305 research outputs found
A distributed delay-efficient data aggregation scheduling for duty-cycled WSNs
With the growing interest in wireless sensor networks (WSNs), minimizing network delay and maximizing sensor (node) lifetime are important challenges. Since the sensor battery is one of the most precious resources in a WSN, efficient utilization of the energy to prolong the network lifetime has been the focus of much of the research on WSNs. For that reason, many previous research efforts have tried to achieve tradeoffs in terms of network delay and energy cost for such data aggregation tasks. Recently, duty-cycling technique, i.e., periodically switching ON and OFF communication and sensing capabilities, has been considered to significantly reduce the active time of sensor nodes and thus extend network lifetime. However, this technique causes challenges for data aggregation. In this paper, we present a distributed approach, named distributed delay efficient data aggregation scheduling (DEDAS-D) to solve the aggregation-scheduling problem in duty-cycled WSNs. The analysis indicates that our solution is a better approach to solve this problem. We conduct extensive simulations to corroborate our analysis and show that DEDAS-D outperforms other distributed schemes and achieves an asymptotic performance compared with centralized scheme in terms of data aggregation delay.N/
Selecting source image sensor nodes based on 2-hop information to improve image transmissions to mobile robot sinks in search \& rescue operations
We consider Robot-assisted Search Rescue operations enhanced with some
fixed image sensor nodes capable of capturing and sending visual information to
a robot sink. In order to increase the performance of image transfer from image
sensor nodes to the robot sinks we propose a 2-hop neighborhood
information-based cover set selection to determine the most relevant image
sensor nodes to activate. Then, in order to be consistent with our proposed
approach, a multi-path extension of Greedy Perimeter Stateless Routing (called
T-GPSR) wherein routing decisions are also based on 2-hop neighborhood
information is proposed. Simulation results show that our proposal reduces
packet losses, enabling fast packet delivery and higher visual quality of
received images at the robot sink
A Level-Wise Periodic Tree Construction Mechanism for Sleep Scheduling in WSN
The wireless sensor network(WSN) has been extensively used to monitor and control the natural ecosystem on a large scale like air quality, natural life, etc. Low battery power,low storage, and limited processing ability are the most critical areas of concern in WSN. To reduce energy utilization, the sensor nodes in WSN work in a cyclic process between active and sleep mode. A certain number of nodes are chosen active and they areresponsible for sensing as well as data transmission and rest of the nodes are gone to sleep. In order to lengthen the lifetime of network, in this paper we proposed a level wise periodic tree construction algorithm that uses a specific set of nodes to participate in tree construction, instead of all the nodes, to minimize the energy consumption. In this proposed approach, the main idea is to put the nodes, which are currently active and have already spent a significant amount of energy, to sleep mode, while giving chances to the leaf nodes, which has comparatively spent less energy, to become an active node and maintain connectivity. The performance of the proposed protocol is evaluated usingthe Castalia simulator. The simulation results show that the proposed level-wise periodic tree construction approach increases the durability of the network in conjunction with the non-level approach
Atomic-SDN: Is Synchronous Flooding the Solution to Software-Defined Networking in IoT?
The adoption of Software Defined Networking (SDN) within traditional networks
has provided operators the ability to manage diverse resources and easily
reconfigure networks as requirements change. Recent research has extended this
concept to IEEE 802.15.4 low-power wireless networks, which form a key
component of the Internet of Things (IoT). However, the multiple traffic
patterns necessary for SDN control makes it difficult to apply this approach to
these highly challenging environments. This paper presents Atomic-SDN, a highly
reliable and low-latency solution for SDN in low-power wireless. Atomic-SDN
introduces a novel Synchronous Flooding (SF) architecture capable of
dynamically configuring SF protocols to satisfy complex SDN control
requirements, and draws from the authors' previous experiences in the IEEE EWSN
Dependability Competition: where SF solutions have consistently outperformed
other entries. Using this approach, Atomic-SDN presents considerable
performance gains over other SDN implementations for low-power IoT networks. We
evaluate Atomic-SDN through simulation and experimentation, and show how
utilizing SF techniques provides latency and reliability guarantees to SDN
control operations as the local mesh scales. We compare Atomic-SDN against
other SDN implementations based on the IEEE 802.15.4 network stack, and
establish that Atomic-SDN improves SDN control by orders-of-magnitude across
latency, reliability, and energy-efficiency metrics
A Survey on Energy-Efficient Strategies in Static Wireless Sensor Networks
A comprehensive analysis on the energy-efficient strategy in static Wireless Sensor Networks (WSNs) that are not equipped with any energy harvesting modules is conducted in this article. First, a novel generic mathematical definition of Energy Efficiency (EE) is proposed, which takes the acquisition rate of valid data, the total energy consumption, and the network lifetime of WSNs into consideration simultaneously. To the best of our knowledge, this is the first time that the EE of WSNs is mathematically defined. The energy consumption characteristics of each individual sensor node and the whole network are expounded at length. Accordingly, the concepts concerning EE, namely the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective, are proposed. Subsequently, the relevant energy-efficient strategies proposed from 2002 to 2019 are tracked and reviewed. Specifically, they respectively are classified into five categories: the Energy-Efficient Media Access Control protocol, the Mobile Node Assistance Scheme, the Energy-Efficient Clustering Scheme, the Energy-Efficient Routing Scheme, and the Compressive Sensing--based Scheme. A detailed elaboration on both of the basic principle and the evolution of them is made. Finally, further analysis on the categories is made and the related conclusion is drawn. To be specific, the interdependence among them, the relationships between each of them, and the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective are analyzed in detail. In addition, the specific applicable scenarios for each of them and the relevant statistical analysis are detailed. The proportion and the number of citations for each category are illustrated by the statistical chart. In addition, the existing opportunities and challenges facing WSNs in the context of the new computing paradigm and the feasible direction concerning EE in the future are pointed out
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
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