Mobile Collection Research Articles

Tour Planning for Mobile Data-Gathering Mechanisms in Wireless Sensor Networks

In this paper, we propose a new data-gathering mechanism for large-scale wireless sensor networks by introducing mobility into the network. A mobile data collector, for convenience called an M-collector in this paper, could be a mobile robot or a vehicle equipped with a powerful transceiver and battery, working like a mobile base station and gathering data while moving through the field. An M-collector starts the data-gathering tour periodically from the static data sink, polls each sensor while traversing its transmission range, then directly collects data from the sensor in single-hop communications, and finally transports the data to the static sink. Since data packets are directly gathered without relays and collisions, the lifetime of sensors is expected to be prolonged. In this paper, we mainly focus on the problem of minimizing the length of each data-gathering tour and refer to this as the single-hop data-gathering problem (SHDGP). We first formalize the SHDGP into a mixed-integer program and then present a heuristic tour-planning algorithm for the case where a single M-collector is employed. For the applications with strict distance/time constraints, we consider utilizing multiple M-collectors and propose a data-gathering algorithm where multiple M-collectors traverse through several shorter subtours concurrently to satisfy the distance/time constraints. Our single-hop mobile data-gathering scheme can improve the scalability and balance the energy consumption among sensors. It can be used in both connected and disconnected networks. Simulation results demonstrate that the proposed data-gathering algorithm can greatly shorten the moving distance of the collectors compared with the covering line approximation algorithm and is close to the optimal algorithm for small networks. In addition, the proposed data-gathering scheme can significantly prolong the network lifetime compared with a network with static data sink or a network in which the mobile collector c- n only move along straight lines.

Subversive Mobilities

The article approaches mobility through a cultural history of urban conflict. Using a case of “The Copenhagen Trouble,“ a series of riots in the Danish capital around 1900, a space of subversive mobilities is delineated. These turn-of-the-century riots points to a new pattern of mobile gathering, the swarm; to a new aspect of public action, the staging; and to new ways of configuring public space. These different components indicate an urban assemblage of subversion, and a new characterization of the “throwntogetherness“ of the modern public.

Optimization-Based Distributed Algorithms for Mobile Data Gathering in Wireless Sensor Networks

Recent advances have shown a great potential of mobile data gathering in wireless sensor networks, where one or more mobile collectors are employed to collect data from sensors via short-range communications. Among a variety of data gathering approaches, one typical scheme is called anchor-based mobile data gathering. In such a scheme, during each periodic data gathering tour, the mobile collector stays at each anchor point for a period of sojourn time, and in the meanwhile the nearby sensors transmit data to the collector in a multihop fashion. In this paper, we focus on such a data gathering scheme and provide distributed algorithms to achieve its optimal performance. We consider two different cases depending on whether the mobile collector has fixed or variable sojourn time at each anchor point. We adopt network utility, which is a properly defined function, to characterize the data gathering performance, and formalize the problems as network utility maximization problems under the constraints of guaranteed network lifetime and data gathering latency. To efficiently solve these problems, we decompose each of them into several subproblems and solve them in a distributed manner, which facilitates the scalable implementation of the optimization algorithms. Finally, we provide extensive numerical results to demonstrate the usage and efficiency of the proposed algorithms and complement our theoretical analysis.

Coverage strategy for periodic readings in robotic-assisted monitoring systems

We consider wireless sensor network applications where mobile robots serving as sinks are responsible to collect readings from sensors in a given area and delivering the readings to a central authority within some bounded delay. We refer to these mobile robots as collectors. This scenario raises a number of challenging issues, as we need to define specific coverage strategies to guarantee that: (i) collectors visit any point of the target area on a regular basis, (ii) collectors cover the entire area, and (iii) trajectories take into account the fact that collected data might have spatial correlation. We propose to define trajectories for mobile collectors based on the concept of space-filling curves. We investigate the appropriateness of different space-filling curves to respect a number of requirements (at both the system and applicative levels). By numerically analyzing a number of scenarios, we show that our proposal is both effective in guaranteeing full coverage and in respecting applicative requirements. Our results assess both the delivery delay and the aggregation accuracy of the investigated curves.

Bounded Relay Hop Mobile Data Gathering in Wireless Sensor Networks

Recent study reveals that great benefit can be achieved for data gathering in wireless sensor networks by employing mobile collectors that gather data via short-range communications. To pursue maximum energy saving at sensor nodes, intuitively, a mobile collector should traverse the transmission range of each sensor in the field such that each data packet can be directly transmitted to the mobile collector without any relay. However, this approach may lead to significantly increased data gathering latency due to the low moving velocity of the mobile collector. Fortunately, it is observed that data gathering latency can be effectively shortened by performing proper local aggregation via multihop transmissions and then uploading the aggregated data to the mobile collector. In such a scheme, the number of local transmission hops should not be arbitrarily large as it may increase the energy consumption on packet relays, which would adversely affect the overall efficiency of mobile data gathering. Based on these observations, in this paper, we study the tradeoff between energy saving and data gathering latency in mobile data gathering by exploring a balance between the relay hop count of local data aggregation and the moving tour length of the mobile collector. We first propose a polling-based mobile gathering approach and formulate it into an optimization problem, named bounded relay hop mobile data gathering (BRH-MDG). Specifically, a subset of sensors will be selected as polling points that buffer locally aggregated data and upload the data to the mobile collector when it arrives. In the meanwhile, when sensors are affiliated with these polling points, it is guaranteed that any packet relay is bounded within a given number of hops. We then give two efficient algorithms for selecting polling points among sensors. The effectiveness of our approach is validated through extensive simulations.

Research on Network Parameter Model of Node Low Energy Consumption Wireless Sensor Network for Greenhouse

Based on the node low energy consumption wireless sensor network for greenhouse, which takes mobile gathering node as center to self-organize subnets, this article mainly studies the relationship among network parameters and strike a balance between energy saving and system stability to establish the model of network parameter. Examples are illustrated to show how to determine network parameters and why the model is effective.

Efficient Data Gathering with Mobile Collectors and Space-Division Multiple Access Technique in Wireless Sensor Networks

Recent years have witnessed a surge of interest in efficient data gathering schemes in wireless sensor networks (WSNs). In this paper, we address this issue by adopting mobility and space-division multiple access (SDMA) technique. Specifically, mobile collectors, called SenCars in this paper, work like mobile base stations and collect data from associated sensors via single-hop transmissions so as to achieve uniform energy consumption. We also apply SDMA technique to data gathering by equipping each SenCar with multiple antennas such that distinct compatible sensors may successfully make concurrent data uploading to a SenCar. To investigate the utility of the joint design of controlled mobility and SDMA technique, we consider two cases, where a single SenCar and multiple SenCars are deployed in a WSN, respectively. For the single SenCar case, we aim to minimize the total data gathering time, which consists of the moving time of the SenCar and the data uploading time of sensors, by exploring the trade-off between the shortest moving tour and the full utilization of SDMA. We refer to this problem as mobile data gathering with SDMA, or MDG-SDMA for short. We formalize it into an integer linear program (ILP) and propose three heuristic algorithms for it. In the multi-SenCar case, the sensing field is divided into several regions, each having a SenCar. We focus on minimizing the maximum data gathering time among different regions and refer to it as mobile data gathering with multiple SenCars and SDMA (MDG-MS) problem. Accordingly, we propose a region-division and tour-planning (RDTP) algorithm in which data gathering time is balanced among different regions. We carry out extensive simulations and the results demonstrate that our proposed algorithms significantly outperform single SenCar and non-SDMA schemes.

Energy-Aware Distributed Intelligent Data Gathering Algorithm in Wireless Sensor Networks

To plan the data collecting path for the mobile collector in wireless sensor network (WSN), an efficient energy-aware distributed intelligent data gathering algorithm (DIDGA) is proposed, which includes cluster formation and path formation phases. In cluster formation phase, an energy-efficient distributed clustering scheme is proposed to form a coverage-efficient WSN, which constructs a minimum connected dominating set (MCDS) based on maximal independent sets (MISs) in distributed and localized manner, and the node with more power is selected to be the cluster head in turn to prolong the network lifetime. In path formation phase, a path formation optimized algorithm (PFOA) is proposed to resolve the path formation NP problem with dynamic requirements. Then DIDGA uses the cluster head relay mechanism for planning the data gathering path. Compared with existed algorithms, detailed simulation results show that the proposed DIDGA can reduce average hop counts, average data gathering time, energy consumption, increase the efficiency of event detection ratio and prolong the network lifetime.

Before and after the deluge: rain-on-snow flooding effects on aquatic invertebrate communities of small streams in the Sierra Nevada, California

Climate change is predicted to increase the frequency of rain-on-snow events in the winter and spring in mountain streams. Flooding caused by such events can drastically alter stream geomorphology, but much less is known about how such floods affect aquatic life. A record flood in early January 1997 afforded an opportunity to carry out a case study of benthic invertebrate community responses to this flood in 14 eastern Sierra streams sampled in the summers before and after the event. All sites were exposed to the flood. Study sites included 8 exposed to livestock grazing disturbance (test) and 6 where grazing was absent or minimal (reference). Reference sites had more riffle habitat, coarser substrata (cobbles), and greater relative abundances of many Ephemeroptera, Plecoptera, and Trichoptera (EPT) genera, whereas test sites had higher alkalinity, more pool habitats and fine substrata, lower diversity of EPT taxa, and higher densities of chironomid genera and elmid beetles. From 1996 to 1997 (before vs after the flood), the densities of total invertebrates and many taxa increased in most sites, and significantly (10×) more at test than reference sites. At all sites, bank stability and riparian vegetation coverage decreased and roots were exposed on the stream banks. At many sites, fine sediments decreased and average substrate sizes increased. Examination of 1996 to 1997 vectors in nonmetric multidimensional scaling (NMDS) space indicated differences in responses at reference vs test sites. Macroinvertebrate assemblages at reference sites changed relatively little, whereas the relative abundances of certain midges and Hydropsyche increased at test sites. Densities of filterers and small gatherers of fine particulate organic matter increased at test sites, and densities of filterers decreased at reference sites. Changes from 1996 to 1997 suggested that the winter rain-on-snow event had little effect in reference streams but increased the densities of small collector invertebrates at disturbed sites where fine sediments were flushed out and particulate organic resources increased. Given the predicted effects of climate change on mountain stream hydrology, these results indicate that benthic invertebrate communities in small pristine streams might be resilient to the effects of large rain-on-snow floods, but that small, mobile collector invertebrates in some degraded streams might increase in response to sediment flushing and increases in particulate organic matter.

Dealing with random and selective attacks in wireless sensor systems

We present a framework for analyzing the effects of random and selective compromises (using order statistics) in sensor networks. We discuss the problem of ensuring data integrity at the source and during transit in sensor networks, and present an analysis of the reliability of reports from mobile collectors. No analysis has appeared in the literature of source integrity for mobile nodes, or of selective attacks in sensor networks. We address transit data integrity by presenting mGKE, a key establishment scheme for general group-based sensor deployments, and present a detailed analytical and experimental comparison of mGKE with current schemes. mGKE outperforms current methods in terms of resilience, connectivity, and memory and communication overhead.

Cyberbroker: A lightweight web object collector

Centralized heavyweight collectors have been used to collect text-based web objects for building search engines. However, these collectors do not meet the need of collecting big web objects such as images and videos. We propose a lightweight mobile on-call object collector for the world wide web. Using this approach, we can deploy a collector easily on the site being indexed. We present a prototype system consisting of mobile Java collectors and search engines for collecting HTML/image objects. We provide analysis to find a lower bound in terms of total data transfer time required. This idealized scenario is complemented with another model based on implementation of the HTTP over TCP. The lower bound and the upper bound of the gains accrued are then validated using experiments.

Experimental random spot testing for drugs in sportsmen.

Twenty-eight active international athletes agreed to be available for random spot urine collections at their homes, places of work and training. Suitable briefed collectors were arranged to conduct the spot collections and forward the specimens for analysis. An average number of 3.4 collections per athlete was made in the 9 month period of the trial. Overall there was a "failure to collect" percentage of 14 during the winter months and 54 during the summer months. The average time interval between initial contact with the athlete and collection was 11 hours 50 minutes. It is concluded that random spot collections of urine from active athletes in training is possible and practical. Improved collection rates could be achieved by additional spot collection at athletic events during the summer and by using regionally based mobile collectors responsible for several athletes.