Computing geometric median to locate the sink node with the aim of extending the lifetime of wireless sensor networks

AbstractIn case of wireless sensor networks (WSNs) the sensed data which are collected by the ordinary senor nodes will have to be forwarded to the sink node (Base Station) in order to be accessible by the remote users. The location of the sink could significantly affect the energy dissipation and throughput of the network. This paper aims to investigate an optimal location for the sink node in such a way that the sum of distances from all the sensor nodes to the sink node is minimized. In an effort to place the sink node within the network our algorithm finds the geometric median of all the location associated with the sensor nodes. In a discrete set of points, the geometric median could be defined as the location which basically minimizes the sum of distances to all the points. Performance evaluation reveals that the proposed location for the sink node extends the network lifetime comparing with other possible location within the network field

Sniffing Multi-hop Multi-channel Wireless Sensor Networks

International audienceAs wireless sensor networks grow larger, more complex and their role more significant, it becomes necessary to have an insight into the network traffic. For this purpose, sniffers play an irreplaceable role. Since a sniffer is a device of limited range, to cover a multi-hop network it is necessary to consider the deployment of multiple sniffers. This motivates the research on the optimal number and position of sniffers in the network. We present a solution based on a minimal dominant set from graph theory. We evaluate the proposed solution and implement it as an extension of the 6TiSCH simulator. Our solution assumes a 50-nodes scenario, deployed in 2x2 km outdoor area, with 10% of packet drops over all channels, when 10 sniffers are used

An energy efficient long hop (LH) first scheduling algorithm for scalable Internet of Things (IoT) networks

Internet of Things (IoT) is becoming more and more pervasive in everyday life and connecting an array of diverse physical objects. It is fast growing and receiving a tremendous amount of research focus. Billions of objects communicate each other with or without human intervention to achieve smart applications. Most of the connected devices are constrained nodes to its ecosystem which have limited memories, CPU capabilities and power sources. Therefore, for implementing autonomous smart systems, efficient energy consumption is imperative. This paper introduces a novel scheduling algorithm called Long Hop (LH) first to optimize energy usage on a Wireless Sensor Network (WSN) that enables IoT system. LH algorithm schedules high priority for packets coming with more hops and longer distances to be served first at the cluster head (CH) nodes of the WSN. Since these packets require more links and nodes (thus increased energy and bandwidth usage) to reach the ultimate destination if not prioritized, the proposed algorithm reduces the overall energy usage and minimizes the total number of packets re-transmission and the effective data transmission distances. This improves the overall system performance and elongates the network lifetime

Optimization Scheme of Forming Linear WSN for Safety Monitoring in Railway Transportation

With the development of wireless sensing network, more and more applications have been deployed in the safety monitoring and in natural disasters prevention. The safety and disaster prevention systems have usually been laid out in linear network architecture, such as those of railway, motorway transportation and pipes. The background of the article is railway hazard goods transportation safety surveillance. The paper discusses about the network architecture of linear wireless sensor networks with multiple sink nodes, and proposes the grouping method of sink nodes and the formation scheme of networks. The scheme can re-establish a monitoring network when the train on the way is disconnected and re-grouped. The switching algorithm of group head nodes is put forward, so that the energy consumption of each node in the group is even. The optimal switching parameters for group head nodes are suggested by the simulation. Compared with the usual monitoring network, the method proposed enables the system life expectancy to prolong more than five times, and meets the monitoring requirements simultaneously

The Beauty of the Commons: Optimal Load Sharing by Base Station Hopping in Wireless Sensor Networks

In wireless sensor networks (WSNs), the base station (BS) is a critical sensor node whose failure causes severe data losses. Deploying multiple fixed BSs improves the robustness, yet requires all BSs to be installed with large batteries and large energy-harvesting devices due to the high energy consumption of BSs. In this paper, we propose a scheme to coordinate the multiple deployed BSs such that the energy supplies required by individual BSs can be substantially reduced. In this scheme, only one BS is selected to be active at a time and the other BSs act as regular sensor nodes. We first present the basic architecture of our system, including how we keep the network running with only one active BS and how we manage the handover of the role of the active BS. Then, we propose an algorithm for adaptively selecting the active BS under the spatial and temporal variations of energy resources. This algorithm is simple to implement but is also asymptotically optimal under mild conditions. Finally, by running simulations and real experiments on an outdoor testbed, we verify that the proposed scheme is energy-efficient, has low communication overhead and reacts rapidly to network changes

Support of multiple sinks via a virtual root for the RPL routing protocol

Data acquisition in large wireless sensor networks consisting of only a single sink can typically lead to scalability and energy efficiency issues. A solution to this problem is the deployment of multiple sinks in the network. This approach is however not supported by the popular sensor network routing protocol, IPv6 routing protocol for low-power and lossy networks (RPL). This paper describes a method to support the usage of multiple sinks for RPL in accordance to the limited guidelines of RPL:IPv6 Routing Protocol for Low-Power and Lossy Networks (RFC 6550). Hereby this paper shows that the concept of a virtual root can work and can be implemented with a minimal complexity. The correct behaviour of this extension was verified, by performance tests, in both a simulation environment and a real-life environment (iMinds wiLab.t office testbed). The chosen approach has the advantage that for an existing deployment of a RPL network, only the sink nodes need to be adapted. The results confirm that the use of multiple sinks in RPL can deliver the desired advantages. For an increase in the number of sinks from 1 to 4, a decrease of about 45% in the maximal and more than 30% in the average energy consumption was obtained in simulations for the used topology. For the real-life tests, the average energy consumption decreased with more than 30% and with more than 50% for the maximal energy consumption when the number of sinks was increased from 1 to 2 on the iMinds wiLab. t office testbed. By using a positioning algorithm to determine the optimal position, for the sinks, possibly even better performances can be obtained

Virtually Moving Base Stations for Energy Efficiency in Wireless Sensor Networks

Energy efficiency of wireless sensor networks (WSNs) can be improved by moving base stations (BSs), as this scheme evenly distributes the communication load in the network. However, physically moving BSs is complicated and costly. In this paper, we propose a new scheme: virtually moving the BSs. We deploy an excessive number of BSs and adaptively re-select a subset of active BSs so as to emulate the physical movement. Beyond achieving high energy-efficiency, this scheme obviates the difficulties associated with physically moving the BSs. The challenges are (i) that the energy efficiency of BSs should be considered as well, in addition to that of the sensor nodes and (ii) that the number of candidate subset of active BSs is exponential with the number of BSs. We show that scheduling the virtual movement of BSs is NP-hard. Then, we propose a polynomial-time algorithm that is guaranteed under mild conditions to achieve a lifetime longer than 62% of the optimal one. In practice, as verified through extensive numerical simulations, the lifetime achieved by the proposed algorithm is always very close to the optimum

Energy-Efficient Node Deployment in Static and Mobile Heterogeneous Multi-Hop Wireless Sensor Networks

We study a heterogeneous wireless sensor network (WSN) where N heterogeneous access points (APs) gather data from densely deployed sensors and transmit their sensed information to M heterogeneous fusion centers (FCs) via multi-hop wireless communication. This heterogeneous node deployment problem is modeled as an optimization problem with total wireless communication power consumption of the network as its objective function. We consider both static WSNs, where nodes retain their deployed position, and mobile WSNs where nodes can move from their initial deployment to their optimal locations. Based on the derived necessary conditions for the optimal node deployment in static WSNs, we propose an iterative algorithm to deploy nodes. In addition, we study the necessary conditions of the optimal movement-efficient node deployment in mobile WSNs with constrained movement energy, and present iterative algorithms to find such deployments, accordingly. Simulation results show that our proposed node deployment algorithms outperform the existing methods in the literature, and achieves a lower total wireless communication power in both static and mobile WSNs, on average

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