RESEARCH Open Access

Mobile service aware opportunisticembedded architecture of mobile crowdsensing networks for power networkmeasurementJianwei Zhang1,2* and Hao Yang1,2

Abstract

In order to improve the intelligent degree and robustness optimization of power grid management system, theopportunistic embedded architecture was proposed for power network measurement with mobile service awarescheme. First, the mobile crowd sensing network for power grid management was proposed to realize theintelligent power grid management. Then, we designed the mobile service aware opportunistic embedded systembased on the requirements of intelligent power grid management and deployment of mobile crowd sensingnetwork. Thirdly, the grid of embedded systems was demonstrated for intelligent management. The experimentalresults show that the proposed scheme has obvious advantages in system complexity, execution efficiency,intelligent power grid management level, etc.

Keywords: Opportunistic embedded architecture, Mobile crowd sensing, Power network measurement, Mobileservice aware

1 IntroductionWith the rapid development of the electricity grid, the wideapplication of intelligent electronic equipment brings greatconvenience and benefit for the human life and productionat the same time; it also brings challenges to power gridmanagement and reliable guarantee. However, unstable andinefficient power supply and power grid management willinevitably bring many difficulties to the human daily lifeand work. So, the effective management of mobile devicesand smart grid management scheme and construction ofreasonable, complete, and efficient smart grid managementbecome the key.With the help of a smart grid management platform,

real-time monitoring, and the management of power usesituation, a power monitoring system was designedbased on a smart grid management platform [1]. Basedon the existing power quality, a monitoring system ofpower quality management platform was proposed in

article [2]. The authors of [3] proposed the integrationservice system of intelligent power grid managementbased on the Internet of Things service system. Accord-ing to the generalized data automatic acquisition prob-lem, the general data that can be used in the intelligentprocessing management model was studied [4]. Basedon the limited capacity of Petri nets, a formal model ofthe smart grid transmission system was established in[5]. For large-scale automatic meteorological station net-work characteristics and requirements of data transmis-sion, the special GPRS data communication terminalsdesigned and the wireless data terminal hardwarescheme are given by the authors of article [6]. A newscheme of high TCP availability was proposed in [7].The program cycle structure was adjusted for optimizingand improving the local equipment’s operation [8]. A setof power equipment monitoring system was designedbased on the embedded system [9], which is mainlycomposed of ultraviolet probe, embedded computer sys-tem, and GPRS module. The aging test design schemewas proposed in [10]. However, the above articles

* Correspondence: zhangjianweijh@163.com1Electric Power Research Institute of Yunnan Power Grid Co., Ltd, Kunming,China2Key Laboratory of CSG for Electric Power Measurement, Kunming, China

© 2016 Zhang and Yang. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made.

Zhang and Yang EURASIP Journal on Embedded Systems (2016) 2016:2 DOI 10.1186/s13639-016-0023-0

ignored the opportunistic control characteristics of em-bedded devices.A group of mental perception network constitutes that

is people-centered was proposed based on the perceptionof social behavior analysis mode of the important way ofdata collection [11]. Mobile terminal group of mental per-ception mode was proposed in article [12]. Mobile groupof city hot issues of data method was studied in [13],based on the hot issues for discovery and classification. Anovel incentive mechanism based on multi-Interaction dy-namic incentive mechanism was proposed in article [14].[14]. A high level synthesis approach was presented in[15] for generating the embedded processor arrays formatrix algorithms based on the polytope model. A novelfingerprint template protection scheme based on chaoticencryption was proposed in [16]. The study of article [17]suggests that the near-tip conditions for both the left andright crack tips in systems with non-horizontal cracks aredominated by mixed mode conditions. A novel simple al-gorithm for dynamic intelligent load balancing was pro-posed for decreasing the power losses in a powerdistribution network [18]. An enhanced way-predictioncache was developed for coping with the weakness of theway-prediction cache [19]. Chutisant Kerdvibulvech pro-posed a methodology for motion analysis and hand track-ing based on adaptive probabilistic models [20]. However,the above researches did not make the future research ofthe relationship between mobile crowd sensing networksand power network measurement.On the basis of the above research results, the mobile

service aware opportunistic embedded architecture ofmobile crowd sensing networks for power networkmeasurement automation was researched and presented.The rest of the paper is organized as follows. Section 2

describes the mobile crowd sensing network for powergrid management. In Section 3, we discussed the mobileservice aware opportunistic embedded system. In Sec-tion 4, we proposed the grid intelligent management ofthe embedded systems. The performance analysis of em-bedded system has been shown in Section 5. Finally, theconclusions are given in Section 6.

2 Mobile crowd sensing network for power gridmanagementFor realizing the intelligent power grid management, thefollowing several issues should be considered:

(1)Grid embedded geographic information system(2)Power grid management communication between

the embedded devices(3)Power grid management redundant components(4)Grid embedded equipment maintenance management(5)Grid communication optimization(6)Embedded system operation and control

Here, the operation and control scheme of the embed-ded equipment of the intelligent power grid is the coreof the intelligent network management. The core func-tionality can be subdivided the following several aspects:

(1)The embedded devices of power management(2)The embedded devices working voltage intelligent

control(3)The self-protection function of embedded

equipment(4)Equipment group of cooperative control(5)Feeder intelligent control of power grid(6)Front-end perception data processing equipment

The above analysis shows that the grid management ofintelligent electric power dispatching and intelligent sub-station of the crowd sensing network management couldbe realized through the deployment of embedded equip-ment and communication network and single front-endembedded devices of data perception, covering the area ofintelligent network, real-time monitoring circuit load, andother important link in the management of power grid.Therefore, in the power grid management, deployment

of mobile crowd sensing network is shown in Fig. 1, in-cluding the embedded devices (ES) and subnet (SS). Inurban, the suburban deploys embedded devices of differ-ent types and scale. The two-way communication link ofthe embedded devices, one of the Internet and mobilecrowd sensing gateway and one of the gateway and thepower grid management center, would be realized.Moreover, through the point-to-point bidirectional link,end-to-end communication between any two pointswould be realized as shown in Fig. 1.In grid management front to join the embedded

system, the function of the platform of the system isshown in Fig. 2. Additionally, Fig. 2 shows the four-stepworkflow of the embedded grid management.

Step 1. Embedded control equipment testingStep 2. Embedded logic controlStep 3. Distributed ES point to pointStep 4. Connectivity of mobile crowd sensing networks

The above four steps and its features of the embed-ded devices and mobile group were established withthe end-to-end communication between crowd sensingnetworks. Moreover, mobile crowd sensing networkscould provide three aspects of the functions of grid datamanagement for the embedded devices.

(1)Data collection. Embedded devices can sense thedata, by collecting incentive mechanism andarousing enthusiasm of embedded devices datacollection.

Zhang and Yang EURASIP Journal on Embedded Systems (2016) 2016:2 Page 2 of 9

Fig. 1 The end-to-end communication between mobile crowd sensing networks and the embedded devices were established with the abovefour steps. Moreover, the mobile crowd sensing networks could provide the following grid data management functions for theembedded devices.

Fig. 2 Function platform of mobile crowd sensing embedded system

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(2)Data forwarding. Embedded devices have certainstorage space, can store the data, and make sure thereceiver forwards the data after creating anend-to-end communication link.

(3)Access to the server. A communication link betweenpower grid management servers was established forhelping the embedded devices to gain the accesspermissions of the servers.

The urban grid management would be researched afterthe deployment of mobile crowd sensing network. As-sumptions embedded devices with functions of percep-tion, collection, and data forwarding. At the same time,each embedded devices has mobile ability, and in ac-cordance with the established time sequence pointmoves, has a fixed mobile trajectory. Mobile embeddeddevices positioning can be achieved by time and speed.In a time domain to a known period, analysis for the

power grid management of mobile crowd sensing net-work coverage quality and work with mobile embeddeddevices combined with cycle and activity were done.In a spatial domain, combined with the feature of

urban buildings and all kinds of noise source, on thebasis of time domain integral, the mobile embedded de-vices perceive an orthogonal segment and can, accordingto the power grid management, control center serviceapplication requests and intelligent decision power gridmanagement level of precision and reliability.Therefore, in each round of data collection, store,

and forward cycle, to meet the power grid manage-ment service request at the same time, combined withthe feature of coverage, distributed embedded cover,covering the size as shown in formula (1), if formula(2) is met, shows the realizing of a complete coverageof the area.

PS SSð Þ ¼

1; t <NT

NES

0; t ¼ NT

NES

tT; t >

NT

NES

8>>>>>>>><>>>>>>>>:

ð1Þ

Here, PS denotes the SS cover granularity. NT presentsthe monitored time length. NES denotes the mobile em-bedded devices. T is the delay of the data collection,store, and forward cycle.

XTt

i¼1

PS SSið ÞXNES

j

PSSj ð2Þ

Here, PSSj denotes the connected probability.

3 Mobile service aware opportunistic embeddedsystemAccording to the requirements of intelligent power gridmanagement, the deployment of the mobile group ofcrowd sensing network was studied. For embedded mo-bile front-end structures, highly integrated and two-waycommunication network at a high speed. In order toprovide reliable, safe, economic, efficient, and environ-mental friendly management objectives and meet thepower grid management mobile service application, mo-bile embedded system involves the following techniques:perception, sensor technology, data logic control tech-nology, and independent decisions.The system has the following characteristics:

(1)The embedded devices working state self-inspectionEmbedded device working condition is defined as

EQS ¼ W v; Pc; Sp; Fq; Ig� � ð3Þ

Here, Wv denotes the working voltage. Pc denotes theperceptual cycle. Sp denotes the storage space. Fqdenotes the forward frequency. Ig denotes integration.

(2)Incentives for embedded devices.In the mobile crowd sensing network, cloud storage,data sharing, and data grid quality evaluation oftwo-way link between the multiple embeddeddevices should be inspired with the multiple mobileembedded equipment state of common sense andmobile service requirements, therefore, to establish,as shown in formula (3), the incentive factors.Through these factors, to select the current mobileembedded devices, the best neighbor node subnetfinishes the work.

MF ¼XNi¼1

EQSiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiAWi þMSi

p

XNi¼1

AWi ≥XNi¼1

MSi

8>>>><>>>>:

ð4Þ

Here, N denotes the mobile devices scale of themobile crowd sensing networks. MF denotes theincentive factors. AW denotes the awareness ability.MS denotes the mobile service ability. Formula (3)shows that only when multiple embedded mobiledevices of total demand, perception ability strongerthan the mobile service to be effective incentiveneighbor devices of mobile group of subnet.

(3)The mobile user requirementsMobile user demand is equivalent to MS. Specificdemand indicators include the following: embeddeddevice control complexity, computational complexity,equipment capacity data storage space complexity,power supply feedback response delay, etc.

Zhang and Yang EURASIP Journal on Embedded Systems (2016) 2016:2 Page 4 of 9

(4)The anti-damage abilityEmbedded mobile devices for neighbor device noise,noise of large power equipment, its own internalnoise, bad environment embedded mobilecommunication reliable guarantee, etc.

(5)Mobile service awareness abilityThe feature description is similar to the one in AW.

(6)Service awareness of the power quality guaranteeBased on (3), (4) and (5), a comprehensiveevaluation analysis of power management systemwould be given for providing power qualityguarantee as the goal, by the formula (4), which isused to analyze the current mobile power qualityguarantee ability.

PQG ¼XNSS

i¼1

aiAWi þ biMSi þ ciAdi

ai þ bi þ ci ¼ 1; i∈ 1;NSS½ �XNi¼1

PQGi ≥XNi¼1

AWi

8>>>>>><>>>>>>:

ð5Þ

Here, NSS denotes the subnet of the mobile devices.(7)Diversity of power supply.

Embedded mobile devices compatible with all kindsof power supply. The device to run in parallel with asingle power supply or more class power has serialor parallel processing ability and has thecomprehensive distributed power supply interface.

(8)Mobile power optimizationAccording to the mobile group of crowd sensingnetwork communication load and speed embeddedmobile devices, integrated optimization on theperformance and the mobile service demand.

In order to achieve the above eight aspects of embed-ded devices and the characteristics of the communica-tion control network, the need to design mobile serviceperceived opportunistic embedded to architecture, asshown in Fig. 3. The opportunity to architecture can bedivided into two subsystems.

(1)The intelligent management of fault perceptionand self-healing smart grid system is suitable forhigh voltage distribution network. Throughself-inspection of embedded mobile devices ofshort circuit and earth fault statistics, and thefault information to share with neighbors mobileequipment, working state is obtained by formula(3) value, thus for grid management provides thebasis for transformer monitoring network andintelligent operation. At the same time, can beembedded mobile devices with two ways of con-necting rod set up the intelligent electric opening

and closing operation decision-making basis isgiven. The child system can obtainreal-time current, voltage of the circuit changesin real time.

(2)The mobile group of the seamless combination of thenet each subnet system. By moving the group ofwisdom subnet to a large area power gridmanagement area for unit division and the seamlessconnection, the system can state monitor real timethe transmission lines and the grounding of thetransformer equipment and subnet bolt bearing load,subnet, etc.

4 Grid intelligent management of embeddedsystemsBased on the above research work, through the mobileservice awareness and opportunistic embedded system,we studied the suitable embedded mobile devices andproposed the power grid management based on mobilecrowd sensing network management system, as shownin Fig. 4.There are point-to-point communication between

mobile service aware server, substation managementside, and base station. The base station manages themobile users and mobile crowd sensing gateways. Theseamless coverage overlapping management and con-tinuous repair and guarantee system would be usedto guarantee the reliable service of submobile crowdsensing networks.Assuming that the system is a continuous system.

y(t) = T{EQ(t)U(t)}. Here, T presents the workinghours of the power grid management system. Com-bined with embedded devices status, the power statusof the continuous variation process of electric powerwas analyzed. When the system satisfies the condi-tions as shown in formula (5), the system has a linearcharacteristic.

y1 tð Þ ¼ T EQ tð Þf gy2 tð Þ ¼ T U tð Þf gy tð Þ⊳ y1 tð Þ þ y2 tð Þk k

8<: ð6Þ

About the v weighting parameters of every mobileservice demand, the relationship of embedded system isshown in formula (6), which described the seamlesscoverage of the management features.

T vEQ tð Þf g−T vU tð Þf gj j≥vy tð ÞT vEQ tð Þf g ¼ vT EQ tð Þf gT vU tð Þf g ¼ vT U tð Þf g

8<: ð7Þ

For adjacent mobile crowd sensing between the netSS1 and SS2, the overlap region, covering managementthrough formula (7), is analyzed.

Zhang and Yang EURASIP Journal on Embedded Systems (2016) 2016:2 Page 5 of 9

Fig. 3 Mobile service perception of opportunity structure of embedded system

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T USS1 tð Þf g þ T USS2 tð Þf g≈ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiT U tð Þf gpNSS

EQ SS1ð Þ >ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiT EQ tð Þf gpNSS

EQ SS2ð Þ >ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiT EQ tð Þf gpNSS

8>>>>>>>>>><>>>>>>>>>>:

ð8Þ

Therefore, the proposed embedded power manage-ment in the embedded system can well meet the prac-tical engineering linear nuclear continuous electricitydemand that continues to provide mobile users anddiversity.

5 The performance analysis of embedded systemWe form the following three aspects: the performance ofthe analysis and validation of the proposed embeddedsystems.

5.1 The system reliabilityThe power grid reliability of the mobile crowd sensingnetwork intelligent embedded management system isthat the power grid can provide stable power protectionand mobile information services anytime and anywhere,at the same time, considering the quality of the embed-ded mobile devices, robustness and fault detection andrepair ability. The performance can be obtained refer-ence formula (8) analysis.

NF ¼XNi¼1

XNSS

j¼1

jP ESi ⊂ SSið Þ ð9Þ

Here, NF denotes the failure unit number per time. Pdenotes the failure number of the mobile embedded de-vices in the mobile crowd sensing subnet networks.

Fig. 4 Embedded power network management system with mobile crowd sensing networks

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5.2 The system manageabilityThe management complexity considers computationalcomplexity and control complexity of the integrationof the software platform and hardware platform. Inaddition, the operation complexity and communica-tion delay between the comprehensive evaluations ofcontrol center server, substation server, and embed-ded mobile devices would be studied in the mean-time. The performance can be obtained referenceformula (9).

SC ¼XNTRA

i¼1

αiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiCPCi þ CTCi

pþXNSS

j¼1

βj COj−CLj

�� �� ð10Þ

Here, SC denotes the complexity of the integratedsystem. NTRA denotes the transformer size. CPC denotescomputational complexity. CTC denotes the controlcomplexity. CO denotes the operation complexity. CLdenotes the communication delays. α denotes the workfrequency transformer. β denotes the mobile group ofthe working time of the subnet.

5.3 The system scalabilityOn the basis of the diversity of user requirementsand the dynamic expansion of mobile services, wewould analyze the scalability based on the size of themobile devices and the change of the coverage andthe proposed system of power grid management per-formance, at the same time, for the embedded mobileequipment deployment way, communication protocolstandards, as well as user operability and trouble-shooting skills. The performance can be obtained byreference formula (10).

SCL ¼ SCNTRANSS

NESP PS−Fcð Þη ð11Þ

Among them, the SCL denoted the system extensionliquidate. SC denoted the cover. PS denotes the commu-nication protocol standards available probability. FCdenotes mobile equipment failure repair probability. Saidmobile service expansion factor.The experimental environment description is as follows:

(1)Grid management scope: 10 km × 12 km(2)Power grid management system running time: 24 h(3)Mobile crowd sensing subnet number: 2−5(4)Embedded mobile devices maximum

communication distance of 1 km

According to formulas (8), (9), and (10), the analysis ofthe mobile device number, percentage of coverage, and

1 2 3 4 5 6 7 80

1

2

3

4

5

6

7

Number of Embedded devices

NF

DPMMSOPNM

Fig. 5 Embedded system reliability

Fig. 6 Embedded system manageability

Fig. 7 Embedded system extensibility

Zhang and Yang EURASIP Journal on Embedded Systems (2016) 2016:2 Page 8 of 9

data size on the performance of the system reliability,manageability, and scalability, the proposed system(MSOPNM) with distributed power management (DPM)system performance is compared, and the results areshown in Figs. 5, 6, and 7.Found from Fig. 5, the proposed system was built

based on the mobile service awareness for mobile de-vices because of the high reliability of embedded systemstructure, while continuously increasing the scale ofmobile devices but still keeping good performance, andis obviously better than the reliability of distributednetwork management system. For distributed networkmanagement system through a long response delayfor mobile devices, the substation builds end-to-endcommunication server and, therefore, managementperformance, as shown in Fig. 6. Faced with massivedata collection, store, and forward cycle, the proposedsystem can be used as user requirements for diversityand dynamic expansion of mobile services to provideeffective guarantee, even if the cover dynamic changestill has good performance of power grid manage-ment, as shown in Fig. 7.

6 ConclusionsThe traditional power supply and power grid manage-ment schemes are unstable and inefficient for the rapiddevelopment of the human daily life and work. Fordealing with the above issues, we researched the oppor-tunistic embedded architecture for the power networkmeasurement with the mobile service aware scheme andmobile crowd sensing networks. About the intelligentpower grid management, we designed the mobile crowdsensing network for power grid management. Then, ac-cording to the requirement diversity of the intelligentpower grid management and deployment of the mobilecrowd sensing networks, the mobile service aware op-portunistic embedded system was studied. Finally, weproposed the grid intelligent management scheme andsystem with embedded systems. The experimental re-sults show that the proposed scheme is superior todistributed power management system, such as the sys-tem complexity, execution efficiency, intelligent powergrid management level, etc.

Competing interestsThe authors declare that they have no competing interests.

Received: 13 November 2015 Accepted: 19 January 2016

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