- freely available
ISPRS Int. J. Geo-Inf. 2016, 5(11), 211; https://doi.org/10.3390/ijgi5110211
- For processing window queries, the information about the largest empty rectangle of the cells is provided in the spatial air index to further bound the search region and skip irrelevant broadcast content, thus reducing access and tuning times.
- Various experiments with different settings verify the effectiveness of the proposed spatial air index method, which outperforms the existing methods SSI and MLAIN.
2. Related Work
2.1. Flat Data Broadcast
2.2. Non-Flat Data Broadcast
3. Proposed Spatial Air Index Method
3.1. System Model
3.2. Mapping of Spatial Data from 2D to 1D
3.3. Generation of the Non-Flat Broadcast Program
3.4. Construction of the Index Structure and Largest Empty Rectangles
- Global index: G = <Ct, HL>
- Ct is the arrival time of the nearest upcoming cell index of Level 1 in the wireless channel. For example, Ct in the first global index in Figure 5 points to the beginning of cell index C(1,0), t5.
- HL contains the arrival time of the cell indexes for all hot cells. For example, HL in the first global index in Figure 5 contains information about all the hot cells, H(2,2), H(2,8) and H(2,13).
- Hot cell index: H(i,j) = <Gt, Ct, SL, DL, LERI>
- Gt is the arrival time of the nearest upcoming global index. For example, in Figure 5, Gt in the hot cell index of H(2,2) in the second row points to the beginning of the upcoming global index, t16.
- SL contains information about the sibling cells of the same level.
- DL contains the coordinates of the spatial objects in that cell, and their corresponding arrival times. From DL, the mobile device can determine whether the spatial objects are contained within the query region before retrieving them from the channel.
- LERI represents the information about the largest empty rectangle of this hot cell. The lower-left and upper-right coordinates of the largest empty rectangle are recorded in LERI.
- Cell index: C(i,j) = <Gt, Ct, SL, CL, DL>
- CL contains information about the corresponding child cells of the next level. For example, in Figure 5, CL in the cell index of C(1,0) of Level 1 contains information about the child cells of Level 2, C(2,1), H(2,2), and C(2,3).
3.5. Access Processing for Window Queries
|Algorithm 1. Process a Window Query|
|Input: Examination set ES.|
|Output: The relevant objects.|
4. Simulation Study
4.1. Simulation Model
4.2. Simulation Results
4.2.1. Impact of Crosspro
4.2.2. Impact of WinLengthRatio
4.2.3. Impact of θ
4.2.4. Impact of φ
Conflicts of Interest
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|θ||2.5||The Zipf factor to control the access skewness of the distribution of spatial objects|
|φ||2||The Zipf factor to control the access skewness of the distribution of disks|
|WinLengthRatio||0.11%||The ratio of the side length of the query region to that of a map|
|Crosspro||60%||The probability that a query region is crossing more than one cell|
|20%||83.63||87.56 (4%)||87.72 (5%)|
|40%||123.56||133.51 (7%)||133.76 (8%)|
|60%||160.70||176.85 (9%)||177.19 (9%)|
|80%||201.04||222.46 (10%)||222.91 (10%)|
|100%||238.93||267.23 (11%)||267.76 (11%)|
|0.08%||77.20||87.64 (12%)||87.77 (12%)|
|0.095%||117.68||130.36 (10%)||130.52 (10%)|
|0.11%||161.68||177.67 (9%)||178.03 (9%)|
|0.125%||224.40||245.50 (9%)||246.95 (9%)|
|0.14%||310.58||337.48 (8%)||339.58 (9%)|
|2.1||182.65||201.82 (9%)||202.21 (10%)|
|2.3||162.77||178.73 (9%)||179.05 (9%)|
|2.5||162.31||178.12 (9%)||178.47 (9%)|
|2.7||159.38||177.73 (11%)||178.07 (11%)|
|2.9||158.88||176.76 (10%)||177.10 (10%)|
|1||185.62||199.99 (7%)||200.54 (7%)|
|1.5||173.56||189.16 (8%)||189.61 (8%)|
|2||161.77||177.74 (9%)||178.09 (9%)|
|2.5||150.24||166.36 (10%)||166.61 (10%)|
|3||142.98||159.07 (10%)||159.25 (10%)|
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