Editorial Mobile Sensing and Data Management for Sensor ...downloads.hindawi.com/journals/ijdsn/2013/898169.pdf · In the paper Moving target oriented opportunistic routing algorithm

Hindawi Publishing CorporationInternational Journal of Distributed Sensor NetworksVolume 2013, Article ID 898169, 3 pageshttp://dx.doi.org/10.1155/2013/898169

EditorialMobile Sensing and Data Management for Sensor Networks

Jianwei Niu,1 Lei Shu,2 Zhangbing Zhou,3,4 and Yan Zhang5

1 State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering,Beihang University, Beijing 100191, China

2Guangdong University of Petrochemical Technology, Maoming 525000, China3 China University of Geosciences, Beijing 100191, China4 Institut Telecom, France5 Simula Research Laboratory, University of Oslo, 1325 Lysaker, Norway

Correspondence should be addressed to Jianwei Niu; [email protected]

Received 14 August 2013; Accepted 14 August 2013

Copyright © 2013 Jianwei Niu et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

With the rapid advent of the Internet of Things, sensorcloud, mobile Internet, and Web 3.0, more and more mobiledevices, such as smart phones, Google glasses, and RFID,plus deployed various sensor networks, can sense and collectsensory data anytime and anywhere. We are moving towardthe era of worldwide sensor networks, in which a hugeamount of heterogeneous sensory data will be created everyday and require advanced data management. In this setting,efficiently gathering, sharing, and integrating these spatialtemporal data, and then deriving valuable knowledge timely,are a big challenge in this context. Furthermore, in themobile environment, data management means a collectionof centralized and distributed algorithms, architectures, andsystems to store, process, and analyze the immense amountof spatial temporal data, where these data are cooperativelygathered through collections ofmobile sensing devices whichmove in space over time.This special issue onmobile sensingand data management for sensor networks is intended toprovide a forum for presenting, exchanging, and discussingthe most recent advances in sensing and data managementtechniques.

To prolong the life time of each node in MSNs, energymodel and conservation should be considered carefully whendesigning the data communication mechanism. The limitedbattery volume and high workload on channels worsen thelife times of the busy nodes. In the paper “An probability-based energy model on cache coherence protocol with mobilesensor network,” the authors propose a new energy evaluat-ing methodology of packet transmissions in MSNs, which

is based on redividing network layers and describing thesynchronous data flow with matrix form.

Mobile cloud computing (MCC) enables mobile devicesto outsource their computing, storage, and other tasks ontothe cloud to achievemore capacities and higher performance.In the paper “Adaptive computing resource allocation formobile cloud computing,” the authors propose a novel MCCadaptive resource allocation model to achieve the optimalresource allocation in terms of the maximal overall systemreward by considering both cloud and mobile devices. Theadaptive resource allocation is modeled as a semi-Markovdecision process (SMDP) to capture the dynamic arrivals anddepartures of resource requests.

Computation offloading is a popular approach for reduc-ing energy consumption of mobile devices by offloadingcomputation to remote servers. The paper “An energy-efficient multisite offloading algorithm for mobile devices”proposes an Energy-Efficient Multisite Offloading (EMSO)algorithm. It formulates the multiway partitioning problemas the 0-1 integer linear programming (ILP) problem, whichis solved through the proposedEMSOalgorithmadopting themultiway graph partitioning-based technique.

The mixed wireless sensor networks that are composedof a mixture of mobile and static sensors are the tradeoffbetween cost and coverage. To provide the required highcoverage, the mobile sensors have to move from denseareas to sparse areas. The paper “An energy-efficient motionstrategy for mobile sensors in mixed wireless sensor networks”presents a centralized algorithm to assist the movement ofmobile sensors. The management node of the WSN collects

2 International Journal of Distributed Sensor Networks

the geographical information of all of the static and mobilesensors. Themanagement node executes the algorithm to getthe best matches between mobile sensors and coverage holes.

With the advance of embedded sensing devices, pervasiveurban sensing (PUS)with probe vehicles is becoming increas-ingly practical. A probe vehicle is equipped with onboardsensing devices that detect urban information as the probevehicle drive across the road network. In the paper “Pervasiveurban sensing with large-scale mobile probe vehicles,” theauthors present the framework of Pervasive Urban Sensingwith probe vehicles, and showcase two cases of urban sensingwith probe vehicles.

Rotating machinery is widely used in modern industry.It is one of the most critical components in a varietyof machinery and equipment. Along with the continuousdevelopment of science and technology, the structures ofrotating machinery become of larger scale, of higher speed,and more complicated, which results in higher probabilityof concurrent failure in practice. In the paper “Concurrentfault diagnosis for rotating machinery based on vibrationsensors”, the authors develop an integrated method usingartificial immune algorithm and evidential theory to achieveconcurrent fault diagnosis for rotating machinery.

The paper “Enhanced mobile multiple-input multiple-output underwater acoustic communications” focuses onmobile multiple-input multiple-output (MIMO) underwateracoustic communications (UAC) over double-selective chan-nels subject to both intersymbol interference and Dopplerscaling effects. Under the assumption that the channelsbetween all the transmitter and receiver pairs experiencethe same Doppler frequency, a variation of the recentlyproposed generalization of the sparse learning via iterativeminimization (GoSLIM) algorithm is employed to estimatethe frequency modulated acoustic channels.

Often, a large number of wireless sensor nodes aredeployed to detect target signal that is more accurate thanthe traditional single radar detection method. Each localsensor detects the target signal in the region of interestsand collects relevant data, and it sends the respective datato the data fusion center (DFC) for aggregation processingand judgment making whether the target signal exists or not.The paper “Weight-based clustering decision fusion algorithmfor distributed target detection in wireless sensor networks”proposes a novel Weight-based Clustering Decision FusionAlgorithm (W-CDFA) to detect target signal in wirelesssensor networks.

Sensor network positioning systems have been exten-sively studied recently. How to acquire the anchor’s positionis a challenge. To address this issue, in the paper “Efficientdeterministic anchor deployment for sensor network posi-tioning,” the authors design an efficient mapping algorithmbetween anchors and their positions (MD-SKM) to avoid thecomplicated artificial calibration and propose a best featurematching (BFM) method to further relax the restriction ofMD-SKMwhere three ormore calibrated anchors are needed.

In vehicular networks, the multihop message deliveryfrom information source to moving vehicles presents achallenging task due tomany factors, including highmobility,

frequent disconnection, and real-time requirement for appli-cations. In the paper “Moving target oriented opportunisticrouting algorithm in vehicular networks,” the authors proposea moving target oriented opportunistic routing algorithm invehicular networks for message delivery from informationsource to a moving target vehicle. In order to adapt theconstantly changing topology of networks, the forwardingdecisions aremade locally by each intermediate vehicle basedon the trajectory information of the target vehicle.

With the increase of the storage capacity, computing,and wireless networking of the vehicular embedded devices,the vehicular networks bring a potential to enable newapplications for drivers and passengers in the vehicles. In thepaper “RoadGate: mobility-centric roadside units deploymentfor vehicular networks,” the authors study the problem ofdeploying the RSUs to provide the desired connectivityperformance while minimizing the number of the deployedRSUs. Besides, the authors analyze a realistic vehicle trace,observe the mobility pattern, and propose a graph modelto characterize it. Based on the graph model, the gatewaydeployment problem is transformed into a vertex selectionproblem in a graph. A heuristic algorithm RoadGate is thenproposed to search greedily the optimal positions.

Optimizing the path planning to reduce the time andcost is an essential consideration in modern society. Usingdynamic path planning to adjust and update the pathinformation in time is a challenging approach to reduceroad congestion and traffic accidents. In the paper “Dataprocessing and algorithm analysis of vehicle path planningbased on wireless sensor network,” the authors present a dataanalysis algorithm that determines an efficient dynamic pathfor vehicle repair-scrap sites and navigates more flexibly toavoid obstacles. The key idea is to design the wireless sensornetwork that helps to obtain data from different devices.

The paper “Trajectory-based optimal area forwarding forinfrastructure-to-vehicle data delivery with partial deploymentof stationary nodes” proposes a trajectory-based optimalarea forwarding (TOAF) algorithm tailored for multihopdata delivery from infrastructure nodes (e.g., Internet accesspoints) to moving vehicles (infrastructure-to-vehicle) invehicular ad hoc networks (VANETs) with partial deploy-ment of stationary nodes. It focuses on reducing the delivery-delay jitter and improving the low reliability of infrastructure-to-vehicle communication.

The design and analysis of routing algorithms are impor-tant issues in WSNs. In the paper “An overlapping clusteringapproach for routing in wireless sensor networks,” the authorspropose a k-connected overlapping clustering approach withenergy awareness, namely, k-OCHE, for routing in WSNs.The basic idea of this approach is to select a cluster head byenergy availability (EA) status. The k-OCHE scheme adoptsa sleep scheduling strategy of CKN, where neighbors willremain awake to keep it k-connected, so that it can balanceenergy distributions well.

WSNs are important parts of Internet ofThings or cyber-physical systems. Data query processing is very importantfor WSNs. In the paper “Continuous top-k contour regionsquerying in sensor networks”, the authors propose a Contin-uous Top-k Contour Regions Querying algorithm which can

International Journal of Distributed Sensor Networks 3

continuously obtain the top-k contour regions and does notlose the rate of precision. This technique takes full advantageof the kth value of top-k result in current round as thethreshold to suppress the nodeswhose readings do not belongto the top-k result in next round.

In WSNs, homogeneous or heterogeneous sensor nodesare deployed at a certain area to monitor our curious target.The sensor nodes report their observations to the base station(BS), and the BS should implement the parameter estimationwith sensors’ data. Best linear unbiased estimation (BLUE) isa common estimator in the parameter estimation. In somesoft real-time applications, we expect that the estimation canbe completed before the deadline with a probability. In thepaper “Energy-efficient soft real-time scheduling for parameterestimation inWSNs,” the authors proposed an energy-efficientscheduling algorithm especially for the soft real-time estima-tions in WSNs. Through the proper assignment of sensors’state, an energy-efficient estimation is achieved before thedeadline with a probability.

WSNs have limited energy and transmission capacity, sodata compression techniques have extensive applications. Formultivariate stream on a sensor node, some data streams areelected as the base functions according to the correlationcoefficient matrix, and the other streams from the same nodecan be expressed in relation to one of these base functionsusing linear regression. By designing an incremental algo-rithm for computing regression coefficients, in the paper “Aself-adaptive regression-based multivariate data compressionscheme with error bound in wireless sensor networks,” theauthors propose a multivariate data compression schemebased on self-adaptive regression with infinite norm errorbound.

The drive-thru Internet is an effective mean to provideInternet access service for WSNs deployed on vehicles.In these networks, vehicles often experience different linkqualities due to different relative positions to the accesspoint. This makes fair and efficient system design a verychallenging task. In the paper “Amortized fairness for drive-thru internet,” the authors propose a novel amortized fairnessMAC protocol. Basically, vehicles with lower link qualitycan defer their fairness requests and let the lost fairnessbe “amortized” in the future when their links become thehigh quality. The inner and inter-AP correlations revealedfrom our extensive field studies are fully exploited, and alink quality prediction algorithm is proposed. Based on thepredicted link quality, the optimal amortized fairness MACis formulated as a convex programming problem, which canbe solved with the desired precision in polynomial time.

Jianwei NiuLei Shu

Zhangbing ZhouYan Zhang

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Editorial Mobile Sensing and Data Management for Sensor ...downloads.hindawi.com/journals/ijdsn/2013/898169.pdf · In the paper Moving target oriented opportunistic routing algorithm