714 research outputs found
Wireless Power Transfer and Data Collection in Wireless Sensor Networks
In a rechargeable wireless sensor network, the data packets are generated by
sensor nodes at a specific data rate, and transmitted to a base station.
Moreover, the base station transfers power to the nodes by using Wireless Power
Transfer (WPT) to extend their battery life. However, inadequately scheduling
WPT and data collection causes some of the nodes to drain their battery and
have their data buffer overflow, while the other nodes waste their harvested
energy, which is more than they need to transmit their packets. In this paper,
we investigate a novel optimal scheduling strategy, called EHMDP, aiming to
minimize data packet loss from a network of sensor nodes in terms of the nodes'
energy consumption and data queue state information. The scheduling problem is
first formulated by a centralized MDP model, assuming that the complete states
of each node are well known by the base station. This presents the upper bound
of the data that can be collected in a rechargeable wireless sensor network.
Next, we relax the assumption of the availability of full state information so
that the data transmission and WPT can be semi-decentralized. The simulation
results show that, in terms of network throughput and packet loss rate, the
proposed algorithm significantly improves the network performance.Comment: 30 pages, 8 figures, accepted to IEEE Transactions on Vehicular
Technolog
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
Efficient on-demand multi-node charging techniques for wireless sensor networks
This paper deals with wireless charging in sensor networks and explores efficient policies to perform simultaneous multi-node power transfer through a mobile charger (MC).The proposed solution, called On-demand Multi-node Charging (OMC), features an original threshold-based tour launching (TTL) strategy, using request grouping, and a path planning algorithm based on minimizing the number of stopping points in the charging tour. Contrary to existing solutions, which focus on shortening the charging delays, OMC groups incoming charging requests and optimizes the charging tour and the mobile charger energy consumption. Although slightly increasing the waiting time before nodes are charged, this allows taking advantage of multiple simultaneous charges and also reduces node failures. At the tour planning level, a new modeling approach is used. It leverages simultaneous energy transfer to multiple nodes by maximizing the number of sensors that are charged at each stop. Given its NP-hardness, tour planning is approximated through a clique partitioning problem, which is solved using a lightweight heuristic approach. The proposed schemes are evaluated in offline and on-demand scenarios and compared against relevant state-of-the-art protocols. The results in the offline scenario show that the path planning strategy reduces the number of stops and the energy consumed by the mobile charger, compared to existing offline solutions. This is with further reduction in time complexity, due to the simple heuristics that are used. The results in the on-demand scenario confirm the effectiveness of the path planning strategy. More importantly, they show the impact of path planning, TTL and multi-node charging on the efficiency of handling the requests, in a way that reduces node failures and the mobile charger energy expenditure
Energy Harvesting Aspects of Wireless Sensor Networks: A Review
Energy harvesting is the process by which energy is derived from external sources e.g., solar power, thermal energy, wind energy, salinity gradients, and kinetic energy captured and stored for small, wireless autonomous devices, like those used in wearable electronics and wireless sensor networks.Energy harvesters provide a very small amount of power for low-energy electronics. The energy sourced from energy harvesters is present as ambient background and is free
Energy-Optimal Scheduling in Low Duty Cycle Sensor Networks
Energy consumption of a wireless sensor node mainly depends on the amount of
time the node spends in each of the high power active (e.g., transmit, receive)
and low power sleep modes. It has been well established that in order to
prolong node's lifetime the duty-cycle of the node should be low. However, low
power sleep modes usually have low current draw but high energy cost while
switching to the active mode with a higher current draw. In this work, we
investigate a MaxWeightlike opportunistic sleep-active scheduling algorithm
that takes into account time- varying channel and traffic conditions. We show
that our algorithm is energy optimal in the sense that the proposed ESS
algorithm can achieve an energy consumption which is arbitrarily close to the
global minimum solution. Simulation studies are provided to confirm the
theoretical results
A reliable cross layer routing scheme (CL-RS) for wireless sensor networks to prolong network lifetime
Design of conventional protocols for wireless sensor networks(WSN) are mainly based on energy management. The solutions for layered protocol of the WSN network are inefficient as sensors network mainly delivers real-time content thus, cross layer communication between layers of the protocol stack is highly required. In this paper, a reliable cross layer routing scheme (CL - RS) is proposed to balance energy to achieve prolonged lifetime through controlled utilization of limited energy. CL - RS considers 2 adjacent layers namely, MAC layer and network layer. Optimization issues are identified in these two layers and solutions are provided to reduce energy consumption thereby increasing network lifetime. To achieve higher energy efficiency MAC layer protocols compromise on packet latency. It is essential to attempt reduce the end-to-end delay and energy consumption using low duty cycle cross layer MAC (CL-MAC). The joint optimization design is formulated as a linear programming problem. The network is partitioned into four request zones to enable increase in network performance by using an appropriate duty cycle and routing scheme. We demonstrate by simulations that the strategy designed by combining (CL - RS) and (CL-MAC) algorithms at each layer significantly increases the network lifetime and a relation exists between the network lifetime maximization and the reliability constraint. We evaluate the performance of the proposed scheme under different scenarios using ns-2. Experimental results shows that proposed scheme outperforms the layered AODV in terms of packet loss ratio, end-to-end delay, control overhead and energy consumption
Minimization of End-to-End Delay for an Improved Dual-Sink Cluster-Based Routing in WBAN
Wireless Body Area Networks (WBANs) are an integral part of a Wireless sensor network, where sensor nodes are strategically placed in the human body to sense physiological signals and transmit them to the medical personnel via server for medical observations. Every sensor node in WBANs has a general limitation in energy efficiency, end-to-end delay, residual energy, etc. Also, the high energy consumption in WBANs is mainly due to the number of hops covered during physiological signal transmission. This work developed a hop-distance scenario to address these challenges and improve on what others have done. It buffered traffic estimation schemes to minimize end-to-end delay and the total network energy efficiency. This work minimizes end-to-end delay dual-sink cluster-based routing in WBANs by improving the existing dual-sink-sink cluster-based scheme (iDSCB). The simulation result shows that the Minimization of end-to-end delay of the improved dual-sink cluster-based (iDSCB) enhanced the performance of the current article DSCB in terms of end-to-end delay and residual energy by 3.15% and 8.88%, respectively
Priority Based Data Transmission for WBAN
Wireless Body Area Sensor Network (WBASN) or Wireless Body Area Network (WBAN) is a growing field in healthcare applications. It enables remote monitoring of patient’s physiological data through wireless communication. It is composed of sensor network which collects physiological data from the patient. There are several issues concerning WBAN such as security, power, routing protocol to address QoS metrics (reliability, end-to-end delay, and energy efficiency), etc. The focus of the study is the issue on different QoS metrics. There were several QoS aware routing protocol that has been proposed which implements multiple queues for different types of data. However, one issue on multiple queue system is starvation, end-to-end delay, and reliability. The study proposed an efficient priority queue based data transmission that improves the end-to-end delay, reliability, and queuing delay of QoS aware routing protocol
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