses a clustering approach. For each cluster, the number of slots required for transmission is calculated by matrix filling theory, not the number of nodes that actually generate data. This ensures that data can be collected in a network with randomly generated data (number of slots ≤ number of nodes), thereby avoiding the allocation of slots for each node and the acquisition of redundant data to lead to the wastage of time and energy. Based on the above, a mixed slot scheduling strategy is proposed to construct energy and delay-efficient, collision-free schedule scheme. After extensive theoretical analysis, by using the DEEDC scheme, the delay is reduced by about 50~80%, and the energy consumed is reduced by about 40~57%.

Section: Existing Research Related To Energy Consumptionmentioning

confidence: 99%

Delay and energy-efficient data collection scheme-based matrix filling theory for dynamic traffic IoT

Xiang

Wang

et al. 2019

J Wireless Com Network

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“…Opportunity routing (OR) scheme 19,41,42 is another routing protocol that takes full advantage of the broadcast function of wireless channels to guarantee transmission reliability. The OR scheme has changed the one-to-one data transmission mode in traditional data transmission.…”

Section: Introductionmentioning

confidence: 99%

Adaptive duty cycle control–based opportunistic routing scheme to reduce delay in cyber physical systems

Xiang

International Journal of Distributed Sensor Networks

et al. 2019

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Wireless sensor networks are the foundation of cyber physical systems. In loss and delay sensitive wireless sensor networks, there is much room for improving the performance of opportunistic routing scheme. In this article, an adaptive duty cycle control-based opportunistic routing scheme was put forward to improve the performance of the opportunistic routing scheme. Our main work is as follows: (a) the proposed duty cycle control-based opportunistic routing scheme implements the opportunistic routing in the duty cycle-based wireless sensor networks. Compared with the opportunistic routing scheme in the non-duty cycle mode, the duty cycle control-based opportunistic routing scheme can effectively reduce the energy consumption by 55.64%, although the performance in the delay is degraded. (b) Next, adaptive duty cycle control-based opportunistic routing scheme is proposed to reduce the delay of nodes in duty cycle control-based opportunistic routing. In adaptive duty cycle control-based opportunistic routing scheme, the node's duty cycle is increased in the area where the energy has remaining, so that the network delay can be reduced without reducing the network lifetime. Compared with duty cycle control-based opportunistic routing scheme, the maximum end-toend delay of the node in the network can be reduced by 69.83%.

“…Nowadays, smart sensors based on IoT are playing a more and more fundamental role in many applications [ 28 , 29 ]. For example, they play a key role in long-term monitoring of a wide range of ecological environments [ 30 ], real-time monitoring and intelligent decision-making on traffic status [ 31 ], and are also widely used in agriculture, military, industrial automation, and many other applications [ 32 , 33 , 34 , 35 ]. However, there are several challenges related to the mass promotion for smart IoT applications, and some of these challenges are to make IoT work with low cost, as well as a green and an energy-efficient paradigm [ 36 , 37 , 38 ].…”

Section: Introductionmentioning

confidence: 99%

“…The issue of reducing delay. Data is routed from the source node to the sink via multi-hop routing, and one of the important performance parameters is delay [ 7 , 9 , 15 , 28 , 30 , 31 , 52 ], which generally refers to the time that the data is generated from the source node until the sink successfully receives the data packet. Obviously, the smaller the delay, the better, because in some delay-sensitive applications, it makes sense to route data to the sink quickly because delayed data transmission may cause disastrous consequences [ 7 , 9 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

“…Obviously, the smaller the delay, the better, because in some delay-sensitive applications, it makes sense to route data to the sink quickly because delayed data transmission may cause disastrous consequences [ 7 , 9 , 15 ]. For example, in the monitoring of emergency events or of industrial sites, such as boilers, metallurgical furnaces, and automatic assembly lines, rapid data transmission enables the control center to adopt corresponding countermeasures to avoid disasters, while dragged data transmission will result in the control center not having adequate time to take measures to avoid disasters [ 10 , 31 , 52 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Energy Conserving and Transmission Radius Adaptive Scheme to Optimize Performance of Energy Harvesting Sensor Networks

Zhang

et al. 2018

Sensors

Self Cite

In energy harvesting wireless sensor networks (EHWSNs), the energy tension of the network can be relieved by obtaining the energy from the surrounding environment, but the cost on hardware cannot be ignored. Therefore, how to minimize the cost of energy harvesting hardware to reduce the network deployment cost, and further optimize the network performance, is still a challenging issue in EHWSNs. In this paper, an energy conserving and transmission radius adaptive (ECTRA) scheme is proposed to reduce the cost and optimize the performance of solar-based EHWSNs. There are two main innovations of the ECTRA scheme. Firstly, an energy conserving approach is proposed to conserve energy and avoid outage for the nodes in hotspots, which are the bottleneck of the whole network. The novelty of this scheme is adaptively rotating the transmission radius. In this way, the nodes with maximum energy consumption are rotated, balancing energy consumption between nodes and reducing the maximum energy consumption in the network. Therefore, the battery storage capacity of nodes and the cost on hardware. Secondly, the ECTRA scheme selects a larger transmission radius for rotation when the node can absorb enough energy from the surroundings. The advantages of using this method are: (a) reducing the energy consumption of nodes in near-sink areas, thereby reducing the maximum energy consumption and allowing the node of the hotspot area to conserve energy, in order to prevent the node from outage. Hence, the network deployment costs can be further reduced; (b) reducing the network delay. When a larger transmission radius is used to transmit data in the network, fewer hops are needed by data packet to the sink. After the theoretical analyses, the results show the following advantages compared with traditional method. Firstly, the ECTRA scheme can effectively reduce deployment costs by 29.58% without effecting the network performance as shown in experiment analysis; Secondly, the ECTRA scheme can effectively reduce network data transmission delay by 44–71%; Thirdly, the ECTRA scheme shows a better balance in energy consumption and the maximum energy consumption is reduced by 27.89%; And lastly, the energy utilization rate is effectively improved by 30.09–55.48%.