Minimum-cost mobile crowdsourcing with QoS guarantee using matrix completion technique

Wang

et al. 2019

J Wireless Com Network

Self Cite

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 Delaymentioning

confidence: 99%

“…In addition, matrix filling technology is combined with mobile crowdsourcing technology (an emerging data collection solution) to obtain a novel matrix completion technique-based data collection (MCTDC) scheme [63]. 3 The system model and problem statement…”

Section: Existing Research Related To Matrix Fillingmentioning

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

Self Cite

“…WSNs consists of a huge number of devices composed of microprocessor, power supply equipment, memory and communication equipment [ 52 , 53 , 54 ] and is an important component of Internet of Things (IoT). With the development of microprocessors, the processing and perceiving ability of sensor nodes is getting stronger and stronger, greatly expanding the scope and field of application, therefore greatly promoting the development of IoT [ 55 , 56 ].…”

Section: Related Workmentioning

confidence: 99%

Minimizing Delay and Transmission Times with Long Lifetime in Code Dissemination Scheme for High Loss Ratio and Low Duty Cycle Wireless Sensor Networks

Wei

et al. 2018

Sensors

Self Cite

Software defined networks brings greater flexibility to networks and therefore generates new vitality. Thanks to the ability to update soft code to sensor nodes, wireless sensor networks (WSNs) brings profound changes to Internet of Things. However, it is a challenging issue to minimize delay and transmission times and maintain long lifetime when broadcasting data packets in high loss ratio and low duty cycle WSNs. Although there have been some research concerning code dissemination, those schemes can only achieve a tradeoff between different performances, instead of optimizing all these important performances at the same time. Therefore, in this paper we propose a new strategy that can reduce delay and transmission times simultaneously. In traditional method, the broadcasting nature of wireless communication is not sufficiently utilized. By allowing sons of the same parent node to share awake slots, the broadcasting nature is well exploited and delay is thus reduced as well as transmission times with lifetime not affected. And, as we discover there is energy surplus when collecting data in area away from sink, we further improve this strategy so that all the performances can be further bettered. Compared with traditional method, the methods we design (IFAS, BTAS and AAPS) can respectively reduce delay by 20.56%, 31.59%, 55.16% and reduce transmission times by 29.53%, 43.93%, 42.04%, while not reducing lifetime.

“…This is because that the energy consumption of sending data from the node is proportional to the square or the fourth of the power of the transmission distance. When the transmission distance increases, the energy consumption of nodes will increase, although their data load is small [ 57 , 58 ]. Based on this, researchers expand the study on how to reduce maximum energy consumption in the network, and attenuate the impact of the energy hole.…”

Section: Related Workmentioning

confidence: 99%

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%.